From 8d6ade57bcd2eafcf8f1a0bb6306913bff99b237 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Johannes=20H=C3=B6rner?= <johannes.hoerner@univie.ac.at>
Date: Wed, 14 Jul 2021 12:10:44 +0200
Subject: [PATCH] initial commit
---
...res_comparison_PAPERPLOTS-checkpoint.ipynb | 1319 ++
...Winton_artificial_forcing-checkpoint.ipynb | 1534 +++
...cation_Semtner_unlim-lim5-checkpoint.ipynb | 370 +
...tion_Winton_Semtner_unlim-checkpoint.ipynb | 779 ++
.ipynb_checkpoints/cdo_pp-checkpoint.ipynb | 347 +
...yflux_icelimit_comparison-checkpoint.ipynb | 1459 +++
.ipynb_checkpoints/overview-checkpoint.ipynb | 500 +
...000ppmv_and_1500ppmv_plot-checkpoint.ipynb | 207 +
..._Semtner_lores_comparison_PAPERPLOTS.ipynb | 1947 +++
.../Winton_artificial_forcing.ipynb | 1575 +++
.../bifurcation_Semtner_unlim-lim5.ipynb | 370 +
.../bifurcation_Winton_Semtner_unlim.ipynb | 779 ++
python_scripts /cdo_pp.ipynb | 347 +
.../energyflux_icelimit_comparison.ipynb | 1459 +++
python_scripts /overview.ipynb | 498 +
..._5000_and_3000ppmv_and_1500ppmv_plot.ipynb | 193 +
.../TOA_balance-checkpoint.csv | 0
.../bifurcation_5mlim_merged-checkpoint.pdf | Bin 0 -> 17403 bytes
.../bifurcation_winton_merged-checkpoint.pdf | Bin 0 -> 17464 bytes
.../hovmoeller_rsut-checkpoint.png | Bin 0 -> 172114 bytes
...del_hi_qtop_qbot_freezing_2-checkpoint.pdf | Bin 0 -> 19225 bytes
...l_hi_qtop_qbot_melting_icon-checkpoint.pdf | Bin 0 -> 19522 bytes
...l_hi_qtop_qbot_melting_icon-checkpoint.png | Bin 0 -> 30758 bytes
...l_hi_qtop_qbot_melting_snow-checkpoint.pdf | Bin 0 -> 17233 bytes
python_scripts /plots/F_sit_fit.pdf | Bin 0 -> 47931 bytes
python_scripts /plots/TOA_EB.pdf | Bin 0 -> 18715 bytes
python_scripts /plots/TOA_EB.png | Bin 0 -> 248263 bytes
python_scripts /plots/TOA_balance.csv | 5 +
python_scripts /plots/bifurcation.svg | 2235 ++++
.../plots/bifurcation_5mlim_merged.pdf | Bin 0 -> 17480 bytes
python_scripts /plots/bifurcation_winton.svg | 2128 ++++
.../plots/bifurcation_winton_merged.pdf | Bin 0 -> 17626 bytes
python_scripts /plots/enthalpy.pdf | Bin 0 -> 15115 bytes
python_scripts /plots/heatflux_comparison.svg | 1682 +++
.../plots/heatflux_scatter_flux_icelat.pdf | Bin 0 -> 30368 bytes
.../plots/heatflux_scatter_flux_sit.svg | 10461 ++++++++++++++++
python_scripts /plots/hice5m_sic_qbot.svg | 2580 ++++
.../plots/hice_unlim_icelat_Jor_overview.svg | 1092 ++
.../plots/hice_unlim_icelat_overview.svg | 5450 ++++++++
python_scripts /plots/hovmoeller_albedo.pdf | Bin 0 -> 24784 bytes
python_scripts /plots/hovmoeller_albedo.png | Bin 0 -> 196650 bytes
python_scripts /plots/hovmoeller_rsut.pdf | Bin 0 -> 26754 bytes
python_scripts /plots/hovmoeller_rsut.png | Bin 0 -> 172114 bytes
python_scripts /plots/hovmoeller_rsutcs.pdf | Bin 0 -> 26407 bytes
python_scripts /plots/hovmoeller_rsutcs.png | Bin 0 -> 173635 bytes
.../plots/hovmoeller_rsutcs_multi.png | Bin 0 -> 324986 bytes
python_scripts /plots/icelat_comparison.pdf | Bin 0 -> 20977 bytes
python_scripts /plots/model_hi_abbot.svg | 965 ++
python_scripts /plots/model_hi_freezing.svg | 1035 ++
python_scripts /plots/model_hi_freezing_2.svg | 1101 ++
.../plots/model_hi_melting_cold.svg | 920 ++
.../plots/model_hi_melting_icon.svg | 1399 +++
.../plots/model_hi_melting_snow.svg | 976 ++
.../plots/model_hi_qtop_qbot_abbot.pdf | Bin 0 -> 16555 bytes
.../plots/model_hi_qtop_qbot_freezing.pdf | Bin 0 -> 15283 bytes
.../plots/model_hi_qtop_qbot_freezing_2.pdf | Bin 0 -> 19225 bytes
.../plots/model_hi_qtop_qbot_melting_icon.pdf | Bin 0 -> 20397 bytes
.../plots/model_hi_qtop_qbot_melting_icon.png | Bin 0 -> 98714 bytes
.../plots/model_hi_qtop_qbot_melting_snow.pdf | Bin 0 -> 18002 bytes
python_scripts /plots/model_hs_abbot.svg | 832 ++
python_scripts /plots/model_hs_freezing_2.svg | 832 ++
.../plots/model_hs_melting_cold.svg | 1203 ++
.../plots/model_hs_melting_icon.svg | 832 ++
.../plots/model_hs_melting_snow.svg | 1200 ++
python_scripts /plots/model_qbot_abbot.svg | 1622 +++
python_scripts /plots/model_qbot_freezing.svg | 1651 +++
.../plots/model_qbot_freezing_2.svg | 1914 +++
.../plots/model_qbot_melting_cold.svg | 1301 ++
.../plots/model_qbot_melting_icon.svg | 1061 ++
.../plots/model_qbot_melting_snow.svg | 1427 +++
python_scripts /plots/model_qtop_abbot.svg | 868 ++
python_scripts /plots/model_qtop_freezing.svg | 868 ++
.../plots/model_qtop_freezing_2.svg | 868 ++
.../plots/model_qtop_melting_cold.svg | 1197 ++
.../plots/model_qtop_melting_icon.svg | 1592 +++
.../plots/model_qtop_melting_snow.svg | 1174 ++
python_scripts /plots/surface_albedo_July.pdf | Bin 0 -> 14513 bytes
.../plots/surface_albedo_July_multi.pdf | Bin 0 -> 16263 bytes
.../plots/winton_icelat_Jor_overview.svg | 2202 ++++
.../plots/winton_icelat_overview.svg | 5632 +++++++++
80 files changed, 73988 insertions(+)
create mode 100644 .ipynb_checkpoints/Winton_Semtner_lores_comparison_PAPERPLOTS-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/Winton_artificial_forcing-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/bifurcation_Semtner_unlim-lim5-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/bifurcation_Winton_Semtner_unlim-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/cdo_pp-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/energyflux_icelimit_comparison-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/overview-checkpoint.ipynb
create mode 100644 .ipynb_checkpoints/paper_5000_and_3000ppmv_and_1500ppmv_plot-checkpoint.ipynb
create mode 100644 python_scripts /Winton_Semtner_lores_comparison_PAPERPLOTS.ipynb
create mode 100644 python_scripts /Winton_artificial_forcing.ipynb
create mode 100644 python_scripts /bifurcation_Semtner_unlim-lim5.ipynb
create mode 100644 python_scripts /bifurcation_Winton_Semtner_unlim.ipynb
create mode 100644 python_scripts /cdo_pp.ipynb
create mode 100644 python_scripts /energyflux_icelimit_comparison.ipynb
create mode 100644 python_scripts /overview.ipynb
create mode 100644 python_scripts /paper_5000_and_3000ppmv_and_1500ppmv_plot.ipynb
create mode 100644 python_scripts /plots/.ipynb_checkpoints/TOA_balance-checkpoint.csv
create mode 100644 python_scripts /plots/.ipynb_checkpoints/bifurcation_5mlim_merged-checkpoint.pdf
create mode 100644 python_scripts /plots/.ipynb_checkpoints/bifurcation_winton_merged-checkpoint.pdf
create mode 100644 python_scripts /plots/.ipynb_checkpoints/hovmoeller_rsut-checkpoint.png
create mode 100644 python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_freezing_2-checkpoint.pdf
create mode 100644 python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.pdf
create mode 100644 python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.png
create mode 100644 python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_snow-checkpoint.pdf
create mode 100644 python_scripts /plots/F_sit_fit.pdf
create mode 100644 python_scripts /plots/TOA_EB.pdf
create mode 100644 python_scripts /plots/TOA_EB.png
create mode 100644 python_scripts /plots/TOA_balance.csv
create mode 100644 python_scripts /plots/bifurcation.svg
create mode 100644 python_scripts /plots/bifurcation_5mlim_merged.pdf
create mode 100644 python_scripts /plots/bifurcation_winton.svg
create mode 100644 python_scripts /plots/bifurcation_winton_merged.pdf
create mode 100644 python_scripts /plots/enthalpy.pdf
create mode 100644 python_scripts /plots/heatflux_comparison.svg
create mode 100644 python_scripts /plots/heatflux_scatter_flux_icelat.pdf
create mode 100644 python_scripts /plots/heatflux_scatter_flux_sit.svg
create mode 100644 python_scripts /plots/hice5m_sic_qbot.svg
create mode 100644 python_scripts /plots/hice_unlim_icelat_Jor_overview.svg
create mode 100644 python_scripts /plots/hice_unlim_icelat_overview.svg
create mode 100644 python_scripts /plots/hovmoeller_albedo.pdf
create mode 100644 python_scripts /plots/hovmoeller_albedo.png
create mode 100644 python_scripts /plots/hovmoeller_rsut.pdf
create mode 100644 python_scripts /plots/hovmoeller_rsut.png
create mode 100644 python_scripts /plots/hovmoeller_rsutcs.pdf
create mode 100644 python_scripts /plots/hovmoeller_rsutcs.png
create mode 100644 python_scripts /plots/hovmoeller_rsutcs_multi.png
create mode 100644 python_scripts /plots/icelat_comparison.pdf
create mode 100644 python_scripts /plots/model_hi_abbot.svg
create mode 100644 python_scripts /plots/model_hi_freezing.svg
create mode 100644 python_scripts /plots/model_hi_freezing_2.svg
create mode 100644 python_scripts /plots/model_hi_melting_cold.svg
create mode 100644 python_scripts /plots/model_hi_melting_icon.svg
create mode 100644 python_scripts /plots/model_hi_melting_snow.svg
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_abbot.pdf
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_freezing.pdf
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_freezing_2.pdf
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_melting_icon.pdf
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_melting_icon.png
create mode 100644 python_scripts /plots/model_hi_qtop_qbot_melting_snow.pdf
create mode 100644 python_scripts /plots/model_hs_abbot.svg
create mode 100644 python_scripts /plots/model_hs_freezing_2.svg
create mode 100644 python_scripts /plots/model_hs_melting_cold.svg
create mode 100644 python_scripts /plots/model_hs_melting_icon.svg
create mode 100644 python_scripts /plots/model_hs_melting_snow.svg
create mode 100644 python_scripts /plots/model_qbot_abbot.svg
create mode 100644 python_scripts /plots/model_qbot_freezing.svg
create mode 100644 python_scripts /plots/model_qbot_freezing_2.svg
create mode 100644 python_scripts /plots/model_qbot_melting_cold.svg
create mode 100644 python_scripts /plots/model_qbot_melting_icon.svg
create mode 100644 python_scripts /plots/model_qbot_melting_snow.svg
create mode 100644 python_scripts /plots/model_qtop_abbot.svg
create mode 100644 python_scripts /plots/model_qtop_freezing.svg
create mode 100644 python_scripts /plots/model_qtop_freezing_2.svg
create mode 100644 python_scripts /plots/model_qtop_melting_cold.svg
create mode 100644 python_scripts /plots/model_qtop_melting_icon.svg
create mode 100644 python_scripts /plots/model_qtop_melting_snow.svg
create mode 100644 python_scripts /plots/surface_albedo_July.pdf
create mode 100644 python_scripts /plots/surface_albedo_July_multi.pdf
create mode 100644 python_scripts /plots/winton_icelat_Jor_overview.svg
create mode 100644 python_scripts /plots/winton_icelat_overview.svg
diff --git a/.ipynb_checkpoints/Winton_Semtner_lores_comparison_PAPERPLOTS-checkpoint.ipynb b/.ipynb_checkpoints/Winton_Semtner_lores_comparison_PAPERPLOTS-checkpoint.ipynb
new file mode 100644
index 0000000..d6e981f
--- /dev/null
+++ b/.ipynb_checkpoints/Winton_Semtner_lores_comparison_PAPERPLOTS-checkpoint.ipynb
@@ -0,0 +1,1319 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Zonal distribution of albedo and shortwave radiation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.core.options.set_options at 0x2b5f7c25dd90>"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "import sys\n",
+ "from scipy import stats\n",
+ "\n",
+ "import sys\n",
+ "import xarray as xr\n",
+ "xr.set_options(display_style=\"html\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'0.16.2'"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "xr.__version__\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=True) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def load_experiment_zm(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.zm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=True) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime=True): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " #if offsettime:\n",
+ " #da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " #else:\n",
+ " #da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return np.squeeze(da)\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " \n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " elif stable==1: # stable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " elif stable==3: # towards Snowball\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "def get_albedo(DS, offsettime=True):\n",
+ " sw_out = get_var(DS,\"rsuscs\", offsettime) \n",
+ " sw_in = get_var(DS,\"rsdscs\", offsettime)\n",
+ " return np.squeeze(sw_out/sw_in.where(sw_in!=0))\n",
+ "\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend\n",
+ "\n",
+ "def equivalent_co2_factor(heatflux): # heatflux in W/m²\n",
+ " alpha = 5.35\n",
+ " return np.exp(heatflux/alpha)\n",
+ "\n",
+ "def selmonmean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "def seltimemean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).mean(dim='time')\n",
+ "\n",
+ "\n",
+ "def icebordermean(DA, l_iceborder, r_iceborder, inside):\n",
+ " if inside:\n",
+ " indeces = np.r_[l_iceborder:r_iceborder+1]\n",
+ " print(\"indeces equatorwards of iceborder: \" +str(indeces))\n",
+ " else:\n",
+ " indeces = np.r_[0:l_iceborder,r_iceborder+1:np.size(DA[\"lat\"])]\n",
+ " print(\"indeces polewards of iceborder: \" +str(indeces))\n",
+ " weights = np.cos(np.deg2rad(DA.lat))\n",
+ " DA_weighted = DA[indeces]*(weights[indeces]/weights[indeces].mean()) #\n",
+ " return DA_weighted.mean()\n",
+ "\n",
+ "def selmean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).mean(dim='time')\n",
+ "\n",
+ "def integrate_zonal_data(data, lat):\n",
+ " #function to integrate ICON data as zonal mean over longitude for each latitude\n",
+ " #latitude dimension has to be equally spaced!\n",
+ " dlat_array = np.ediff1d(lat)\n",
+ " dlat = dlat_array.mean()\n",
+ " if not np.all(dlat_array == dlat):\n",
+ " print(\"Latitude array not equally spaced!\")\n",
+ " return\n",
+ " \n",
+ " # upper and lower limit of each longitudinal band\n",
+ " latlim_lower = lat-dlat/2\n",
+ " latlim_upper = lat+dlat/2\n",
+ " \n",
+ " # area from the north pole to lower and upper limit\n",
+ " lower = 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(latlim_lower+90)))\n",
+ " upper = 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(latlim_upper+90)))\n",
+ " return (upper-lower) * data\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "321.23447741995005\n"
+ ]
+ }
+ ],
+ "source": [
+ "albsnow_warm = 0.66\n",
+ "albsnow_cold = 0.79\n",
+ "albice_warm = 0.38\n",
+ "albice_cold = 0.45\n",
+ "\n",
+ "albocean = 0.07\n",
+ "\n",
+ "scale_ssi_preind = 0.9442 \n",
+ "ssi_preind = (11.95005, 20.14612, 23.40302, 22.09443, 55.41679, 102.512, 24.69536, 347.4719, 217.2217, 343.2816, 129.3001, 47.07624, 3.130199, 13.17521)\n",
+ "\n",
+ "tsi = scale_ssi_preind*np.sum(ssi_preind)\n",
+ "print(tsi/4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "winton_exparray=np.empty(10, dtype=\"U100\")\n",
+ "semtner_exparray=np.empty(10, dtype=\"U100\")\n",
+ "\n",
+ "winton_simarray=np.empty(10,dtype=object)\n",
+ "semtner_simarray=np.empty(10,dtype=object)\n",
+ "\n",
+ "winton_zmsimarray=np.empty(10,dtype=object)\n",
+ "semtner_zmsimarray=np.empty(10,dtype=object)\n",
+ "\n",
+ "winton_exparray_all=np.empty(10, dtype=\"U100\")\n",
+ "semtner_exparray_all=np.empty(10, dtype=\"U100\")\n",
+ "\n",
+ "winton_simarray_all=np.empty(10,dtype=object)\n",
+ "semtner_simarray_all=np.empty(10,dtype=object)\n",
+ "\n",
+ "\n",
+ "winton_exparray[0]=\"mlo_aqua_3000ppmv_winton\"\n",
+ "winton_exparray[1]=\"mlo_aqua_2437ppmv_winton\"\n",
+ "winton_exparray[2]=\"mlo_aqua_2625ppmv_winton\"\n",
+ "winton_exparray[3]=\"\"\n",
+ "\n",
+ "semtner_exparray[0]=\"mlo_aqua_2250ppmv_hice_unlim\"\n",
+ "semtner_exparray[1]=\"mlo_aqua_1688ppmv_hice_unlim\"\n",
+ "semtner_exparray[2]=\"mlo_aqua_3000ppmv\"\n",
+ "semtner_exparray[3]=\"mlo_aqua_1875ppmv_hice_unlim\"\n",
+ "\n",
+ "\n",
+ "#winton_exparray_all[0]=\"mlo_aqua_5000ppmv_winton\"\n",
+ "winton_exparray_all[1]=\"mlo_aqua_3000ppmv_winton\"\n",
+ "winton_exparray_all[2]=\"mlo_aqua_2437ppmv_winton\"\n",
+ "winton_exparray_all[3]=\"mlo_aqua_2625ppmv_winton\"\n",
+ "winton_exparray_all[4]=\"\"\n",
+ "\n",
+ "#semtner_exparray_all[0]=\"mlo_aqua_5000ppmv\"\n",
+ "semtner_exparray_all[0]=\"mlo_aqua_2250ppmv_hice_unlim\"\n",
+ "semtner_exparray_all[1]=\"mlo_aqua_1688ppmv_hice_unlim\"\n",
+ "semtner_exparray_all[2]=\"mlo_aqua_3000ppmv\"\n",
+ "semtner_exparray_all[3]=\"mlo_aqua_1875ppmv_hice_unlim\"\n",
+ "\n",
+ "\n",
+ "for i in range(0,10):\n",
+ " if winton_exparray[i]!=\"\":\n",
+ " winton_simarray[i] = load_experiment(winton_exparray[i])\n",
+ " winton_zmsimarray[i] = load_experiment_zm(winton_exparray[i])\n",
+ " semtner_simarray[i] = load_experiment(semtner_exparray[i])\n",
+ " \n",
+ " if semtner_exparray[i]!=\"\":\n",
+ " semtner_simarray[i] = load_experiment(semtner_exparray[i])\n",
+ " semtner_zmsimarray[i] = load_experiment_zm(semtner_exparray[i])\n",
+ " \n",
+ " if semtner_exparray_all[i]!=\"\":\n",
+ " semtner_simarray_all[i] = load_experiment(semtner_exparray_all[i])\n",
+ " \n",
+ " if winton_exparray_all[i]!=\"\":\n",
+ " winton_simarray_all[i] = load_experiment(winton_exparray_all[i])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 165,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# calculate iceborders\n",
+ "count=0\n",
+ "Nmin_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Smin_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Nmax_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Smax_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Nmin_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Smin_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Nmax_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Smax_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "for ind in [0,1]:\n",
+ " timemean_sicW = seltimemean(get_var(winton_zmsimarray[ind], 'sic', False),40)\n",
+ " timemean_sicS = seltimemean(get_var(semtner_zmsimarray[ind], 'sic', False),40) \n",
+ "\n",
+ " Nmin_iceborderW[ind] = np.min(np.where(timemean_sicW<1)) # minimum iceborder where there is open ocean\n",
+ " Smin_iceborderW[ind] = np.max(np.where(timemean_sicW<1))\n",
+ "\n",
+ " Nmax_iceborderW[ind] = np.min(np.where(timemean_sicW==0)) # minimum iceborder where there is no ice\n",
+ " Smax_iceborderW[ind] = np.max(np.where(timemean_sicW==0))\n",
+ "\n",
+ "\n",
+ "\n",
+ " Nmin_iceborderS[ind] = np.min(np.where(timemean_sicS<1))\n",
+ " Smin_iceborderS[ind] = np.max(np.where(timemean_sicS<1))\n",
+ "\n",
+ " Nmax_iceborderS[ind] = np.min(np.where(timemean_sicS==0)) # minimum iceborder where there is no ice\n",
+ " Smax_iceborderS[ind] = np.max(np.where(timemean_sicS==0))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 244,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "axis 0: mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n",
+ "axis 1: mlo_aqua_3000ppmv_winton and mlo_aqua_2250ppmv_hice_unlim\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(2,1,figsize=(6,4),sharex=True,sharey=True)\n",
+ "month_name=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
+ "axcount=0;\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ " albedo_W = get_albedo(winton_simarray[ind])\n",
+ " albedo_S = get_albedo(semtner_simarray[ind])\n",
+ "\n",
+ " SW_out_W = get_var(winton_simarray[ind],\"rsuscs\", True) \n",
+ " SW_out_S = get_var(semtner_simarray[ind],\"rsuscs\", True) \n",
+ "\n",
+ " monmean_Wzm=albedo_Wzm.where(albedo_Wzm['time.year'] >= albedo_Wzm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " monmean_Szm=albedo_Szm.where(albedo_Szm['time.year'] >= albedo_Szm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " monmean_W=albedo_W.where(albedo_W['time.year'] >= albedo_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " monmean_S=albedo_S.where(albedo_S['time.year'] >= albedo_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " SW_outmonmean_W=SW_out_W.where(SW_out_W['time.year'] >= SW_out_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " SW_outmonmean_S=SW_out_S.where(SW_out_S['time.year'] >= SW_out_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " ax[axcount].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[axcount], Smin_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ " ax[axcount].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[axcount], Smax_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "\n",
+ " month = 8\n",
+ " rect_snow=mpl.patches.Rectangle((-90,albsnow_warm),180,albsnow_cold-albsnow_warm, alpha=0.4, color='lightblue')\n",
+ " rect_ice=mpl.patches.Rectangle((-90,albice_warm),180,albice_cold-albice_warm, alpha=0.2, color='blue')\n",
+ " ax[axcount].hlines(albocean,-90,90,linewidth=1,color='grey',alpha=0.5)\n",
+ " ax[axcount].add_patch(rect_snow)\n",
+ " ax[axcount].add_patch(rect_ice)\n",
+ " lW=ax[axcount].plot(monmean_Wzm['lat'],monmean_Wzm.sel(month=month),c='C1',label='Winton')\n",
+ " lS=ax[axcount].plot(monmean_Szm['lat'],monmean_Szm.sel(month=month),c='C0',label='Semtner')\n",
+ " print(\"axis \" +str(axcount) +\": \" +winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ " #ax[axcount].annotate(month_name[month-1],(0,0.55),horizontalalignment='center')\n",
+ " axcount+=1;\n",
+ "#ax.annotate(equivalent_co2_factor((SW_outmonmean_W.sel(month=month)-SW_outmonmean_S.sel(month=month)).values).round(3),(40,0.37),horizontalalignment='center',verticalalignment='top')\n",
+ "ax[1].set_xlim(-90,90)\n",
+ "ax[1].set_ylim(0,0.82)\n",
+ "ax[1].set_yticks([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8])\n",
+ "legend_color(ax[0],['3L-Winton', '0L-Semtner'],9)\n",
+ "ax[1].set_xlabel('Latitude [°]')\n",
+ "ax[0].set_ylabel('Surface albedo []')\n",
+ "ax[1].set_ylabel('Surface albedo []')\n",
+ "#fig.suptitle('monthly mean zonal mean surface albedo over the last 40 years\\n' +winton_exparray[ind] +' & ' +semtner_exparray[ind])\n",
+ "#plt.subplots_adjust(left=0, bottom=0, right=1, top=0.9, wspace=0.05, hspace=0.1)\n",
+ "\n",
+ "ax[0].text(-0.12,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.12,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "plt.savefig(\"plots/surface_albedo_July_multi.pdf\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 243,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x144 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(1,1,figsize=(6,2),sharex=True,sharey=True)\n",
+ "month_name=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
+ "axcount=0;\n",
+ "ind=1\n",
+ "albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ "albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ "albedo_W = get_albedo(winton_simarray[ind])\n",
+ "albedo_S = get_albedo(semtner_simarray[ind])\n",
+ "\n",
+ "SW_out_W = get_var(winton_simarray[ind],\"rsuscs\", True) \n",
+ "SW_out_S = get_var(semtner_simarray[ind],\"rsuscs\", True) \n",
+ "\n",
+ "monmean_Wzm=albedo_Wzm.where(albedo_Wzm['time.year'] >= albedo_Wzm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "monmean_Szm=albedo_Szm.where(albedo_Szm['time.year'] >= albedo_Szm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "monmean_W=albedo_W.where(albedo_W['time.year'] >= albedo_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "monmean_S=albedo_S.where(albedo_S['time.year'] >= albedo_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "SW_outmonmean_W=SW_out_W.where(SW_out_W['time.year'] >= SW_out_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "SW_outmonmean_S=SW_out_S.where(SW_out_S['time.year'] >= SW_out_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[axcount], Smin_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[axcount], Smax_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "\n",
+ "month = 8\n",
+ "rect_snow=mpl.patches.Rectangle((-90,albsnow_warm),180,albsnow_cold-albsnow_warm, alpha=0.4, color='lightblue')\n",
+ "rect_ice=mpl.patches.Rectangle((-90,albice_warm),180,albice_cold-albice_warm, alpha=0.2, color='blue')\n",
+ "ax.hlines(albocean,-90,90,linewidth=1,color='grey',alpha=0.5)\n",
+ "ax.add_patch(rect_snow)\n",
+ "ax.add_patch(rect_ice)\n",
+ "lW=ax.plot(monmean_Wzm['lat'],monmean_Wzm.sel(month=month),c='C1',label='Winton')\n",
+ "lS=ax.plot(monmean_Szm['lat'],monmean_Szm.sel(month=month),c='C0',label='Semtner')\n",
+ "print(winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ "#ax[axcount].annotate(month_name[month-1],(0,0.55),horizontalalignment='center')\n",
+ "\n",
+ "#ax.annotate(equivalent_co2_factor((SW_outmonmean_W.sel(month=month)-SW_outmonmean_S.sel(month=month)).values).round(3),(40,0.37),horizontalalignment='center',verticalalignment='top')\n",
+ "ax.set_xlim(-90,90)\n",
+ "ax.set_ylim(0,0.82)\n",
+ "ax.set_yticks([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8])\n",
+ "legend_color(ax,['3L-Winton', '0L-Semtner'],9)\n",
+ "ax.set_xlabel('Latitude [°]')\n",
+ "ax.set_ylabel('Surface albedo []')\n",
+ "#fig.suptitle('monthly mean zonal mean surface albedo over the last 40 years\\n' +winton_exparray[ind] +' & ' +semtner_exparray[ind])\n",
+ "#plt.subplots_adjust(left=0, bottom=0, right=1, top=0.9, wspace=0.05, hspace=0.1)\n",
+ "\n",
+ "plt.savefig(\"plots/surface_albedo_July.pdf\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 167,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton: SWin=321.23425 SWout=98.25365; LWout=222.16487\n",
+ "mlo_aqua_1688ppmv_hice_unlim: SWin=321.23425 SWout=97.2439; LWout=223.32451\n",
+ "\n",
+ "mlo_aqua_3000ppmv_winton: SWin=321.23425 SWout=94.45228; LWout=225.86537\n",
+ "mlo_aqua_2250ppmv_hice_unlim: SWin=321.23425 SWout=93.05864; LWout=227.3154\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import csv\n",
+ "## get components of TOA energy balance\n",
+ "\n",
+ "fieldnames=[\"simulation\", \"SW in\", \"SW out\", \"LW out\"]\n",
+ "f = open(\"plots/TOA_balance.csv\", 'w')\n",
+ "writer = csv.writer(f)\n",
+ "writer.writerow([\"simulation\", \"SW in\", \"SW out\", \"LW out\", \"SW cs out\", \"LW cs out\"])\n",
+ "for ind in [1,0]:\n",
+ " \n",
+ " SW_in_W = get_var(winton_simarray[ind],\"rsdt\", True) \n",
+ " SW_in_S = get_var(semtner_simarray[ind],\"rsdt\", True) \n",
+ " SW_inmean_W=seltimemean(SW_in_W, 40).values\n",
+ " SW_inmean_S=seltimemean(SW_in_S, 40).values\n",
+ " \n",
+ " SW_out_W = get_var(winton_simarray[ind],\"rsut\", True) \n",
+ " SW_out_S = get_var(semtner_simarray[ind],\"rsut\", True) \n",
+ " SW_outmean_W=seltimemean(SW_out_W, 40).values\n",
+ " SW_outmean_S=seltimemean(SW_out_S, 40).values\n",
+ " \n",
+ " LW_out_W = get_var(winton_simarray[ind],\"rlut\", True) \n",
+ " LW_out_S = get_var(semtner_simarray[ind],\"rlut\", True) \n",
+ " LW_outmean_W=seltimemean(LW_out_W, 40).values\n",
+ " LW_outmean_S=seltimemean(LW_out_S, 40).values\n",
+ " \n",
+ " SWcs_out_W = get_var(winton_simarray[ind],\"rsutcs\", True) \n",
+ " SWcs_out_S = get_var(semtner_simarray[ind],\"rsutcs\", True) \n",
+ " SWcs_outmean_W=seltimemean(SWcs_out_W, 40).values\n",
+ " SWcs_outmean_S=seltimemean(SWcs_out_S, 40).values\n",
+ " \n",
+ " LWcs_out_W = get_var(winton_simarray[ind],\"rlutcs\", True) \n",
+ " LWcs_out_S = get_var(semtner_simarray[ind],\"rlutcs\", True) \n",
+ " LWcs_outmean_W=seltimemean(LWcs_out_W, 40).values\n",
+ " LWcs_outmean_S=seltimemean(LWcs_out_S, 40).values\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " print(winton_exparray[ind] +\": \" +\" SWin=\"+str(SW_inmean_W) +\" SWout=\"+str(SW_outmean_W) +\"; LWout=\" +str(LW_outmean_W))\n",
+ " print(semtner_exparray[ind] +\": \" +\" SWin=\"+str(SW_inmean_S) +\" SWout=\"+str(SW_outmean_S) +\"; LWout=\" +str(LW_outmean_S))\n",
+ " print(\"\")\n",
+ " \n",
+ " \n",
+ " writer.writerow([winton_exparray[ind], str(SW_inmean_W), str(SW_outmean_W), str(LW_outmean_W), str(SWcs_outmean_W), str(LWcs_outmean_W)])\n",
+ " writer.writerow([semtner_exparray[ind], str(SW_inmean_S), str(SW_outmean_S), str(LW_outmean_S), str(SWcs_outmean_S), str(LWcs_outmean_S)])\n",
+ " \n",
+ "f.close()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 233,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "clear sky:\n",
+ "637.0255380792839 PW; 1.2489118006869346 W/m^2 = 1.2489128 W/m^2\n",
+ "0.23056602641189058\n",
+ "0.8042223095666693\n",
+ "-0.03478833597856455\n",
+ "all sky:\n",
+ "515.034057095216 PW; 1.0097430530043008 W/m^2 = 1.0097504 W/m^2\n",
+ "0.16410614491583508\n",
+ "0.709068870009622\n",
+ "0.12682498507453116\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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m5JOQY31TCOcs3b1j6RedzRVtmxDZZni5GTRwXNe6vLNiP1NONuXNgDBrXCSTXIqVb1f+MWcHX9zZlRoh/gx5+2eubl7dpXMfm7mVt2/qQItaweTblQMJacWf5IKvNx6jaY2qbkkuefl2vL3MkINFSkuAQz9D70f5asNRjiVn8u8bWnm+Ul0Er7pd6FG3Cz3sdl44sZXtG1axbHc8K1OieHejH29v3IQ3+TQPzqZVjUBaN4yhVYMYGlWvWioJx4yK7EROnp2UjBySM3I5dTaL46dTOR4fz7GEFPYnZrL/rI0Mu/UnFOw0lBP0sh2hU/UcujasTsOWHZGYoeBb/to/hAT4cFPXOnzw0wEe7ziWmNhPIDvt9+HkjUJtOZpC3WqB1Klm/Zte37YWS3aecuncxLRsooKtp1gvm9C4ujXfTkZOHv+cs4PYU6nk5SsPX9WYAS1rMGvDUZbsPIXdrsSeSuXu3g3Izbfz7abj+Hrb+OT2zqzef5ptx8/w8Iwt+Pl4Mfu+HvR/9UdGdIxm2a5T5OUr/xvXgUZRVZzeZ0VsPNm5djJy8pk+oYhxzozzRWKZTYby5qf76FIvnCuaRHo6qgvZbNhqt6dN7fa0GQqPZCSRtm81G7ZtZ+2Rs2xNDeH7PfWYvucoYA1kWtsviwYhQt1qQdSODKNW9erUrlaValX8CA/yJdjf+6ITqEkuDv/4dAHrjmeTmQeZ+UJGnpCW/+c/jw07NTlNA9sJRnkn0ihEaVajKi0a1ScwpitE3V740Onl0B096/PxLwf5IKs/z+W+Y8390WaUp8Mq106dzaJWyO9judUM8WfL0RSXzr2zVwOunLySbg2qcUXTSEZ0iMbfx4u3l++jR6NqvDKyLWcyc7nhf7/Qq3EEYPX2/v7B3mTn5tP3lZU8eU0zFjzUm3/N28k3m45zZ6/6fLr6EM9c15w20aHn7xUe6MP3D/bm818PMXXVAV6+sY3T+2w6nMKih3sTGlgx3rses2M2RDRh/slQElKP8Mbodp5/ailOYDhV2gymb5vB9AXIyUBPbuPI3u3sPBzH/sQM9qd6sy8him3xkaTsygMuHIHbR+xU9c4jwEsJ8lYCfeCju690ettik4uILFPV/sVtq+iqJmwiOi2fQLIJlBwCvfIJC7AT6i+EB3gTGexP7YhwqkdVxzu8AUQMgirVK3QleI0Qf25oV5uvfovjoZAmhG+bZZJLMQrrc+zqO+ChqxpzQ/tarNqbyJwtcczdEsdX93Tnp72JLN11iimrDgKQnZtPnGPcqe4NqlHFz5sqft5U9ffmKkcRXLMaVdl18myR9xrUyqr7aVU7hEU7TgI4vU+vxhEmsRQn9RQc/gX6PM7MDUdpEBFE94YXMSZceeEbiNTpSt06Xal7bpuqNYtt8iHSEo4Qd/IUcadTSErPISkjj9NZSmquFxl5NjJyfMnAD19xXoxeZHIREX8gEIgQkTB+/z8UDNQq+W/oGhH5CBgMxJ8bz0xEwoGvgHrAIWCUqiY79j0F3AnkAw+q6mJX7vP4X+61XvgEWqMMV+CkcTEm9GnArI3H+LzqXTy07ymrmWVQhKfDKrdqhPgTd+b3lvgnzmQRFexPWkL6n459bNZWdsSdpXqwH5/cbo16XLdaEDdXC2Js5xg6PP8Dyek5KMq74zvSMPLCIsnNR1Lw9f69/kNEzq+LWPU/RTl3nJdNyMu3jnN2n8By0HS13HMUie2veR3rFx/jyUHNyv9Ti6tErPrgkGiq1IMmWEuh8nOtwVb9gp1e0lnN3T3ARqAZsMnxeiMwB/if8zgl3IUl1Glkv/sEGPSHbZOAZaraGGsEgUmO+7YAxgAtHee84xiupnhBEdbiG3jZJBaAxtWr0qdJJNPi65Jrx5rj2yhS2+gQDp1O52hSBjl5duZtjePqFoVX6E8e2ZaFD/U+n1iW7z7FueGWDp1Ox8smBAf40KdxJJ+uPnR+3/bjZy4qpip+3qRlFz+FQknvc9nb/g1ENmPmQV+8bMKIjp5p7elxXj7WXEbFzFtT5JOLqr4BvCEiD6jqWxd5+zjH4uxT2guoU9yFVHWViNT7w+ahYBUfAp8CK4EnHdtnqGo2cFBE9gFdgF8vIvbLzs3d6nL3ZwksqzaEQdu+toZwNwrl7WXjX0NacctH68i3K6M6RdPEUTH/9Oxt/GueNStlzVB/Zt/X84Jzv910nOfn78Lfxwtvm/D6mPZ42YQH+zfmuXk7GfT6TyhKdFggH93W2eWYbuwYzd9mbz9foV+Ukt7nsnZ6Pxz5ldwrn+ObVcfp1zSKqKqm6bczrgxceUth21X1MyfnbFbV9sVct9hjChxbD5hfoFgsRVVDC+xPVtUwEXkbWKOqXzi2fwgsVNWvC7nmBGACQJ06dToePnzYlVAqjIsZxC/frvR+eTkNvBP5In0CPLwNQovN+2USm2G4qlTfV8ueh59fY8l1q5nw9QGm3tKpyCfWUo+lHHE2cKUrDdo7F1h6A88CQ4o5p7sL13XlmItV2JNSodlTVaeoaidV7RQZWc6aEpYxL5swtksdfj5dhYP2GrDtT7nYMC5f9nxrGuOG/Zm5I43Iqn70a3p5f2a4otjkoqoPFFjuBtoDTpuVqGqxE0G7cowTp0SkJoDjZ7xj+zGg4Mhx0VjFc0YxRneJwdsmfBk43hprzDAMy8Ef4exx4puOY0VsAiM6RJuOpi64lL9QBlDkBN0icrWITBWRdo71CZcYmzNzgXPDBt+K1cjg3PYxIuLnmNSsMbCuFO5f6URV9WdgyxrMSm9H1qm9cHyjp0MyjPJhyzTwD+Xrs83P17MZxXOln8s8fi9a8gKaAzOdnHIf1uyVf3M0GW5XkgBFZDpW5X2EiBwD/gm8BMwUkTuBI8BIAFXdISIzgZ1AHnD/uUnOjOKN71aX77edYJ5/X0au/9AjUyAbRrmSdQZ2zSO/3Ximb4yjS/1wGkSaUSxc4UoP/ckFXucBh1X1mJPjE1Q1BXhMRF7Cqqu5ZKo6tohdhXbiVNUXgBdKcs/LVbcG4TSKqsIXGcMZuf0RGPBvCAz3dFiG4Tnbv4W8LH4MHcHRpGSeGNjM0xFVGK7UufwI7AaqAmFATjGnfF/g3ElAka3KjPJFRBjftQ5b00L4LacmbPnS0yEZhmdtmQaRzflsjzeRVf0Y2NJDox9XQMUmFxEZhVVvMRIYBawVkRuLOl5V5zjOi3CsX2wfGcODRnSMJsjXi0/8b4b1H4Ld7umQDMMzEvfCsXUcbnwzP+5NYGyXOheMmGA458pf6hmgs6reqqq3YHVK/LsL531UosgMj6jq78OIjtHMT2tKYtJpOLDc0yEZhmdsmQbixZcZXbGJcFOX0uv7VRm5klxsqhpfYP20i+ddPmOoVDK3dK9Hjl2YYRsM6z7wdDiGUfbs+bB1BlkNBzHztyQGtqxOjRDTI/9iuJIkFonIYhG5TURuw6pTWeDCec67/hvlVqOoKvRuHMEX9gHkxv4AyZVr9ALDKNaBFZAax9zgMaRk5HJzt3qejqjCcaVC/3HgfaAN0BaYoqpPunBt8+RSgd3avR4ns31ZbO8Mm0ybDOMys2Ua6h/G54dCaRxVhW4NTKvJi+VS7ZSqfquqE1X1EVWd7eK1nypBXIaH9WsWRUx4AJ/6jIRtMwufyMQwKqPMFNg1n23172BbXCo3d69beYbWL0Ol1vRBVbeX1rWN0udlE27tXo/1GTXYkSRwdK2nQzKMsrHjW8jPZlZeb/y8bQxtd5kOrV9CpdquTkQ6ichsEdkkIr+JyDYR+a0072m4z8hOMfj72JhmHwC/ORuUwTAqkS3TyIpszZy9OQxsWYOQAB9PR1QhFZlcROQGEYkq4fW/BD4GRgDXY80oeX0Jr2mUkZAAHwa2rMF87Un29nnWDHSGUZklxMKx9SyNupOzWXmMNOOIXTJnTy7jgc0isldEPhGRCSLS8iKvn6Cqc1X1oKoePreUIF6jjA3vEM2ZfF9WpNeFfcs8HY5hlK6t00G8mJXSmFoh/vRoaKb8vlRFJhdVvVFVawNXA0uwWot9JiIJIuJKU2SAf4rIByIyVkSGn1vcELdRRno2rEZkFV++5Ur47StPh2MYpWvXfE7GXMNPB84womM0XjZTkX+pih24UlUPiYg/EOBYzr12xe1AM8AHODeOiALfXnyohid4e1kVmp/+kkXy7g8Jy04Fv6qeDssw3O/0fji9l29CJmJXGNHBFImVRJHJRUSexpotMhKIBdYAbwMTLmIY+7aq2rrEURoeNaxDbT74+SDzs9tx86750K6ogaoNowLbuwRV+OZEJF3qVaFeRJCnI6rQnNW53ALUBBZhVcxPU9XNFzk/yhoRaVGSAA3Pa1EzmKbVq/CtXGX1eTGMymjPIjYF9+dAcg43mor8EnNW59IMGABswJqsa7aIrHPMMnm7i9fvBWwRkVjTFLniEhGGd4hmc24dDu7bBRlJng7JMNwrOxUO/cLXPoMJ9PXiutY1PR1Rhee0n4uqJqnqfOAfWD3uZwH9AFdHMxyENdXwAExT5AptaLvaCDA7rwfsNyMlG5XM/hXk5NtZcLoGA1pUJ8jPlXkUDWec9XMZIiIvichPQDzWjJSRwKOASzPmFGx+bJoiV2w1Qvzp2agas/UKdO9ST4djGO61dzGrvLtzJlsZ0q6Wp6OpFJyl59uA1cATwEZVLW4GSqOSu6F9NI/tO82W3Xtpb7eDzUycZFQCdjvsWcJc34mEqg+9GkV6OqJKwVmdy3BVnayqv6pqjohUE5FhItKxLAM0yo8BLavja1PmpTeDk1s9HY5huMeJLWSkneGHszFc06qmmW3STZwVi80XkVaO1zWB7cAdwOci8rCzi4rIwyLSWURMwWUlEuzvQ9/G4czP707+HlM0ZlQSexazzN6BzHxhSFtTJOYuzlJ0/QIjG98O/KCq1wNdsZKMM9HAG0C8iKwUkRdF5DoRMZMiVHDXd6hHPGGs37bT06EYhnvsXcxc32uJqupHl/rmI8pdnCWXgqMU9scx+6SqpvJ7b/tCqepjqtoDq+L/aSAJKyFtFxHzqVSB9W8eRYAtn3knQ02TZKPiSz3FmeOx/JhZn8FtapnhXtzIWXI5KiIPiMgwoANWZ0pEJABrOBdXBADBQIhjiQPMxCAVWKCvN1c1DGRhfhdy95omyUYFt3cJi/M7k2O3mVZibuYsudwJtMRqNTZaVVMc27thDaNfJBGZIiK/AF9hDSGzGhipqp1U1dUOmMUSkUOOjplbRGSDY1u4iPzgGM35BxEJc9f9DMv1XVuQRDCrN5lKfaOC27OIudKPOuGBtI0O8XQ0lYqz1mLxqnqvqg5V1SUFtq9Q1cnFXLcO4AecBI4Dx4AUN8RbmH6q2k5VOznWJwHLVLUxsMyxbrjRFc2qU9Urh3mHxGrGaRgVUW4WCXs3sDq3Mde3rWmmMnazUmlzp6qDgM5YHS/B6ni5XkSWiMhzpXHPAoYCnzpefwrcUMr3u+z4eXsxsA4szm5N9rEtng7HMC7N4Z+Zk90BO8INZipjtyu1Bt1q2Y7VEGAh8AvQEHjInbcBlojIRhGZ4NhWXVVPOGI4ARQ6m6Zj8rMNIrIhISHBjSFdHq7v1opUAlm5+ldPh2IYl2bPYr62X0Hb2sE0rm6mkXC3S0ouItK5mP0PicgMETkKrMIaUywWGA64s61fT1XtAFwD3C8ifVw9UVWnOOqAOkVGmh65F6tHq4ZEeGUwa1eGKRozKh5VduzYym57DDd2ivF0NJWSy8lFRFqIyL9EZC/wbjGH1wW+BrqoagNVvVlV31HVrarqtk8iVY1z/IwHZgNdgFOOTp/nOn/Gu+t+xu98vGyMaebNsuxmHN2+ytPhGMbFSdjNNymN8bUp15uOk6XCaXIRkboiMklEtgKfA/cBVxeoPC9KX1X9+lzxVBHX3nTx4V5wfpCIVD33Gmvk5e3AXOBWx2G3AnNKch+jaDdd0xcBpq3Y4ulQDOOi5O5ayJz8nvRvHEZooK+nw6mUnM1EuRqrb8oM4EZV3SsiB1X1kAvXbVbMvC3iuHZJVMeaYwas32Oaqi4SkfXATBG5EzgCjCzhfYwi1IoI46rwRL46UYOH05Lxq2JafRsVw8otezhNU0Z0beTpUCotZ2N/JWAN41Ida6j9vVgV6K5o7sIxFzOj5Z+o6gGgbSHbT2ONKGCUgVt6N2XJnGQWLFnEsOFm+mOjAkg/zTenqhPhm8sVTU19a2lx1s9lKNAa2AQ8JyIHgTAR6VLcRYuax+UPyzH3/RqGp/To0o0G3ol8/luap0MxDJck71jKMnsHhrYIxcfLjIBcWpyOWqyqZ4CPgI9EJAoYA7wuIjGqappYGNi8bIxrCs/vqMX27b/RqlUbT4d0Xr5dSUtP52xKCmnpZ0lLSyMtI4OMzCwysrPJzMohIyePzJw8snLtZOXmk52vZOcp2fmQY7eWXLv8vqiQr0KeCnYV8rF+Khd2wBMUmyg2wEvseIviJYq3KN4C3jbFS8BbFJuAtw1s4liwfhakgF0vXPLO/bRDniOmPLucf52vQp4jPrvj5wUxCthQbFixeYkdH0ecPmLHx6b42MDHpvjZFF8v8PMS/LyEAB8hwMeGv48XAb7eBPr5WkuAH1UCAqgSFERQUBWqhoQQHByGn69P+eikmJnCt8tXk8sARvRu5+loKrVih8QXEX+gEdb7e4qqvikidUs9MqPCuPGaq3llxxq+WLaBl0ohuagqqWnpnE48RVLSaZJSUkg6m0ZSaiYpGTkkZ+aRkg0pOcLZPG/O5vtw1u5Pmvo7uao3Bd/+vuQQQA5+kudY8vGVfHxtdnzFjp9NCXJ82J5LEl7ye0IQQEQd8QrqiDtfIV+FfIU8u5CrYFchLx/y7DayHB/8eY5EhQp2IB8b8odSaC8UESuNeYuVFM4lLV9RAm2Kt7cjgdnAW8DL5khWjp8FP99/T1SO+BTyHYkqxy7kKeTm2siw28hRG9nq5Vi8yVYfMvEl708fIbmO5ewFW33II1iyCPHKJtg7lxCffEJ9IczfRmigN+FB/oRVDSI8pCrh4eFUC48krFokPj5unLUjN5M57/+dl1KuoksNGy1qh7rv2safOKvQ9wZexBrN+DDWezNaRD4Gnimb8IyKICSiFsPCj/DViYbY3p/FI6MHEhkaXOx5aenpxJ+KIz4+noSkZBJSUklIzSIhPZfETCExx4vTuX6ctgeR86exUv0AP3zJIUwyCPXKIsQ7lxi/bEJ8IdhXCPb3oqq/N1UD/KgS4EeVAH+CAgMICgwiKDCQgMAgawkIwuYbCF5m+qGLkp9LblYamRkZZKSnkpGZQXp6BmkZGaRnZJCemc3ZzGxSM3NIzc7jbJadMzlwJsdGcrYXB9P9SLYHkEpggYumO5ajAIRKOtW8Mqnmm0Okn52IQBuRVXyJCgkiMiyEyIhqREXWpFpk9WJizeOjd1/mXycH0TXKztR7ryqtv4rh4Ox/0ytAVax5XVIBRCQYa0iXybi3p71RwT09bhB+n33NFwdbM/flH/hL82ya1q5mPWGkZXI6LZtTafmcyrRxMsubBHtVMhavLHAFAYLxIZBqkkqEdxYRvtk0q5JFtcBUIoJ8Ca8aQHhwVaqFhRIeFk54tUgCqoYhJil4hpcPPkFh+ASFEVyCevHcrHRSkhJITj5NUnIKSWfOcPpsBqfTskhKzyUxU0nM9mLXWT8SkoMKJKMc4ARwAht2633jlc6Xv+4hKlCoFuhNgI+NAB8bB04m83liZwbVyuT1vwzD38fLDX8Awxln/ysHA01U9fyzuaqeFZG/ALsxycUooGrtZjw76Rlu2bSM/yzYySs7G8LOPMAf8MePHGp4naW6TxaN/VLp6pNAg5rhRIUEERUWQlREBJGRNQipVh2bj+l3cDnx8Q8islYQkbXquXR8VtoZEuLjSEhIJD7pNAnJacSnZnIo4SxJuT4czwxic2oQSRqEnm+zVI2bYk7z/F9uNnO2lBFnyUULJpYCG/PlXOGyYRQkQoOOVzG1Q39it28gOzubsLBqhFeLILDAE8aKFSsA6NevnyejNSoo/yohxFQJIabBhdv/+L7S/Hyys7PIzMwgX5WIiEKHGTRKibPkslNEblHVzwpuFJHxWE8uhlE4EZq2djr8nGGUOvHywj8wCP/AIE+HcllyllweAL4WkTuAjVitxTpjzS45rAxiMwzDMCooZ8lljqp2EJH+QAusGteFqrqsbEIzDMMwKipnyUUAHMnEJBTDMAzDZc6SS6SITCxqp6q+VgrxGIZhGJWAs+TiBVQBTLs9wzAM46I4Sy4nVPVfZRaJYRiGUWk4GxLUPLEYhmEYl8RZcjFzohiGYRiXxNl8LkllGYhhGIZReZiZcgzDMAy3M8nFMAzDcDuTXAzDMAy3M8nFMAzDcDuTXAzDMAy3M8nFMAzDcDuTXAzDMAy3q7TJRUQGiUisiOwTkUmejscwDONyUimTi4h4Af8DrsGai2asiLTwbFSGYRiXj0qZXIAuwD5VPaCqOcAMYKiHYzIMw7hsOBsVuSKrDRwtsH4M6FrwABGZAExwrKaJSKyb7h0BJLrpWu5iYnJNeYwJymdcJibXVPaY6ha1o7Iml8JGdNYLVlSnAFPcfmORDarayd3XLQkTk2vKY0xQPuMyMbnmco6pshaLHQNiCqxHA3EeisUwDOOyU1mTy3qgsYjUFxFfYAww18MxGYZhXDYqZbGYquaJyF+BxVjTNX+kqjvK6PZuL2pzAxOTa8pjTFA+4zIxueayjUlUtfijDMMwDOMiVNZiMcMwDMODTHIxDMMw3M4kF8MwDMPtTHIxDMMw3K7EyUVEVorI2072rxOR4SW9j2EYhlFxlMWTy/PAyyJinpIMwzAuE2Xxgb8AqIo1QrFhGIZxGXBXcvEWkTdEJNmxvHLuSUVV87ESzFg33cswDMMo59yVXMY5rtUduAdrtOGHC+xfB1zhpnsZhmEY5Zy7hn85ATyoVnf/3SLSBJgIvObYHwfUFhFvVc1z0z0NwzCMcspdTy5r9MJxZH7FSibBjvVMrGHw/d10P8MwDKMcK6sWXOFAlqqmXeyJIvKRiMSLyPYC254VkeMissWxXFtg31Misk9EYkVkoJviNwzDMC6Cu5JLVxEpOEFXNyBOVc861lsBmy7x2p8AgwrZ/n+q2s6xLAAQkRZYw+u3dJzzjoh4XeJ9DcMwjEvkruRSC3hdRJqKyI3A48D/FdjfG1h0KRdW1VVAkouHDwVmqGq2qh4E9gFdLuW+hmEYxqVzV4X+l1jzpqzFmk74QxzJRURqAz2A8W661zl/FZFbgA3Ao6qaDNQG1hQ45phj25+IyASsVm0EBQV1bNasmZvD86zU1FQAqlat6uFI/qw8x2ZUXOXpfVWeYilNGzduTFTVyML2lTi5qGrfAqt/LeSQh4FPVPVYSe9VwLtYPf/V8fNV4A6sRgN/CrGwC6jqFByT5nTq1Ek3bNjgxvA8b8WKFQD069fPw5H8WXmOzai4ytP7qjzFUppE5HBR+8qiQj8e+Ls7L6iqp1Q1X1XtwFR+L/o6BsQUODQaqxm0YRiGUYZKPbmo6iuqesqd1xSRmgVWhwHnWpLNBcaIiJ+I1AcaY3XgNAzDMMqQu+pcSo2ITAf6AhEicgz4J9BXRNphFXkdwhoVAFXdISIzgZ1AHnC/Y/gZwzCM0pOTAaf3QmYyZCZT4+RG0oPqQn4v8PLxdHQeUe6Ti6oWNibZh06OfwF4ofQiqqBUQQqrkjIM45LlZMD6qfDz65D5e6PW5udebPsH1O4IzYdApzvAq9x/5LrN5fObXk7sdsKSNhNxej0cfxuSD0HKEQiKtN7o0Z2gXm+o3cHTkRpGxWS3w/oPYNUrkB4PDftDh1us/2MBYazZsJmqaQdoGZwGh36BhY/Dpk/hulehTjdPR18mTHKpTDJTYMs0WP8B7ZL2k+cVAFFNoXoraHoNnD0BxzfArrnW8R1ugYEvgl/lbi5pGG6Vnwdz7offZlhf0kZ9BnW7X3BIZuApMgNr0bJfP6vUYPd8WDgJPhoI7cbDoBfBP8RDv0DZMMmlstj7A3w7wXo0j+nKzqghxEf2oG//AX8+Nj0Rfn0bfnkDDqyEG96Dej3LPGTDqHDycuCbO2DXPLjyb9D7seKLm0Wg+fXQ8Er48b+w+i3rS97YGRBev2zi9gCTXCq6/DxY+SL89Kr1hHLzt1CrPacc7ewBsvPy2XQ4hczcPIJ8vQny86F616eIbDIIZt8Ln1wHVzwJfSeZehnDKEpuJnx1M+z7AQb+B7rfR75dWfBbHO/9uJ89p1Lx9bLh5+OFzZ5LszAbuVEn6dMkEn8fL/ANgqufs5LMzFtg6pUw+otK+8XOJJeKLPUkfH0nHP7ZKuK65r/gEwDA6Uw7m+Lz+ezjdaw5kERm7oWN5mwC47vVZeItKwhd+RT8+BIk7Yeh/wNvP0/8NoZRfqXFw1fj4eg6uP4N7O1v5ev1R3n3x/0cTEynQWQQd/SqT16+kpNnZ9fBY2yMz+fnzzcS4ONF78YRXNWiOlc2iyKiwRVw93KYNgo+G2rVw3S81dO/oduZ5FJRHfwJvr4DctKsYq12Yzmdls2iTYeZsyWOdQezAKgfkcGoTtH0bhxJtSq+ZOTkk5adx097E/hizWHmbo1j4lVPclPfRnivfB7OHIPRX0JQNQ//gpe5vT/A6X0Q2RQim0PVGuap0lNO/AbTx0LGaRj5MSn1r+PhT9ezMjaB1rVDeHdcBwa0rIGX7fd/nxUrEsizKwF12rB4x0mW7jrFkp2nEIF2MaF0qR9Oh15f0WHz34mc9yAcWw/XvnL+y2FlIBdOw3J5qlDDv9jtsPoNdOm/2BfcjTWtn2Vzkh+bj6ZwMDEdgIaRQbQJyaFLDS/GDu5f5KV2nzzLc3N38uuB07SNCeWNDqeot/ReCK4JN35caq3JLpehMS5Z0gH4XzfIz/59W0gduG0+hNX1XFzlXKm8r3bOsYqOA8JgzDS22etz7xcbSUjN5u/Xt2B81zpIIUn/j7GoKjtPnGXpznh+3BPP9uNnycm3A9CsSiYjsr5haI1kom56t0LVw4jIRlXtVOg+k1wqTnLJSz7KomlvsvS4N6u9OhKfa33LiajiS/s6YbSvE0qfxpG0rBXMypUrgeL/o6kqc7fG8ffvtpNnV/7ZM4BR2/+CpJ+Cfs9Az4fA5t5ZC0xycUIVvhzJ5/v82NrgbsK9cwjPT6DRvk/o364JMux/no6w3HL7+2rdVFjwGER3QUd9zozdOfxzzg4iq/rxzrgOtI0JveRYsnLz2RF3ho2Hk1m4/SSbj6TgRT59vXfw134NaH/lqArxpOosuVxUsZiI2IAqBeZpMcpATk4u382ewTtbczlk70uEXz7dm0bTs1EE3RtWo054YKHfnlwhIgxtV5vO9cJ5dOZWnlxxmpXNP+Slmh8Qsuw52L8chk+1nmaM0rd7Ptv37OEfOS8SfDCHrNx8svNCgYd5c9P/GNJ7H0Q08nSUld/qt2HJM9D0WrKGfsDfvt/H1xuP0adJJG+MbkdYkG+JLu/v40XHuuF0rBvOhD4N2RefxrertzNzfTbDfghk0Jr/8fio/jRs3Lz4i5VTxSYXEZkG3AvkAxuBEBF5TVVfKe3gLne5+Xa+Xvozb/90nON54bTyT+S9a2IY0Lk1Npt7v9XUCg3gy7u6MvWnA7yyOJZdYeN594qraL76Ufh0MNy+CKoUOrK24S456eiCSTwrDxAe5Mfyx/oS7O9Nek4+I99ZxeT4kQxa8TK+I6d6OtLKbdVkWP48tLiBw33f5N6pm9h14iwP9m/MQ/0bX1C34i6NoqrwxA3duH9gBz6Y9S1Tdtbkhw/3MjJ6I38ddQ3RURWvDtSVgStbOJ5UbgAWAHWAm0szqMtdvl357sf1XPXcTJ5akUokSXzcN4t5/7iZQV3buD2xnGOzCfdc0ZAZE7qRmZvPsOWhfNtlOpyNg8+HWeMmGaVn1SvMSanLhuwYnhzUjJAAH0SEKn7ePHltK45oFNO3pkD8Lk9HWnn98oaVWFqPYlPnV7n+nTXEpWTy8W2dmXh1k1JJLAUFBfjy0C1j+PGhTtwcuY9vj1Wh32s/87cpMzmZlFqq93Y3V5KLj4j4YCWXOaqaSxFzpBglk52Xz8xlaxn4r694eGE8AXkpfNjxMLP/djP9Bo1AbGUxQwJ0qhfO/Ad60y4mlInL0ni10SeQGAtf3AjZFesNXmGc3k/aLx/wInfSNjqEGztGX7D7iiaRdK8XzJv5w0lbZgoNSkXcFlj2L2gxlK2dX+bWTzYSFuTL/Ad60a9ZVJmGElGzLs8+OpGVN0cyMmQXMw740ee/y3jq/W/YH3e6TGO5VK58Wr2PNfJwELBKROoCps7FjZLSsnln9lJ6P/stT/yQiHdOCm+1iGXB0zfSf+R9iH9wmccUWdWPL+7syqhO0by1OY8Pmn8McZthxk1Wx03DvTZ/zlu51xOf68+zQ1r+6elURJh0XWtOazBTt2M1jzXcJy/bahUWFMm2ji9w80frCQ3yYfrd3YgJD/RYWLVa9uTFSU+yYqQfN1bdzjcHbfR/cw13/d8Mft11iPLcIKvYOhdVfRN4s8CmwyJimvmUkN2urN55kBkrNrDkuB85eNPL+wiTOwXQ+5rRSDnoZ+LtZeM/w9uQmpXHvzecJLTLe9z4292w5n9WKzLDPex2Dm9ewUf5j3Jjx2ja1wkr9LC2MaFc17IaU3dcx7gV7xB103tlHGgltuJFSNjFjkEzGf/FLqr6W4mlVmg56HciQkzHQbzYYSATd67ks0W/8NmpRiz9dAf1/dYyul0EI/r3JDLY39ORXsCl1mIich3QEigY/b9KJaJKTFXZfDCeBT+vZ+G+DI7nBBGCMi54K2O61adp7/vKXScqL5vw+ph2nP1kPU9uEILr3suA5S9Ak2sgsomnw6scjq1jRkpT7Nh4fGBTp4c+dk1rFu9M4N1d/vwzJ90aUsQomaPrYPWbHGsxgVuXehHkK8yY0I3oMM89sRRKhIiW/ZjYsh9/OfobC5Ys4qsDvry0tgqvrF1Cz2oZDO5YnwHd2hMaWLLWbO7gSmux94BAoB/wAXAjZnZHl2Xm5PPrrkOs2LidZYdyiMsJxId8evsc5ImmwsCrBuIfM9rTYTrl5+3F+zd3YtzUNfz1yBVMD1xHxzn3wR2L3d4H5nJk/20Wc+y96NOoGtWL+fZZPyKIaxr4Mmd/V56OXYJP62FlFGUllZMBs+/lTJWG3H70WrLzcph+dw+PFoW5IiCmDSPubMOInAz2rZnL12v2siCpNk8sSeTpJYvoFp5OvxY16d+1A/Uiy75YHVx7cumhqm1E5DdVfU5EXgW+Le3AKqr07Dw2H4xn/badbDh0mvVJ/uSoNwHk0dNnH482Eq7q0ZmQpo9WqImDqvh58/HtXRj+zi/cnfYo3x6ZSL0170CPBzwdWsWWn8u6rduI0yt5smMdl04Z0qMN8/Zv4pc1q+hrkkvJrHiBnNOH+Eu1Lzl0KpNPb+9C4+oVaAoK30Aa9RnDpD7w5NmTbP91EfO3HmVpcnWe/zmY53/+ifp+aXSt5UWXZvXo3Lo50WGX3i/uYrjy6Zbp+JkhIrWA00DFGZ+glNjtyvGUTA7EnyX2wEF2HD7FjoRcDmT4Y8eGYKeZJDK+ajz9GoXRpUt3/OrcUKG/6YcH+Z5PMLfnP8e3y54hrPFAUzxWEgdW8l1Ga4K8YUCLGi6d0qdpFMFeucw97E1fUzR26Y6sRVf/j6dDXmF1nJ3JI9vSo1GEp6O6ZBJcg9YDb6P1QHgqI4kjW1awYuseVsXZWHCwPjMOnoKFp4jwzqRVaC4ta1alRYM6NK5Xl7qRVfDzdu9nkyvJZb6IhAKvAJuwmiFXul5cqkp2np3MnHyy8vLJzMknOSOXlPQsks+cIT4xiRNJZ4hLyeR4aj4H033J1t//fDU5S0uvo1wblkXHOiG0b9WC4IZjITDcg7+V+9WPCGLqLZ24aeoaJuQ/xOfTxuF/5wLTwfISZW39hu/z+zOwXU0CfF37z+3n7cU1jQOZv7s9WbuW4N/WPL1ctNxMmHM/L3vdxdfxtXiwf+M/Nf+u0ALDqdNjBLf2gFtVsSfuI3bbOtbFHuO3hHx2nA7jp8Qg8rcdBY5iw04dvwxiqtipHexDrbAq1IgIo1pYGKGhYYRXDSTI1ws/Hy/8vG34eduKffpxpbXY846X34jIfMBfVc+U/LcvX8b9dzqrk53PDBdCGjXlNLUliV5BmTQI9aJhVFUa16tDeL0uEDGuQj+ZuKpTvXBeG92Ov05T7okfwXtfjCXg9u/Ar4qnQ6tYcjJYvv0YqQQy3MUisXOG9GjHV7vXs3zNaq41yeXirfwP75xqxnt5/RjXtQ6PXNXY0xGVHhFskY1pfmVjml/p2JaTQVbcDvbt3cX+uET2J2ayP9XGsaQgdp2uRuLBACDRsRRu3cSOTm97UYX+qpoNZBd7YAU0qvoJenntIMBb8PexEeBjIyTQj7Agf8KCqxARHk5QRH0I7mUNf34ZJBFnBrepRXp2Hk99C+OP+PHR9LsIGf8ZeHu+lUqFsWchs3M6ExUodG94cU3PuzWKJNInm7lH/LjWFI1dnMOr+WLVDv6bdwdD29Xi+aGtyqQOolzxDcS/Xmda1etMq4Lb7fmQepKs00eJPxVH8pmzJKWmk5yWSUZOnmOsO6uUJzigh9NbVJwa5VJ2w22PejqECmd05zoE+/vw0HRldKwfn315D1FdhkN0F6ha3dPhlXvJm+ey0j6c2zrUvehhRbxswnVNqzJte2vO7lhCcHvz9FKsUzs48sM7fL0ri7fyb6N/kzAmj2xbasMpVUg2LwipjX9Ibeo0sMb6ulQmuRglck3rmlT178aET5Srd1Wjbew2mskCmlbJoGZ4CCHhEYRWq0G12g3xr98dfMt3E88yk53K93szycWbGzpcWln/kF4d+GT7GpasWcuNJrlc4ExyAof2bCc58RQpyYnEJSSxJD6YLXotAAOahvHm+K74eJXNkEqXI1f6uSxT1f7FbTMuX70aRzDzvj589NM+dh8L5ZOkNuScETgDHLSO8SaNFrYP6RCSRnRAHvXqXebDxu9ZzHe53WgS5kWLmpfWD6F93XBi/DKZeyyQGy/zorHE1Cx+3XOMQ4lpPL/8GAdyzzWkqepY6tOiaiaTutRhcKeG5a+DZCVUZHIREX+szpMRIhIGnHt2DAZqObuoiLjSRMquqinFHSQiHwGDgXhVbVXg+l8B9bDGPRulqsmOfU8Bd2JNEfCgqi52IRajhFrVDuG1MVYFX26+ncOnM0hMyyYlI4eUlGSOHD3CpsPV+ColmsxkX/zichi04y1G9WhK9579sbm5GWR5F7d1KRv0eh7v3KBEc/Fc3zyE97e0IPG3H4jodIN7gyznsnLzWbL1ELN/2sKqU77kE04kNtoFJTKiXjaN69WlWlRtQiNrUS04sFz0Wr+cOHtyuQd4GCuRbCqw/SxQ3HR4cY7F2f8aL1wr0vsEeBv4rMC2ScAyVX1JRCY51p8UkRbAGKyhamoBS0Wkiarmu3Afw018vGw0iqpCo6hzrcdqAi0AyMu38+XXs9l8II7lZ2swZ2Eu9X74kkd7V+e6qwdcHuXfuZl8v9fqPja4be0SXer63p14Z8tqFq3byvjLJLnk5Nn5anUsby/bzalsX2qRxoSQfbSp7k9QdBv6DBjn6RANnCQXVX0DeENEHlDVty7yurtUtb2zA0RksysXUtVVIlLvD5uHAn0drz8FVgJPOrbPcLRqOygi+4AuwK8uR26UKm8vG3WiwqkTFc5L3bqx+IeFvLsulwdW5DFlzWc8dX17enRo4+kwS9e+ZczP6UjrCKFutZIVZTWrFUqDgDS+Px7I+Nws8Clfgxe6k92ufLvhMK8v2sqxDG86yUEmN06g54Dh2KJvYcXKlZhvkeWHKxX6Z0Tklj9uVNXPCjvYobsL13XlmKJUV9UTjjhOiMi5yRZqA2sKHHfMse1PRGQCMAGgTp2StIkwLpV/QABDhwxn8KBsvvv2S17d6sNNM49yzY/beO62IUSFVaBhOC7C4c3L2KpX8VSnktc7iQiDm4Xw9uZA4rctI6rDdW6IsPzZdeIsz0z/mU3xShs5zAsxu+kzbAJSq52nQzOK4EpTic4Flt7As8AQZyeoalZxF3XlmEtQWJlKoRMeqOoUVe2kqp0iI03vck/y8vVjxJg7WP7EVTxeeyfLTgVy1SuLmbl0dbmer+KS5OUwPzYNgOvauqdH+OBeXbBjY/G6yjfHS3p2Hi9+t5HBb/zIofgzvBr6DXNub8YV9/3PJJZyrtjkoqoPFFjuBtoDRdaMicjVIjJVRNo51ie4LdrfnRKRmo7r1wTiHduPATEFjovGqvsxKgD/sJrc/8DjLBzuRzNbHE8sTebmV74iLrESzU13aBXzc9rRIRK3tVhqUjucxgGpzDvqD3k5brlmebBmfyKD/ruAKWtOMtL7J5b1O8qIR99BmgyAy63TYwV0KY28MwBnYyXcBzwOjBeRK4F2l3CP4swFbnW8vhWYU2D7GBHxE5H6jjjN9AAVTMMu1zLj6fE8X+83NiX5MPDVH/h2xdpK8RSzb8Mydmk9Bnd273Ajg5tWZX1+I07t+NGt1/WEzJx8np31K2OmrkUyEvkq5lteeuguwgY+UanrlCqbYpOLiMwTkbmO5Xsglt8/zAuToKopqvoYMACrOO2Sich0rAr5piJyTETuBF4CrhaRvcDVjnVUdQcwE9gJLALuNy3FKiZbYDg33/sUC4f50czrOBMXJ/KXN2Zy+mxm8SeXV/Z85seeRVCua+feer7rendDsbFwzVa3XresbTx4mmtfnscnG5O41WcFi4ZA179MNSNvV0CuVOhPLvA6DzisqsecHP/9uReqOklESjThh6qOLWJXoZ04VfUF4IWS3NMoP+p2HcyM5vF88PH7vHqiNQNens8LgxszqHs7T4d20fTQz8zLakvnKC12UrCL1ah2NZoFnGH+UV9uy8+rUHMFgdVn5f/mrmPq+kRqSTLT6m2kx9hJEFKJRiq+zLhS5/IjsBurm2sY4LRQV1XnAIhIhGP9YpsxG8YFvIKjuOfBvzFvUDY1SOTeOcd5+O2ZpKSVRpuQ0rNr9Tz2a22u79KsVK4/uGkVNuQ15MTOn0vl+qVl29Ekrv/vXN5fn8Ro319YNNyfHve8ZRJLBedKsdgorHqLkcAoYK2I3OjCtT8qYWyG8TsRmvYdzXePDeHhqM3MP+bH1f+Zy6JfXeou5XmZKUyPVXzFznXt65bKLa7tY7Xu/351xfibZOflM3n2am743y+cTU3jk/pL+c9jD1Gl81hTYV8JuFKh/wzQWVVvVdVbsDol/t2F88y7w3A7n7DaPPzIM3w3IJNIkrh3Thz3vT6D+JQ0T4fmVNqmr/k2tzuDmwYRHlQ6w5A0qBVJ68BkZh0OQrPL999j+5HTDHnpO95em8ww37UsGeFL3wmvQXBNT4dmuIkrycWmqvEF1k+7eF7Fb9pjlE8itLpyDHMeH8rjNbey9KQfV/93UbnuFzN79W+kE8DNVzoduKLEbu4aTay9NmtXOGtz4znZeflM/vpHhr6zmpS0DD5q+BOTn3iQkM6jzdNKJeNKklgkIotF5DYRuQ2rwn6BC+eZd4pRqnxCa3L/Q0+zcKgXTWwneGJpMje9PJ2DJ4qePc8TNG4LXyQ1p1VoDu1iQkv1XkP69SLUlsFn605COUu0vx04wZD/fMPbG9IY5reBJWNCufLul6BKVPEnGxWOKxX6jwPvA22AtsAUVX3ShWs/VcLYDMMlDbsP4aunx/Figx1sT/Fm4Bs/89asxWTnlY9W6OtWziNW63Bz7+alPuOhv683oxvaWZzRmBN71pfqvVyVlZvPS18uZNiU9aSkZ/Nxiy1MfmoiIe2u93RoRilyqROlqn6rqhNV9RFVne3iOdtLFpphuM4WGM5NE55g2c01uMo/llc35nHtv2eyZvs+zwaWm8nnu+wEe+UwxM0dJ4sy/tp+2BGmLVldJvdz5petsQx8fhbvbbMzIug3ltzZkH63PAP+IZ4OzShlpToNm4h0EpHZIrJJRH4TkW0iUvkGQDLKjaiWfXjnmYf4uOMhsrOzGfNFLBPfmUXi2QyPxBO/aT6LctsxskUQAb5lM2dNTM0o+oclMj0uiuzU02Vyzz86fTaTR9+Zybjp+5DcDKZ1Pcx/n3qCkMbO5103Ko/SnuPzS+BjYARwPdakX+ZZ2ChdPv70G3k/PzzYg/sjNjPviC9XvrSQzxasIt9ehvUQqsxYuZk8vBl/dUkGAb94t1zRkkQNYeGi+WV6X7tdmb74Z6586XvmHPHjvogtLHq4Dz2G3QfeZrKuy0mRyUVEbigwlP2lSlDVuap6UFUPn1tKeE3DcElAzSY8/ugzLBycR2uvI/xjVSpDXpjBxtiyeQsmrJ3Jh8ltuaJGDvWjynb6gF5dOtPAJ4lPf8sss4r93YfjuPGl6Ty14gzNbMdZODifJx59Gv/ql/mU1pcpZ08u44HNIrJXRD4RkQki0vIir/9PEflARMaKyPBzSwniNYyLI0KjXiP44uk7eLvFbhLT8xjx8XYmTZlNclp26d03O5V/LdhDJv78fUyhIxWVKptNuKVNEJtzY/jh+5mleq+s3HxenTafwe9u4PBZeLXpbmY8cyuNew03zYsvY0UmF1W9UVVrYw0MuQSrtdhnIpIgIq40RQa4HWtU5EFYxWHnisYMo0xJQAiDb3mUZfe15e7Qjcw64MWV/5nHV8vXYy+ForIV30xhXk4H7u8SSqMawW6/vituGjqE5n6JPPVLPsmnnA0HeOk27NjLdf/+ird+E4YE7WTpXY0ZcfujSEBoqdzPqDhcaYp8CNgEbAa2YM2dEuDi9ds6JuS6VVVvdyx3XGqwhlFSVeq04Zkn/sb3V6fQkOM8uSSeES/PYtuhU267R3pcLH/bFkHjgFT+MqS32657sXx9vXl1TCdSNIh/fDzHrcVjZ9Kzeer9mdz4+R6ycnL5pMsxXnv6UcIalWgQdKMScVbn8rRjuP01WH1WfIG3gTaq2s/F668RkRZuiNMw3Mdmo1n/W5g5aQyT62/i6Jk8hry3jmc+XkByegkn21Jl8hffEafhvDSqM77epd1mxrkWzVvyYNMzzEupx4IFJe+1r6p8t3Id/V+cw8yD/twVvpUlD/ag7/B7wMvHDREblYWzd/4tQE2seVG+BKap6uaLnB+lF7BFRGJNU2SjvLFVrc6N9/ydZbdFc1uVdcyIzeOKF+bz7rxfyMy5hA6YdjvffvE/Pklqwfh66XRs3tD9QV+Cv4wbQ2vfk/zt52wS409e8nU27T3CqJem8/CiBGqTwNyBmfzt8acIqlk2/XeMiqXISR9UtZmIhAM9gL7AJBGpAmwFVqvqxy5cf5BbojSMUhTSrA//nNSN0T98xMu/pPDyL358sm42D/erz7De7fD3Kb5/Sm5WBi+8M5VP4hvRNTiJJ28ZWQaRu8bH15dXR7dn8OdHGP/2It68uQdNGrs++db+E8lMnvkDC08EEYmdFxtsZ/TYO/GqGlGKURsVndMZhVQ1CZgvIouAjkAf4B7gDqz+K06ZZsdGheHtS7Nr7uXjvsmsnf8RL2/25qklAby8bA43NPJmVP/utKgTWeipx44d45EPFrA+qxF3NUhm0h034e1dNh0mXdWkZQfe73+Mx5b7cf2HO3iq825uHX59kcPR5OXbWb5lH1+s3MKqhCCCsPFI5AbuGjmMoDrjyzh6oyIqMrmIyBCsp5aeQEtgB9Z0w48Cnh9XwjBKQ0AYXUc+yjcDT/LLwi+YsTOLabGt+CR2HTG+aTSsmkv9MF+qV/Vjd1wyG0/7cDQvlAAieLNXHkMGl98P3n5XD2FRs708+fFCnl3fkAW7P6dX/RAa1Y2mYf0GpKSms2PvfnYeS+SX43ZO5AZSgywejtjJuAE9iGz9D9O02HCZsyeX27CSyBPARlUtYU2nYVQcElyDXqMfo5c9n+RdK5nz4zrWJwgHk4NZe7o6mXgTJd50DErklpppXN2rG/WatvV02MWKjGnMh0/X5cvPp/D+niBe+80bfjsJ/F4XE0E27bwP88+WPlw1YDDe1W/xXMBGheWszuWCzo4iUg2rWOyIqm50dlEReRj4BdisqnluiNMwPMPmRVjL/tzWsj+3AdjtaOoJzp4+RXDtvohfkIcDvHji7cv42//K+NwsMk7s4sC+Pew/fpLgAF9aNqhDVL3uEDoGbJ5t6WZUbM6KxeYDk1R1u4jUxOrrsgFoKCJTVPV1J9eNBt4Amjlah63GSja/OupxDKNistmQkNqEhNT2dCQl5+NPYJ32tKrTnlaejsWodJx9NalfYNj824EfVPV6oCtWhX6RVPUxVe0B1ACeBpIc52wXkZ0lD9swDMMoz5wll9wCr/vjmH1SVVMBu4vXDwCCgRDHEgesvfgwDcMwjIrEWYX+URF5ADgGdMDqTImIBABOu+KKyBSsFmapWMlkNfCaqia7I2jDMAyjfHP25HInVoK4DRitqimO7d0ovo9LHcAPqwnKcawEleLshEshIoccvf63iMgGx7ZwEfnBMZrzDyIS5u77Gsbl7rvvvuPuu+9m6NChLFmyxNPhGOWQs1GR41X1XlUdqqpLCmxfoaqTnV1UVQcBnYFzxz0KrBeRJSLynDsCL6CfqrZT1U6O9UnAMlVtDCxzrBvGJXn22WeZPNl6G3t5edGuXbvzy6FDh0p07TvuuIOoqChatXJenb5o0SKaNm1Ko0aNeOmll4o9/5FHHuH1118/vz5w4EDuuuuu8+uPPvoor732Woliv+GGG5g6dSqffPIJX331VYmuZVROpdbWUC3bsepqFmK1FmsIPFRa93QYCnzqeP0pcEMp38+4TAQEBLBly5bzS7169Up0vdtuu41FixY5PSY/P5/777+fhQsXsnPnTqZPn87OnTudnt+jRw9Wr7b6OdvtdhITE9mxY8f5/atXr6Znz54uxbht2zYGDx58wRIfH39+/7///W/uv/9+l65lXF5KJbmIyEMiMkNEjgKrsOZwiQWGA+FuvJUCS0Rko4hMcGyrrqonABw/C51N0zH52QYR2ZCQkODGkIyK7oUXXqBp06ZcddVVxMbGltp9+vTpQ3i48/8O69ato1GjRjRo0ABfX1/GjBnDnDlznJ7fs2fP88llx44dtGrViqpVq5KcnEx2dja7du0iLCyMZs2acdddd9GqVSvGjRvH0qVL6dmzJ40bN2bdunUAtG7dmvnz51+wREVFoao8+eSTXHPNNXTo0MHNfxmjMnA6tlhRRKSzqq53ckhd4GvgkXMf9KWkp6rGOaZj/kFEdrt6oqpOAaYAdOrUqQwnVjfKs40bNzJjxgw2b95MXl4eHTp0oGPHjgBkZmbSrl07AOrXr8/s2bP/dH7v3r1JTU390/bJkydz1VVXXXQ8x48fJyYm5vx6dHQ0a9c6b3BZq1YtvL29OXLkCKtXr6Z79+4cP36cX3/9lZCQENq0aYOvry/79u1j1qxZTJkyhc6dOzNt2jR+/vln5s6dy4svvsh3331X5D3eeustli5dypkzZ9i3bx/33nvvRf9uRuXmcnJxzMsyBhgLnAE6OTm8r6pOLOZ6m1S1RF95VDXO8TNeRGYDXYBTIlJTVU84On/GO72IYRTw008/MWzYMAIDAwEYMmTI+X3nisWKO9+dtJAJvooabLKgc08vq1evZuLEiRw/fpzVq1cTEhJCjx49ACtBtm7dGoCWLVvSv39/RITWrVsXW5/04IMP8uCDD178L2RcNpwmFxGpi5VMxgJ5WE8knRyzUzpzrmd+kZfG6vdyyUQkCLCpaqrj9QDgX8Bc4FbgJcfPks+QZFxWXPnwLoq7n1yio6M5evTo+fVjx45Rq1atYs87V++ybds2WrVqRUxMDK+++irBwcHccYfVB9rPz+/88Tab7fy6zWYjL8+M2mSUjLPhX1ZjJYAZwI2quldEDrqQWACau3DMJczGdIHqwGzHB4E31mRmi0RkPTBTRO4EjgDlZ2INo9zr06cPt912G5MmTSIvL4958+Zxzz33uHy+u59cOnfuzN69ezl48CC1a9dmxowZTJs2rdjzevbsyauvvkqDBg3w8vIiPDyclJQUduzYwdSpU0lLS3NrnIbxR84q9BOAqlgf4ucmsnCpbkJVD7uwHCtJ4Kp6QFXbOpaWqvqCY/tpVe2vqo0dP81YZobLOnTowOjRo2nXrh0jRoygd+/epXavsWPH0r17d2JjY4mOjubDDz88v+/aa68lLi4Ob29v3n77bQYOHEjz5s0ZNWoULVu2LPb81q1bk5iYSLdu3S7YFhISQkSEmeTLKH1SWJnu+Z0iIcAIrGKxRkAoMFBV15VJdGWkU6dOumHDBk+H4VYrVqwAoF+/fh6O5M/Kc2xGxVWe3lflKZbSJCIbC/QxvEBxM1GeAT4CPnK0yBoDvC4iMaoa4+xcwzAM4/JVbGsxEfHHempRYIqqvumo6DcMwzCMQjmr0PcGXsQaKv8wVv1MtIh8DDxTNuEZhmEYFZGzCv1XsHrT11fVjqraHmv4llB+HzPMMAzDMP7EWXIZDNztmL8FAFU9C/wFuLa0AzMMwzAqLmfJRbWQpmSqmo+LTZINw6i8ChuV+e9//ztt2rShXbt2DBgwgLi4OAB++eUX2rRpQ+fOndm3bx8AKSkpDBw4sNBRCEpTbGzsBaNbBwcH8/rrrzNr1ixatmyJzWajYOvR8hR7USNhv/XWWzRt2pSWLVvyxBNPlI+4VbXQBfgOuKWQ7eOBuUWdVxGXjh07amWzfPlyXb58uafDKFR5js1w3Y8//qgbN27Uli1bnt925syZ86/feOMNveeee1RVddiwYbpnzx5dsmSJTpw4UVVVJ06cqCtXrnRbPJfyvsrLy9Pq1avroUOHdOfOnbp792694oordP369eePuZTYS+s9XtjffPny5dq/f3/NyspSVdVTp05dctwXC9igRXyuOmst9gDwtYjcAWzEelrpjDV18bBSzHeGYVQAffr0+dMYZMHBwedfp6ennx9Kx8fHh8zMTDIyMvDx8WH//v0cP36cK664oixD/pNly5bRsGFD6tYtugFseYq9sL/5u+++y6RJk84P3xMVZQ0E7+m4nSWXOaraQUT6Ay2wxgNbqKrLyiQywzAqpGeeeYbPPvuMkJCQ850Jn3rqKSZMmEBAQACff/45jz32GM8//7yHI4UZM2YwduxYp8eU19jP2bNnDz/99BPPPPMM/v7+TJ48mc6dO3s8bmd1LgKgqstU9S1VfdMkFsMwivPCCy9w9OhRxo0bx9tvvw1Au3btWLNmDStWrODAgQPUqlULVWX06NGMHz+eU6dOlXmcOTk5zJ07l5EjnQ8/WB5jLygvL4/k5GTWrFnDK6+8wqhRo1BVj8ft7MklUkSKHDZfVUs2T6phGJXaTTfdxHXXXcdzz/0+s7mq8u9//5uvvvqKv/71rzz33HMcOnSIN998kxdeeKFM41u4cCEdOnSgevXqLh1fnmIvKDo6muHDhyMidOnSBZvNRmJiIpGRkR6N29mTixdQBWvwysIWwzCMC+zdu/f867lz59KsWbML9n/66adcd911hIWFkZGRgc1mw2azkZGRUdahMn369GKLxAoqT7EXdMMNN7B8+XLAKiLLycm5YHBSj8VdVE0/sKmofZVtMa3FylZ5js1w3ZgxY7RGjRrq7e2ttWvX1g8++ECHDx+uLVu21NatW+vgwYP12LFj549PT0/Xvn37ak5Ojqqqrlq1Slu1aqUdOnTQ2NjYEsdzMe+r9PR0DQ8P15SUlPPbvv32W61du7b6+vpqVFSUDhgw4JJjL633eGF/8+zsbB03bpy2bNlS27dvr8uWLbvkuC8WTlqLFTkqsohsVqtXfqVnRkUuW+U5NqPiKk/vq/IUS2lyNiqys2Kx/qUUj2EYhlHJFZlc1EyyZRiGYVwiZ08uhmEYhnFJTHIxDMMw3M4kF8MwDMPtTHIxDMMw3M4kF8MwDMPtTHIxDMMw3M4kF8MwDMPtKm1yEZFBIhIrIvtEZJKn4zEMw7icVMrkIiJewP+Aa7DmohkrIi08G5VhGMblo1ImF6ALsE9VD6hqDjADGOrhmAzDMC4bzuZzqchqA0cLrB8DuhY8QEQmABMcq2kiEuume0cAiW66lruYmFxTHmOC8hmXick1lT2mIueHrqzJRQrZdsHwz6o6BZji9huLbChqlFBPMTG5pjzGBOUzLhOTay7nmCprsdgxIKbAejQQ56FYDMMwLjuVNbmsBxqLSH0R8QXGAHM9HJNhGMZlo1IWi6lqnoj8FViMNV3zR6q6o4xu7/aiNjcwMbmmPMYE5TMuE5NrLtuYipyJ0jAMwzAuVWUtFjMMwzA8yCQXwzAMw+1McnEDEWknImtEZIuIbBCRLgX2PeUYgiZWRAZ6ILYHHPfeISL/LUdxPSYiKiIRno5JRF4Rkd0i8puIzBaRUE/H5Li3x4cwEpEYEVkhIrsc76GHHNvDReQHEdnr+Bnmgdi8RGSziMwvRzGFisjXjvfTLhHp7um4ROQRx7/ddhGZLiL+ZRKTqpqlhAuwBLjG8fpaYKXjdQtgK+AH1Af2A15lGFc/YCng51iPKidxxWA1tjgMRHg6JmAA4O14/TLwcjmIyctxvwaAryOOFmX1b1QgjppAB8frqsAex9/lv8Akx/ZJ5/5mZRzbRGAaMN+xXh5i+hS4y/HaFwj1ZFxYHcoPAgGO9ZnAbWURk3lycQ8Fgh2vQ/i9T81QYIaqZqvqQWAf1tA0ZeUvwEuqmg2gqvHlJK7/A57gwo6tHotJVZeoap5jdQ1WvyiPxkQ5GcJIVU+o6ibH61RgF9YH1lCsD1IcP28oy7hEJBq4DvigwGZPxxQM9AE+BFDVHFVN8XRcWK2CA0TEGwjE+nwq9ZhMcnGPh4FXROQoMBl4yrG9sGFoapdhXE2A3iKyVkR+FJHOno5LRIYAx1V16x92efpvdc4dwELHa0/GVF7+HueJSD2gPbAWqK6qJ8BKQEBUGYfzOtYXFHuBbZ6OqQGQAHzsKK77QESCPBmXqh7H+kw6ApwAzqjqkrKIqVL2cykNIrIUqFHIrmeA/sAjqvqNiIzC+uZyFS4MQ1PKcXkDYUA3oDMwU0QalHZcxcT0NFYx1J9O81RMqjrHccwzQB7wZVnEVAxP3vtPRKQK8A3wsKqeFSksvDKLZTAQr6obRaSvxwL5M2+gA/CAqq4VkTewipw8xlGXMhSrWDcFmCUi48vi3ia5uEhVrypqn4h8BjzkWJ3F74/qpT4MTTFx/QX4Vq2C1XUiYscatK5U4yoqJhFpjfUm3+r4cIoGNjkaQHgkpgKx3QoMBvo7/l6UdkzFKDdDGImID1Zi+VJVv3VsPiUiNVX1hIjUBOKLvoLb9QSGiMi1gD8QLCJfeDgmsP7NjqnqWsf611jJxZNxXQUcVNUEABH5FuhRFjGZYjH3iAOucLy+EtjreD0XGCMifiJSH2gMrCvDuL5zxIOINMGqYEz0VFyquk1Vo1S1nqrWw/rP2EFVT3oqJrBaZQFPAkNUNaPALk/++5WLIYzE+hbwIbBLVV8rsGsucKvj9a3AnLKKSVWfUtVox3toDLBcVcd7MiZHXCeBoyLS1LGpP7DTw3EdAbqJSKDj37I/Vr1Z6cdUVq0WKvMC9AI2YrXoWQt0LLDvGaxWP7E4WpSVYVy+wBfAdmATcGV5iKtADIdwtBbzZExYFfVHgS2O5T1Px+S497VYrbP2YxXfeeLfqBdWcdxvBf4+1wLVgGVYX6SWAeEeiq8vv7cW83hMQDtgg+Pv9R1WsbRH4wKeA3Y7Pgc+x2r9WOoxmeFfDMMwDLczxWKGYRiG25nkYhiGYbidSS6GYRiG25nkYhiGYbidSS6GYRiG25nkYhiGYbidSS6GcZFEJO0iju0rIj0KrN8rIrc4Xt8mIrUu4f6HpMBUBS4ev01EOjnWW4rIryLyqYjYHNteEZGTIvLYxcZjGIUxw78YRunqC6QBqwFU9b0C+27D6thWFsO69FPVRMfricAQrN7tA4BFqvq4iKSXQRzGZcIkF8NwAxG5Hvgb1qgIp4FxQABwL5DvGCzwAazhN9KwRifoBHwpIplAd6xhOTqpaqLjKWOyqvYVkWrAdCASa/gZKXDf8cCDjvuuBe5T1fxiwvXC6nVvp/ABMg2jxEyxmGG4x89AN1VtjzX3yhOqegh4D/g/VW2nqj+dO1hVv8YaJmScY1+mk2v/E/jZce25QB0AEWkOjAZ6qmo7IB8rqRXnDeB7rIS25KJ+S8NwkXlyMQz3iAa+coww64s1+5+79AGGA6jq9yKS7NjeH+gIrHeMMh2AC6PbqupmoKsb4zOMPzHJxTDc4y3gNVWd65hj5NlLuEYev5cm+P9hX2GDAArwqao+Vcg+w/AoUyxmGO4RAhx3vL61wPZUrLnnC/PHfYewnkQARhTYvgpHcZeIXIM10i5Yo9neKCJRjn3hIlL3EuM3DLcyycUwLl6giBwrsEzEelKZJSI/Yc2Zc848YJiIbBGR3n+4zifAe459AVhDo7/huEbBSvnngD4isgmrddcRAFXdidWIYImI/Ab8ANR09y9rGJfCDLlvGJWciBzC0QqtmOOeBdJUdXJZxGVUbubJxTAqvwRg2blOlIURkVeA8YDp62K4hXlyMQzDMNzOPLkYhmEYbmeSi2EYhuF2JrkYhmEYbmeSi2EYhuF2/w8rzvfTrs6I4QAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton\n",
+ "mlo_aqua_1688ppmv_hice_unlim\n"
+ ]
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(2,1,figsize=(6,4),sharex=True, sharey = True)\n",
+ "dN1=np.zeros(3)\n",
+ "dN2=np.zeros(3)\n",
+ "dE=np.zeros(3)\n",
+ "dglob=np.zeros(3)\n",
+ "ind=1\n",
+ "for sky_ind in range(2):\n",
+ " SW_out_W_cs = get_var(winton_zmsimarray[ind],\"rsutcs\", True) \n",
+ " SW_out_S_cs = get_var(semtner_zmsimarray[ind],\"rsutcs\", True)\n",
+ "\n",
+ " LW_out_W_cs = get_var(winton_zmsimarray[ind],\"rlutcs\", True) \n",
+ " LW_out_S_cs = get_var(semtner_zmsimarray[ind],\"rlutcs\", True)\n",
+ "\n",
+ " SW_out_W = get_var(winton_zmsimarray[ind],\"rsut\", True) \n",
+ " SW_out_S = get_var(semtner_zmsimarray[ind],\"rsut\", True)\n",
+ "\n",
+ " SW_in_W = get_var(winton_zmsimarray[ind],\"rsdt\", True) \n",
+ " SW_in_S = get_var(semtner_zmsimarray[ind],\"rsdt\", True) \n",
+ "\n",
+ " LW_out_W = get_var(winton_zmsimarray[ind],\"rlut\", True) \n",
+ " LW_out_S = get_var(semtner_zmsimarray[ind],\"rlut\", True)\n",
+ "\n",
+ "\n",
+ " timemean_SWinW = seltimemean(SW_in_W, 40)\n",
+ " timemean_SWinS = seltimemean(SW_in_S, 40)\n",
+ " timemean_SWoutW_cs = seltimemean(SW_out_W_cs, 40)\n",
+ " timemean_SWoutS_cs = seltimemean(SW_out_S_cs, 40)\n",
+ " timemean_LWoutW_cs = seltimemean(LW_out_W_cs, 40)\n",
+ " timemean_LWoutS_cs = seltimemean(LW_out_S_cs, 40)\n",
+ " timemean_SWoutW = seltimemean(SW_out_W, 40)\n",
+ " timemean_SWoutS = seltimemean(SW_out_S, 40)\n",
+ " timemean_LWoutW = seltimemean(LW_out_W, 40)\n",
+ " timemean_LWoutS = seltimemean(LW_out_S, 40)\n",
+ "\n",
+ " SW_out_W_integrated = integrate_zonal_data(timemean_SWoutW,timemean_SWoutW.lat)\n",
+ " SW_out_S_integrated = integrate_zonal_data(timemean_SWoutS,timemean_SWoutS.lat)\n",
+ " SW_out_W_cs_integrated = integrate_zonal_data(timemean_SWoutW_cs,timemean_SWoutW_cs.lat)\n",
+ " SW_out_S_cs_integrated = integrate_zonal_data(timemean_SWoutS_cs,timemean_SWoutS_cs.lat)\n",
+ " \n",
+ " \n",
+ " if sky_ind==0:\n",
+ " N1_W = SW_out_W_cs_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_W = SW_out_W_cs_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_W = SW_out_W_cs_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_W = SW_out_W_cs_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_W = SW_out_W_cs_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ "\n",
+ " N1_S = SW_out_S_cs_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_S = SW_out_S_cs_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_S = SW_out_S_cs_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_S = SW_out_S_cs_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_S = SW_out_S_cs_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ " \n",
+ " dglob[sky_ind] = SW_out_W_cs_integrated.sum()-SW_out_S_cs_integrated.sum()\n",
+ " elif sky_ind==1:\n",
+ " N1_W = SW_out_W_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_W = SW_out_W_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_W = SW_out_W_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_W = SW_out_W_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_W = SW_out_W_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ "\n",
+ " N1_S = SW_out_S_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_S = SW_out_S_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_S = SW_out_S_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_S = SW_out_S_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_S = SW_out_S_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ " \n",
+ " dglob[sky_ind] = SW_out_W_integrated.sum()-SW_out_S_integrated.sum()\n",
+ " \n",
+ " dN1[sky_ind] = (N1_W.values+S1_W.values) - (N1_S.values+S1_S.values)\n",
+ " dN2[sky_ind] = (N2_W.values+S2_W.values) - (N2_S.values+S2_S.values)\n",
+ " dE[sky_ind] = E_W.values - E_S.values\n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " #areas\n",
+ " NA1 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[ind]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmin_iceborderS[ind]]+90)))\n",
+ " NA2 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmin_iceborderS[ind]]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmax_iceborderS[ind]]+90)))\n",
+ " E = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmax_iceborderS[ind]]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smax_iceborderS[ind]+1]+90)))\n",
+ " SA2 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smax_iceborderS[ind]+1]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90)))\n",
+ " SA1 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90)))\n",
+ " \n",
+ " \n",
+ " if sky_ind!=2:\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[ind], Smin_iceborderS[ind]]],0,400,color='darkgray', alpha=1)\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[ind], Smax_iceborderS[ind]]],0,400,color='darkgray', alpha=1)\n",
+ " else:\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[ind], Smin_iceborderS[ind]]],-200,200,color='darkgray', alpha=1)\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[ind], Smax_iceborderS[ind]]],-200,200,color='darkgray', alpha=1)\n",
+ " \n",
+ " if sky_ind== 0:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW_cs['lat'],timemean_SWoutW_cs,c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS_cs['lat'],timemean_SWoutS_cs,c='C0',label='Semtner')\n",
+ " elif sky_ind==1:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW['lat'],timemean_SWoutW,c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS['lat'],timemean_SWoutS,c='C0',label='Semtner')\n",
+ " elif sky_ind==2:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW['lat'],-1 * (timemean_SWoutW_cs-timemean_SWoutW),c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS['lat'],-1 * (timemean_SWoutS_cs-timemean_SWoutS),c='C0',label='Semtner')\n",
+ " \n",
+ " if sky_ind==0:\n",
+ " print(\"clear sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsutcs\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsutcs\", True), 40)\n",
+ " else:\n",
+ " print(\"all sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsut\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsut\", True), 40)\n",
+ " \n",
+ " print(str(dglob[sky_ind]*1e-12) +\" PW; \" +str(dglob[sky_ind]/(4 * np.pi *6371000**2)) +\" W/m^2 = \" +str(total.values)+\" W/m^2\" )\n",
+ " print(dN1[sky_ind] / dglob[sky_ind])\n",
+ " print(dN2[sky_ind] / dglob[sky_ind])\n",
+ " print(dE[sky_ind] / dglob[sky_ind])\n",
+ " \n",
+ "ax[0].set_xlim(-90,90)\n",
+ "ax[1].set_xlim(-90,90)\n",
+ "ax[0].set_ylim(0,150)\n",
+ "legend_color(ax[0],['3L-Winton', '0L-Semtner'],9)\n",
+ "ax[1].set_xlabel('Latitude [°]')\n",
+ "ax[0].set_ylabel('TOA SW out cs\\n[W m$^{-2}$]')\n",
+ "ax[1].set_ylabel('TOA SW out as\\n[W m$^{-2}$]')\n",
+ "#ax[2].set_ylabel('CRE [W m$^{-2}$]')\n",
+ "ax[1].annotate(\"dF = \" +str(round(total.values.tolist(),2)) +\"Wm$^{-2}$\",(-20,40)) # 1.01 Wm$^{-2}$\")\n",
+ "ax[1].annotate(f'{100*round(dN1[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(70,20))\n",
+ "ax[1].annotate(f'{100*round(dN2[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(45,20))\n",
+ "ax[1].annotate(f'{100*round(dE[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(20,20))\n",
+ "\n",
+ "#ax[1].annotate(\"dF = 1.01 Wm$^{-2}$\",(-20,40))\n",
+ "#ax[1].annotate(\"16%\",(70,20))\n",
+ "#ax[1].annotate(\"71%\",(45,20))\n",
+ "#ax[1].annotate(\"13%\",(20,20))\n",
+ "\n",
+ "#ax[0].annotate(\"dF = 1.25 Wm$^{-2}$\",(-20,50))\n",
+ "#ax[0].annotate(\"23%\",(70,20))\n",
+ "#ax[0].annotate(\"80%\",(45,20))\n",
+ "#ax[0].annotate(\"-3%\",(20,20))\n",
+ "\n",
+ "ax[0].text(-0.15,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.15,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "plt.savefig(\"plots/TOA_EB.pdf\")\n",
+ "plt.savefig(\"plots/TOA_EB.png\", dpi=500)\n",
+ "plt.show()\n",
+ "print(winton_exparray[ind])\n",
+ "print(semtner_exparray[ind])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 230,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'13'"
+ ]
+ },
+ "execution_count": 230,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "f'{100*round(dE[sky_ind] / dglob[sky_ind],2):.0f}'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 191,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n",
+ "clear sky:\n",
+ "637.0255380792839 PW; 1.2489118006869346 W/m^2 = 1.2489128 W/m^2\n",
+ "0.23056602641189058\n",
+ "0.8042223095666693\n",
+ "-0.03478833597856455\n",
+ "all sky:\n",
+ "515.034057095216 PW; 1.0097430530043008 W/m^2 = 1.0097504 W/m^2\n",
+ "0.16410614491583508\n",
+ "0.709068870009622\n",
+ "0.12682498507453116\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ "for sky_ind in range(2):\n",
+ " if sky_ind==0:\n",
+ " print(\"clear sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsutcs\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsutcs\", True), 40)\n",
+ " else:\n",
+ " print(\"all sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsut\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsut\", True), 40)\n",
+ " \n",
+ " print(str(dglob[sky_ind]*1e-12) +\" PW; \" +str(dglob[sky_ind]/(4 * np.pi *6371000**2)) +\" W/m^2 = \" +str(total.values)+\" W/m^2\" )\n",
+ " print(dN1[sky_ind] / dglob[sky_ind])\n",
+ " print(dN2[sky_ind] / dglob[sky_ind])\n",
+ " print(dE[sky_ind] / dglob[sky_ind])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 246,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " \n",
+ " f1 = ax[axind,0].contourf(albedo_Wzmmean.lat,albedo_Wzmmean.month, albedo_Wzmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " f2 = ax[axind,1].contourf(albedo_Szmmean.lat,albedo_Szmmean.month, albedo_Szmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " c2 = ax[axind,1].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(winton_exparray[ind])\n",
+ " ax[axind,1].set_title(semtner_exparray[ind])\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " cbar.set_label(\"surface albedo\")\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")\n",
+ "plt.savefig(\"plots/hovmoeller_albedo.png\",dpi=300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 247,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,1,figsize=(8,12), sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_W = get_albedo(winton_simarray[ind])\n",
+ " albedo_S = get_albedo(semtner_simarray[ind])\n",
+ " \n",
+ " sic_W = get_var(winton_simarray[ind], \"sic\")\n",
+ " sic_S = get_var(semtner_simarray[ind], \"sic\")\n",
+ " \n",
+ " albedo_Wmean = selmonmean(albedo_W, 40)\n",
+ " albedo_Smean = selmonmean(albedo_S, 40)\n",
+ " sic_Wmean = selmonmean(sic_W, 40)\n",
+ " sic_Smean = selmonmean(sic_S, 40)\n",
+ " \n",
+ " ax[axind].plot(sic_Smean.month,sic_Smean)\n",
+ " ax[axind].plot(sic_Wmean.month,sic_Wmean)\n",
+ " \n",
+ " axind+=1\n",
+ " #c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 250,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 0, 'latitude [°]')"
+ ]
+ },
+ "execution_count": 250,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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/Z5aVGhpq97m9SlxyCdx2G3R3R9N+paxQ+w1BBTlpLdROeh1SLaxQ24Shfl9h9aRtjhvyUp++jZX6UB86A7Y+6RaODNuECTBqFNx/f/htV8PqkGqWluyR1SHlZ1kkExULkOpB3+HQpw22FRkWq0TmQ73QOp+9WmHAZNi8yJ/2KvXBD8J110XTdqWmTYPly2Hnzqh7kkhpCY6KSXMdUjnDbMZExQKkeuHnMNuECW4I65VXSrQX0dDRu98N8+fDli2lj41a794wdSo88kjUPTE5kjY0l8Q6pHJZFslEwQKkeuFnobZIeXVIUa2HNHgwvOUtcEPBrf7ixeqQ3lBuRmh+55SKskdJC3bKlYY6pGqzSFaHZIKW/FeXKU/7GdDxQOFhsUqVXDByttvipCeiYukPfQiuvda/xxskq0OqSKnAyI9gKHOOsAOrtNQhBTHd37JIJmwWINWLfuOhoQl2rvTnfKUWjOzTDn1HwPZn/WmvUmed5ep6liyJpv1KzJrltm/Zv7/0sXWuHmqO8klaHZIxaWABUr0QgfYzXRbJDyeeCOvWuYUOC2mbCx0RDR01NBzMIsXdgAEwcWIygrmIVDqkVq+SWodkxdomjixAqieZYTY/NDbCzJml92WLaj0kgPe/H266CXbvLnlo5Epl5OpIbiDkV2BU7nBZ0uqV0lCHVC2rQzJBqt9XVj3KZJD8rEMqWqg9xwVIUdUBjR7tgrhbbomm/UqUqulKkYtany8rCKnXrFHQdUhhsW1HTNJZgFRP+h8DPfth1yv+nK/U7Kt+4wGBzpf9aa8aH/5wMobZSu1xV2fqMTAqxa86pLguGGnDbCZuLECqJ2/UIT3oz/mmT4fnn4fOzsLtRbkeEsDFF8OLL7qfOBsxAoYMcX/PFIv78FXc+1eOpNYhlcNmspkwWYBUb/ws1O7TB04+GR59tEh7Edch9eoF73tfMlbWtjqkwFUTACUhaIprHVKlw2zVZJGsDskEJZ6vKhMcPwu1oXQdUtuc6BaMzPjgB+EXv4ADB6LtRykpr0PKDTSSEHhEJbsOqRCb7m9MsCxAqjcDp8CB7bB7jT/nKxUgDTwe9nbAngiLTSdNctujzJ8fXR/KYQtGRiquAVt2oXZ2HVIt4lqHZEycWIBUb6QB2s6ADT5lkWbNgkWLCmdnGhqhbRZsesif9qqVhGLto492i0W++mrUPfFdXIMPEz9WrG3iwgKkeuRnHdKgQXDUUfDEE4WPaYtwX7aMd7zDzRJ7PcZTj0WsDikEaQ3WsuuQ4lSoHfR0/91jejjqu/8TaBumPlmAVI/az4CNPs1kg/LqkKIs1Abo188FSddfH20/SknhMFuxgCQuwUpc+pGtnuuQKskitayxjzETDHtm1aNBJ7qaoD3r/TlfqQ/1oafBjuVwYKc/7VXrQx+Cn/403msNpbxQO2hxDHT8YHVIB9lUfxMWC5DqUUOjN7vMpyzSnDnFFzls7A2DT4VNRZYDCMNpp0HfvvCgj9kzv514IqxZA5s3R92TulFOUJXWwMsYU5gFSPVquI91SKNHuw1XlxcZEoh6PSRwNT5xL9ZuaoIZM1KTRbLAIlxpqkOyYm0TNQuQ6pWfhdqQjPWQAN7zHvjTn2Dr1qh7UlgK65DiJimBW6F92fzadiRNrFDb+M0CpHo1+BTYtRr2bvLnfKU+1IfNgi2LoHu/P+1Va+hQOP98uPHGaPtRTErqkAY27C3ruCiDlaQESkEJsw7JNq81SWMBUr1qaHLrE/k17FUqQGoeCP0nwtYiywGE5Z3vhFtvjboXhU2fDkuXwq5dUffEGF+FsfWIMX6xAKme+TnMdswxsGcPrF5d+Jg4rIcE8OY3w+OPw7ZtUfckv759XbH2Y49F3ROTcHGqQ8rwI5OUO5PNpvqbINizqp75GSBlFjksNjQUh/WQwK2JdNZZ8d56xOqQApeU4bVK65DiunFttSrJIlkdkvFTU9QdqB8adQcON2Qa7FwJ+7dC8+Dazzd3Lvzv/8KLL+a//cBOWH03zOmCxoifepdeCr//PbzrXdH2o5C5c+Hb3466F6G5qPV55ndOibobRSWhj0nR9NLriV2HydQPC5DC0Hc0dK6CIVOj7smhGpvdIo4bH4HRF9V+vne+E3bsAC0QDPbqD7fvgaeXwKmn195eLS6+GD7xCbf3WXNztH3JZ+LEVO7JZuKna8LoSAqogwqSMlmk3AU1s7NvucpZtTzbVZPurrxjJnEsQApDuzfFfezbo+7J4YbNgk0P+xMgjRwJX/hC8WMe/E9Y+FD0AVJ7O0yeDA88AOedF21f8undG/bti7oXxhhTt9I1WB1XbXNhY0ynbbfNho0Phdfe5F7xmcL+1rfCH/8YdS/yq7MAKQlDV0noY0ZcF4ysVjl1SLmF2l1rWw65vGz9cN/6853l5/p2LhNfFiCFYcg02PkiHNgRdU8ON2ymW5+o50A47U2bBAseLDwMF6a3vtUtGhmHvuSqswDJFGcLRh7Ozz3Z7t00ybdzmfSwACkMjc2u/mjjI1H35HDNg6DfONj6dDjtnXSuWyxy1apw2ivm+OOhuxuej+Fspj59LEAyoYmqYNoWj0wnEblARF4QkZUicnWe20VEvuvd/oyInBpFP0uxACkscZnink+Yw2ztc+G4lngMs4m4BSPHjo26J4fLZJDimN0yqWSzyowfRKQR+AFwITAFuExEcsenLwQmej9XAD8MtZNlsgApLG0x2Ky1kGGzXaF2GNpmw/ht8KCP+8DVYupU6N8/6l4crrERGhqgqyvqnpg6EucgKW6ralsdUkHTgZWq+rKq7gd+A1ySc8wlwC/UeRQYJCIjw+5oKRYghaVtJmxZAt0xHDZpm+UySGFkK3oPhVPGwAP3BN9W0lkdkslSTh1StmoLteMcJOUqtaJ2kIXapqDRwGtZl9d411V6TORsmn9Yeg2A/se6IKltVtS9OVTrBNADsPs16BfCcNO0c2DDL6Cjw023N/llAqTW1qh7YhJi95geX7bdCHNtpLgsGnnvpkkVr4eUBtt7+lQ4Q3PdMBFZnHXFPFWdl3VZ8twp99t3OcdEzjJIYWqP6TCbiBtmC6sOaeSZMGVgPOqQ4swySBVL0lT8uItD0GJiaZOqTsv6mZdz+xrgiKzLY4C1VRwTOQuQwtQ2Jx6btebTNivEOqQ5MKHT9horpXdv2Ls36l5UbXtPn7KOs6AmvixIKs7qkPJaBEwUkfEi0gy8E7gt55jbgPd5s9lmANtVdV3YHS3FAqQwtc11QYjGcL2SMDNI/cbCcf3gAVuuvyjLIJkiim2dkU+1C0bGKUjyo1Db6pCCpapdwJXAHcAy4CZVfU5EPioiH/UOmw+8DKwEfgJ8LJLOlmABUpj6Dofew2D7c1H35HBDToUdy6FrVzjtzTwbXlgBnZ3htJdEFiDFRlyyXIVqZAoVavsl6CCplnqnSgu1i7EFI/2hqvNV9RhVnaCqX/Gu+5Gq/sj7XVX1H7zbT1DVxcXPGA0LkMLWNjeew2yNvWHglPAWjBxzFkwcCI/EcPHMuLAAyVQhe0Xt7JlsxpjK2KsnbHFeMHLIVDfLLgxtc+DofVaHVEwKAqS4ZF5M7eI01BYnVoeUXhYgha3dyyDFcYXkMAOkgZPh2G5bD6mYkSNh9eqoe2FSJA0b1wbNhtlMhgVIYWudANoNu16NuieHCzNAkgaYOReWPAH794fTZiW0Bw50wr7N7t8ozJljGTZTVKWF2rUKMotUbh2SFWqbsFiAFDaR+K6HNPB46HwJuoIt+HzDhLNhVD944olw2iuH9sCmx2D5t2Dpf8CzX4ZFH4O7z4QNIW+PMneurRVlDhNVoXac+VmobUyGBUhRiOt6SGEXarfNhWOJV5Zk3Z2w5J+g82UYMAlGngfj3wvH/jM886+wY0V4fTnxRFizBjZvDq9NkwpWqF0bG2YzYAFSNOK8cW2Yw2yDT4GjO+GBe8NprxxLvwyn/Bec9gOY8AEYfbELko64FBqaXeAUlqYmmDEj8VmkYoXaVsQdvlrrkKxY+3BWqJ1OFiBFYdCJsGcd7N0YdU8ON2QqbA0pQGpshhlT4aGHoCcmi2f2n+iC1+3LYedK2L4MOha6rFJDb2gdF25/5s6NV4bNxE7YdUhBCmv/N7A6JFOaBUhRaGiEYTPDW7m6EkOmwuYQ1+yafC60NsKyZeG1Wczkz8COF+HZf4eXroOVP4bVN7kFPk/9Jgw4Ntz+WB2SyaMeN1XNlq9QO7cOqVY2zGYsQIqKFWo77XNhcnN8siSDjoPTfwInfdUFiyPe7NUgfRwGRvCGOX06PPss7ApphfMUqOdhu7AKtZMwzGaF2qZWFiBFJc6F2gMmh1eoPXQGjN8GD94fTnulbHsWXv0N9D8axr4dRl8EQ0+DXgOi6U/fvnDSSfDYY9G075MkBy1J7XuxQm1bD8l/VoeUPhYgRWXodNjxfHRr7BQTZqF2r1Y47Rh48L5w2iuldxv0Hel+j8umwlaHZGIoqCxSnOqQbJitvlmAFJXGPjD4ZNgcw8xAmIXaACefC3t2xWPV6L4joP0s6DngFrPs3gd7N8Gu12DHC7D9+fD7ZAGSKSFNhdrGxIUFSFGK68a1Q6eFl0ECGH4GHNcajyCg5wA882/Q7RWBHtgJj34AnvoMPPlpuO/C8Ps0e7YbYjtwIPy2TWxZoXbwhdqmvlmAFKW4blw78Hg3xb2r9iX9y9I2B47aBg8+GE57xTT0gjW/g8YWt19en2Gw7SmY8CGYPs/VIh3YGW6fBg+GcePgqafCbddnubU8Sa3tibtChdpB1CHFvVjbj0LtSobZrA4pXSxAilLbbNj8uMtaxEmmUHtbSIXafdrg5BHwwN3htFdKr0Gw53W3LQxAvyNh0Elu+K15IOyNYDjDhtlMFbILtZMkzDokYwqxAClKzYOg9SjYEqO9yDLCXg/ptHNgzevx2FZjyFR44Xvw0s/gkcuh/UxoaHK3jbrIZZbCZgGSMYGwBSNNIRYgRa1tLmyM4UKAYRdqjzwTpgxyq2pH7dRvuoDotd+6IbWjPgjNg91tkz4JAyaG36fMgpFRBGcmEaIq1I77MJsfbDZbfbIAKWpxrUMKc6o/uAUjJ+yKRx1SY284+Ro4608w7XvQf8Kht0VhzBjo1w9eeCGa9n1idUf+qrRQO23rIVVTqB30gpFWh5QegQVIIvJTEekQkaVZ1w0RkbtEZIX37+Cg2k+Mdi+DFJc1dzIGnRBuoXa/cTCld3zqkFQP/sSFDbOZMoW1onZGnLNIuYXaxpQryGfOz4ELcq67GrhHVScC93iX61vLaGgaADtiNmW3sTcMmBReobYIzDwLnlsWj201RA7+xIUFSKFLQ8bLCrVLK6cOyYbZ6k9gAZKqPghsybn6EuB67/frgUuDaj9R2mO6HtKQkNdDGvsmmDAw8dtqBMYCpLKlIbAxxkSrKeT2hqvqOgBVXSci7YUOFJErgCsAxo4dG1L3ItI2Fzruh4kfibonhxp0Amx/Ltz2xgi8+CKcfXZ47SbFpEnQ0QE7dsCAiPaGKyH7dTt4VJ/A2rmo9XkLgjxnD1v+RnZj8ogNJbMhnaMbAllQsWvCaJue77E6pHSI7eCsqs5T1WmqOq2trS3q7gSrbU48Z7K1HAG714TXXkMzNMSo5iduRGD0aFi7NuqeFJT9um0d3Cvq7pgyWKF2+WyYrb6EHSBtEJGRAN6/HSG3H08DjoWu3W6/rzjpdwTsDrFP0hSvoug4GjUq1gFSmC5qjWBfvAQJu1A7CH5lpMop1C53PaR7N02yQKlOhB0g3QZc7v1+OfCHkNuPJ5F4TvdvCTlAamgCkllQGhoLkCwwMrFggVL6BTnN/0bgEeBYEVkjIh8CrgHOE5EVwHneZQMHp/vHSe82ONDpslthsAxSaTEfYquEBTrhCWsmW5yn+wfFAqX0CqxIW1UvK3DTOUG1mWhtc+Cln0bdi0OJuGUIdr8ezurRYhmkkkaNgldfjboXJuFyC7V3ju+bt5YnzbrWtvg6DJkbJFW6iKeJn9gWadedwafArldhX+7KCBELc5itIaYZJFW44YZ49M2G2IwJjJ/7smUyS9k/JlksQIqLhiYYdjpsjMFeZNnCDJDimkESgY9/HDZujLondR8g2bBcaVHtyRalamayRcGCpmSxAClO2ubWd6F2Q1P8tlzJGDsWVq+OuheJD5ByA5wgA556WifJj+GcpE/3LyXfTLZ80/39zCKVI1/QZMFTPIS9UKQppn0uPP35qHtxqJYxsO2ZcNqSJiAGw1j5HHmkC5CmTYu2HyNHugBJNV7boJhYahq1+40gYPeYnpLT3f2oRfJ7wciml16vy+JvqGXdpXt87Ue9sgxSnAw9HbY+Hd4GseUIe4jNMkjFtbRA376wJWa1aiZxOkfb238hYWeRTDzZKyROmlrcdhubY7QXWZiLRca1SBviEyBB4ofZqpVvOM5qkvyX9qG2clmQZCxAipu4bVzbckR4K3zHtUgbXIAUl+n1KQuQLMiJn3oKkqrddsRUR0SGiMhdIrLC+3dwgeN+KiIdIrI07D5mWIAUN3Er1G4eAj373IKRQZNGG2IrR8oCJJM+cakZyp3JVs6WI9ksixSIq4F7VHUirljq6gLH/Ry4IKxO5WMBUty0zYZNj0JPV9Q9cURcoXYYm9Y2xLhI2wIkkyCFpvrnrqhdrA4paVmkoBa6tCDJd5cA13u/Xw9cmu8gVX0QiLTY0gKkuOk91NX9bHs66p4cFFahtjS6GqQ41iGNGAHbtsGeGBTQp2i7ERO8WlaLjkuQ5OesOBO54aq6DsD7tz3i/hRk0/zjqM2rQxoyNeqeOGFlkKQBhHgGSA0NMGYMrFkDE0PYdqWYUaPgnvqaxmt1SiZIpbYdWbZ+eGoX4NzR1afC5QTuGSYii7OumKeq87KPEJG7gRF57hyzdWyKswxSHMWtDumU/4Yj/zakxhqIdaF2HIbZEjrEVizICSoAqqfFIoMSlyySXyqtQzKH2aSq07J+5uUeoKrnqurxeX7+AGwQkZEA3r8dYT+ActkzJY4yM9nikknp0w5N/cJpSxpAu8Npq1IWIJkYK3c17dw6pHJUEyTFpVDbL1aL5JvbgMu93y8H/hBhX4qyACmO+o2Fxj6wc0XUPYmA2Ey2UkaMgA0boCemf6eQ2fBbbdK+YKSfe7JZkOSLa4DzRGQFcJ53GREZJSLzMweJyI3AI8CxIrJGRD4UdkfT/cpIsrgNs4VFGoAYZ5DisBZSczMMGhSPzXNDYAFQdfyumUnbUFuuctdDsiCpNqq6WVXPUdWJ3r9bvOvXqupFWcddpqojVbWXqo5R1evC7qsFSHEVtwUjwyIS38xIXDJIkMphNguEglPLTLYkKXeqf611SMvWD7dAqQ5YgBRX9ZpBsiLt8owaBa/b1GcTb37WIcVxqr8FSulm0/zjauBk2L8Ndq+FllFR9yZEMS/Sfu01VzwvEm1fUphBMuHZPabHZnP5KDtISutyAPXIXiFxJQ1uVe2NC6PuSbgkxkXa/fq5nzjU/tRJgGTDbuEot1A7qXVI+Qq18wWIfuzLlskqWXYp+SxAirN6HGaThvgGSBCfYbaEraZdbqATREBkayGZKOUGTBY4JYcNscVZ+1x4/KNR9yJkMR5ig4MB0rRp0fZj1Cj44x+j7YNJlKZRu4tmSDpHN/g6JT6pSq2q7ZdCQVK5Q3QWZAXPAqQ4G3wqdK50tUjNg6LuTThEiG2RNsQng1QnQ2zluqj1ecsU5TF5xAbfP0h3ju9b0cawXRNGx7LAupiwgqR8LPCJDxtii7PGZhhyGmx8OOqehEjin0GKw1pIdRAgWf1R5cpdTRuqW1E7baxQ3RRjz464a58br0Ltrt2w4QFY9StY9UtY+xfYs86/uiFpiM8WK/nEJYPU3g5btsCBA1H3xHcWGEUnDatqV5LdKsaPgm2TbMl/NaRdnAq11/4F5p8Ez38dNj0Cmx6DlT+Gu86AV27wqZGE1CBFrbER2trcliPGhCyJs9msvspUymqQ4m7YTNj6JHTvdfuzRWnJVXDO3dDvyEOv7zkAt02AsX/nhgVrYTVI5csMs40ZE3VPTEKUKtSGYIq1k1iHBNHWIpnoWQYp7nq1woDJsHlR1D1xwUtjixtO6+lyP1174MBOr4jchzdVaYjvViPgNordtg32+JPGr0mK65BsmC0cVodUug7Jhtrql2WQkqBtjhtma58bbT8mXgn3ngej3+plkRT2dsBrv4UJH4aGGrNHAAix3awWoKHBZWzWrIGJE6PtS4oDJL/N75xiQVcFyskiVTqbzZiksQxSErTPhY4YFGofeyWceRv0aYedL8COF9yw3xm/g2M/7rI/tYr7QpEQn2G2hOzHZoFJtGzri9pZFqk+WQYpCYZMg21XRt0LWPFjOOpyOPYfA2wk5tP8wc0gi0NxdHs7LF4cdS9MEUlen8kWjjT1zjJISdDQOx5BQ0NzSFPwI94ItpS9e6ElBt8oGxvjvSRCCqQx+1XPRceFAr5y1kOyLFL9sQySKd+ED+S/Pg6724epsxNaW6PuhYm5NAZXxtQTC5BM+Vb8GIafDQMmQvc+6HgAuvcAAl2dcMRfR78UQRgsQDKmYkmd6m/qlw2xmfK9dB009HK/N/aGxVfCC9+DNX+Ah98De9ZH27+wWIBUtjhlUZJaCxS0Wqb6J3HByFrYMFt9sQDJlK+xN4esddRnBMz8Ocy4DtrPAOqkHmbnTujfP+pemJDEKcgLWxq2HjGmWvbsN+VrHgIbH3IrZ294AJoHu8UiwZueH4NC8jBYBsmUUM9BVdpZFql+WA2SKd+078HD74KnPw8ozPwFtI5zt417N/QaGGXvwmMBkjF1LRMk1fOMwHpgAZIpX7+xcN5Ct71IU07twYQP+ddOnGfE7d/vZu01+7FqeLoNbNgLVB9IVrL6dbn1RbaitvGT7dWWbjbEZiqXGxzVk85OV38U5yDO+M6CKlOIDbmllwVIxlRi504bXjPGHMKCpHSyAMmYSlj9kSkhbdmmepnJVs5q2sV0rW2xQCll6uOZb4xfLEAKVRBrF9l6SNHpmjA66i4ELhMoWbCUfFakbUwlMjVIxhhTQr4gKaiibgvI/GcBkomZmC82aRmkunVR6/OWfcpj5/i+9F+1J+puJEaxQKZY8GQBUPgsQDKmElakbYpIav3R7jE9NdfgmNpZEBQv9oowphKWQQqd1SH5r9JhnjgUatdD/ZKJl+if9cYkidUgxU69BztJY4GOSQoLkEz5Vt/iVpGuZ5ZBqmtJHUIzxlTOAiRTnp4ueOjvbAVpC5BMARY8GZMuFiCZ8vTsg4beUfcielakHQkbRqtvNiyXHiIyRETuEpEV3r+D8xxzhIjcJyLLROQ5Ebkqir5agGTK020BEmA1SMb4wAKeunY1cI+qTgTu8S7n6gI+qaqTgRnAP4hI6N+SLEAy5enZB41hBUgxHsazIbbUqDYrldahtN1jeoreHoeZbEGzpQ5CcQlwvff79cCluQeo6jpVfcL7fSewDAg9qrZngylP917LIIEFSCavtAZNxgRguKquAxcIAe3FDhaRccApwGPBd+1QtlCkKU/3PmjsE3UvomcBUmTmd06xQCSmglxN24bjgrX3QC+WrR9eyV2GicjirMvzVHVe9gEicjcwIs99P19JQyLSCvwW+CdV3VHJff1gAZIpT6hDbDFmRdqxYsXbxoRuk6pOK3aAqp5b6DYR2SAiI1V1nYiMBDoKHNcLFxzdoKq31tTjKtkQmymPFWk7VqRtsCE1P8Q1M2R1SIG7Dbjc+/1y4A+5B4iIANcBy1T1myH27RD2TDDlsQySY0NsJkeagqVShdrG+OAa4DwRWQGc511GREaJyHzvmNnAe4GzReQp7+eisDtqQ2ymPLYOkmMBUqpYXVO8xTXLZKqnqpuBc/Jcvxa4yPt9ITGYzmwZJFMem8UG+/e7f5ubo+1HHbOaIxMGG2YzYAGSKZfNYnMF2lZ/ZDxJyjxNHrHhsOuaRu2u+Dz1sBaSMRn2bDflsRokG14zxmc2hGbiLJIASUT+2dtfZamI3CgidZ6aSACbxWYBkjlMkrJISRN18GTDbCb0Z4CIjAY+DkxT1eOBRuCdYffDVMgySBYgxYTVIQXLZrIZ40QVIjcBfUWkCWgB1kbUD1MuyyDZGkgx41egZAGXP3aO7xt1F3xnWaT6Fvo0f1V9XUS+AawG9gB3quqdYfcjUXr2gTRG24euTmhqqe0c3d1w6qmw4fCC0Tds3QjnxPSNdsMGGDgw6l4ctG8fNNlKHSbZuiaMpuml1w+7rlppDNRMNEJ/dxWRwbjdfMcD24CbReQ9qvqrnOOuAK4AGDt2bNjdjJfNi2DQydH2YftzMPL82s6xdCns2QNPPZX/dlW4/QS47Kra2gnKTTfBpZdG3YuDFi2CGTOi7sUhsl+3o0YHF9THKesTp74kVXaQFHXtkTEZUeQPzwVWqepGVT0A3ArMyj1IVeep6jRVndbW1hZ6J2Nl40JonxttH7Y+BYNPru0cCxbAGWfAiBH5fwbshyG9oCWGb5AdHfDAA/D2t0fdk4MWLoS5ET8vcmS/bocMSf/wRFKCowo3I41E14TRgQdHlS5TYPVY9S2Kd7DVwAwRafH2WzkHWBZBP5Jj4wJoi/CDsGs37HoFBtb4YbBwIcyZU/j2zYtg6GkgkS+gergbboBLLolPkfa6dbBtG0yeHHVPTEJ1ra1xyDyGbHjN+Cn0AElVHwNuAZ4AnvX6MC/sfiTGgZ2wY7kLHKKy7VkYMBkaelV/DlWXQSqW8di8CIZE+DgLUYWf/Qze//6oe3LQggUwezY0pD9LY5Kh/6o9UXehKFvk0lQqkmeMqn5BVSep6vGq+l5V3RdFPxJh0yMw+JRop9hvfbL24bVVq1ygcdRRhY/ZsijaQLCQp55yq2ifcUbUPTlowYLi2Thj6ozf2SMbXjMWUsfdxoXRDq+BFyCdUts5MtmjQsNn2gNblsCQabW1E4Sf/xwuvzxe2ZoY1h8lWTW1RHGsP7p306SouxAJG1ozQYjRO77Jq2NBOgq0S9Uf7VwBzUOgz7Da2vHb/v1w443wvvdF3ZODtm+HlSvdkgnG+KzY2j+tryczq2LDa6Ya9qyJs+79bthp2GGT/MLT0wXblsLgk2o7Tzn1R3EcXrv9dpgypfjQYNgefhhOOw2am6PuiUmAJMxgq4Vlj0xQLECKsy1LoP9EaI5wccIdL7hp971qWEG6owPWr4cTTih8TFwLtH/+83gVZ4PVHxlTgWqyR1Z/ZMACpHjbuADaIv4g9Gt4bdYsaCyycGAcC7Q3bIjf2kdg9UcxEMf6o0qkZYq/ZY9MkCxAirO0FGiXqj/q6YKtT8OQmNXU/PrXbuXsuKx9BG57kSeegJkzo+6JiZl6K9AuJziy2iNTC3v2xJX2wMaHYlCg7cMU/1L1R9ufg35jodeA2trxUxzXPgK3vcjkyfEK2lIi6Vkh4w8bXjMZFiDF1fbnoXkw9B0ZXR9UvSG2GjJInZ2wbJkrKi4kjvVHcVz7CKz+yFQkrQXaNrRmwmABUlxtjMH0/t2vQUMz9B1R/TkeeQROOQX69Cl8TBzrj+K49hGUzsaZwFmmKRlseM3Uyp5BcdWxMD0F2qUyHpsXx2uByDiufQTQ3e2m+FsGydSxILNHNrxmslmAFFdRb1AL/q6gXUj3XtixrPZAzE833+yWJIjT2kcAS5fCiBHQ3h51T0yCVTuDLQ6LRJYbHFn2yPjBnkVxtOtV6Nnn1kCK0tYnYUiNAdKMGW6Kf8E2noYBx0JTTGoKVOEb34BPfjLqnhzO6o9MAfU2gy0Ilj0yuSxAiqMOL3tUaN+ysGx9CgadXNs5vvpVGDSo8O1xK9C+9143xHbBBVH35HBWfxS4UvVFaa8/KrbNSNQse2SKEZGTRORK76fGrR8ceybF0cYY1B/t2+J++k8Itp24FWhnskdxK85WtQUiTUXSOoMtCJY9SjYRuQq4AWj3fn4lIv9Y63mbaj2BCcC4d0G/cdH2YetTMPhEkIADhS2L4dh/CraNci1d6qb3//73UffkcKtWuX/Hj4+2H8ZEwKb1mxI+BJyuqrsAROTrwCPA92o5qQVIcdQeg7V3al3/qBwHdkLnKzDo+GDbKdf//A9ceSX07h11Tw6XqT+KetjVmBizfdfqlgDdWZe7vetqYgGSyW/rkzD8TcG2seUJGHQiNPQKtp1yrFsHf/gDrFgRdU/ys/ojU0DaC7Qte2TK8DPgMRH5nXf5UuC6Wk8as0ILExt+bDFSSpzqj773PXj3u2Ho0Kh7kp8FSJFLQ4F2WjapzceyR/VLVb8JfADYAmwFPqCq3671vJZBMofr2gOdL8HA44JtZ/MiGH1xsG2Uo7MT5s2Dxx6Luif5dXS4n+NjMhRpTI7+q/ZE2r7NXKtPIjIk6+Ir3s8bt6nqllrOb88qc7jtS6H/MdAYcC3OlpisoP3Tn8Kb3gQTAp6xV62FC91aUo2NUfekLqQhU+T3DLaoFom0VbNNCUuAxd6/G4EXgRXe70tqPbllkMzh/FhBu5R9m2HfJrdIZJS6uuBb33Jbi8SVLRBpCkh7/VE5bGitfqnqeAAR+RFwm6rO9y5fCJxb6/ktg2QOF8YMts2LYfCpwS8jUMqtt8Lo0W7F77iy+qPIpSGrlDRWnG0qcFomOAJQ1T8DZ9Z6UguQzOG21EmBdmZbkU99Ktp+FLNzJyxfDqfFpJjdmBix7FHyiMgQEblLRFZ4/w7Oc0wfEXlcRJ4WkedE5EslTrtJRP5VRMaJyJEi8nlgc619tQDJHKqnG7Y/G0KAFIP6o4ULYds2eOtbo+1HMY8+CqeeGs+1mUyilJrBFqdtRix7lGpXA/eo6kTgHu9yrn3A2ap6EnAycIGIFEvzXwa0Ab/zftq862piNUhBUXVDVc2DQBqhqRV6Dyl1r+jtXAF9hkPzwPKOr/Zxbl4Ep36rlp7W7hvfgE98It7Fz1Z/ZAqo9/ojyx4l1iXAWd7v1wP3A5/NPkBVFej0LvbyfrTQCb3ZaleJSKuqdhY6rlIWIAXhwE547mtuT7X9W6DvaOjTBgMmwRF/DQNjXM9QyfpH1T7O3WuhZ1+026m88AI88ki8i7PBBUif+UzUvag78zuncFHr82/8niRJ34PNskepN1xV1wGo6joRac93kIg04maiHQ38QFULrsMiIrOAa4FWYKy3We1HVPVjtXTUAqQgrLvTBQ3nPegud74CW5+ANbfBkn+G6T+C1pjuqVVJgXa1j3PLIhhyWrTbZnzzm/D3fw8tMV44b/9+WLTITfE3xrzBskf+0QMNlS4gOkxEFmddnqeq87IPEJG7gRF57vv5svul2g2cLCKDgN+JyPGqurTA4d8Czgdu8+77tIjUvGeXBUhB2L8F+h0JPV2AQOs493PEX8Pz/wXPf90FD3G09Uk49uPlHVvt49wccYF2RwfcdJPLIsXZE0/AxIkwsMzhTmNMXhYc+WqTqhYtIFXVglPsRWSDiIz0skcjgY4S59omIvcDFwCFAiRU9TU59Et3d6FjyxWfqrw0GXURNPWDpz8Pmx91mZVdq92/25+H/kdH3cP8VCtbA6naxxl1gfaPfwzveAe0583sxofVH5kCwqw/CnORyHKG1yrNHllwFDu3AZd7v18O/CH3ABFp8zJHiEhf3JpGy4uc8zVvmE1FpFlEPgUsq7WjlkEKQstoOOELsOLH8Nw10NAELUfAnrXQPASOfGfUPcxv9xpAoO+o8o6v5nGqugzSjIgySF1d8POfx7/2CODBB+G97426F3UtafVHaWdbiqTCNcBNIvIhYDXwDgARGQVcq6oXASOB6706pAbgJlX9U5FzfhT4DjAaeB24A/iHWjtqAVIQVKHvSDjxi9C9D3Ysd0FD/2Ogf0y3swDYcA+0n1l+bVA1j3PHC9BrgLtfFH7+czjiiPivK9Td7ZYhuPbaqHtSt5IYHBUq0E7CJrVBFGdb9ih+VHUzcE6e69cCF3m/PwOUvVqxqm4C3u1XHzMsQApaY28YfJL76emGngPQ0CvqXuW39s8w6sLq7lvu49y4ANoiGjbatQu+8AX4/e+jLRAvx9KlbghweLJnJJlkiHoNJBtaM7UQkaNwGaQZuOUAHgH+WVVfruW8lq8Mggjs3wZduw+9fuNCN/MrjnoOwPq7YeQF5d+nmsfZsQDaI9o243/+B844I/7ZI6j77UWSmL0JS9rWP7Jp/cYHvwZuwg3NjQJuBmquo7AMkt82PQav3+aGnw5sd8NJAybDkX8HjX3cOkFxtOb3MOh4aCmz/qjax7lxARz3Od+6XbYNG+A734HFi0sfGwcLF8IFFQSrpu4FMbwWdIF2ucGRZY9MCaKqv8y6/CsRubLWk5YdIHkV4uOy76Oqv6i1A6nScwCe+ASMOA8GHO2GnfZsgO1L4emn4fh/cytOx9GL/wsTy6xpq/Zxdq6C7j1uIcmwffGL8P73w/iYrj+VTdVlkL7ylah7YmImiOxRVMNrQWWOLDiqHyKS2bbhPhG5GvgNbojt74Dbaz1/WQGSiPwSmAA8xcG1BRSwACnb5sehq9MVLWcc6ITOl2HFD2Dpf8Kp34isewVtf94VWI+5tLzjq32c6++CEeeGX/+zfDncckv81z3KWLXKBUlHHRV1T4wJRCXBUSXZIwuO6s4SXCyS+VD5SNZtCvxHLScvN4M0DZji7Y9iCul3pBtmWvYNF2y0HgW9WmHwiTD+cngyprvGr/gRHP3/oLG5vOOrfZzr7oLRF/vW7bJdfTV89rMwJAF74cHB+qO4F5IHxOqPKhf18NrO8X3pv2pP2ceWy6b1m2JUNdAhgXIDpKW4ZcPXBdiX5GsZA0dfAS9d57bs6DUAGvq4YaUD2+CIt0fdw8Md6IRXboALnyr/PtU8zp5u2HAvTP22P/0u14IF8NRT8JvfhNtuLWyBSJNHGobXgizItuxR/RGRvy52u6reWsv5iwZIIvJHXJqqP/C8iDwO7Mtq/G21NJ5KI85209i3P+eGrbp2us1Zx1wKIw5b+iF6r/4a2s+AfkdUdr9KH+fWJ6DvCLe4ZFhU4VOfcrU8ffqE126tFiyAK2uuLzQm0Sx7ZMrw1iK3KRBcgATEsGAmARqbYcgp7kc1vkMlqvDiD+CUKv+bK3mc6+92Rd1huvlmt3L2ZZeF224tOjrcjLsTToi6JyZGimWPoh5eK5dlj4zfVPUDQZ6/aICkqg8AiMjXVfWz2beJyNeBBwLsWzrENTgC2PSIGxbzI7NV6nGuvwsmfbL2dsq1bx987nNuJeqGBH0TXbgQZs2CxsaoexIJqz8KT1jDa9UERpY9MpUSkbcAxwFvDBeo6pdrOWe5NUjnAZ/Nue7CPNeZJFnxQ5j49yABvxl17Xb7r7WfEWw72X74Q5g0Cd70pvDa9IPVH5kKFMoexUUYi0AmKXvUNGp36YNqkIQtZYIgIj8CWoA3AdcCbwcer/W8pWqQ/h74GHCUiDyTdVN/4OFaGzcR2rsRXv8TTPtu8G11PAiDT4Fe/YNvC2DbNvjqV+G++8Jpz08LFsC3vhV1L0yMVFOcHYfhtWqDo6RP6w86CIpr2xGbpaonisgzqvolEfkfaqw/gtIZpF8Dfwa+Blyddf1OVd1Sa+MmQi//FI74K2geHHxb6+8Kt/7oa1+DSy6B444Lr00/7NwJy5YlYysUk2hBD6+FERzFSR0HJnGRWWNit4iMAjYDNS8BUKoGaTuwHbhMRBqB4d59WkWkVVVX19oBE4Gebrf20Zybw2lv/V0wfV44bT35JPzsZ25qf9I8+iicemqyZtz5yOqPKhPX4bWw9laLMntkAVHs/ElEBgH/DTyBm8H2k1pPWu5K2lcCXwQ2AJlnpQIn1toBE4F1f4HebTB0WvHjfvUr2LIFPv7x6tvasx52vQZDSrTlh9274d3vdkNUo8rcUy5OrP7I5EjS8FqtgVHcs0cWFMWXqmZWzP6tiPwJ6OMleGpSbpH2PwHHqurmWhs0MbDih3DMx0ofN38+nHtubW11roJxl0FDCPsif+YzcPLJLkhKov79Yfr0qHthEqCW7FFUe6/5KczskQVGyaKq+8har7EW5X5qvYYbajOl9Hhb1TXEdJp25yrY/Fjp4bXMhqlf+lJt7bXNdD9Bmz8f/vhHt1luUn3601H3IDUuan0esGG7pIhb9siCIgPlB0gvA/eLyO0cupL2NwPpVZJ13A/PXwNn3xV1T/Jb+WO3X1pTiXT46tVw4AAcfXQ4/apFRwd8+MNw440waFDUvTHGF0kaXqtFpcFRkNkjC4xMtnKfmauBu4Bm3BT/zI/J1bEAhkyNuhf5de+Fl34KR3+k9LGZepg4L3QJLtP14Q/D5ZfDmWdG3RtTpaAyPZlMUprU8/CaBUcmH3HeIyL/7l0eKyI11yuUlUFS1S95jfZ3F7Wz1oZTa+MCmPSJqHuR3+pb3HpEAyaWPjazo3zczZsHr78Ot9wSdU+MMRWKy9CaBUeJ97+4CWRnA18GdgK/BWpaM6WsZ6eIHC8iTwJLgedEZImIJGyRmRD0HIDNj0Pb7Kh7kl+5xdmQjADphRfgX/8VbrgBmpuj7o2JqSRmkQoNrxXLHiVteC0uQ2sWHKXC6ar6D8BeAFXdihvxqkm5NUjzgE+o6n0AInIWbo2BWbV2IFW2PAmtR0HzoKh7critT8Pu12DUW0ofu2mTy8qcdFLw/arW/v1uttqXv+y2FDHGk8SAKAxxGl6LQ3BkgVGqHPDWalQAEWnj4JJEVSv3WdovExwBqOr9QL9aG0+djQugLabr2Lx8PRz1/vKm2z/0EMycGe8NU7/4RRg5Ej760ah7YmoUxkyzJAVN1WSP0syCI1OG7wK/A9pF5CvAQuCrtZ607FlsIvJvwC+9y+8BVtXaeOpsXABj3xl1Lw6nPbD6Jjj7zvKOj/uChQ8+6FbLfvrp+BeRGxOCoIfX+q/a49sK2VHXHVlwlD6qeoOILAHOAQS4VFWX1Xrecp+pHwTacEVPtwLDgPfX2niqaA9sXAjtMazb2fiw23NtYJnf1ONcf7RjB7zvffCTn0B7e9S9MQmSpCyS3/wYXuu/ak/pg0qIemjNgqN0EpEZwOuq+gNV/T6wRkROr/W85WaQJgBH4AKqJlyUdja21chBO16ApgHQMjrqnhxu9f/BkX9X3rG7dsHSpfFd0fmnP4XTT4eLL466JyaGkh4ExXF4zY/AqBppDo4mj9jg27nqdeg1xw+BU7Mu78pzXcXKDZBuAD6Fm8UW3Q6BcbZxQTyzRz3dbnr/uQ+Wd/yjj7rtOvqGs+FkRVThuuvge9+LuifGJ2GvdH1R6/OpW1271PBaXIqzK8kepTE48jMoKnXeFYG0FGuiqpq5oKo9IlLz/lblnmCjqv6x1sZSrWMBtJ8RdS8Ot/FB6DuyvLWPABYujO/w2qJFsGdP8heEzLyOrX7KlCHIDEGl0/v9rEUqJG3BUVCBkTnEyyLycVzWCOBjuB1AalJuSP8FEblWRC4Tkb/O/NTaeKpsXAhtMQwsXq1geA2qK9DWnoMf+kG69lr44AeTH1iIJP8xJFhch+HC3lqkHH4Nr5WbPUpLcDR5xIY3fkwoPopbduh1YA1wOnBFrSctN4P0AWAS0IuDQ2yKK9g2u9dA1y4YcGzUPTlUTxe8diuc/2h5xx84AI89BrMrXOhSvDe/TKAUxEa9nZ1w883w3HP+nzss2gM7lrslFwYdDwMmQb8joY8Vm/shroFPlIIYXgsqixTkNiJhsYAoGqraAfg+hbzcAOkkVT3Br0ZFZBBwLXA8LtD6oKo+4tf5Q9fhrX8Ut6zAhnuh3zi3eGU5nnwSxo+HwYPLb6NrDyz/JuztcDPlmgdBv7Ew6CToP6GaXud3880uszVqlH/nDNuqX8Jrv4UBk92/3XuhsS8MmwET/h/0HhJ1D0OVtlqgIEQ5vBZ29shvYWePLDiKjoj0AT4EHAf0yVyvqh+s5bzlPnMfFRE/382+A/xFVScBJwE1r1cQqbguEFnN8Fql9UeLPwb7t7gPd2mAXa/Cih/BQ++E9XdXdq5irrvObUqbZK/fBuPeA6d8Hc74Pcy91QVGmx6Bp652GT8Tirhlm+I4vFaM3zPbkjy0ZkNpsfBLYARwPvAAMAa3H1tNys0gzQEuF5FVwD7cQkyqqhVP8xeRAcAZeOsoqep+YH+l54mVjQvhqA9E3YtDde+HNb+HE75Y/n0WLoS//dvyjz/QCevugr9ac/htnS/D/RfBxcvLP18hy5fDSy/BRRfVfq4o9T8W1v0FBp/sMntNLTD6Ivdzz9nQ8SCMODvqXpqUiMvstVKSHhyZWDhaVd8hIpeo6vUi8mvgjlpPWm6AdEGtDWU5CtgI/ExETgKWAFep6i4f2wjP/q3Q+QoMPiXqnhxq/d1ejcsR5R2v6gKkSqbQ9+yDAcfAyp/AiHOhd5sbZtRuOLATGnzaQPa669zikL16+XO+qBz3L/D812DVL2DINOg/0f2t6HF1bENi9hxKkGoyQnGf8h/UxrTgz/BaObVIYQ+vhRUcWWAUOwe8f7eJyPHAemBcrSctK0BS1VdrbSinzVOBf1TVx0TkO8DVwL9lHyQiV+BVoY8dO9bH5n22Zz20jCpvj7Mwrb4JxlaQDVq+HFpbYcyY8u/Teyic8GV49dduocxe/aHXANi3GTY/DhNqnkQA+/bB9de74C3JVKFXKxz9ETf0ueoX7vo+7bB3vRtqa66g9iumsl+3g0f1iXUAEhfVDK+VEkb2yI9Cbb+yR5Y1Sg4RGQL8Hy6AeQX4W1XdWuDYRmAxbpXsYqsDzxORwcC/ArcBreTEFNWI4lN9DbBGVR/zLt+CC5AOoarzgHkA06ZNC2EOeS1iVpzdvd/Vu5z0n+Xfp9rtRdrnQMsYN8y4e7Ur1u43Fib+1F1fq9/9Dk48EY45pvZzRSlTwN9vLEz5tPt950vQtRMGnhDMzL8IZL9uxx4/IOav22QKo/Zo5/i+NdcZhZE9ssAoka4G7lHVa0Tkau/yZwscexWuRnlAvhtF5CpV/Q6wzAuyHsSNUvki9ABJVdeLyGsicqyqvoDbtiReFZNJt/5uN1OqkgCllgUiW8e5n2w93e6n1g/+H/0I/uEfajtHnKgC6graM7P8DuyEhv6RdqsexTm7VcvstVLZo0oXh8wn6uyRzVBLtEuAs7zfrwfuJ0+AJCJjgLcAXwE+UeBcH8BN+voeNW4rkk9U40L/CNwgIs241S5jVuGccK/dDGPfUdl9FiyAz32uuvYyH/rg1vppaHIzs7r3wMjzqjsnuGG/F16ASy6p/hxRUz2YPcqsEyVZH2B7N8Jrt8DEv4+mfykQtxlplah0eC3MbUVqySKVyh5VGxxZYJQKw1V1HYCqrhORQgvBfRv4DFDs2+MyEXkFaBeRZ7Kur3oiWbZIAiRVfQqYFkXbqde9H9bcBif+R/n3WbPGLcQ4qcJaCFX3oZ8hwhvDjdoNvQZWdr5cP/6xWzm72adi7yiIwJYn3CKiTf0OjsZqjwuUdr8GrUdH2kVTP+KSPaqGBUfBaNhfcWA9TEQWZ12e5w2tv0FE7sZNu8/1+XIaEJGLgQ5VXSIiZxU6TlUvE5ERuBlrbyvn3JWIWWWxqVlm9lolw2uZ7UUqXehSBCRnCC1ziv1b3Cytau3ZA7/8JSxeXPrYODuwE+6a6xbr7HckjDgPRl98cHit40EYc2mkXTTRKJQ9KjS8FsWmtNVkkfzOHllgFDubVLVogkNVzy10m4hsEJGRXvZoJNCR57DZwNtE5CLcwo8DRORXqvqePMduBJ71eTIZYAFS+lQ7vFZN/dHz/w07lrmZWH2Gu5/ew9ySB0u/DCd91W2pUY2bb4bp02HcuOruHxcb7oWh02D2TbB2Pmy4D1b93GWTBp3sfj/2qog7WX/iXH8UZ7Vmj+IcHFlgFJrbgMuBa7x//5B7gKp+DvgcgJdB+lSB4AhV7RaRYSLS7K2r6BsLkNKkmuE1cAXa739/5e2t/BGMegs0trhp/psecetCaTdsfRpaalie4Uc/gs8WmtiQIMNmwpTPuYBowgfcz96NbsXxJz8NbWfEb4saE5lqi7PLyR5VO7yWySKVExz5OXPN1jRKrWuAm0TkQ8Bq4B0AIjIKuFZVq1kR+FXgIRG5DXhjTUVV/WYtHbUAKU023ONqXSoZXtu6FVatglOqWKSw/zFwxF/D8LMOXpeprbnt6Or3FnvmGVi9Gt7yluruHyd92mFUzjqrvYdCnzY35X/YzGj6lRJJLdD2uzg7CcrNHllglG6quhk3ez33+rXAYcGRqt6Pm+lWzFrvp4HiRd0VsQApTVZXMbz20ENw+unVrVI999bDr8vM0Br/XreydjV+/GO371pTSp+emb/RpH+2Am1Ts7gsClksexSn4MgCo/RR1S8Fcd6UfgLVoZ4DsOYPcEKFz5Nq648Amoq8aZ7wherO2dkJN97oskhpN/jkqHtgYqTa4uxy+DF7LWhBBkcWFKWbiNzHG2vNHKSqNW1uaQFSWqz3htfK3XstY+FC+PKXg+lTNX7zGzjjjMq2PDGmAlEXaPu5tUiQtUeVqDV7FFRwlKTA6Oxh5W3sHcTWNCnwqazf+wB/A3TVelILkNKimuG1PXvgqadgxoxAulSxnh741rfg29+OuicmAZJaf1SJNNQeRSHugVG5wVAl963nwElVl+Rc9ZCIPFDreS1ASoOeLrf3WqXDWo8/DscfD/36BdOvSt12G/TtC+cWXEIjPlShq6u62i1Ttypd+6iYuGSPigkzexT3oAhqC4wqOfdtgbUST94GuBkNwFTyL1RZEQuQ0qDjQeg3zs2KqkQt9Ud+U4WvfQ3+5V+SMe192TL427+FpUuj7okxeYUVHNUytd+P4CjugVGQQZF5wxJcDZLghtZWAR+q9aQWIKXBa7e66faVWrgQPvpR//tTjXvvhR074NJLo+5JeRYsgKlTo+6FqVDU9Uf5VFOcHcbMtVrVshltOSwwMhmqOj6I88b/VWaK0x5Y87vKA6TubnjkEbfFSBx89atw9dXQkJCnZJyyb3UoifVHYdaIVJI9qnZD2lpVmz2aPGJDrIOjs4ctt+AoZCLyDhHp7/3+ryJyq4icWut5LYOUdJsfh+bBbgZbJZ5+GkaPhmHDgulXJR57DFauhHe9K+qelGfXLrjzTviPClcsN8YHccoeFRpeK5U9qiY4intQZCL1b6p6s4jMAc4HvgH8EDi9lpPG55VmqlPt8JofGZBHPwRbcicPVOFrX4NPfzo5Bc/XXuuWIhgfSFbXpFCYK2cnIXtUqbgGR5Ytio1u79+3AD9U1T8AzbWe1AKkJFOtLUCqZXitpxteuwVajqz+HADPPQePPgofqrmeLhz798P//I8bDjSJkqT6o2qFGRyFlT2KY3BkgVHsvC4iPwb+FpgvIr3xIb6xIbYk2/asq0EadFJl91N1Bdrf+EYNbT8NfUdDnxqH6K65Bq66yk3vT4Jf/xqOPRamTYu6J3UrifVHlUh6cXYxSQ6OLCCKtb8FLgC+oarbRGQk8OlaT2oBUpJlskeVTotfudINZx1ZQ/anYwG01zhEt2oV/PnP8P3v13aesPT0wNe/npz+mlgIqzi7luxR/1V7ytpvLSxxCIwsIEoOVd0N3Jp1eR2wrtbzWoCUZGtuhdN+VPn9MvVHtaw3tHEBjLm0+vsD/Pd/w0c+AgMH1naesNx2G7S2wtk1be9jDFD58Fqx7FHYdUfVDK+Vmz2KMjiyoMhkswApqXasgL0bYVgV24TUWn+kChsXwqn/U/051q1z+64tT8gbUmYhy6uvTsZCluYQcaw/yiforUXiPqU/7ODIAiJTjAVISbXmVjjir0CqqElYuBA+8Ynq2965Ehp6QUuFK3dn+9a34D3vgfb26s8Rpvvvh23bkrOQpYkFv4bX/MoeBanWhSHDCI4sIDKVsAApqV67FU76SuX3W78eNm+G446rvu2NC6CthiG6rVvhuuvgySer70PYrrkGPvtZaGyMuid1LS0F2vmG15KSPap0a5FyskdBBkcWFJlqWYCURLtec1mc9jMrv++CBTB7dm0rVm+ssUD7+9+Ht70NxtaQgQrTE0+45Qje/e6oe2LqkB8z14IeWgt6W5FKWEBk/GIBUhKt+T2Mfqsb5qqUHwtEdiyASZ+s7r67dsH3vgcPPlhbH8L09a+7IcnevaPuialCUuqPqhH28FotG9MW4lf2yAIj4zcLkJLotVthUpU1RAsWwA9+UH3be9bB/q0wsMoPnZ/8xK1CPSm8falqsmKF20j32muj7olJmEL1R2EPr0WZPSo1vFZrcGRBkQmSBUhJs3cjbH0SRp5X+X23b3cf+LUscrhxIbTNrq44vKfHrUL9+99X337Y/vu/4WMfg/79o+5J3UtL/VElai3OTspWIpWywMiEwQKkpHn9Nhh5PjT2qfy+jzzigqPmGrao6VgAbVUuEbBoEQwYAFOnVt9+mNauhVtugRdfjLonJsWCLs4uV6nFIv0uzq4me2SBkQlTstetr0fV7r0G/tQfZWawVeNPf4KLL66t/TB9+9vw3vfCsBq3UzHGU8nikEnIHlVbnG3BkUkCC5CSZP92l8EZdVF19691gcj922HnChhSZQYoSQHS1q2u7qiW9aJM5KIq0A5re5FCoh5aq3TPtVIsODJRsCG2JFl7u5va36uKeph9+9x09Zkzq29/08Mw5DRorGKIbs0aWL26tvbD9L//C299a2371Rnf1GP9USFRLAzp5+y1SrJHFhiZKFmAlCS1DK8tXux2oR8woPr2X7+9+vWPbr8dLrwQmmLwlHvwQejogO7uwj/f/S7cd1/UPTUpUsnstVrWPgore1RoeK1Y9siCI5MkMfi0Sri966F5cPDtqMKG+2BalTvJr1hR2+rZPd3w8nVw/uPV3X/hwnhs8rptG5x5Jvz1X7tVsQv9/Pu/w5T0rp9j0inqoTVj0sQCpFp1eNPeg7ZnLTQ0Qd8R1Z+jltWztz8L/Y6EQSdUd/8XX4S///vq2/fLQw+5QO23v426JyZgSa0/SsK+a4VY9sikiRVp16qWWV2V2PYsDDw++HYK6ajhcaq6AOmYY/ztUzX8mMlnjA/8nt4fVPYoX/1RnLYWMSYoFiDVoqcLNj0aTgZp27PVZ2/8sHFh9esfbdrkNrYdOtTfPlVj4cLaZvIZU4VKpvcXEnT2qNgaSOWw7JFJGwuQarH1Keh3BPQO4YM/ygBJtbYNajPZIxF/+1WpvXvhqadgxoxo+2Eqlub91Iwx8WQBUi02LgxneA1g+1IYGFGA1PkyINBvfHX3j8vw2uOPu8Lr1taoe2ICltSAqtrZa2kpzrbskYkTC5BqEVb9UU8X7FgOg2qYhVaLzOOsNgO0YgVMnOhvn6ph9UcmoeJUnJ2v/siv4TVj4sQCpGqpusLlaoedKrHrFegzHJr6Bd9WPrXUH0F8MkhWf2RiIi77r8WJZY9M3FiAVK2dL7oNY/uNDaGtldA6Ifh2Cqk1EIxDgNTd7TbrtQDJhKzcAu04Dq/VuoK2ZY9MLhEZIiJ3icgK79+8CwmKyCsi8qyIPCUii8PuJ1iAVL1apr1XqvMl6H90OG3l2rMB9nZUv8RATw+sXBn9ENszz8DIkdDWFm0/TOCSWn9USJKH18pl2aO6cjVwj6pOBO7xLhfyJlU9WVWnhdO1Q1mAVK2NC8MZXgPY+VJ0GaSNC6FtFjQ0Vnf/NWtg8ODoC6Ot/siEIOxNav3KHtU6xT8fyx6ZAi4Brvd+vx64NLquFGcBUrXCKtAGL4MUVYBU4+OMw/AauPojC5BMDOSrP6pl77Wks+xR3RmuqusAvH/bCxynwJ0iskRErgitd1lsq5Fq7F4L+7fBwMnhtNcZcQbp1G9Xf/84BEiqLoP09a9H2w9jKhSn4bUgWHAUvcYDFT/PhuXUBM1T1XnZB4jI3UC+fbE+X0E7s1V1rYi0A3eJyHJVfbCSjtbKAqRqbFzgVs+WEL71aY9bh6j1qODbynVgp1teYOhp1Z8jDgHSSy+5DWjHjYu2H6Ym8zuncFHr8yWPiRM/VtAuJOi1j3ILtCupP7LhtVTbVKomSFXPLXSbiGwQkZGquk5ERgIdBc6x1vu3Q0R+B0wHQg2Q6jevW4swF4jcsw569Xc/Ydv0CAw+FRp7V3+OOKyBlKk/inolb2PyqNfhNcse1a3bgMu93y8H/pB7gIj0E5H+md+BNwNLQ+uhpz5fmbUKa/0j8IbXIprB5sfjjEMGyeqPTAIldXjNskemhGuA80RkBXCedxkRGSUi871jhgMLReRp4HHgdlX9S9gdtSG2Su3f5oKWwaeG017UM9imfLb6++/fD6+9BkdFMDyYbcECuOqqaPtgDP4tEJn0rUUse1S/VHUzcE6e69cCF3m/vwycFHLXDmMZpEptfNjV5DQ2h9NeVDPYuvfDlkUwbGb151i1CsaMgeaQ/lb5rF8PGzfC8VWu42RMypUzxb/c+iPLHpk0sQCpUhsX1LbtRqWimsG2ZQn0nwjNA6s/R1yG12bPhgZ7qqdd1AXa1ayBVKj+qNjwmmWPjAmHfWpUKswCbYhumxE/1nmKS4Bk9UfGVKTWLUaMSQN7FVSiey9sfbK2YadKRTXElpYCbVtBOzIDG/ZG3YVI5U7xT9MGtdUOr1n2yCSJBUiV2LwIBkyGXiFtm7F/K/R0Qe+Q9w/THtj0UO1DiStWRBsg7dgBL7wAU6dG1wfjq6iH0cIQt+G1fPVH1bDgyCSNBUiVCHN7EXAz2PpPCH/9nu3PQ/MQ6DuytvO8+GK0ayA98ogLjnrXsI6TqUmphR39ksTAKU3rH1lxtkmj9LxCw9CxENrroEB7ow/Da52dsHkzHHGEP32qhtUfmRQJInsUxCa1+Vj2yCSRBUjl6umGTQ/Xxwy2Dh8yZStXwtFHRzt7zOqPYiGsLFIaxGFxyFIF2oW2FzEmbSxAKtf2Z6HvCOhTaOPhAOxcGU2Bth8z9aIu0N63DxYvhpkhFtQbU0CaCrQrZdkjk1QWIJXLj6xKpaLIIO16FXr2Qf8atzeJOkBassS1P2BAdH0woYhj/ZHfm9TGee0jqz8yaWUBUrnCLtAGr0g75H3YMoFgrYXhUQdINrwWK2kfZqt0kch8BdpxGF7LVesMNssemSSzAKkcqm7YKcwC7a49sG8T9B0TXpvgXyAYdYBkBdomJeKUPbL6I1NPLEAqR+fLgEC/8eG1uWsV9DsSGhrDaxP8WSASol0DqacHHnoI5oQY0JqS0p5FSgM/V9C27JFJOguQyrHRp2GnSkSxxcjeTbDndRh0Ym3n2bwZurth2DB/+lWp556DoUNhxIho2jeByq45imP9Ua5yCrSjGF7zY4q/1R+ZNLMAqRx+ZVUqEcUWI5segqEzoKGptvNkhtfCXuAyw+qPYsuySJVJ6vCaZY9MGkQWIIlIo4g8KSJ/iqoPZYuqQDvsDJJfgaDVH5k6VmoGW1JW0PZrixFjkirKV+pVwLII2y/Png2wdyMMPC7cdjsjmMGWhgLte++FO+6As86Kpn1TkmWRDhXH2WvlKDS8ZtkjkxaRBEgiMgZ4C3BtFO1XZONCaJsVfrF0GGsg7VoNr94ET34G7jnb1T0NnV77eaMIkLq74Utfgve8B266CcaHWFBvTADiNLxmTD2KKoP0beAzQMGvTiJyhYgsFpHFGzduDK1jh9m5AvpHkA3Z/Tq0BLiPmfbAH4+GV26AXgNh8mfhrS9Ckw97M61ZE/4ebHfcATfe6BaIPOeccNs2b8h+3W7ZUjgz4kcWKS4F2sXWQErSCtrFZrDZ9H5Tj0IPkETkYqBDVZcUO05V56nqNFWd1tbWFlLv8hgyFbYsjqBhBQnwv0caoKkVTr8Ojv88jDofeg/159x9+ritPsLUqxeMGQMjR4bbrjlE9ut2yJDgnr9xCY7MoWx4zaRJFBmk2cDbROQV4DfA2SLyqwj6UZ5hM2Drk9C9N+SGxWV5gtRnOOwNYJpuv36wO+RvnIMHw5Yt4bZpTIWSUqBtjIkgQFLVz6nqGFUdB7wTuFdV3xN2P8rWqz8MmASbQ84iSQOgwbbRZ0QwAVJLC+za5f95ixkyBLZuDbdNY4wxqWVfZ8rRNtfN8ApVWBmk9f6ft1+/8AOkwYMtQEoYm81WmBVoGxO9SAMkVb1fVS+Osg9laZ/r1ggKUygZpBQNsQ0cCJ2dbjabMQmR1Cn+xtQDyyCVo20ObHoYesL88A0hg9Q3RUNsDQ0wYABs2xZuu8YYY1LJAqRy9Gl3wcT2peG1GVYGaU9KhtjA1SFZobYxgcu3SKTNYDNpYwFSudrmhDvMJjaLrWJWh5Q4VodkjIkrC5DKFXqhdggZpDQNsYEFSCYVrEDbmHiwAKlc7V6ApAEHLRmhZZBsiM0YY4zJZQFSufqNBwQ6Xw6pwRAySL3b3Ua8fgdiUQVIlkEyxhjjEwuQyiXiDbMtDK+9oDNIjc3QawDs8znr0tISTQ2SZZCMMcb4xAKkSrTNCbEOKYQMEgQzzGYZJFMBK9ROPpvBZtLIAqRKhLlgZBgZJAhmJpsFSMYYYxLOAqRKDDwe9nbAngBmfh0mpAxSEDPZbIjNmMPkblSbbxVtm8FmTHxYgFSJhkZomxVOHVKYGSS/F4u0DJIxxpg8RGSIiNwlIiu8fwcXOG6QiNwiIstFZJmIzAy7rxYgVaptTkiF2mHWIKVkiM0ySImVljqkZeuHh95m00uvh96mMTW4GrhHVScC93iX8/kO8BdVnQScBCwLqX9vsACpUmEtGBlaBmmE/0XatlCkMcaY/C4Brvd+vx64NPcAERkAnAFcB6Cq+1V1W0j9e4MFSJUaehrsWA4HdgbckISzKGUQGaS+fWH/fugOc3NfXAbJAiRTh/zOIu0eE8KXM1OvhqvqOgDv3/Y8xxwFbAR+JiJPisi1ItIvzE4CNIXdYOI19obBp8KmR2Dkm4NrJ4zNaiGYIm2Rg4Xa/fv7e+5iWlrgwAHYtw969w6vXWN8ENcC7aZREUy4MKFp2NdT6XNvmIgszro8T1XnZR8gIncDI/Lc9/NlttEEnAr8o6o+JiLfwQ3F/VslHa2VBUjVyEz3DzJAIsFF2nBwmC3MAEnk4DDbiHyvTRNnF7U+z/zOKVF3wzdda1sCbyOK+qPJI8KYxWtibJOqTit2gKqeW+g2EdkgIiNVdZ2IjAQ68hy2Blijqo95l2+hcK1SYGyIrRphFGqHlUHq0w77NgWz3YhN9TcmNFasbRLiNuBy7/fLgT/kHqCq64HXRORY76pzgNBncliAVI1hs2DLIujeH2AjIWWQGnpB80DYt9nf89pUf2OMMYe7BjhPRFYA53mXEZFRIjI/67h/BG4QkWeAk4Gvht1RG2KrRvNA6D8RtiyBtoCWZggrgwQHtxvp0+bfOaOc6m8BkjHGxJKqbsZlhHKvXwtclHX5KaDoUF7QLINUrcCn+4eUQYJgZrJFtZr24ME2xJZgaVkPqZR8q2hXKt+Qmg2zGeMfC5CqFfS+bKFmkEb4v32KDbEZU7a4zmAzpp5ZgFSttjmw6aEAszxhZ5BSst2IFWmbOhd2FunsYctDbc+YsFiAVK2+I6F5CGwPaEgg9BqkAIbYLINU17b39Im6C7GRu1GtMSb+7FVbi/Yg65BCzCAFsVhklNP8LUBKtHqpQzLGxJsFSLVoC7AOKewMkt+LRUZZg2RDbCblSg2jWbG2MbWzAKkWbXNcBimQPdNSMIvNpvkbU5IVaBsTTxYg1aL/ROjZD7tX+3/usGexpWWIzTJIsZKmrUOMMfXFAqRaiAQ4zBZmBqnNbTfS0+3fOW2avzGRsmE2Y2pjK2nXKrNg5Pj3+HveMDNIme1G9m92e7P5IcpZbFu2uGFPkfDbN77we+PaQoXfScxwWeBjTDgsQKrVsJmw6uf+n1caoeeA/+ctpHc77O3wL0Dq3x927PDnXJXo3dsFZ+vWwahR4bdvYiOus+H8WEU7KpNH+DwUb0yM2RBbrXr1h+69/p83iMLpYhr7+vs4Jk6EFSv8O18lzjwTFi6Mpm1jYsTvbNOy9cN9PZ8xcWYBUly1jIHda8Jrr6HZFZz75Zhj4OWXYb+P5yzX3LkWICVcEoe+ytU5Oh5vu7mz55Kc2TImCPF4pZrDtYyB3SHWGjT6HCD17g1HHhlNFmnOHFgQ5EbCJgnSHGQZY4JnAVJc9R0Ne8LOIPlc8zRlCjwfQR3I1KkuMNu+Pfy2zSHiWgdUT6oZZrOtUYyxACm+wh5ik17+ZpAgugCpuRlOOw0efjj8tk2shJFFSvtmrV1rW6LugqmAfSnxjwVIcZX0ITaILkACV4dkw2wmZDbLy5j0sAAprvqOgr3r/F28sRi/i7Qh+gDJCrUTye+sT1S1SE2jIlhJPgL3bpoUdReMCYQFSHHV2AzNg2FfRzjtBVGDNGkSrFwJXV3+nrccM2bAE0/Avn3ht20AGNgQwPIXCbV7TDxniNk+cMYUZgFSnPUNcZitIYAapL59YfRoeOklf89bjv79XYC2aFH4bZvYsRlt/rG1kOLL6o/8ZQFSnLWMDq9QO4ghNnDDbM895/95y2F1SMZUxNZCMuYgC5DiLMyZbEEMsUH0dUgWICVKkJkeyyJVxqb6J9PEMWuj7kJq2CsgzlrGwJ6whtgCzCBFFSDNmeOm+neHVOhuTErZVH9TjyxAirO+YQ6xBVCDBNEGSO3tMHw4LF0aTfsmdiyLdDgr1E4Hqz/ynwVIcRb6EFsAAdKkSfDii9FlcWyYzRhjTBUsQIqz0IfYAqhBam11mZxVq/w/dzksQEoMy+4YUxurP/KXBUhxlhliUw2+raAySADHHRd9oXYYf0OTCBaIGWPKYQFSnPVqdYHL/q3BtxVUDRJEW4c0fjyIRJfBMqaEneP7Rt2FiuWuhWSraUfL6o+CYQFS3IVVhxRkBinKtZBE3Gw2G2YzWcLKIsVlu5Gml8ofqs9eC8mm+pt6Zs/+uAurDimoGiSINoMEVoeUAFEMewXVZlo3rLWp/vFm9Uf+swAp7sKa6h9kBmnyZFi+HHoiWqXXAiRjjDEVsgAp7kIbYguwBmnAABgyBF59NZjzl3L88dDRARvS+c3eJEP2hrWdo+P11mtrISWX1R8FJ16vUnO4UIfYAgqQINphtsZGmDULHnoomvaNMcYkjgVIcRfqEFtANUgQ7VR/sEJtE6izhy2Pugumjln9UTAsQIq7NMxiAyvUNgXZukTpYFP9TTlEZIiI3CUiK7x/B+c55lgReSrrZ4eI/FPYfbUAKe5axsDuMIbYAqxBgugDpNNOc4XiO3dG1wdjEqjQVP/ctZBM+BJaf3Q1cI+qTgTu8S4fQlVfUNWTVfVkYCqwG/hdqL3EAqT4ax4MPXvhQGew7QSdQZo82QVIUa1o3bs3nHoqPPJINO0bkyDZayFls6n+xgeXANd7v18PXFri+HOAl1Q19Fk+FiDFnQj0DaFQO+gapMGDoX9/eO214NooZc4cWLgwuvaNMcZnCaw/Gq6q6wC8f9tLHP9O4MbAe5VHUxSNmgplhtkGHBtcG0EPscHBYbaxY4Ntp5C5c+G//iuatk1eVn9kTLRk34GKVloHhonI4qzL81R13iHnFLkbGJHnvp+vqG8izcDbgM9Vcj+/WICUBC0hzGQLeogNDgZIF1wQbDuFzJoFixbB/v3Q3BxNH0zdaRq124amjO8irD/apKrTih2gqucWuk1ENojISFVdJyIjgY4ip7oQeEJVI1nEzobYkqBlDOwJIUDqDilAisrAgTBxIixZEl0fjIkpPxaLtJlspgy3AZd7v18O/KHIsZcR0fAaWICUDH1DmMnW0AwaYA0SRL8WErhhNqtDMsaYqFwDnCciK4DzvMuIyCgRmZ85SERavNtvjaSXRBAgicgRInKfiCwTkedE5Kqw+5A4oQyxhViDFNVMNrAFI2MkzfVHlW5Yu3N837KOq7BWxLf7Fprqb6KVwAJtVHWzqp6jqhO9f7d4169V1YuyjtutqkNVdXtUfY3iWd8FfFJVJwMzgH8QkfS+U/ohjMUiw6hBGjoU+vaNdibb3Lluy5GoNs41JuGy66lsLaRwXdT6/Bs/JnihF2l70/oyU/x2isgyYDRg/+OFtIyB3QEHFWHUIAFMnepqgKKayTZypFty4Pnn3Sa2xoRo95iexGRjWl/vid2muvXIgqHoRDqLTUTGAacAj0XZj9jrMwK6dsGBHdBrQPXn6e4ufFtDM/Tsc8NfItW3UcrUqW4m2V/9VXBtlHLGGXD55W5W2/Dh7mfEiIO/Dx8OffpE1z9T1odCmofoTH2zoCgeIguQRKQV+C3wT6q6I8/tVwBXAIyNKtsQFyIw4BjY8QIMPa26cxx7LHznO4Vvb+rrArEdL8DAAGeinHkmfC6SJS0O+spX4MEHYcMGWL8eHn3U/Z653NHhapXuuSfafiZQ9ut21OjGgsdZcFOdrgmja6olCsO9myalfvPeqybdHXUXTAgiCZBEpBcuOLpBVfNWqHsLT80DmDZtWoRVvTExYApsf776AGnqVFixArZvd9Pd82mfCxsXBhsgzZ7t9kTbvNnVJEVh5Ej4u78rfHtXl+vbpk0wbFh4/UqB7NftCSc2V/W6Teq357OHLa9omnvn6IaCW3pEpf+qPWUXjBuTdlHMYhPgOmCZqn4z7PYTa+AU2LGs+vs3N8O0afDww4WPaZsLGwOe4dW7txviujvG38CammDGDFfMbXznV/YoqYFUUmXXTtXzwpeWPaofUVTgzQbeC5wtIk95PxeVulPdG+hlkGpRag2g9rnQEcIU+AsugL/8Jfh2ajF3ri0HYGqSPdW/adTuCHtyUKXDc+VkuPLNZLMFI00ahB4gqepCVRVVPVFVT/Z+5pe+Z53zK0Aq9qE/YDJ07Qh+Ucrzz4c77oh2PaRSLEAKhNUeFWZDW8bEi83hTIrWCbDndeiqYTuAmTPhiSdg3778t4vAsNnBZ5GOPhpaWuDZZ4NtpxbTp8PSpbBrV9Q9qSv1MGy2e0y86o6MMflZgJQUDU0uSNr5QvXn6N/fzWZbtKjwMZlC7aBlskhx1bcvnHQSPGYrUJj6UmxPtkJ1SPUyzGb1R/XFAqQkCaMOKYxCbbA6pDpUD8NrYUxv75owuqb7x32ZAGPiwgKkJBkwBbbXMJMNSn/oDzkVOl+G/dtqa6eUN70JHn8cOjuDbacWFiCZgCVhpeq4LUVgTFji/+o0Bw2cAjtqzCDNmeOm+hdaVbuhFwydDhsDnuLe2uqWHbj//mDbqcXs2W6I7cCBqHuSeOVkj9JYfxTHmWy1SspWKcbUyp7pSeLHENvw4dDe7gqQC2mbE94wW5zrkAYPhnHj4Mkno+6JKSBtQVVcZrIVq0PKVo91SKZ+WICUJP0nQueq2jeVnTOn9HpIVqjtlKrZMiXVQ+1R0lgdUuWsQLv+WICUJI29od+RsHNFbecpVVszdAZsfQq699bWTiknnQQ7d8LLLwfbTi2sDslUqJxC7aRN9bc6JFOPLEBKGj/qkDIf+oUWauzV6grCNz9eWzuliMCb3xzvLFImgxTnRS1jzLJH6VRJHZINs5mksgApaQb6MJPtqKPcB/6qVYWPsW1HnDFjoF8/t8GuCUzaaokqEdeZbH7VIRmTVPF8ZZrCBvhQqC1SxnpIIRVqn3eem8m2v8a6qiBZHVJVtvf0iboLsZA9k80vta6FBMHsy5ZWVn9UnyxASho/htjAFWoXq61pmwObHoGeAssB+GXYMLe698MPB9tOLawOyfgkLVP9K2XDbCaJLEBKmgHHuiLtnq7azlPqQ79PG/QdBdueqa2dcsR9NpsFSKZCtayoHZep/qUU2nbEmLSwAClpmlqgz0i32nUtTjgB1q+Hjo7Cx9i2I86kSW623Zo1Ufckleq1/igJM9nKrUPKZnVIJi0sQEqigVNgR42F2o2NMGsWPFRkxeywCrVPPx1eecUFbHEkUnrtKBOZeg2w/GB1SKVZ/VH9sgApifxYURtKDx1lCrWDnuLe1ATnnAN33hlsO7WwYTYToLjOZPOT1SGZpEn/qzKN/AqQShVq9xsH0gSdL9XeVilWh2RM4hSqQ7JhNpMGFiAlkR9T/QFOOw2WLYPOzvy3i4Q3zHb++XDXXdAT0xT+Kae4daO2bo26J6lSL8NjcZ3qX45q6pCMSQMLkJJo4CTYsRy0xmCiTx/3wf/oo4WPCatQe+xYN+X/iSeCb6savXrB9OnxXo7AxEqhmWzlTPUPcyab1SEVZvVH9c0CpCTqNQB6D4Fdr9Z+rlJDR2FlkMDNZrNhNmNSy+qQTJJYgJRUA3zYcgRKf+gPPA72bYI9IcwwO//8eE/3twDJ+Cx7qn9SC7WtDsmkVTJfkca/FbVnzoRFiwpv9SEN0DYbNoYwxf2MM+Cpp2D79uDbqsaMGa5/e6wmww/1Un+URvU0zGbqlwVISeXXTLZBg2DChOK1P2ENs/XtC7Nnwz33BN9WNfr1g+OOcwGliRULtmpTqg6pHgu1rf7IWICUVH4FSFDGxrUhFWpD/FfVtmE2U4FathxJkuxhtlKsDskkhQVISTVgsguQ/FjEsdSH/pCpsPNFOLCj9rZKyQRIQS9OWS0LkEyVKp3qX85MtrCm+lfC6pBMWliAlFS9h7h92fZUNkU3r8w2GoXWIGrs7YKkjSFMcT/2WGhocOszxdHs2fDII9DdHXVPEq3eh8TKmeofN7nDbFaHZNLOAqQkG+jTTLZRo1wtUrGgpG1uOIXaInDhhfDnPwffVjXa2tzf6+mno+6JSaGkzmQzplwiMkRE7hKRFd6/gwsc988i8pyILBWRG0WkT9h9tVdjkvm1ojZYHVIlSv2tjKlA9lT/KFW6YGSuQtP984l7HZIVaAfqauAeVZ0I3ONdPoSIjAY+DkxT1eOBRuCdofYSC5CSza+p/lDGxrUzYcsS6N7nT3vFnH22W917167g26qG1SEZA5Q3zGZ1SCbHJcD13u/XA5cWOK4J6CsiTUALsDb4rh3KAiQ/SFM07Q6cAp0v+3OuuXNhyZLCt/ca4BWGL/WnvWL693f7xD3+ePBtVaPU38qYLGmayVaP0/2N74ar6joA79/23ANU9XXgG8BqYB2wXVXvDLWXgGhcZwtlEZGNgA/7ahxmGLApgPMGKWl9Tlp/wfqc7UhVbavmjva6PUTS+py0/oL1OVvZr1sR+YvXj3L1AfZmXZ6nqvNyznk3MCLPfT8PXK+qg7KO3aqqh9QheXVJvwX+DtgG3Azcoqq/qqCfNYso9VGZat+gSxGRxao6LYhzByVpfU5af8H67Bd73R6UtD4nrb9gfa6Wql4QwDnPLXSbiGwQkZGquk5ERgIdeQ47F1ilqhu9+9wKzAJCDZBsiM0YY4wxYbkNuNz7/XLgD3mOWQ3MEJEWERHgHCD0tV8sQDLGGGNMWK4BzhORFcB53mVEZJSIzAdQ1ceAW4AngGdxscq8/KcLTiKG2AIU+h/cB0nrc9L6C9bnuEviY01an5PWX7A+J4KqbsZlhHKvXwtclHX5C8AXQuzaYRJRpG2MMcYYEyYbYjPGGGOMyWEBkjHGGGNMDguQjDHGGGNyWIBkjDHGGJPDAiRjjDHGmBwWIBljjDHG5LAAyRhjjDEmhwVIxhhjjDE5LEAyxhhjjMlhAZIxxhhjTA4LkIwxxhhjcliAZIwxxhiTwwIkY4wxxpgcFiAZY4wxxuSwAMkYY4wxJocFSBUSkXEioiLSFHVfTHyIyJ9F5PKo+1Ev7HVYX0Tk5yLyn0Vu7xSRo8LsUzlE5Isi8ivv97FePxuj7pcpjwVIBhGZIiKLRWSr93O3iEzJul1E5Osistn7+S8Rkazbx4nIfSKyW0SWi8i5Oed/l4i8KiK7ROT3IjIkzMcXBlW9UFWvL+dYEblfRD4cdJ9MsojIDBG5S0S2iMhGEblZREZm3f5pEVkqIjtFZJWIfDrn/q+IyB7vQ7hTRO7MuT21r0NVbVXVl6PuRzGqutrrZ3fUfTHlsQDJAKwF3g4MAYYBtwG/ybr9CuBS4CTgROBi4CNZt98IPAkMBT4P3CIibQAichzwY+C9wHBgN/C/wT0UYxJrMDAPGAccCewEfpZ1uwDv8467ALhSRN6Zc463eh/Crar65jfuaK9DYyqnqvajCvAK8GngGWAXcB3ujeTPuDequ3FvTOMABZq8+43CBRRbgJXA/yujrenAI8A2YB3wfaA56/bzgOXAdu+2B4APe7d9EfhV1rG5/fkAsMzr88vARyr8OzQB/wDszrruYeCKrMsfAh71fj8G2Af0z7p9AfBR7/evAr/Oum0CsD9zPHA/8DXgce/x/gEYkvPYrsAFceuAT2ad64vAzcCvvMf7rNefzwEdwGvAm71j3wksznms/wzcVuRvMd77P2rwLl8LdGTd/ivgn7IeR+b/6P3AQuAbwFZgFXChd9tXgG5gL9AJfN+7fhawyPsbLAJmZbVzP/AfwEPe47wTGBb1a8Zeh8G9Dr1znArsLHL7d4Hv5fztzi1wbGJfh94xPwd+ANzutfEYMCHrdgWO9n7vC/wP8Kr3WBYCfb3bZuDez7YBTwNnlfmcPDfn8f4q529zObAa2AR8vsSxmefI/cB/ev3pBP6I+5J5A7AD9z4wLurXZD3/WAbpUH+De1M8Bngr7k35X3BZlQbg43nucyOwBvcG/XbgqyJyTol2unFvCsOAmcA5wMcARGQY8FvgX73bXwJmV/AYOnAZngG4N+lvicip5dxRRLbhPri/h3tDzTgO92aS8bR3Xea2l1V1Z5Hb37ivqr6Ee2M+Juv49wEfxP0Nu3Bv/NneBEwE3gxcnTOE91bgl7gPzSeBO3D/V6OBL+O+NYP78DxWRCZm3fddwK8pQFVX4d6oTvGumgt0ishk7/IZuA/NfE4HXsD9H/4XcJ2IiKp+HhdAXqnuW/6V3lDH7d7jHgp8E7hdRIbm9PUDQDvQDHyqUL9ToK5fh1nOAJ7Ld4M3xD03z+03eMNzd4rISVnXJ/Z1mOUy4EteGytxXzby+QYwFfelYwjwGaBHREbjXmf/6V3/KeC3mWx3jeYAx+KeQ/+e9R5RyjtxWb3RuKD1EVzWcAguwP6CD30zVbIA6VDfU9UNqvo67kPsMVV9UlX3Ab/j4AclACJyBO6F8VlV3auqT+GyDO8t1oiqLlHVR1W1S1Vfwb15nOndfBHwvKreoqoHgG8D68t9AKp6u6q+pM4DuGzD3DLvOwgYCFyJe5PLaMV9E8vYDrR6b9K5t2Vu71/gvrm3A/xSVZeq6i7g34C/zSlk/JKq7lLVZ3FvHpdl3bZAVe9Q1S7ct9g24Brvb/cbYJyIDFLV3bhvxZcBeG/Qk3Bv2MU8AJwpIiO8y7d4l8fjPvyeLnC/V1X1J+rqDa4HRuIyIfm8BVihqr/0nhM34jIXb8065meq+qKq7gFuAk4u0e8kq+vXofeYTgT+HZdNy+eLuPfv7CG4d3NweO4+4A4RGeTdlvTXIcCtqvq418YN5HkNiEgDLsi7SlVfV9VuVX3Ye+68B5ivqvNVtUdV7wIW4/6va/UlVd2jqk/j3hNOKnUHz8+858l23BeBl1T17qy/4ynF726CZAHSoTZk/b4nz+XWnONHAVtysiev4r4NFCQix4jIn0RkvYjswGVrhmWd87XMsaqq2ZdLEZELReRRr9BzG+7FP6zE3d7gvTn+CPiFiLR7V3figoGMAUCn17fc2zK37yxw39zb4dDH9yrQK6fPubePyrqc+3+0SQ8WQe7x/s38v/2ag2/q7wJ+771hF/MAcBbu2/yDuLT4md7PAlXtKXC/Nz5Ms9rIff5kjMI9rmy5z6PsD+fdRc6VBnX9OhSRo3Efllep6oI8t1+Jy/a8xfvgz/TxIe9Dereqfg03jJQJypL+OoTyXgPDgD64jF+uI4F3iMi2zA8usB6Z59hKVfv6rPS5bkJkAVJt1gJDRCT7W9hY4PUS9/shLkMwUVUH4IYPMrPC1gFHZA70sjRHZN13F9CSdXlE1rG9ccMC3wCGexmh+VnnLleD10bmA+Y5Dv1GdBIHU/vPAUfl/A1yb3/jvt5U3N7Ai1nHZz++scAB3Fh+odvXVvBYst0JDBORk3Fv0OWk9R/Afcic5f2+EDfUciaFh9dK0ZzLa3Fv3tnKeR4ZJzWvQxE5Eldn9R+q+ss8t38QuBo4R1XXlDidZrWZ9NdhuTbhygQm5LntNVyWbFDWTz9VvabEOQv+X5t0swCpBqr6Gq7A7msi0sdLi38Il/4tpj+utqVTRCYBf5912+3AcSLy1+LWePk4h74gnwLOELemxkBcIWRGM+5NbyPQJSIX4uoFihKR80TkFBFpFJEBuBqYrbgxcIBfAJ8QkdEiMgr4JK5oElV90evTF7y/wV/hZrr91rvvDcBbRWSuiPTD1SPcmvNt/z3ilhpo8W6/RQ+dCvtvItLizcT5APB/pR5TPl7a+hbgv3Fj/HeVcZ8VuG9y7wEeVNUduG95f0P1AdIGIHvNlvnAMd407CYR+TtgCvCnKs9fV1L0OhwN3Av8QFV/lOf2d+OyXOdpzpR2rx+zRaTZ+xt8GpdNecg7JNGvwwrO3QP8FPimiIzy3tNmekHrr3B/g/O96/uIyFkiMqbEaZ8C3ikivURkGq7GzdQBC5Bqdxlu3H8trj7iC97YdjGfwqWWdwI/IeuNRlU3Ae8ArgE244oiH8q6/S7v+GeAJWR9iHpvdh/H1ahs9dooZ2x/EK7IdTsuNX00cIGq7vVu/zFuhsWzwFLch8ePs+7/TmCa1+Y1wNtVdaPXp+eAj+LeoDtwH0ofy2n/l7iAaz0uPZ5bhPsArijzHuAbqnon1fs1cC5ws/dGXY4HgM2qujrrsnBonVYlvgO8XdyaU99V1c24gt5P4v7PPwNc7D0XTHnS8Dr8MC5w/oIcXMuoM+v2/8QV8S/Kuj0TSPXHZcS24jJnF+BmTm72+pSG12G5PoV7r1qEm9X4ddxM1NeAS3CZwo24jNKnKf05+G+4jNRWXJG4nxkvE2PihtZNnInI/bipotdG3Re/FXtsIjION0W+VwBvosZUxF6H9jo09cUySMYYY4wxOQILkETkpyLSISJLs677b3FbUTwjIr/LmoKaOuL25urM8/MvEfXnXwr0589R9CdOROS5An+bd0fdN1Mbex0mR5SvwwLtdopI2UszmINE5AIReUFEVorI1XluFxH5rnf7M5KzRphXI/akiERahxnYEJuInIGbWvoLVT3eu+7NwL2q2iUiXwdQ1c8G0gFjjDHGhErc2lkv4hZ7XYOrBbtMVZ/POuYi4B9xy1+cDnxHVU/Puv0TuLrWAap6cYjdP0RgGSRVfRBXIJd93Z1ZY9iPAqVmDxhjjDEmOaYDK1X1ZVXdj1so9JKcYy7BJU9UVR8FBom3MbM3q/AtuMVeIxVlDdIHcYuhGWOMMSYdRnPooqJrOHzR1mLHfBtve5iA+le2pigaFZHP4/b6KbhOiYhcgdsckX79+k2dNGlSSL2LqaeWwLHHQN/+pY/1U+fL0Gsg9Pa2BXv5ZRgwAIaVvTi3v7Y+B6/sh5NPBql0/UtTqSVLlmxS1bL3qsp+3ba0yNSjJkTyFhOI7T19ou7CIXZ0Hd6fvQd6HXJZD5T+Diy9Dv8c6tPrwCGXBzTtPeyYqLT3Oab0QXWuktftGWf10a1byo9Flj574DncYpwZ81R1XtblfG/MubU8eY8RkYtxG4IvEZGzyu5UQEJ/9xKRy3FrvpyjRQqgvD/4PIBp06bp4sWLQ+phTJ19BFx4Bnz6J+G2++L/wpZFMMPb8un66+GPf4Rbbgm3Hxl/OQ0+sRV++EOYPj2aPtQREcndAqWo7NftCSc2663zIwqkAzC/c0rUXTjEvZsO/9K4bP2h2/11rW057Jh8mkYdutPH5BEbDrl89rDlFfYuOFdNujvqLsReJa/brVt6qOR1eswR6/aq6rQih6zh0FXXx3D4quuFjnk78DavRqkPMEBEfqWq7ym7gz4KdYhNRC4APgu8rcy9d0zGrNNhwYPhtzv8TbDhvoOXL7wQ7r4b9u8Pvy8A0gSnnwgLDtuiyhjjk9xAK18wZkwBi4CJIjJeRJpxCwnnLpR6G/A+bzbbDGC7qq5T1c+p6hhVHefd796ogiMIdpr/jcAjwLEiskZEPgR8H7eC610i8lTWKrCmlDe/A55YFX67AyZB9z7o9Npub4dJk6ILUBqa4PQTLEBKsfmdU2KXrUm7cjNNcfCd5edG3QVThDcR60rgDtx2VTep6nMi8lER+ah32HzgZdzK7D/h8FXdYyGwITZVvSzP1dcF1V7qzfwr2HoAVj8HY48Lr10RGH6WyyK1jnfXveUt8Kc/wTnnhNePN/rTBNOnwL/+AFStDsnklQmwLmp9vsSRyXX2sOWHZXYmj9hwSPanadRu34KfezdNitVQm4kvVZ2PC4Kyr/tR1u8K/EOJc9wP3B9A98pmK2knRa9mOL4N/nJ9+G3nDrNdfLELkKLQ0AtGDobWVlhub9ZxVk1Rs2WO4iN3mM2YemMBUpLMOBnuj6BAsd0LkDI19SefDLt3w4svht8XaYKeLpg714bZjPFROZkmq0Uy9cQCpCQ5522w+IXw2+1/tPt350r3r8jBYbawNTSBWoCUFJVkhHKPtWxS9OKaRbI6JBMGC5CS5Jz3wOrdsCV3xmTARNwwW0fOMNvtt4fbD/AySAdcgLRwYfjtm0RJe5CVryYod4p+7hT+YpJUrG1M0CxASpJ+g2DiALjzF+G3nVuHdM458PjjsH17uP3IZJAmTYKdO2HNmnDbNxUrJ0jxM5BJe1AUNRtmM/XCAqSkmX4c3De/9HF+G55Th9SvH8yZA3feGW4/pJerQRJx7dswmwlJmmfEZcvNIsV1mM2YoFmAlDRnng+PPRt+u63jobEP7MhK6UcxzJbJIIHVISVIsaxOtbeZ6FgWydQDC5CS5oL3w/JtsKcz/LZzh9ne8haYPx96QtxTUCxAMpVJe5Dldx1SPnHMIlmhtgmaBUhJ034kjOoDD/wmgrbfBB33H7w8bpxbWXvRovD60OAVaQOccgq88gps3Rpe+6Zq+QIVv4OXtAdDYbEp/8ZYgJRMp02Eu38XfrvDz4QN9x+sQ4Lwp/tnapAAevWC00+Hhx4Kr31jjDF1wQKkJDrjHHhkSfjt9jsSmlphx7KD14W9qnZ2DRJYoXbCVJPhsaxQNCyLZOqdBUhJdMF74ZkO6O4qfazfhp/lskgZM2fC6tXw+uvhtC85AZLVISVWmIFP2oOscuqQamV1SKbeWICURBNOhdZGeDyChRrbzzq0DqmpCc4/P7zZbNk1SAAzZsDTT8OePeG0b2Ir7UGQMSZcFiAl1alHwl3/F367+eqQwpzun9mLLaNfPzj+eLdopUmE+Z1TLJiJQDUz2WyYzdQzC5CSas4cWPhw+O3mq0O64AK4775wsjgNvQ4dYgMbZqsDFlDFQxyH2YwJigVISXX+ZfBkRNts5NYhDRkCJ50E999f4A4+yq1BAivUNobg6pDinkWyOiQTFAuQkurk8+BADyx/JPy2c+uQwE33D2OYrSFniA1cgPToo9AVQdG6iYWw93szxqSfBUhJ1dAAJ42EP/8y/LYL1SH96U+HXhcEySnSBhg2DEaPhmeeCbZtY4wNs5m6YQFSks2aDgvuD7/dfHVIxx3n/n0+4A0989UggdUhGVODljUNtKwp/HEQ92E2Y4JgAVKSnfc3sOTlaNrOrUMSCWdV7Xw1SGABUh2wIbLSStUhlZrJVixIijOrQzJBSOarwThz3g4b98HaFeG3XagOaf78YNvNV4MEBwu1gx7iM4lmQZYxplwWICVZcx+YMgT+8vPw285Xh3TGGbBkCezaFVy70gR64PDrjzwSmpth5crg2jaxZEGPvwplkbKH2QrVIdkwm0kTC5CSbsbJcP+d4bebrw6ptRWmTg12qCt3ocg3rhcbZjPGJ0kdajPGT/YqSLqz3wqLlpU+Lgi5dUgA554Ld90VXJuFirTBAqQ6YNmi0vxaDylpQZLVIRm/JesVYA533vtg1S7Y3hF+2/nqkM49F+6+O7g2C9UggQVIpiwWZFWvnGE2Y9LCAqSk6z8EjmqFu38Vftv56pBOOw1efRU2+LuT+BsKzWIDmDIFtmyBdeuCadvEjgU7lcudyVYsU1RNFsnqkExaWICUBqdNhnsDnl6fT746pKYmOOssuPfeYNrMt1BkRkMDzJ4NCxcG07YxdShpQ23G+MWe+Wlw1vnw6NPRtF2oDimoYbZiNUhgw2x1wLJGpeWrQwqCDbOZNLMAKQ0ueD8s2wL794bfdqE6pLvuCmZNomI1SGABkimLBVmVyc4ixXlVbSvUNn5qiroDxgcjJ0B7b3jg/+C8y8Nte/iZ8OSnXDAk4q479ljo6YEVK+CYY/xtr9A6SBlTp7p2d+6E/v39bdvEShKCnItaS2+9E9bjmDxiQ11kfMIIkq6aFOBEFBMblkFKi2lHwz2/C7/dfkdCY1/YmbWatwi86U3w4IP+t9c8BPYWKQBvboYJE2BZREsfmFBEFRyVE/DE4ZwQ3jCbMWllAVJazD0THn48mrbb5sDGnMLoM84IJkAaeBzsWQ97NxY+xgq1jSmq1J5s+RQaZrNVtU1aWYCUFhe8D55e74a2wtYeYoDU0AjDZh7eXjarQ4qFgQ0R1MSZiu0eE8F7RsJZrVN9sAApLY49HXo3wJK/hN92vgzSMcfAnj1uTSS/tc+FjiIB0Ny5LoNkG9cac4hqVtSuhWWRTJJZgJQmp46Fu/4v/HYHHgd7O2BP1puviMsiBZHJaZsLG4ucd8wYty/cCy/437apSFD1NVGq5DGVWyuVxL+TraptChGRC0TkBRFZKSJX57ldROS73u3PiMip5d43TBYgpcnsmdHU3kgDDJsFmx469PqghtmGngbbn4cDnYWPmTPHhtlMUUmYBVerYoXatdYhlcuySPVFRBqBHwAXAlOAy0Qk98V2ITDR+7kC+GEF9w2NBUhp8ua/gydWR9N2+xzYGFKA1NgHhpwCmx8tfIzVIcVGErMjxpRidUgFTQdWqurLqrof+A1wSc4xlwC/UOdRYJCIjCzzvqGxAClNTrsYdnfDysXht52vDun4492ebEHsy9ZWRh2SBUjGlMWPQm0bZjOe0cBrWZfXeNeVc0w59w2NLRSZJg0NcNJw+Msv4cpp4bY95DTYthS6dkFTP3ddY+PBoa63v93f9trmwvJvFL590iTo7IQ1a1xNkjE+uqj1ed+H6II4Zz61LhjZsqbhjYCqa21LWUN1926aZOsyxdT2nj4VPu/WDROR7G/h81R1XtZlyXOn3BkzhY4p576hsQxS2syYBg/eF367TX1h8EmwOWctpqCG2dpmweZF0L0//+0iLjiz9ZBiwYbZohNmYFIs8LJapNTYpKrTsn7m5dy+Bjgi6/IYYG2Zx5Rz39BYgJQ2514Ki1eUPCwQbbOhI6T1kJoHQesE2Ppk4WOsUNuYoqop1K7FvZsmpSpQsjqkvBYBE0VkvIg0A+8Ebss55jbgfd5sthnAdlVdV+Z9Q2MBUtqcdRms2wsdAaw/VMqw2YfPZDv1VHjpJdi61f/22uYUn+5vdUixYlmkdCpn89pcaQuUzEGq2gVcCdwBLANuUtXnROSjIvJR77D5wMvASuAnwMeK3Tfkh/AGC5DSpncLTB4Mf/lZ+G0PO90Ne2Uv0NirF8yYAQ89VPh+1Sq1YOQpp8ArrwQTnJm6V88BX7Hp/pXUN1mQlE6qOl9Vj1HVCar6Fe+6H6nqj7zfVVX/wbv9BFVdXOy+UbEAKY1OPxHuvyP8dvuOhKYW6Hz50OsDq0Oa62bOaYEZOL16wfTp8PDD/rdtqhK3oCKMouhK2ghr49p8K2pHteWIZZNMXFmAlEZvuggejygrOeQ0l0XKFlSA1DLK1SLtKFKEanVIxiRCUgMlq0NKLwuQ0ui898HKnbBrW/htD51++Ey26dNh6VI37d5vbXNsPaSEiVsWqd5VW6idPcyWW4dUyzICmUApicGSSRcLkNJo8Ag4sh/c/cvw2x46HbbkBEh9+7p6oEeLrHxdrVL7ss2YAU895TbONcZnFuwFywIlEyULkNLqtElw7x/Db3fIVNj6FPR0HXp9UMNspQq1+/VzK3ovWlT4GBM6CywKC+tvk68OyU9+rqxtgZKJggVIaXXmufBokTWCgtI8EFqOgO05NVBBBUj9j4GevbCryB50NsxmTFkLRtZSqF3NdP9KxXX4zeqQ0skCpLS64HJYugkOFFhpOkj56pBmzYLFi2HfPn/bEsm/D1w2K9SOJcsixUc5dUitrx8ePBWb7h+0OAZKJl0sQEqrIybDkGZ46Lfht51vJlv//jB5cjBDXaUKtefMgUcege5u/9s2xhQUxga2FiiZoFiAlGZTj4K7IwiQ8mWQIOD1kIoESMOGwejR8Mwz/rdtapKGLFI5j6HS9ZaS+ncJY5itEAuUjN8sQEqzuWfAw4+F3+7gk2Dni9CVk7YPKkAafLKrQdq3ufAxVodkCghjsci4KrdQOzO8Vs0wWxhZpGxxrVMyyWMBUpqd/x54ci30hLxCbmNvGHjc4RvJZoa6urry369aDU0wbAZsLLKdiQVIsZXUbEkSlVOonSZhBkpWqJ0+FiCl2ZTZ7n/4mfvCbzvfMNvQoW6o69ln/W+v3ELt7H3ijDGHqXXLkSiH2QqxjJKphgVIadbQAKeMgTtuCL/toaflr0OaOdNlkfxWaj2kI490e7O99JL/bZuaJT2LFET/w/6blLuidr5htlLCHmYrxIIkUwkLkNJu9kxYWCSzEpSh0w+fyQbBBUhDT4dtzxxe95QhYsNsxgQkyun+lbIgyZQrOc9qU53z3gFPvBJ+u/2Phb0dhxdOBxUgNbXAoBNhc5GidAuQjDlMNStql8oi5RtmW7Z+eOozSVaHlC4WIKXdzEtgexesCnmKe0Oj23YkN4s0eTJs2gQdHf63WWqYzRaMjLWkD7MlRdSF2mkPkkx6WICUdo1NcEIb/OX68NvON8zW0ACnnx5MFqlUofZxx8HmzbB+vf9tm7pXKsBL+3IClQyzxSmbZEwhFiDVg5mnwoJ7w2+30IKRQQ2ztc2GTY8evlFuRkMDzJ4dTU2WKUtUWaS4Bi9R/T3KmclWzTBbrqiDJMsimWICC5BE5Kci0iEiS7OuGyIid4nICu/fwUG1b7KcfQkseiH8doeeBlsWHT61ftasYAKk3kOh31jY+lThY6wOyZjDZOqQyp3J5qe0BUlWh5QeQWaQfg5ckHPd1cA9qjoRuMe7bIJ29rvgtT2weU247bYc4f7d/dqh159+OixZAgcO+N9mqW1HLECKPatFSq5qZ7NFPeRmmSSTT2ABkqo+CGzJufoSIFMMcz1waVDtmywtA+CYgXBHyHVIIvmH2QYOhHHjgtkbrdTGtVOnwosvwo4d/rdt6l4ag7tiQ2l+DLNlizJQsiDJ5Aq7Bmm4qq4D8P5tD7n9+nX68XDfn8Nvd0iRBSMfftj/9trnukLtQitmNzfDtGnBtG18k8ZAo1pB/C2inslWStTDbsYANEXdgUJE5ArgCoCxY8dG3JsUmDkdvv/r8NsddDy8/LPDrz/+eJfJ8Vu/sbB/K/QcgMbm/MdMmABrQh5urBPZr9tRoxsj7o2JQsuahpq3K4GDQVI16zRVK5NFqjWAtDqkdAg7QNogIiNVdZ2IjAQKLoajqvOAeQDTpk2zDbRqNXUiLN8M+/ZB797htdtyxOE1SAAjRwZXCyQCFHnKiNiebAHJft2ecGKz/ZF9ENUMu91jemhZ00Dn6IaCQ2mdo4MfhMjOJoUVLOUbbot71s34L+wA6TbgcuAa798/hNx+/erfF44Y4IqjZ80Kr91iAdK6dQE1KiVuLnG7iVzYQYFfw1hxXS6gEk2jdte04awf2aNCogiWMnKDJguY0i+wAElEbgTOAoaJyBrgC7jA6CYR+RCwGnhHUO2bPE4a7rI2YQZIfdrgQKfbI60p60030AAJimaQwDJIJnRxr6uaPGJDRbU/YWSPiokyWAILmOpBYAGSql5W4KZzgmrTlHBSu1sk8bOfDa9NaYCW0bB7DQw45uD1mQBJNYCMjmWQjCnl7GHLUzNzK+pgCQ4NmCxYSgdbSbuenDQcHnoIeoJLgeeVb5itXz/o1Qu2bw+mzVIZIssgmQSI65Bd1NmjYjJLBdi6SqZWsZ3FZgIwtC8MHQrPPQcnnBBeu6XqkAYN8re9coq0TWzFNSgoJan9TrPcICmJM+JMdOL7NcAEI4qVpFuOgF1hFmqXEQBZBsl4wqgNinv9USXinD0qJYrMkmWTkiu5z3RTnblzw9+stV+RDNLatQE1ahkkY/yS5KAon7ADpXs3TbJAKYHS9aw3pc2Z4zJIYWZQQp/qbxkkY/yQO2XfAqXaWKCULOl6tpvSjj7abRL76qvhtRnFWkjFAiDLIMVWUut4guh3GH+LQvUxTaN2H3Zd2oKjbFEESib+0vuMN/mJhF+HFHaAVKpIGyyDZACrPzKHisMMOBMfFiDVo7ADpObB0NMFB3Ycen1UQ2y21YgxpoSgg6V6zSKJyBARuUtEVnj/Di5w3AUi8oKIrBSRq/Pc/ikRUREZFlRfLUCqR2EXaou4Qu3cmWyBrqZtAZAxlYpqkcW4CypQqtMg6WrgHlWdCNzjXT6EiDQCPwAuBKYAl4nIlKzbjwDOw+3IERgLkOrRiSfC66/Dpk3htZlvmM0ySCYFklp/lCRda1vK+glaEIFSHQZJlwDXe79fD1ya55jpwEpVfVlV9wO/8e6X8S3gMwT8TdgCpHrU2AgzZ4abRcoXIA0aBPv3w65d/rdnRdqJk9QNaqNuo1ZxX8iwksAnrIDJ70CpzoKk4aq6DsD7tz3PMaOB7A+MNd51iMjbgNdV9emgO2oraderTB3SpZeG016+AEnkYBbp6KP9a8uKtI3xze4xPbSsCf+7tB8BTu458s3Oq0UmSPJjaPLeTZMiCVZ3dPWpMEC7Z5iILM66Yp6qzss+QkTuBkbkufPny2wk37dYFZEW7xxvLvM8NbEAqV7NnQuf/nR47bUcAZseOvz6IAIk26zWmMQKMvOTOXcQgVId1W9tUtVpxQ5Q1XML3SYiG0RkpKquE5GRQEeew9YAR2RdHgOsBSYA44Gnxb2PjwGeEJHpqrq+wsdRkg2x1avp092ebEEMb+UT+nYjlkEywUtz/ZHfQUQ5wqgjyrTjd1t+DLvVyVDbbcDl3u+XA3/Ic8wiYKKIjBeRZuCdwG2q+qyqtqvqOFUdhwukTg0iOAILkOpXnz5w0knw6KPhtFdsuxHfAyTLICWN1R+ZKAQVKNWiDoKka4DzRGQFbibaNQAiMkpE5gOoahdwJXAHsAy4SVWfC7ujFiDVszDXQ8rUIOVmboLKIJXKEFkGydQoLpmetAgre1SobT/btyCpMFXdrKrnqOpE798t3vVrVfWirOPmq+oxqjpBVb9S4FzjVDWw6dgWINWzMNdD6tUfGpph/5ZDrw8iQCpVpG0ZJGMO4VdxcO7ebUnjZ6Bkq3EnnwVI9WzWLHjsMbc3WxjyzWQbNSr8ITawDJKJpThkpeqo2LigKLNZGWnOIiWFBUj1bPBgGD8ennwynPbyFWpHMcRmGaRQbO/pU9ZxSaw/ikMgE6agM0NxCEhy+ZFNsixSslmAVO/CrEPKV6gd2BBbCZZBMgGyAu30qDVQsiApuSxAqndRFGpnGzYMduxwK2r7qkQGyQKkUKQx05LGxxSlSoOPljUNZf0E0c9qA6VqgyQbZouWBUj1LlOoHUbA0DL28ACpoQHa22G9n8tYWJG2MX6IYi2kYioJfIIKmsIOkkx0LECqd6NHw4ABsDyEJe5DWwvJhtjipFjGJWnZmCD7m7S/Rdj8CHD8CpTCDJIsixQdC5AMzJkTzjBbmKtpW5G2ycMWiKxeEIXa5QYafg+Z+REoxbGw3PjLAiQTXh1SyxjY8zpozhut3wGSFWnHThqyI2l4DMWUsxZS0tc5yhVFkGRZpOSwAMmEt2BkYx/oNRD25qyzEshUf8sgGZMGQRRc556/ljaqKd62eqRksADJwLHHuk1r16wJvq1+42DXq4deF0gNkm01Eje5GZgkZWSC7mvc/hbFFov0K4tUTlARdHCU21atgVKQLIsUPguQjMuohFWH1O/IkAKkYjdbBqkeWf2Rf9I21JYtrCDJskjxZwGScVIVIGGb1cZU3DIl5Uhin8MQdJAUZvYoX9vVth9kJsmySOGyAMk4YRVq9zsSdr1y6HVhF2lbBsmYshVbC6naIKlUEBFlcJQt6H5YFine4vEsNNE74YRw1kLqPQz2bTn0uoED3WravrIMkqmdZY+So/X1nkN+/FJNkGRZpHRoiroDJiYaG8Npp3sPNPU99Lo9e6Bv3/zHV82ySHFlQUe67B7TQ8uaBt+G3KoJSPIFRJnrOkf7s8BkmuuuTH6WQTLh6t4DjWEESMYkR9KLu6MMHkpli/zKKFUauJWbRbJhtviyAMmEywIkk2KWHTtUnPZy83voLUo2zBYOC5BMuLp2Q2PONysLkEwMhR3sJD2LFIWwA564FI+bcNj/tglXoRqkFtvXyBhTvmqDo1qDqkqCJCvWTjYLkEy48g2x7d5tGSRjSFcWKU7Da7niNtRmdUjxZAGSCZcNsZmIWH1QevgR4NRyjrgMtVkWKVjx+F829cOKtE0C1BJMWSAWLD+zP2FkkoLeo80ExwIkE67Q1kEyJpnSNMyWZnHJIpng2P+wCVf3nvxDbFakbUxqlKo/ilN9UtzqkSplw2zBsQDJhKtrd/BF2raNiEk4yyLlF1QwE3SQVM4wmxVqx48FSCZcYdUg2VYipkp+1BBZHVLyVBMkxWWYzbJIwYjH/66pH1aDZExZ4pRFqmRILE7DZ5VK+nCb8ZcFSCZcNs3fGJMilkVKr3j8z5r6UWiIzYq0TQiSNvQVpyxSvQgqi2TT/ZPHAiQTLltJ29SJpAVjpnp+ZZFqLdS2LJK/LEAy4ereHX0Nks1yMwXEMaiJKos0ecSGiu+T5PqjbFaLZMACJBMm7YHuffFYSdtmuRljiqg0SConixTGMJtlkfxjAZIJT/deaOwNkvO0syJtY4wxMWMBkglPvhlsYEXaJrXiOGQXlLQMr2ULIotUStoXjBSRISJyl4is8P4dXOC4C0TkBRFZKSJXZ11/sog8KiJPichiEZkeVF8tQDLh6d4DTXkCISvSNjFQT8FMEqWlLshms3E1cI+qTgTu8S4fQkQagR8AFwJTgMtEJPMC/S/gS6p6MvDv3uVAWIBkwtNdJINkAZIxJoaiyCKl3CXA9d7v1wOX5jlmOrBSVV9W1f3Ab7z7ASgwwPt9ILA2qI42BXViYw6Tbx82CCBAsllqcTCwYW/UXTA+SuMQWrlaX++hc7QFPj4ZrqrrAFR1nYi05zlmNPBa1uU1wOne7/8E3CEi38AleWYF1VELkEx4Cg2xBZJBsllqJr/5nVNCnTofdnvGVGLvgV6V1j0NE5HFWZfnqeq87ANE5G5gRJ77fr7MNvK9gWe++f498M+q+lsR+VvgOuDcMs9bEQuQTHiKDbFZkbaJkNUfmVIqySK1rGlg95jCQ3Nda1uKZuSWrR9e1TpUIdmkqtOKHaCqBQMWEdkgIiO97NFIoCPPYWuAI7Iuj+HgUNrlwFXe7zcD15bd8wpZztCEp9AQmxVpG2NMvbgNF+Tg/fuHPMcsAiaKyHgRaQbe6d0PXKB0pvf72cCKoDpqAZIJT9fuw4fYDhxw//bqFX5/TOBsaMkUksSaprTMpIvYNcB5IrICOM+7jIiMEpH5AKraBVwJ3AEsA25S1ee8+/8/4H9E5Gngq8AVQXXUhthMePLVINkMNmOMqRuquhk4J8/1a4GLsi7PB+bnOW4hMDXIPmZYBsmEJ18NktUfmYiFUX9kNU7pUW4Wqdbp/mlfMDIJLINkwpOvBskySMaYEPRfteeN33eOj/49p1ShtomeZZBMePINsVmBtjEmQP1X7TkkOMpcVwurRaoPkQRIIvLPIvKciCwVkRtFpE8U/TAhKzTEZgFSqsWxUNuGvJKlmoAkX2CUe3vQbFXtZAv9f09ERgMfB6ap6vFAI24Kn0m7fLPYLEAyEQozULKgLBylAqNqj80VRhbJ6pCiFVUNUhPQV0QOAC0EuJeK8ajClj3QkW9NLg5Otw9S9578NUhWpG2M8UG1wU7/VXsiqUuyOqR4Cz1AUtXXvT1UVgN7gDtV9c7c40TkCrz1DcaOHRtuJ9Po13fCV26FAfcVPmbSpGD7sG8TNA869LpNm2DgQH/b0R6KbjXS0wNiW5EEIft1O2p0Y8S9qc1Frc9b1qeORBUkmfiKYohtMG5X3vHAKKCfiLwn9zhVnaeq01R1WltbW9jdTJ8HHoYvvddlkAr9PPtssH3YshgGn3rodY88Aqefnv/4anXvgaYib3T79kHv3v62aYBDX7dDhhx8e0lqHVIc+m1BWvl2ju9bcZCTuU8UwZFlj+Itigqyc4FVqrpRVQ8AtxLgbrwGlzF56nU4/93R9WH369C9F1qPOvT6hx6COXP8bSvfUF62vXuhj80LMOGzYKc65e6BllFO0FNrUFRpn6oR4/3Y6kIUNUirgRki0oIbYjsHWFz8LqYmzz8E3Qonvim6Pmx+DIaefujQ1s6d8MILcOqphe9XqZ4DgIIUeWpbBsmUEIfMEUQfUE0esSGwQuGuteHUHmYHQWEPoxXbsPb/t3ff8XFVd/7/Xx9J7gXbWO4Y2xRjY3DBFdsUUwIkAdJIsiEhpH3TdiGb7Ibd5JtNst/kR5JdstnNJrsOZU1LQgIshNCMKZaNbXDv4GAb917lLunz++OOsCyrjKSZe+7MvJ+Pxzw0d+beOR9LGs3H53zOOZJ8sfcgufs84I/AQmBZKoapccdRUF58BEb0gaKAU053pRKkmubOjZKjTCYrlUej3qOGaozUgyRSkDKVHMXReyThBfkpu/s/ufsF7j7M3T/t7sdCxFEwZr4Gl44NG8PuudB9/KmPzZoV//AaqAcpkKT0yjRVrsbdVC/vyvIkjTyRbnLUWO9RY/VHGl4LT2lwIViwFq75aLj2qypgz0I4c8ypj4dKkNSDJAGlO2wWenhNpNApQcp3G1fD7uMw8SPhYti/HNr3O3WK/4kT8MYbMGFCZtuqSLMHSQmSSOI0tPJ0Eoa1khCDxEc/7Xz3wjQY1h1atQ4Xw655pw+vLV4MAwdC166ZbSvdHiQNsUk9kjCkpt6j5GlKctTS4TVJBiVI+e7V6TB+RNgYdtdRoJ2N4TVIvwZJPUhBJCH5aI5cjTup4prBlilx9xyp/igZlCDluzdXw1U3ho1h19x4E6SGFokE9SBJcA31ECWt96jQP6w1rFa49JPPZ/u2w7uH4OpPh4vh+H44vAG6XHTyMffsLBAJ6kESaQbNYKtbc5IjDa/lDyVI+Wz6g3BOJ+jQJVwMe96MthcpqrFw4zvvQOvWkI099lSDJC0Qeigtab1HSRNnb042kqN0FHqPXZIoQcpnL/8Zxgb+g7trLnSPaXgNNIstB4ROQiS3achL4qLftHw2bylceV3YGHbNgzNjWCCymnqQJEuyndjlcu/RkF7bY+35KO9blNVEKVu9Rxpeyy1KkPLVscOwai9cd3u4GNyjGWxx9iBVbzXSUExKkCQBkpIQtbT+qKmJUSZnsGUjSQo1tAYaXksaJUj56tXfQe+20OPscDEcWgdFraNFIqvt3AnbtsGFF2anzcojUNzA8FlFRbQnXUmIfZolyUIO/SUlWWqqJHygZypJynavlHqPco8+JfLVjCfhknPDxnBgDfS47NTHZs+OVs8uLs5Om40NsWmbEZGMSEJyVK28bxEdNze9FycTCVGmeo8kedSDlK/mzIfLrgwbQ5/3waWPnPpYNofXoPF1kLRRbSLkaqF2puN+tnxoTvQe1U6GkpQcVWtKspOp3qJ0k6N0eo+S+D3NB2Y23My+nroNb8q1SpDyUWUFLNkO138mdCRgdupxHAmSepBEsibJH+TViU9jt3w2pfvq0CEkhpndATwC9EjdHjazv073+vz+TSlU85+D9sVw7ujQkZyqvBxWrIAxY7LXRmMJknqQEiNJvUhJiiVOTS3QbmlylGtbjDQkiUNrSo5O83lgnLt/z92/B4wHvpjuxUqQ8tH038PILCzC2FIzZ8Lo0dA+i38kG1sHST1IIs2S5J6juDUlOdLwWlAGVNY4rkw9lhYlSPlo1uswaWLoKE43YwZcfXV221APUk7JxZ6bXIw5LvqgD0e9R3V6AJhnZt83s+8Dc4H70r1YCVI+WrgBrv1E6ChO99JLcNVV2W1DNUgikkWZ7j3KBCVHdXP3e4DbgT3AXuB2d/+3dK/XNP9889Y8OFYFlwReQbu2HTtgw4ZoiC2b0pnFpgQpUW7ouDInZnLlG21Q23TZqDtSr1vmmVm3GofrU7f3nnP3Pem8jhKkfPPCwzC8V7QYYpK8/DJcdln2F2hMpwdJQ2xSg4bMJB1JLMoG9R7VYwHgRPVG/Yl6jwzoAmwABqbzIgn7FJUWm/kKTMjiLLHmmjEj+8Nr0PhWIxpiS6RcS1JyLd4kaGwGW/tNyf04ak5ypJWzw3H3ge4+CHgB+KC7d3f3M4EPAE+k+zrJ/Y2U5jn/fLj5c6GjON1LL2W/QBtUpC0iGXO4X1Vie45AvUdpGOPuz1YfuPtzwOXpXqwEKRdVNfCG/fETMOGm+GJJx9q1UWIyZEj222psLzb1ICWWemXio/qjxrUkMUq396gl9Ue5mhyZWTczm25ma1Jfu9Zz3v1mtsPMltd6/GdmttrMlprZk2bWpYHmdpnZd81sgJmdbWbfAXanG6sSpFxwvBz+ch+sfTA6Tlp9UeWxU4/do1u16tlrtVfVzkos6kGS9Ckpk7okudcoD9wFzHD384AZqeO6/A9Q12yj6cAwd78YeBv4hwba+iRQCjyZupWmHktLwj5p5TRHd8CTPWD5D+HNr8Dzo+HwltBRnVR5DJb9AKpqrMVldjIZcofXXoun/gi0UGSOy6WEJZdilfS1NDmKo/YoV3uPUm4CpqXuTwNuruskd59JND2/9uMvuntF6nAu0K++htx9j7vfAUx291Hufme6M9hACVLyzf8baNcPbn4Xrl8MhzZA2Udg34rQkUXe/S0cWgdFxXB8P2x7CWZ+GP5yb/S8GTzwAHwihnWZ3NWDJBJYLk9bj7PnKJe/Ty3U0923AqS+9mjBa30OeK6+J83sUjNbCaxMHQ83s1+l++Ka5p90XUfArtlRQtTlQrj6NZhxFbz5Nbjm1dDRwfpHYPAd0f23/h0Ob4Buo2DtA7DlWZj8R2jdOp5Yqo5DUUmUrNVHPUiJp3WRskv1R6fKZFKUizPX/ERRU/fI625m82scT3X3qTVPMLOXgF51XPudZoRYp1Q9UQXRZrT1+TnwPuBpAHdfYmaXpduGEqSk63IxFHeA7S9D+7PgjCFw+VPw4kRY9G0Y+ZNwsZ04GPVorXvw5Ncrn4dO58Cw78LMm2HvIuh2STzxNNZ7BFEPUrtGzpGCoCGy+CRxk9pM9xYV0KrZu9y9wRV/3b3eKctmtt3Merv7VjPrDexoagBmdhvRlP2r3GsWvNYZy0Y7tf61sr5za9MQW1JVz1TrewN0vgBW/RQ2PAbl78KZY+Csm6GiPGiIFLeDyY9D/1tg70LofH6UHAFUnYDyddA5hplr1dJJkNSDlBOUvEg2VE/bD50cFfDwGkS9Obel7t8GPNWUi83sOuDbwI3u3tg3fqOZXQq4mbU2s28Bq9JtSwlSkuyYBSvujhKLqqMnH7/8f6NEY+VPYe7tsPoXsPF/wQPPtCgqgS7DoN+HYMRPYex/n3xu/aPQcRCUxPg/xxMHoKRDw+ccPAjtk/e/WclNSuSSq2YylM31jOIcVktA71Em3A1cY2ZrgGtSx5hZHzN7b80iM/stMAcYbGabzOzzqad+CXQCppvZYjP7rwba+jLwNaAvsBkYkTpOi4bYkuLtX8GCv4G2vWD1v0K3MTDsO1A6MXp+youw7Iewc3bUm9TvJhj767AxexVYUVTz06YbkNr+puJI9PiF/xhvPLvfhK4jGz7nzTfhs5+NJRwRSV8uTq1vTnJU4L1HuPtu4LRpze6+BbihxnGd0/Hd/dwmtLUL+FQzwgSUICXHugfhnC/B2F9FidC2l2H+12Hs1GhIDeCi70Vfj2yDdnXVv8XM6umALGkHAz8dbywAO8ugdHL9z+/fD2vWZH/DXGmxXCnSzpU4q6lAOzOa22tUiAtDhmRmg4BfAOOJ9mabA3zD3demc72G2JLi+H7YPS+6f9H34JzPQXFHWJpKinbOhiWpCQBtWjIrMkP2LIINj8PaabDuYTj4l5PPbX8Ftk6PP6YdZdCjgQRpzpwoOYprVp0kWq4lN7ksF2d31UfJUU55FHgM6A30Af4A/Dbdi5UgJcW438CRrbDwm9HxoM9Aryth//JoYciNT0Dn1B/00Ctp75oLi74F6x+Cw5tg3xJY9TNY/W9RcXbVCeh0XrwxHd0FRzZHs/7qU1YGkxtIoERE6lDS5/B7t+ZQchSMuftD7l6Ruj1M1JOUlrSH2FKV4ANqXuPuDzYlUmlAt7HQ72bY/AwUtYERP4aLfwhv/ydsmw6j/jV0hCe9/SvofR0M/Ts4vg+ObocDb8PmP0XDg8P/Of6Yds2GM8dHheP1KSuD72RsGQ4RyXOZ6PlSchQ/M0sVxPKKmd0F/I4oMfo48Od0XyetBMnMHgLOARZzcg0BB5QgZUpJa7j4/8Hi4/DOfVGvTNdR0VpDbRMwpFZTr6uj4cDj+6B1l2hz2FZdolqpubfD9lehx+Xx7L1WrbHhtWPHYOFCmDAhvpgkr2mILn9lakhQyVEwC4hylOoPof9T4zkH0vpffLo9SKOBoY0tyCQt1LYbjP4l9LwSlvwjHHgLhv8/6HN96MhO1ef6qLdozm3QfQIcfAdKx8M5n4cDq6HNmTX2Yquqv5g7k3aWRUsN1Gf+fBg8GDp3zn4s0iJxJh7Plg8tmKn6cRVor9rWM5Z2Mi3TdVKFPlstJHcfmInXSTdBWk60bPjWTDQqDShpCwM/BWd9LHWcwILitqUw+Q+w5TnYMRM2PQm734ANf4h6kTY9DXsWwKDPxpMcVRyCfcvhzLH1n6P6IxFJyXbReEuTI/UetYyZfbih5939iXRep8EEycz+RNQd1QlYaWZvAMdqNHJjOo1IMyQxMaqtz/XRbLWOg2DS72DvMnjr59GCje88Byt/AlNegvZ9sxvHrnnQdXi0vEB9ysrgc5/LbhwiUq+SPodj3XIkV2fOKTnKiA828JwDLU+QgH9JOxwpTB0HwsE1sOoe2PEKnPdVOD+1UOmCb0R7sWU7QWps/aPKSnj9dbj//uzGIQVD9UdhJTX5Uc9RMrj77Zl4nQYTJHd/DcDMfuLu3675nJn9BHgtE0FIDjv3i9D7fdHaR4c3wKAav5cH/9L4ytaZsKMMLriz/udXrIDSUuiZm7URhUSJh0ByE6D6ZKLeSMlRdpjZ+4ELgfc24XT3H6Zzbbo1SNcQbQ5X0/V1PCaFprhttElthwFw1odO7r22Z2EqYfpMdtuvOhHNqKvekqUuqj+SBhRCoXZSVtDOtcSnMZkqxFZylB2pfdraA1cC9wIfBd5I9/rGapC+AnwVGGRmS2s81Ql4vcnRSv4qbg3FqeUIKo7Azlkw5O+y3+7exVFy1rpr/eeUlcF112U/FpEESkpylE8yOUNNyVFWXeruF5vZUnf/gZn9K2nWH0HjPUiPAs8B/x9wV43HD7r7nqbHKnmj4ggUt4GjO6FdraGrknZw7pejpCnbGlv/yD1KkH70o+zHIgVBw4CFKRvT9pUcZd2R1NfDZtYH2A2kvQRAYzVI+4H9wCfNrBjombqmo5l1dPcNzYtZctrmZ2Hd/0Sz1c4YBq06Qe/roXtqmv3GJ6DriGh2W7btLIP+t9T//Lp1UFUFg2KIRVpEiUfmqfeoZbK5lpGSo1g8Y2ZdgJ8BC4lmsP0m3YvTXUn768D3ge1AVephBxrY+Ery1ptfhgnTwErg2G7YvwLWTYtqjs76cNSr1L5/9uNwj4byRv9H/efMmhXVH8W5qrfknHysQ1Jy1DxxLPCo5Cge7l69YvbjZvYM0DbV8ZOWdIu07wQGu/vuJsYn+ebQJqgoh85DoF2v6LEzR8PO2bDm19DhbDjv/zT8GplyYDWUdIT2/eo/RwXaIlKHUCtdKzkKw92PUWMdx3SkmyBtJBpqkzj819/B0vnwq1dCR3K6AysAg1m3wMU/iLZFad8Pzv54lDitfQC6XRLT9iKzoHRSw+eUlcHXvpb9WKQg5MowoHqPIknb7kPJUW5JN0FaC7xqZn/m1JW078lKVIXuxT9H+4Yl0TsPwMU/BAzWPRRtN1I6CfrdCHuXxrf3GjReoL1jB2zbBhddFE880my5knjkgpDJUdz7sCUtAaqPEqPclG6CtCF1a526STYtWAtf/8fQUZzu6C7Y+jyM/TUUd4h6inbNgbX3w+K7oPs4GH53fPHsLIML/6H+52fPhgkToLg4vpgkZ+VjHVK+yJVEqDYlRmGZmQGfAga5+w/NrD/Qy93TWgsprQTJ3X+QaqxTdOjlzQ1YGrFlDew8BpM+GjqS061/GPp+8OSaQ93HRUnSBXfCkW3Q5kwoahVPLIc3QcVB6NzA/5ZVfyQFJl+G1nI1IapJyVEi/IpoYtkU4IfAQeBxYEw6F6c7i20Y8BDQLXW8C/iMu69oRsDSkOf/B4Z2g9ZtGz01Vu5RT9Elvzj18aLUr1B1wXZcdqTqjxqanVZWBvdoFFgKQ64nR0qKJAvGufsoM1sE4O57zSztUbB0h9imAn/r7q8AmNkVRGsJXNq0WKVRr74I40eEjuJ0+5ZE6x71uDx0JJHGNqgtL4dVq2BMWv9REGlUkuukcj05ymVKihLtRGoNRwcws1JOLlXUqHQTpA7VyRGAu79qZh2aFKak583V8KN/bvy8uK19EAZ8Or4C7MbsLIOBt9X/fKtW8OKL0DZhPXFymiQlHqpDCiOXeo+UEOWUfweeBHqY2Y+I9mL7broXpz2Lzcz+L9EwG8CtwLqmRClpOLAL1pXD1beGjuRUVSfg3Ufh6pmhI4kc3wvl66DbyPrPadMGLlUHp0jSJTk5UjKU29z9ETNbAFwFGHCzu69K9/p0E6TPAT8gKm4yYCbw2aaFKo2a/iAM7Aidu4eO5FRbX4y2Del8fuhIIjtnw5nj4isIF0kwDa+1jJKg/GVm44EV7v6fqeNOZjbO3eelc326CdI5wFlAUeqaq4iqwrXVSCa9/AyMHRI6itOtexAGfiZ0FCels0CkSAYlaRgwn2hbD8myXwOjahwfquOxeqWbID0CfAtYThMKnKSJ5i6Br381dBSnOr4Xtr4AY34dHVdUQEm6vzZZsqMsWqwyzkUpJSuUeBSuTCVHSoCkAebuXn3g7lVmlvYHWLon7nT3PzU5NEnf8aOwag9c99nQkZxqwx+g1zXQphscOQLDhsHcuVBaGiae4+WwZxF0H6/kSLIilwq1C2l4TYmQNMNaM/sbol4jgK8S7QySlnQ/Yf7JzO41s0+a2Yerb02NVBow8zEobQO9zwkdyalqDq9NmwZDh4ZLjgDKboKS9jD3dji0IepFEpGc0pTeoyndVys5kub6MtFyRJuBTcA44EvpXpxuD9LtwAVAK04OsTnwRNphSsNeegJGJyw5OvgXOPA29LkuOr7vPvjxj8PF8+bXwYqhyzBoUwrzPg/nfRX63ghFxdFilg0tHCnSDBoGTE8m92FTQnS6pvRq3pm9MHKKu+8APtHc69NNkIa7e8Z2/DSzLsC9wDCiROtz7j4nU6+fk15/Az7yodBRnGrdQ3D2J6PZYhs3wtq1cMUV8cfhDlXHo61Fuo6EA6thzH/C+t/BW7+AE/th0GeVHOUYJR4tk6vDaw31HikxaloiJA0zs7bA54ELgfcWxXP3z6VzfboJ0lwzG+rumfrJ/QJ43t0/mlr2u32GXjc3VVXBkm3wmwTNFPOqaHht8uPR8dNPw/vfHy3AGDczKG4T7QP3zv0ntzcZ8AnocBbM+Qy07XWyp0ukhXKpDimXKDk6Sb9fsXgIWA28j2gvtk8BGV8HaRJwm5mtA44RrYXk7t7kaf5m1hm4jNQ6Su5+HDje1NfJK4tegDZFMHhc6EhO2jkLSjpEPTYA//u/8JWvBA2JriPh+J5o4cry9dC2J5ROhMHfgGO7wsYmIs2Wj8mREqBEONfdP2ZmN7n7NDN7FHgh3YvTTZAy+V/zQcBO4AEzGw4sAO5w90MZbCO3vPA7GHlW6ChOVV2cbQZ79sC8eVGSFLeadUWdzoHe10ZDa6t/Dl0ugq4j4C//BRd8M/7YJO9pGDBzkrxidn2U5OS8E6mv+8xsGLANGJDuxWnNYnP3d+u6NT1WIErKRgG/dveRRAs33VX7JDP7kpnNN7P5O3fubGZTOWLWLJiUoG0xKo/Dxiej+iOARx+Nhtc6BNh+z+zkTDV3OLwZzv9qtKr3ofWw4kfQ/xY45/b4Y5PT1Hzf7tlT/wxDJR4tkyv1R0N6bX/vVp987D2S+plZNzObbmZrUl+71nPe/Wa2w8yW1/HcX5vZW2a2wsx+2kBzU1Ov/13gaWAl8JN0Yw2x4t8mYFONpb7/SB0JkrtPBaYCjB492ms/n1cWboB/+nnoKE7a9hJ0viCq73GH3/wG7rkn3hhW/iyqNbrgG9F6R1WV0Uy1HTNh8B3QNTW6W3kcilvHG5vUq+b79qKLW+f3+1ZOkYs9RBLEXcAMd7/bzO5KHX+7jvP+B/gl8GDNB83sSuAm4GJ3P2ZmPWpfaGZ3uPsvgFXuvpdoe7RBTQ009pX23H0bsNHMBqceuoooqytMf5kPhythzAdCR3LShseiXhmA+fPh4EG48sr42t/4JKz6Kbz7GMz7QvRYUTEc3gJHd0bT/A+sgaM7lBzlIPUeSTX1HhWkm4BpqfvTgJvrOsndZwJ76njqK8Dd7n4sdd6OOs6pHlL4j5YEGmop4r8GHjGzpcAIIODiOoE9/xBc3BOKErIqdOUx2Pw09P9odHzvvfCFL8Qbn5XAqJ/DVS9B5VGYcTUcehd2zYEeE+HYbtj8J/DK+GKSgpLk2pNcGV7LdUn+HchxPd19K0Dq62k9QI04H5hsZvPM7DUzG1PHOavMbD1wgZktrXFblso70hJkUy13XwyMDtF24sx8BSZcEjqKk7ZNhzOGQfu+UF4Ojz0GK1bEG0O/D0LFEShpB+PugxU/htduiob9SifDlj9D3w9Au97xxiUtpt4jkWQpOg7tNzXpP8DdzWx+jeOpqaH195jZS0CvOq79TjNCrK0E6AqMB8YAj5nZoFp7rn3SzHoRzVi7sSUNSUjz18Dn7wgdxUnv/v7k8Npjj8HkydCnT/xxlLSLvha3gYt/AGcMjbYX2fIsnP/1aGFIEclZGl7LWbvcvcEODne/ur7nzGy7mfV2961m1huoa4isIZuAJ1IJ0RtmVgV0J5odX9NOYFkLJpQFG2ITgB3vwtajcMUnQ0cSqTwKm5+B/h+Jju+9F774xbAxVetzfbSadukkGFG4I7Iikn0aXsuqp4HbUvdvA55q4vX/C0wBMLPzgdbAaQvhuXslUW9XswtV1YMU0vP/Axd0gTYJWUh86wvQdXg0dLViBaxfD9dfHzqqyLu/h5KOcJm2/8tVuTK8luQPR9UfSR64m2hY7PPABuBjAGbWB7jX3W9IHf8WuIIoydkE/JO73wfcD9yfmv5/HLit5vBaLe8Cs83saaIlhQBw97SmZStBCunV52Fckxcjz553H4OzPx7dv/deuP12KEnIr8ihDXDuF6G4bePnikiiaXitcLn7bqLZ67Uf3wLcUOO4zqGV1O4bt6bZ3JbUrQjo1NRYE/LpV6DeWAHf+27oKCIVh6Pi51H3wLFj8PDD0erZSbGzDIaetlyW5Ihc6T0Skfzh7j9oyfVKkEI5tA/+chCuScgGtRv+GO1r1q4n/P73MHw4DGryulrZUXkM9syH0gStNi4izZL03qMkD7FK05jZK8Bpw2/uPiWd65UghTLjYTi7A3StayZkAGvvi1aohmjl7C98IWw8Ne1ZCJ3Og1adQ0cizZBLvUdJ/nBU/ZFIk32rxv22wEeAinQvVoIUyoynYfTgxs+Lw4E1cGA19PkArF0LS5bAzTeHjuqknWXR+kciEkR1r4+SNMkl7r6g1kOzzey1dK/XNP9Q5i6CK+pdKiJea++HAbdG23bcfz/ceiu0TVAx9I4y6KEEKRflUu+RNK6lw2MaXpM4pTbGrb51N7P3UfcClnVSD1IIJ47D8l1w3WdDRwJVFbBuGkx5CSoq4IEH4IUXQkd1klfBrtkw7jehIxEJJkk9N1O6r05UPJmi5CgvLSCqQTKiobV1wOfTvVgJUghznoRureGsIaEjga3PQ/uzo5Wq//Qn6N8fhg0LHdVJ+1dA6zOhXUJqtSRt+6sS1AuZBn1A1q2uXp98TZIkv7j7wJZcryG2EF78A4xq0c8tc965D85JJdRJWjm7mlfC4L8JHYWI1NLU4bIkD68pOc5PZvYxM+uUuv9dM3vCzEale70SpBBenweTLwsdBRzZDttfjRaH3L4dZs6EW24JHdWpnlsJf0nIcgOSM27ouFIfejFIN+lRciSB/F93P2hmk4D3AdOAX6d7sYbY4lZVBYu2wL+nuxBoFq17EM76ELTqBL9/AD74QejYMXRUp3r44WQtOSASs6QPZdU1wy3JCZEUlMrU1/cDv3b3p8zs++lerB6kuC19JfquD50UNg73aO2jQZ+Ljh95BP7qr8LGVFtlJbz+OkwK/L2SnFKzR0C9A/GZ0n31e7dcod+PvLfZzP4buAV41sza0IS8RwlS3F78LYzsB0WBv/W7Xo++lk6ENWuijWmvTsiyA9WWLYNevaBHj9CRSJ7TB2XdcinZaSr9zAvCLcALwHXuvg/oBvxduhcrQYpb2UyYOC50FPDO/VHvkRk8+ih8/OPJ2Zi22qxZMFnrH0n66vrQ0wehSGFy98Pu/oS7r0kdb3X3F9O9XglS3Bauh2sCF0KfOAgbn4CBn4mG2h55BD71qbAx1aWsTMNrUtCSXn+Uq5Q0SzqUIMVp3VLYXwETbg4bx4bHoOfl0dpCCxZEheNjx4aNqTb3KEFSD5JkgD4QpZp+FyRdSpDi9MJDcFEpFAceynrnPhiUWvuoujjbLGxMta1dG8U0MCHrRUniNfeDTx+YdcvH+iP9rKUplCDFaeZLMD7tNaqyY/8qOLQe+lwfzRL73e+SO7w2eXLyEjfJWbn24ajhtczKtZ+/hJewqtw89+Zb8PMvhY3hnfui2qOiEpg+Hfr2hcGDw8ZUFxVoSxPow0/qo98NaS71IMVl9ybYeASmBOytqToB6x86ufbRo48ms/cIThZoe1XoSCSP6MOycGg1dWkp9SDF5cWH4PwzoH3ncDFsfgY6DYbO58ORI/DUU/DjH4eLpy4bHofNc2DCu3B+PzDl8NKwlnwI6gO0brlcf6SfqWSKPn3i8sqzMPbCsDHU3Jj2mWfgkkugd++wMdW0/TVY9C3YCAwqhVkfgl1zoaoidGSSR3LhA1T1R02nHiPJNCVIcZm3DK68IVz7hzdHq2f3/2h0nMStRfavgL4fhNcroPXXovsrfwJ7F0fPV1U2eLkUHn0gFrbqpEi/B5INSpDicPgAvLUfrrstXAwb/gj9PgQlHWDPHnjlFfjwh8PFU5fu4+DEAVj+UlR/NPTvoPt4WHBH9HhRcegIRSQwJUUSF9UgxeGV30K/dnBmv3AxbJsOg1IJ2uOPw7XXwhlnhIunLu36wIkT0GYNXDwoemzot+HA29HWKBfcGTQ8SZZ8rT3S8NqpkvyzkvymBCkOLz8Fo88P137VCdhZBhOmRcePPAJ33hkunpqqKk/2DLXrDQfHw+TnYOsTUHkZdL0Y2vfTbDaRmIQq0FYiJEmjBCkOcxbAp28N1/6uedDpPGhzJmzaBMuWwfXXh4nlv/8bNm+G4p1w5Ixom5PKE1DpUbK0cBG872bYvzxK6gD2LoIrng0TrySSPkxzm35+kguUIGVbVRUs2w2XXxsuhr2L4MzUXmsvvwzXXANt2sQfx7Zt8NWvwk9ugV6Pw+GLYN/HoagIii1avPL88+DmD0P3tnB8L+xZAKP+NepFEolZOh/kz5YPjSESEYmbEqRsW7ECOpdAr9JwMZSvhY7nRPfnzYNx48LEMWsWfPAaGLUbzvoP2DETilfB+Aei56sqoiQJouSo83nRTURikcvrH4lkmmaxZdusWXBhh7AxlK+Fjqmi55AJUlkZTLgSxt8PA2+FS34Ox/fBnM9Gz1cnR3sWwvpHofJYmDhFAimUAm31ukkuUIKUbWVlcGHHsDFUJ0hHj8KqVTByZJg4qvdXa98vWm6gbQ8YOxVO7IfXPxOds3cxlK+Dsz8BxQGGASXxVL8iInFQgpRN7qkEKWAPknsqQRoIixbBBRdAu3bxx3HgALz1VrR6d01tS6MkyQz+NBhm3QKlE6OCchERkUCUIGXTu+9G6/r0CdgTcnQHlLSHVp3hjTdg7NgwccyZEyVHdRWHty2FLhdHi0FOfhLa9Yo/PpECp/ojkVMpQcqmsrJoSMksXAxJqj+aPLnu547vha3Pw5QXoUvg/epEJBaqQ5KkU4KUTdU1NyHVTJBC9iC9NqP+70XrrnD5n6DLRfHGJDlH9UciEhclSNlUVhbtKRZSdYK0axfs3BnVIMXtwFZ4cy6MG1P/OcVt44tHRE6h4TWJi5l1M7PpZrYm9bVrHeecZWavmNkqM1thZnc05fpMUYKULbt2RStGDx8eNo5DqTWQ3nwTRo+OFmWM28sPQf9O0KVb/G2LSGJpmK0g3QXMcPfzgBmp49oqgG+6+xBgPPA1MxvahOszQglStsyaBRMmQHHgHegPvhP1IC1eDKNGhYnhlT/DGP0hFGlIoayBJAXvJiC1MSjTgJtrn+DuW919Yer+QWAV0Dfd6zNFCVK2JKH+CE4OsS1bBhcFqvGZuxSuvC5M25I3VH+UHRpek5j1dPetECVCQI+GTjazAcBIYF5zrm8JbTWSLWVl8NOfho2h8igc2wXt+sLy5fCtb8Ufw/FyWLEPrr8t/rZFJPGeLR+q5Deg4hPQcXNVUy7pbmbzaxxPdfepNU8ws5eAutZr+U5TGjKzjsDjwJ3ufqAp12aCEqRsOHQoSkhCzRirVr4eOvSHyipYswaGDIk/htm/hy5toe/A+NsWEZFM2+Xuoxs6wd2vru85M9tuZr3dfauZ9QZ21HNeK6Lk6BF3f6LGU2ldnwkaYsuGuXNhxIgwK1bXVD28tmYNnHVWmHheehJGnxt/uyIikkRPA9VDCrcBT9U+wcwMuA9Y5e73NPX6TFGClA1Jqz9avhyGDQsTw5z5cNmUMG1L3tAQTHao/kgCuBu4xszWANekjjGzPmb2bOqcicCngSlmtjh1u6Gh67NBQ2zZUFYG3/hG6ChOTZBCFGhXnoAlO+CXt8bftkgBWLWtJ0N6bQ8dRoupDqlwuPtu4Ko6Ht8C3JC6PwuocwuK+q7PBvUgZdqJE9GWHpdeGjqS1BpIAXuQlj4HXgxDGhyulgJzQ8eV+jDMoFXbeoYOQSQvKUHKtEWLYOBA6Jq1xT3TF3qI7YXfw6j+YfeiE8lTLU2MNLwm0jAlSJnW0KascXKPEqSiXrBpE5wboFB69uvht1qRRKnZc6RepJO0SGQ0zKaVtSVJlCBlWlIKtI/tjPY3+8tmOO88aNUq3vbdYeFGeN8n4m1X8o4SqdPl87CakiRJCiVImeQeJUhJ6DU5+A50CDi8tm4e7KuCsdfG37YkUl2JjpIfqYuSJEkCJUiZtHo1dOwI/fqFjiQB9UcPwUW9wu9FJ5JnMtF7lAv1Rxpyk9CUIGVSUuqPIEqQOp0TLkF67VW4dEz87YrksXweWquPkiQJRQlSJiWl/gjCT/Ff8A5c/ZH425VEamgorbnPSeFQkiQhKEHKpKT1IFX2gH374Oyz4217xxrYeAyu/Gi87YrksYZ6jwqhZ0lDbhI3JUiZsmkTlJfD4MGhI4mUr4UNx+HCC6Eo5h/zi9Pg/G7Qrn287UoipdMLpJ6i+ORC/VFDlCRJXLTVSKaUlUWz15KwKGLlUTi6E7buCFR/9CKMGx5/uyI5KJ01kAqhh6gpqpMkJdaSTepBypRE1R+9C+3PgpUrwyRIb6yCKR+Iv11JnKZ8gNU+Vx9+0hj1Jkk2KUHKlKTVH3UcBMuWxZ8gle+At8vhWm1QKyLZp9okyRYlSJmwdy+sWwcjRoSOJFK+FjoMDDOD7ZVHoE8HOLNHvO1K4pxRdLTJ16jXKLtyvf6oIUqUJNNUg5QJs2fDuHHxb+dRn/K1cDSVoPSMuXbh5T/BWP2REskU1R81Tc0kSQm3tESwHiQzKzazRWb2TKgYMiZJw2sA5e/AZot6j+IuGp+3BK7Q9iLSfDd0XKkPNskI9SpJS4TsQboDWAV0DhhDZsyaBf/8z6GjOKl8Law/N/7htROHYdkeuO4z8bYrIqza1pMhvbbX+3w+D681pnaSpARc0hEkQTKzfsD7gR8Bfxsihow5cgSWLImG2JLAPUqQ/rIDxk2Mp80Da2DHq/DG89CxNZx9fjztiog0Q129Si1JmrLZS6VkLpxQPUj/Bvw90Km+E8zsS8CXAPr37x9PVM2xfj306QMdOoSOJFJ5BKoqYMsOiOv7tvS7cGwXbDgTxlwWT5uSSDXft336aqPixqSzBpLEI6lDcc2La2vG4yhEsdcgmdkHgB3uvqCh89x9qruPdvfRpaWlMUXXTEnasd6KAI9Wz66qiqfNko5w9iegzwegS+942pREqvm+7dZNk2RFJHeF+As2EbjRzNYDvwOmmNnDAeLIT1YMXhUlbZWV8bTZ6gw4sT+etkRERGIQe4Lk7v/g7v3cfQDwCeBld9eqghlTBMScILU+A44rQZLcktQhlWwo5AJtkeZSH3i+sSL1IIkUoIZmsIlI0wVdKNLdXwVeDRlD3jEDDIqLYuxB6nIyQXKPp00REZEsUg9SPrIiKCqOr0i7ugcp7kUpRfKcVtEWCUcJUj6yIii2eIfYVIMkOaS6/qiQ6pBEpGmUIOUjK456kOIs0j6xL562RKRJVKAt0jxKkPKSepBERERaQglSPrLieIu0a85iU5G2iIjkASVI+ciKopW0Nc1f5DS1645UhyQidVGClI+sKN4epOLWUNQKqo7H056IiEiWKUHKR1Ycbw8SRL1IFYfja09ERCSLlCDlo7h7kCBKkCqVIImEoFW0RTJPCVJeKoKiGGexQSpBOqIibUm0+uqNkliHpEUiRcJSgpSP4p7FBtF2I5VH4mtPRBqlNZAkacysm5lNN7M1qa9d6zjnLDN7xcxWmdkKM7ujjnO+ZWZuZt2zFasSpHykITYREUmmu4AZ7n4eMCN1XFsF8E13HwKMB75mZu9185rZWcA1wIZsBqoEKR9ZgCG21mdAhXqQRESkQTcB01L3pwE31z7B3be6+8LU/YPAKqBvjVN+Dvw9kNWaDiVI+ciKA9UgqQdJkiuJdUYiBainu2+FKBECejR0spkNAEYC81LHNwKb3X1JluOkJNsNSAgxbzUCqWn+74C3j69NkQx6tnwoN3RcGToMkVgVHaui07om9f53N7P5NY6nuvvUmieY2UtArzqu/U5TGjKzjsDjwJ3ufsDM2qde49qmvE5zKUHKR9UraVfEnCBVHQaUIImI5LFd7j66oRPc/er6njOz7WbW2923mllvYEc957UiSo4ecfcnUg+fAwwElpgZQD9goZmNdfdtzfi3NEhDbPnIiqOfrGqQREQkWZ4Gbkvdvw14qvYJFmU/9wGr3P2e6sfdfZm793D3Ae4+ANgEjMpGcgRKkPJTiCJt1SBJgqn+SCQx7gauMbM1RDPR7gYwsz5m9mzqnInAp4EpZrY4dbsh7kA1xJaPQm01ogRJcpzqkESyy913A1fV8fgW4IbU/VmApfFaAzIdX03qQcpHFqBIu3qITStpi7RYU1bRrm+bES0SKdIySpDykobYREREWkIJUj7SOkgiIiItogQpH4UYYqverFYkYZpaoK2CbhEBJUj5KcQstuLWUc+VV8TXpkgCqKhbJD8pQcpHIYbYAIrbQ+XxeNsUyVEv77ogdAgi0gAlSPnIiuJfKBKgVXuoOhFvmyIiIlmgBCkvpYbYqqribbZYCZIkS3PriVSHJCJKkPKRFcdfpA2pBElDbCKhaQ0kkZZTgpSPrChagzTuBKlEPUgiLZWJRSJFpOW01UhLtWsHBw+GjuJURa2htcGRmKfdF7eDqvJ42xRpQGMzzDSUlhn1fZ/1/T1VU2Y86nsXnnqQWurss+H4cdi4MXQkJ7XtCWcWxR9TUTF4zHVPIpJI+oCXXKcEqaXMYNIkKCsLHclJ7XpBtxOwfn28e6NZcfyF4SItEHINo0zUCTVlOC4uz5YPVXJUB62XlXuUIGXC5MnJSpDa9obW+6CoCPbti6/domJAm9VK4Sn0D7/qpEiJUWbo+5gMSpAyYfJkmDUrdBQntesFR7ZFw3/r18fXrmmITUSktkJPoHOVEqRMGDEC3n0X9uwJHUmkXW84shUGDIjiikuRhthEWkoz00SSQQlSJpSUwPjxMHt26Egi7XrD0VSCFGsPUlG8NU8iIgmn3qPcpQQpU5JUqN02NcTWv3+8CZJmsUkOytQHmD4IJRNUf5QcSpAyJUmF2iXtobgNnFUa8xBbiRIkkQTQRrgiLacEKVPGjYNly+Dw4dCRRNr1hp7tAvQgaYhNRATUq5jrlCBlSvv2cNFF8MYboSOJtO0FpSXx9iB1PwO27Y+vPREROcUdF7wUOoS8oQQpk5JUh9SuN7Q9FK3yfeBAPG1e2B/e3RtfeyIZEqoOSZvK5i/1HuU+JUiZlKQ6pLa94di2eKf6t2kLQ3rAnDnxtCcikkdUoJ0sSpAyaeJEmDsXKipCRxJmsciiEhjRKzlJoohIAOo9yg9KkDLpzDOjqfVLloSOJMxikVYCw3sqQRIRkZynBCnTklKHVL1YZJw9SFYMF3aDBQvg2LF42hTJEK2HJJkQ8uevAu3MUoKUaUmpQ6peLDLOHqSiEmhfBIMHR0mSiEgBaUlypPqj5FGClGnVCVLo9YCqh9hi7UEqAa9MTpIoUgBWbesZOgRBPYf5SAlSpvXvD+3awZo1YeNo3Q0qD0O/nvHWIFVVKEESkYKi5Cg/KUHKhiQkCGbQtid0djh4EA4dyn6bRSXgFVEd1uzZUKVtRyS3qA5JmiopP2vVH2WeEqRsSFShdmqqfxy9SFYClcegZ08oLYXly7PfpohIIJlKjlR/lExKkLIhCT1IEBVqV89kiyNBOmMo7Fsa3Z88GWbNyn6bIjlOq2nnpqT0HEn2KEHKhiFDYN8+2LIlbBztep+cyRZHoXan86DqKBzakJwkUUQkw5QcFQYlSNlQVBQNs4XuQak5ky2WITaD0kmwo+zkMGPo2XwiTaQ6JKnpho4rT7sljeqPsqMkdAB5qzpBuOWWcDG07QV73oQBU+Dpp+Nps3Qy7CyDMX8FlZVRz9XAgfG0LSLSDCGTnkKrPzKzbsDvgQHAeuAWd99b65yzgAeBXkAVMNXdf5F6bgTwX0BboAL4qru/kY1YlSBly+TJ8OUvh42heogtrh4kgB6T4Z17o96k6jokJUgi0kJJ7LmRZrkLmOHud5vZXanjb9c6pwL4prsvNLNOwAIzm+7uK4GfAj9w9+fM7IbU8RXZCFRDbNkyahS8805UixRKzf3Y4losssvwqAbp2G7VIYlIRig5yis3AdNS96cBN9c+wd23uvvC1P2DwCqgb/XTQOfU/TOArBX7qgcpW1q3hjFjYM6ccDFUz2Lr3Rv27oWjR6Ft2+y2WVQC3cfDztlRgvSrX2W3PZEEu6HjyoIbQskkJUaNy8H6o57uvhWiRMjMejR0spkNAEYC81IP3Qm8YGb/QtTJc2m2AlWClE3VdUiTA7Xfticc3Qk49OsHGzbA+ednv93qOqSL74atW2HnzmhdJJEcoQ/msArl+5+E5NmOnaDknc1NuaS7mc2vcTzV3aee8ppmLxHVD9X2nSbFZtYReBy4090PpB7+CvANd3/czG4B7gOubsrrpktDbNkUeoipuDW07gLHdsW7aW2PybBjFhQXw4QJ4WfziUjOKJTkKIftcvfRNW5Ta5/g7le7+7A6bk8B282sN0Dq6466GjGzVkTJ0SPu/kSNp24Dqo//AIzN5D+uJiVI2TRhAixaBMcDbrlRc7HIuOqQzhwH+5dBxWEtGCkiaUnqFHrJuKeJkhxSX5+qfYKZGVHP0Cp3v6fW01uAy1P3pwBZ2/hUCVI2dewYLRq55nC4GGouFhlXD1JJO+hyMeyeF74XTUQkT+Vg/RHA3cA1ZrYGuCZ1jJn1MbNnU+dMBD4NTDGzxanbDannvgj8q5ktAX4MfClbgcZeg9TQ+gZ5afJkWP67cO1Xz2QbOBD+/Of42q1eMHLM38PKlVBeHiWMIiJSsNx9N3BVHY9vAW5I3Z8FWD3XzwIuyWaM1UL0IFWvbzAEGA98zczCV6ply6RJsOJQuParh9gGD4a33oqv3dLJsHNWNGtuxAiYOze+tkVEEi4JBdrSsNgTpEbWN8g/kybBqkPRqtIhVA+xVSdIVTHVQ5VOhF1zoapCdUgi0iDVHkkSBa1BqmN9g/zTowd0bQXLAv0BaNcHDm+Czp2ha9f46pDadINO58LS78KUy+Cee2D0aPirv4Jjx+KJQUREpJmCrYNUz/oGNZ//Eqniq/79+8ccXYaNOhteeQam3Nb4uZnWZRgsWRrdv+QSmD8/vq0/Ln8aFv4tHPkjzPhP4AK4/fYohokT44lBYlXzfdunb3HgaHLHlO6reXnXBe8dD+m1nVXbeqZ9/aptPRnSa3s2QpM6nNev5Ys335GBOCS7gvQgNbC+wXvcfWr1Ogulub7I4KTJ8HqgTrJOg+HoNji+P1rZ+80342u7fT+Y9BiM/iVs/QEc/QlcPl6z2vJYzfdtt26aJBtSzYQr6VSPI0kU+1+wRtY3yE/XfQoWbY6v/qemouJoyv3exTB2LLyRlU2PG9bnOnj/cuhyEbR/DGa+Gn8Mkij6QJRclYneI8kNIf6L19D6BvnpwsuiCYvLXwvTftdRsHdhVAO0cGGYgvHitnDRP8G4i2HO7DDJooiISJpCzGKb5e7m7he7+4jU7dnGr8xhRUUwoi+88GiY9ruNhD0LoVs36NkTVq8OEwfA+VfBGa1h+fJwMUhQ1b1H6kUSkSRTkUBcLh0HZTPDtN11FOxdFN2Puw6pth6T4YJWqkMSEZFEU4IUl2s/BgvXhWn7jAuhfG20N1qoOqRqZ46HQXtVhySAepEyqa5ZbyrUzizVHxUWJUhxGX8z7KuA9QGGlopbQ+chsG9p+B6kVh1h9PlRguQeLg6RBiThw1rT9kXCUoIUl1atYVh3eGFamPa7jYrqkEaOhBUrwi7WePHVUHkM1q8PF4MEUVfikYRkRESkNiVIcZowCl6bEabtriOjmWzt28P558OSJWHiAOh5GVzYQXVIIjVM6R5w8oSInEYJUpym3AjzY9wwtqZul0Q9SBC+Dql0EgzcBzMDFa1L4qgXSZJO9UeFRwlSnK66FTYchj0B3mhdLoYDq6OhrdB1SG1LYURPmPlyuBhE8lBTticRkYYpQYpT+85wXucwdUgl7aLNY/ctC9+DBDD6Kti2DXbuDBuHSC351pulmWwizaMEKW7jhsGrz4Vpu9slsGcBXHghbNwI+/eHiQOg1+Vw4Rkwa1a4GCRWjX346cPxdJrJJhKOEqS4XfE+mLcsTNtdUwlSSQmMGAELFoSJA6IFIwcdUh2SiIgkkhKkuL3vs7B6Hxwpj7/t6h4kCF+H1GEADG0dblafJJJ6kSSJVKBdmJQgxa20P/RtB68E2Jet63A4sAoqj4evQzKD8VfCW29DeYBkUaQO+Zqg5VIdkkhSKEEKYcx5MOOp+NstaQ8dB8H+5eF7kADOugLO6wJz54aNQ7KuKYlHviYp6cjEWki5PpOtkH/+kixKkEK4/CqYG6j+p3qY7Zxzop6bbdvCxAFQOhnOO6EFI0VEJHGUIIXwvs/A0h1QWRF/29UJkln4XqQuw+DcY6pDktOoF0GSQvVHhUsJUgiDRkDHYpj3p/jbrlmoHbwOqQgmXgrzF8Dx4+HiECG5SZmm+ouEoQQplEsGwPTH4m+36wjYvyIq1A7dgwQwcAr07QiLFoWNQ7KmuYlHUhOWXKVCbZGmUYIUyqRJMHtO/O2WdICOA+HAypMJknv8cVTrMRkGm+qQRDJIhdoiLacEKZRrPwGLNoVpu3rByN69oX17WLs2TBwA3UbDoAPw2ivhYpDE0gelhKT6o8KmBCmUEdfAiSpYNTv+truNSk4dUnEbGD8cZpdBVVW4OKSgKRETkdqUIIVSVAQj+sDzD8ffdpJW1AYYcjV0KIZVq8LGIRmXicSj0JKXTKyFJCItpwQppEvHwszX4m+360jYtxyqToTvQYJoPaQhbbRxrUg9MjWTTYXaIulTghTSNR+BhQHqf1p1hA79Yf9KuOQSWLwYKgKsyVSt9FIYtC9Msig5odB6kST8z1z1R6IEKaSJH4Gdx2DLmvjbrh5mO+MMOOssWLEi/hiqteoMlwyEmS+Hi0Ekz+T6TDaR0JQghdS6LVx4Jjz3QPxtd7sE9iyM7o8ZE36YbcTVcOQQbNgQNg7JmP1VbTP6etnqUQjdUyEiyaQEKbTxI+DVF+Nvt2utmWyhC7V7XgZDO2o9JJEmqtjSPnQIInlJCVJoUz4I8wPMWuk2EvYthaqKZPQglU6Cc/YrQRLJMhVqS0hm1s3MppvZmtTXrnWc09bM3jCzJWa2wsx+UOO5n5nZajNbamZPmlmXbMWqBCm0qz8N6w7B/h3xttuqM7TvBwdWwfDh8PbbcPhwvDHU1K43DOumjWulQYU8HKY92eKjAu2suguY4e7nATNSx7UdA6a4+3BgBHCdmY1PPTcdGObuFwNvA/+QrUCVIIXWqRsM6gjTH4q/7epC7bZtYejQ8PuhjbsKNm6C3bvDxiEFo5ATrlygn09eugmYlro/Dbi59gkeKU8dtkrdPPXci+5ePe16LtAvW4EqQUqCaybAlvXxt9vzCjiR+h28/nrYtSv+GGrqdx1cPRTWrw8bhyRaIXxoNnWxyPrqkDSTTRKop7tvBUh97VHXSWZWbGaLgR3AdHefV8dpnwOey1ag5iE3Kk2Tme0E3s3CS3cHAmcFTZZrMedavKCYazrb3Uubc6Het6fItZhzLV5QzDWl/b41s+dTcaSrLXC0xvFUd59a6zVfAnrVce13gGnu3qXGuXvd/bQ6pBrPdwGeBP7a3ZfXePw7wGjgw56lRKYkGy+aac39A90YM5vv7qOz8drZkmsx51q8oJgzRe/bk3It5lyLFxRzc7n7dVl4zavre87MtptZb3ffama9iXqIGnqtfWb2KnAdsDz1GrcBHwCuylZyBBpiExERkfg8DdyWun8b8FTtE8ystHp2mpm1A64GVqeOrwO+Ddzo7lmdWaQESUREROJyN3CNma0BrkkdY2Z9zOzZ1Dm9gVfMbCnwJlEN0jOp534JdAKmm9liM/uvbAWaE0NsWTS18VMSJ9dizrV4QTEnXS7+W3Mt5lyLFxRzTnD33cBVdTy+BbghdX8pMLKe68/NaoA15ESRtoiIiEicNMQmIiIiUktBJUipdRUWmdkzqeNGlzwPyczWm9my1Djr/NRjSY+5i5n9MbUU/Cozm5DUmM1scOp7W307YGZ3JjXeamb2jdTy+8vN7LepZfkTHXNL6H2bfXrfZl+hvW/zQUElSMAdwKoax+kseR7ale4+osZU0KTH/AvgeXe/ABhO9P1OZMzu/lbqezsCuAQ4TLTeRiLjBTCzvsDfAKPdfRhQDHyCBMecAXrfZp/et1lUoO/b3OfuBXEjWo58BjAFeCb12FtA79T93sBboeOsFfN6oHutxxIbM9AZWEeqti0XYq4R47XA7KTHC/QFNgLdiCZZPJOKPbExt/Dfq/dt9uPV+zb7cRbU+zZfboXUg/RvwN8DVTUeS2vJ84AceNHMFpjZl1KPJTnmQcBO4IHUkMi9ZtaBZMdc7RPAb1P3Exuvu28G/gXYAGwF9rv7iyQ45hb6N/S+zTa9b7OsAN+3eaEgEiQz+wCww90XhI6liSa6+yjgeuBrZnZZ6IAaUQKMAn7t7iOBQ+RAl7GZtQZuBP4QOpbGpGoUbgIGAn2ADmZ2a9ioskPv29jofZtlhfS+zScFkSABE4EbzWw98Dtgipk9DGy3aKlzLI0lz+Pm0boQuPsOojH2sSQ75k3AJj+5qeAfif7wJjlmiD7IFrr79tRxkuO9Gljn7jvd/QTwBHApyY65ufS+jYfet9lXSO/bvFEQCZK7/4O793P3AURdsi+7+62kseR5KGbWwcw6Vd8nGq9eToJjdvdtwEYzG5x66CpgJQmOOeWTnOymh2THuwEYb2btzcyIvserSHbMzaL3bTz0vo1Fwbxv80nBLRRpZlcA33L3D5jZmcBjQH+iX+CPufuegOG9x8wGEf3vE6Iu8Efd/UdJjhnAzEYA9wKtgbXA7USJeCJjNrP2RMWTg9x9f+qxpH+PfwB8HKgAFgFfADqS4JhbSu/b7NL7NvsK8X2b6wouQRIRERFpTEEMsYmIiIg0hRIkERERkVqUIImIiIjUogRJREREpBYlSCIiIiK1KEESERERqUUJUoEys/JGnu9iZl+tcdzHzP6Yuj/CzG5oRpvfN7NvNfH8zWb2w9RxkZk9aGavm9mFqccmm9lKM1ve1HhEco3etyLxUYIk9ekCvPeH1t23uPtHU4cjgCb/oW2mn7v791L3rwXmAR8CvpmKqyzGWESSrgt634pkhBKkAmdmHc1shpktNLNlZnZT6qm7gXPMbLGZ/czMBpjZ8tQGkT8EPp567uO1/4eZOm9A6v53zOwtM3sJGFzjnHPM7PnUjudlZnZBGuEWE+3qXgVYZr4DIrlH71uR7CsJHYAEdxT4kLsfMLPuwFwze5poN+9h7j4CoPoPp7sfN7PvAaPd/eup575f1wub2SVEe2iNJPpdWwhU78w+Ffiyu68xs3HAr4ApjcT6AvAw8BngS83614rkB71vRbJMCZIY8GMzu4zof3h9gZ4Zeu3JwJPufhgg9QccM+tItJP1H6J9GwFo09iLuXsF0R9ukUKn961IlilBkk8BpcAl7n7CzNYDbZv4GhWcOlxb8/q6NvsrAvZV/y9XRJpM71uRLFMNkpwB7Ej9kb0SODv1+EGgUz3X1H5uPTAKwMxGAQNTj88EPmRm7cysE/BBAHc/AKwzs4+lrjEzG565f5JI3tP7ViTLlCDJI8BoM5tP9L/S1QDuvhuYnSrc/Fmta14BhlYXewKPA93MbDHwFeDt1GssBH4PLE6dU1bjNT4FfN7MlgArgJsQkXTpfSuSZeZeV0+qSHipItJyd/+XRs4bADzj7sPiiEtE6qf3reQL9SBJkpUDX6pecK4uZjYZ+BOwK7aoRKQhet9KXlAPkoiIiEgt6kESERERqUUJkoiIiEgtSpBEREREalGCJCIiIlKLEiQRERGRWv5//9h0Mq7EbRcAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [2,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " rsutcs_Wzm = get_var(winton_zmsimarray[ind], \"rsutcs\")\n",
+ " rsutcs_Szm = get_var(semtner_zmsimarray[ind], \"rsutcs\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ " rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ " \n",
+ " #f1 = ax[axind,0].contourf(albedo_Wzmmean.lat,albedo_Wzmmean.month, albedo_Wzmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " f2 = ax[axind,1].contourf(albedo_Szmmean.lat,albedo_Szmmean.month, albedo_Szmmean-albedo_Wzmmean)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " c2 = ax[axind,0].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"red\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(winton_exparray[ind])\n",
+ " ax[axind,1].set_title(semtner_exparray[ind])\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " cbar.set_label(\"surface albedo\")\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 256,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-70. -65. -60. -55. -50. -45. -40. -35. -30. -25. -20. -15. -10. -5.\n",
+ " 0. 5. 10. 15. 20. 25. 30. 35. 40. 45. 50. 55. 60. 65.\n",
+ " 70.]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 360x864 with 4 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "from matplotlib.colors import LinearSegmentedColormap\n",
+ "fig, ax = plt.subplots(2,1,figsize=(5,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "cmap1 = plt.get_cmap(\"Reds\")\n",
+ "cmap2 = plt.get_cmap(\"Blues_r\")\n",
+ "\n",
+ "cmap = LinearSegmentedColormap.from_list(\"blub\", colors, N=12)\n",
+ "ticks=np.linspace(-70,70,29)\n",
+ "print(ticks)\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " rsutcs_Wzm = get_var(winton_zmsimarray[ind], \"rsutcs\")\n",
+ " rsutcs_Szm = get_var(semtner_zmsimarray[ind], \"rsutcs\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ " rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ " \n",
+ " #f1 = ax[axind,0].contourf(rsutcs_Wzmmean.lat,rsutcs_Wzmmean.month, rsutcs_Wzmmean, levels=ticks)\n",
+ " f2 = ax[axind].contourf(rsutcs_Szmmean.lat,rsutcs_Szmmean.month, rsutcs_Szmmean-rsutcs_Wzmmean, levels=ticks,cmap=\"seismic\")\n",
+ " \n",
+ " c1 = ax[axind].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"C1\",linewidths=1.5)\n",
+ " c2 = ax[axind].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"C0\",linewidths=1.5)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"C1\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"C0\")\n",
+ " \n",
+ " ax[axind].set_xlim(35,85)\n",
+ " ax[axind].set_title(str(winton_exparray[ind]) +\"-\" +str(semtner_exparray[ind]),fontdict={'size': 10})\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind])\n",
+ " cbar.set_label(\"$\\Delta$TOA SW cs out [Wm$^{-2}$]\")\n",
+ " axind+=1\n",
+ "ax[0].set_ylabel(\"month\")\n",
+ "ax[1].set_ylabel(\"month\")\n",
+ "ax[1].set_xlabel(\"latitude [°]\")\n",
+ "ax[1].set_xlabel(\"latitude [°]\")\n",
+ "plt.savefig(\"plots/hovmoeller_rsutcs_multi.png\",dpi=300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 285,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-70. -65. -60. -55. -50. -45. -40. -35. -30. -25. -20. -15. -10. -5.\n",
+ " 0. 5. 10. 15. 20. 25. 30. 35. 40. 45. 50. 55. 60. 65.\n",
+ " 70.]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x432 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "from matplotlib.colors import LinearSegmentedColormap\n",
+ "fig, ax = plt.subplots(1,1,figsize=(6,6))\n",
+ "\n",
+ "ind=1\n",
+ "\n",
+ "cmap1 = plt.get_cmap(\"Reds\")\n",
+ "cmap2 = plt.get_cmap(\"Blues_r\")\n",
+ "\n",
+ "cmap = LinearSegmentedColormap.from_list(\"blub\", colors, N=12)\n",
+ "ticks=np.linspace(-70,70,29)\n",
+ "print(ticks)\n",
+ "albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ "albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ "sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ "sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ "\n",
+ "rsutcs_Wzm = get_var(winton_zmsimarray[ind], \"rsut\")\n",
+ "rsutcs_Szm = get_var(semtner_zmsimarray[ind], \"rsut\")\n",
+ "\n",
+ "albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ "albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ "sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ "sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ "rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ "rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ "\n",
+ "#f1 = ax[axind,0].contourf(rsutcs_Wzmmean.lat,rsutcs_Wzmmean.month, rsutcs_Wzmmean, levels=ticks)\n",
+ "f2 = ax.contourf(rsutcs_Szmmean.lat,rsutcs_Szmmean.month, rsutcs_Szmmean-rsutcs_Wzmmean, levels=ticks,cmap=\"seismic\")\n",
+ "\n",
+ "c1 = ax.contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999999],colors=\"C1\",linewidths=1.5)\n",
+ "c2 = ax.contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999999],colors=\"C0\",linewidths=1.5)\n",
+ "plt.clabel(c1,fmt='%1.1f',colors=\"C1\")\n",
+ "plt.clabel(c2,fmt='%1.1f',colors=\"C0\")\n",
+ "\n",
+ "ax.set_xlim(35,70)\n",
+ "cbar = plt.colorbar(f2)\n",
+ "cbar.set_label(\"$\\Delta$TOA SW cs out [Wm$^{-2}$]\")\n",
+ "\n",
+ "ax.set_ylabel(\"month\")\n",
+ "ax.set_xlabel(\"latitude [°]\")\n",
+ "\n",
+ "\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[ind], Smin_iceborderS[ind]]],1,12,color='darkgray', alpha=1)\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[ind], Smax_iceborderS[ind]]],1,12,color='darkgray', alpha=1)\n",
+ "\n",
+ "plt.savefig(\"plots/hovmoeller_rsutcs.png\",dpi=300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 133,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-20. -19. -18. -17. -16. -15. -14. -13. -12. -11. -10. -9. -8. -7.\n",
+ " -6. -5. -4. -3. -2. -1. 0.]\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 0, 'latitude [°]')"
+ ]
+ },
+ "execution_count": 133,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "ticks=np.linspace(-20,0,21)\n",
+ "print(ticks)\n",
+ "\n",
+ "\n",
+ "\n",
+ "for ind in [2,0]:\n",
+ " T1zm = get_var(winton_zmsimarray[ind], \"t1_icecl\")\n",
+ " T2zm = get_var(winton_zmsimarray[ind], \"t2_icecl\")\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " T1_Wzmmean = selmonmean(T1zm, 40)\n",
+ " T2_Wzmmean = selmonmean(T2zm, 40)\n",
+ " \n",
+ " f1 = ax[axind,0].contourf(T1_Wzmmean.lat,T1_Wzmmean.month, T1_Wzmmean,levels=ticks)\n",
+ " f2 = ax[axind,1].contourf(T2_Wzmmean.lat,T2_Wzmmean.month, T2_Wzmmean,levels=ticks)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(\"T1\")\n",
+ " ax[axind,1].set_title(\"T2\")\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "unsupported operand type(s) for /: 'tuple' and 'int'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-68-c3a95e9b0ab5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap1\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbytes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'tuple' and 'int'"
+ ]
+ }
+ ],
+ "source": [
+ "plt.plot(2,2,color=cmap1(0,bytes=True)/256)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([[1. , 0.96078431, 0.94117647, 1. ],\n",
+ " [0.99987697, 0.95820069, 0.93748558, 1. ]])"
+ ]
+ },
+ "execution_count": 70,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cmap1(range(2))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "new-kernel",
+ "language": "python",
+ "name": "new-kernel"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/Winton_artificial_forcing-checkpoint.ipynb b/.ipynb_checkpoints/Winton_artificial_forcing-checkpoint.ipynb
new file mode 100644
index 0000000..91be494
--- /dev/null
+++ b/.ipynb_checkpoints/Winton_artificial_forcing-checkpoint.ipynb
@@ -0,0 +1,1534 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Offline sea-ice models: Semnter 0-layer and reformulated Winton 3-layer\n",
+ "\n",
+ "Sea-ice models are written to resemble the models as implemented in ICON-AES 1.3.00. The Winton model is almost exactly structured as in Winton (2000), except for small fixes (which are also in the ICON code).\n",
+ "The Semnter 0-layer models is further simplified, especially as brine pockets are neglected (as in the ICON code). \n",
+ "Calculcation of surface fluxes is not a part of either model, it's implemented in the same way as in ICON.\n",
+ "\n",
+ "Semtner, A. J. (1976) ‘A Model for the Thermodynamic Growth of Sea Ice in Numerical Investigations of Climate’, Journal of Physical Oceanography, 6(3), pp. 379–389. doi: 10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2.\n",
+ "\n",
+ "Winton, M. (2000) ‘A Reformulated Three-Layer Sea Ice Model’, Journal of Atmospheric and Oceanic Technology, 17(4), pp. 525–531. doi: 10.1175/1520-0426(2000)017<0525:ARTLSI>2.0.CO;2.\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import xarray as xr\n",
+ "import matplotlib.pyplot as plt\n",
+ "import math\n",
+ "import pylab as pl"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.27\n"
+ ]
+ }
+ ],
+ "source": [
+ "# physical constants from ICON\n",
+ "dtime = 600 # model time step [s]\n",
+ "Ki = 2.1656 # heat conductivity ice [J/(msK)]\n",
+ "Ks = 0.31 # heat conductivity snow [J/(msK)]\n",
+ "rhoi = 917.0 # density of sea ice [kg/m^3]\n",
+ "rhos = 300 # density of snow [kg/m^3]\n",
+ "rhow = 1025.022 # density of ocean water [kg/m^3]\n",
+ "ci = 2106 # heat capacity of ice [J/(kgK)]\n",
+ "cs = 2090 # heat capacity of snow [J/(kgK)]\n",
+ "Tf = -1.9 # freezing temperature of ocean water [°C]\n",
+ "Tmelt = 273.15 # melting temperature of water [K]\n",
+ "zemissdef = 0.996 # longwave emissivity factor [] ICON\n",
+ "#zemissdef = 1-0.7 # longwave emissivity factor [] Abbot(2010)\n",
+ "sigma = 5.6704e-8 # Stefan-Boltzman constant [W/(m^2K^4)]\n",
+ "# albedo values defined in runscript!\n",
+ "albsnow_warm = 0.66\n",
+ "albsnow_cold = 0.79\n",
+ "albice_warm = 0.38\n",
+ "albice_cold = 0.45\n",
+ "I0 = 0.17 # ice surface penetrating radiation []\n",
+ "L = 2.8345e6 - 2.5008e6 # latent heat of fusion [J/kg]\n",
+ "muS = 0.054 * 5.0 # constant of linear salt - freezing point relationship * Sea ice bulk salinity [°C]\n",
+ "\n",
+ "hcilayer = 0.1 # thickness of stabilizing constant heat capacity layer [m]\n",
+ "\n",
+ "print(muS)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# functions\n",
+ "def E(T): \n",
+ " return ci*(T+muS)-L*(1+muS/T) # enthalpy of melting for upper layer [J/kg] #(1)\n",
+ "def E2(T):\n",
+ " return ci*(T+muS)-L # enthalpy of melting for lower layer [J/kg] #(25)\n",
+ "\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ "\n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# surface fluxes (not actually part of the Winton Model!)\n",
+ "def surface_fluxes(Tsurfold, hsold, rsds, rlds, lhflx, shflx, albedo):\n",
+ " #print(\"calculate surface fluxes\")\n",
+ " # check for snow on ice\n",
+ " if hsold>0: \n",
+ " I=0 # fraction of penetrating radiation []\n",
+ " #print(\"snow on ice\")\n",
+ " else: \n",
+ " I=I0\n",
+ " #print(\"bare ice\")\n",
+ " if hsold>1e-6: # ICON checks diferently for Tsurfmelt and I!\n",
+ " Tsurfmelt = 0 # melting temperature of surface [°C]\n",
+ " #print(\"snow on ice\")\n",
+ " else: \n",
+ " Tsurfmelt = - muS\n",
+ " #print(\"bare ice\")\n",
+ "\n",
+ " # surface energy flux balance \n",
+ " # longwave incoming + longwave outgoing + shortwave balance + latent heat flux + sensible heat flux\n",
+ " # in ICON: addition of zemissdef\n",
+ " SWnet = rsds * (1-albedo)\n",
+ " FS = 1* ( zemissdef *(rlds - sigma* (Tsurfold+Tmelt)**4 ) + SWnet*(1-I) + lhflx + shflx ) #UPWARD flux!\n",
+ " dFS = -4 * zemissdef * sigma * (Tsurfold+Tmelt)**3\n",
+ " \n",
+ " #print(\"FS = \" +str(FS) +\" W/m^2\")\n",
+ " #print(\"dFS = \" +str(dFS) +\" + \" +str(rhoi * hcilayer /dtime *ci) +\" W/(m^2K)\")\n",
+ " \n",
+ " return FS, dFS, SWnet, I, Tsurfmelt "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 2.a) temperature calculation\n",
+ "def set_ice_temp(Tsurfold, T1old, T2old, hiold, hsold, FS, dFS, SWnet, I, Tsurfmelt, c_stability=True):\n",
+ "# if hsold>1e-6: \n",
+ "# I=0 # fraction of penetrating radiation []\n",
+ "# Tsurfmelt = 0 # melting temperature of surface [°C]\n",
+ "# print(\"snow on ice\")\n",
+ "# else: \n",
+ "# Tsurfmelt = - muS\n",
+ "# I=I0 # fraction of penetrating radiation []\n",
+ "# print(\"bare ice\")\n",
+ " \n",
+ " # Factor B + stabilizing ice layer in ICON ?\n",
+ " # stabilizing ice layer dominates the sensitivity of temperature on surface flux balance -> surface temperature is far less sensitive\n",
+ " B = -dFS #(8)\n",
+ " if c_stability:\n",
+ " B = B+rhoi * hcilayer /dtime *ci \n",
+ " A = -FS - Tsurfold * B #(7)\n",
+ "\n",
+ " #conductivities\n",
+ " K12 = (4*Ki*Ks) / (Ks*hiold + 4*Ki*hsold) # coupled conductivity of snow-ice layer (upper layer) [W/(mK)] (5)\n",
+ " K32 = 2*Ki/hiold # coupled conductivity of both ice layers (lower layer) [W/(mK)] (10)\n",
+ "\n",
+ "\n",
+ " A1 = (rhoi*hiold)/(2*dtime) * ci + K32*(4*dtime*K32+rhoi*hiold*ci)/(6*dtime*K32+rhoi*hiold*ci) + (K12*B)/(K12+B) # (16)\n",
+ " B1 = -1*(rhoi*hiold)/(2*dtime) * (ci*T1old - (L*muS)/T1old) - SWnet * I - \\\n",
+ " K32 * (4*dtime*K32*Tf + rhoi*hiold*ci*T2old)/(6*dtime*K32 + rhoi*hiold*ci) + (A*K12)/(K12+B) # (17)\n",
+ " C1 = -1 * (rhoi*hiold)/(2*dtime) * L *muS\n",
+ "\n",
+ " # temperature T1\n",
+ " T1 = -1 * (B1+ (B1**2 - 4*A1*C1)**0.5)/(2*A1) # (21)\n",
+ "\n",
+ " # temperature T2 (not necessary to calculate here?)\n",
+ " T2 = (2 * dtime * K32 * (T1 + 2*Tf) + rhoi*hiold*ci*T2old) / (6 * dtime * K32 + rhoi * hiold * ci) #(15)\n",
+ "\n",
+ " # surface temperature\n",
+ " Tsurf = (K12 * T1 - A) / (K12 + B) # (6)\n",
+ " #print(K12,A,B)\n",
+ "\n",
+ " if Tsurf>Tsurfmelt: #check for melting of upper snow or ice surface\n",
+ " #print(\"surface melting\")\n",
+ " Tsurf = Tsurfmelt\n",
+ " \n",
+ " # recalculate A1 & B1 for surface melting\n",
+ " A1 = (rhoi*hiold)/(2*dtime) * ci + K32*(4*dtime*K32+rhoi*hiold*ci)/(6*dtime*K32+rhoi*hiold*ci) + K12 # (19)\n",
+ " B1 = -1*(rhoi*hiold)/(2*dtime) * (ci*T1old - (L*muS)/T1old) - SWnet * I- \\\n",
+ " K32 * (4*dtime*K32*Tf + rhoi*hiold*ci*T2old)/(6*dtime*K32 + rhoi*hiold*ci) + K12*Tsurf # (20)\n",
+ "\n",
+ " # recalculate T1 & T2\n",
+ " T1 = -1 * (B1+ (B1**2 - 4*A1*C1)**0.5)/(2*A1) # (21)\n",
+ " T2 = (2 * dtime * K32 * (T1 + 2*Tf) + rhoi*hiold*ci*T2old) / (6 * dtime * K32 + rhoi * hiold * ci) #(15)\n",
+ "\n",
+ " Qtop = K12 * (T1-Tsurf) - (A+B*Tsurf) # (22)\n",
+ " else:\n",
+ " Qtop = 0\n",
+ "\n",
+ " Qbot = -4 * Ki * (Tf-T2)/hiold # (23)\n",
+ "\n",
+ " # calculated values \n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf) +\" °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1) +\" °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2) +\" °C\")\n",
+ "\n",
+ " #print(\"Qbot= \" +str(Qbot) +\" W/m^2\")\n",
+ " #print(\"Qtop= \" +str(Qtop) +\" W/m^2\")\n",
+ "\n",
+ " # Temeperatures may change in the ice growth scheme!\n",
+ " # ICON output values\n",
+ " #print(\"ICON: \")\n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf_ICON) +\" °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1_ICON) +\" °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2_ICON) +\" °C\")\n",
+ " \n",
+ " return Tsurf, T1, T2, Qbot, Qtop"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 2.b) ice thickness calculation\n",
+ "\n",
+ "def ice_growth(hiold, hsold, Tsurf, T1, T2, Qbot, Qtop, prls, prcs):\n",
+ " # snow thickness calculation\n",
+ " #print(\"calculate snow accumulation\")\n",
+ " hs=hsold +(prls+prcs)*dtime / rhos\n",
+ "\n",
+ " #print(\"hs: \" +str(hsold) +\" -> \" +str(hs) +\" m\")\n",
+ "\n",
+ " # initialize h1 & h2\n",
+ " h1=hiold/2\n",
+ " h2=hiold/2\n",
+ "\n",
+ "\n",
+ " #print(\"calculate ice thickness change\")\n",
+ " # bottom accretion\n",
+ " if Qbot<0:\n",
+ " #print(\"bottom accretion\")\n",
+ " dh2 = Qbot * dtime / (rhoi * E2(Tf)) #(24) \n",
+ " T2 = (dh2*Tf + h2*T2)/(dh2 + h2) #temperature change of lower ice layer due to added mass (26)\n",
+ " h2 += dh2 \n",
+ " \n",
+ " hi = h1+h2\n",
+ " \n",
+ " fluxres_w=0\n",
+ " # surface melting\n",
+ " if Qtop>0:\n",
+ " #print(\"surface melting\")\n",
+ " dhs = -min( (Qtop*dtime) /(L *rhos) ,hs) #(27)\n",
+ " dh1 = -min(max((Qtop*dtime - L*hs*rhos) /(-1*E(T1) *rhoi),0 ),h1) #(28)\n",
+ " dh2 = -min(max((Qtop*dtime - L*hs*rhos + E(T1)*h1*rhoi)/(-1*E2(T2)*rhoi),0 ),h2) #(29)\n",
+ "\n",
+ " fluxres_w = max(Qtop*dtime - L*hs + E(T1)*hiold + E2(T2)*h2 ,0) #(30)\n",
+ " h1 += dh1\n",
+ " h2 += dh2\n",
+ " hs += dhs\n",
+ "\n",
+ " # bottom melting\n",
+ " if Qbot>0:\n",
+ " #print(\"bottom melting\")\n",
+ " dh2 = -min( (Qbot*dtime) /(-E2(T2)*rhoi) ,h2) #(31)\n",
+ " dh1 = -min(max((Qbot*dtime + E2(T2)*h2*rhoi) /(-E(T1)*rhoi) ,0),h1) #(32)\n",
+ " dhs = -min(max((Qbot*dtime + E2(T2)*h2*rhoi + E(T1)*h1*rhoi)/(L*rhos) ,0),hs) #(33)\n",
+ "\n",
+ " fluxres_w += max(Qbot*dtime - L*hs + E(T1)*hiold + E2(T2)+h2, 0)\n",
+ " h1 += dh1\n",
+ " h2 += dh2\n",
+ " hs += dhs\n",
+ " \n",
+ " hi = h1+h2\n",
+ "\n",
+ " # snow ice conversion\n",
+ " dhs = -max((hs - ((rhow-rhoi)/rhos)*hi)*(rhoi/rhow),0)\n",
+ " dh1 = -dhs\n",
+ " if dhs<0:\n",
+ " print(\"convert snow to ice\")\n",
+ "\n",
+ " # adjust T1 due to incorporation of zero heat capacity snow\n",
+ " f1 = h1/(h1+dh1)\n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(-muS) # (39) with T2=-muS\n",
+ " T1 = (Tbar - (Tbar**2 + 4*muS*L / ci)**0.5)/2 # (38)\n",
+ "\n",
+ "\n",
+ " hs += dhs\n",
+ " h1 += dh1\n",
+ " hi = h1+h2\n",
+ "\n",
+ " # even up h1 & h2 and change temperature accordingly\n",
+ " if h1>h2:\n",
+ " #print(\"convert h1 to h2\")\n",
+ "\n",
+ " f1 = h1/(0.5*hi)-1\n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(T2) # (39) \n",
+ " T2 = Tbar # (40)\n",
+ " elif h2>h1:\n",
+ " #print(\"convert h2 to h1\") \n",
+ "\n",
+ " f1 = h1/(0.5*hi) \n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(T2) # (39) \n",
+ " T1 = (Tbar - (Tbar**2 + 4*muS*L / ci)**0.5)/2 # (38)\n",
+ "\n",
+ "\n",
+ " # check if T2>-muS through ice conversion\n",
+ " # not explicitly defined in Winton (2000), taken from the ICON code\n",
+ " # available energy h2*ci*(T2 + muS) is used t euqally melt upper and lower layer with enthalpies E(T1) and E2(-muS)\n",
+ " if T2>-muS:\n",
+ " print(\"T2 over bulk melting temperature: melting\")\n",
+ " #hi = hi - h2*ci*(T2 + muS) / (0.5*L- 0.5*(ci*(T1 +muS) - L * (1+muS/T1)))\n",
+ " hi = hi - h2*ci*(T2 + muS) / (-0.5* E(T1) - 0.5* E2(-muS))\n",
+ " T2=-muS\n",
+ " \n",
+ " #print(\"hi: \" +str(hiold) +\" -> \" +str(hi) +\" (\" +str(hi_ICON) +\") m\")\n",
+ " #print(\"hs: \" +str(hsold) +\" -> \" +str(hs) +\" (\" +str(hs_ICON) +\") m\")\n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf) +\" (\" +str(Tsurf_ICON) +\") °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1) +\" (\" +str(T1_ICON) +\") °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2) +\" (\" +str(T2_ICON) +\") °C\")\n",
+ "\n",
+ " #print(\"\")\n",
+ " return hi, hs, T1, T2, fluxres_w"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# surface fluxes \n",
+ "def surface_fluxes_semtner(Tsurfold, rsds, rlds, lhflx, shflx, albedo):\n",
+ " #print(\"calculate surface fluxes\")\n",
+ "\n",
+ " # surface energy flux balance \n",
+ " # longwave incoming + longwave outgoing + shortwave balance + latent heat flux + sensible heat flux\n",
+ " # in ICON: addition of zemissdef\n",
+ " SWnet = rsds * (1-albedo) # = swflx_ice\n",
+ " nonsolar_ice = 1* ( zemissdef *(rlds - sigma* (Tsurfold+Tmelt)**4 ) + lhflx + shflx ) #UPWARD flux # =nonsolar_ice!\n",
+ " dnonsolarT = -4 * zemissdef * sigma * (Tsurfold+Tmelt)**3 # dnonsolarT\n",
+ " \n",
+ " #print(\"FS = \" +str(FS) +\" W/m^2\")\n",
+ " #print(\"dFS = \" +str(dFS) +\" + \" +str(rhoi * hcilayer /dtime *ci) +\" W/(m^2K)\")\n",
+ " \n",
+ " return nonsolar_ice, dnonsolarT, SWnet\n",
+ "\n",
+ "\n",
+ "# set ice temperature\n",
+ "def set_ice_temp_semtner(Tsurfold, hiold, hsold, nonsolar_ice, dnonsolarT, SWnet, c_stability=True):\n",
+ " \n",
+ " # effective heat conductivity of ice&snow\n",
+ " k_eff = (Ki * Ks) / (Ks*hiold + Ki*hsold) # in Semtner paper not a variable but used in the formula for Fs\n",
+ " \n",
+ " F_A = -1*nonsolar_ice - SWnet # Flux from atmosphere, not in Semtner paper\n",
+ " \n",
+ " F_S = k_eff * (Tf - Tsurfold) # Flux into ice\n",
+ " \n",
+ " deltaTdenominator = k_eff - dnonsolarT \n",
+ " if c_stability:\n",
+ " deltaTdenominator = deltaTdenominator +rhoi*hcilayer*ci/dtime # addition of constant heat capacity to stabilize surface temperture (not in Semtner paper)\n",
+ " \n",
+ " deltaT = (F_S - F_A) / deltaTdenominator\n",
+ " \n",
+ " if Tsurfold + deltaT > 0: # Tsurf > 0°C -> Surface melting\n",
+ " deltaT = -Tsurfold\n",
+ " Tsurf = 0\n",
+ " \n",
+ " Qtop = (F_S - F_A) - deltaT * deltaTdenominator # Qtop >0 -> melting \n",
+ " # (F_S - F_A) -> flux imbalance from old surface temperature Tsurfold\n",
+ " # Tsurfold * deltaTdenominator -> flux imbalance resulting from warming Tsurf to 0°C (Tsurfold in °C!)\n",
+ " \n",
+ " Qbot = - F_S + deltaT * k_eff # originally Qbot = -F_S\n",
+ " else:\n",
+ " Tsurf = Tsurfold + deltaT\n",
+ " \n",
+ " Qtop = 0\n",
+ " Qbot = k_eff * (Tsurf - Tf)\n",
+ " \n",
+ " return Tsurf, Qbot, Qtop, F_A, F_S\n",
+ "\n",
+ "\n",
+ "def ice_growth_semtner(hiold, hsold, Tsurf, Qbot, Qtop, prls, prcs):\n",
+ " \n",
+ " #print(\"calculate snow accumulation\")\n",
+ " hs=hsold +(prls+prcs)*dtime / rhos\n",
+ " \n",
+ " \n",
+ " if hs>0:\n",
+ " hs = max(hs - dtime * Qtop / (L*rhos),0) # alf*rhos = qs\n",
+ " hi = hiold\n",
+ " else:\n",
+ " hi = max(hiold - dtime* Qtop / (L*rhoi),0) # alf*rhoi = qi\n",
+ " \n",
+ " hi = hi - dtime * Qbot / (L*rhoi) # Qbot=-F_S; alf*rhoi = qi\n",
+ " \n",
+ " return hi, hs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def set_albedo(hi, hs, Tsurf): # after set_ice_albedo in mo_sea_ice.f90 in ICON\n",
+ "\n",
+ " if hs>1e-2*rhow/rhos: # snow has to be thicker than 0.034m\n",
+ " if Tsurf==0:\n",
+ " albedo=albsnow_warm\n",
+ " elif Tsurf <=-1:\n",
+ " albedo=albsnow_cold\n",
+ " else:\n",
+ " albedo = (1 + Tsurf)*albsnow_warm - Tsurf*albsnow_cold\n",
+ "\n",
+ " else: # bare ice\n",
+ " if Tsurf==0:\n",
+ " albedo=albice_warm\n",
+ " elif Tsurf <=-1:\n",
+ " albedo=albice_cold\n",
+ " else:\n",
+ " albedo = (1 + Tsurf)*albice_warm - Tsurf*albice_cold\n",
+ " \n",
+ " \n",
+ " return albedo\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 135,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ -86400. -85800. -85200. ... 2677200. 2677800. 2678400.]\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b7bb266d780>]"
+ ]
+ },
+ "execution_count": 135,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# initial conditions\n",
+ "init_Tsurf = -10\n",
+ "#init_T1 = -1.3\n",
+ "#init_T2 = -2\n",
+ "init_T1 = -10\n",
+ "init_T2 = -6\n",
+ "init_Qbot = 0\n",
+ "init_Qtop = 0\n",
+ "init_hi = 1\n",
+ "init_hs = 0\n",
+ "\n",
+ "prls = 0\n",
+ "prcs = 0\n",
+ "albedo_init = albice_cold\n",
+ "\n",
+ "# boundary conditions\n",
+ "lhflx = 0\n",
+ "shflx = 0\n",
+ "\n",
+ "initial_conditions=\"melting_snow\"\n",
+ "if initial_conditions==\"melting\":\n",
+ " # melting -> melt ratched effect with abbot (2010) zemissfac\n",
+ " rlds = 0 \n",
+ " shflx = 60 \n",
+ " rsds = 500\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 4\n",
+ "elif initial_conditions==\"melting_icon\":\n",
+ " # melting -> melt ratched effect with ICON zemissfac\n",
+ " rlds = 0\n",
+ " shflx = 150\n",
+ " rsds = 750\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 4\n",
+ " \"\"\"\n",
+ " rlds = 0\n",
+ " shflx = 150 \n",
+ " rsds = 800\n",
+ " init_T1 = -4.5\n",
+ " init_T2 = -2.5\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 1\"\"\"\n",
+ "elif initial_conditions==\"melting_snow\":\n",
+ " rlds = 0\n",
+ " shflx = 150\n",
+ " rsds = 650\n",
+ " init_T1 = -8\n",
+ " init_T2 = -4\n",
+ " init_Tsurf = -5\n",
+ " init_hi = 5\n",
+ " init_hs = 1\n",
+ "elif initial_conditions==\"freezing\":\n",
+ " # freezing\n",
+ " rlds = 0 \n",
+ " shflx = 20\n",
+ " init_hi = 2\n",
+ " init_hs = 0.5\n",
+ " rsds = 500\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -9\n",
+ " init_T2 = -5\n",
+ " init_Tsurf = -5\n",
+ "elif initial_conditions==\"freezing_2\":\n",
+ " # freezing\n",
+ " init_hi = 0.05\n",
+ " init_hs = 0.0\n",
+ " prls = 0\n",
+ " rlds = 0 \n",
+ " shflx = 20\n",
+ " rsds = 500\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -1.9\n",
+ "elif initial_conditions==\"melting_2\":\n",
+ " rlds = 120 \n",
+ " rsds = 300\n",
+ " init_hi = 1\n",
+ " init_T1 = -5\n",
+ " init_T2 = -3\n",
+ " init_Tsurf = -8\n",
+ "elif initial_conditions==\"snowball\":\n",
+ " shflx = -50\n",
+ " rlds = 0\n",
+ " rsds = 800\n",
+ " init_T1 = -7\n",
+ " init_T2 = -5\n",
+ " init_Tsurf = -10\n",
+ " init_hi = 20\n",
+ "elif initial_conditions==\"abbot\":\n",
+ " shflx = 80 \n",
+ " rlds = 0\n",
+ " rsds = 40/ albedo_init\n",
+ " init_T1 = -3.5\n",
+ " init_T2 = -2.8\n",
+ " init_Tsurf = -8\n",
+ "else:\n",
+ " rlds=0\n",
+ " rsds=0\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "#artificial radiative forcing\n",
+ "days = 31\n",
+ "spinupdays = 1\n",
+ "time_artificial=np.linspace(-int(spinupdays),int(days),(days+spinupdays)* int((60 * 60 * 24)/dtime)+1) # timestep has to be 600s = 10m = 1/6h = 1/144d \n",
+ " # = dtime / (60 * 60 * 24)\n",
+ "print(time_artificial*24*60*60)\n",
+ "rsds_array_artificial = rsds*np.sin(time_artificial*2*np.pi-np.pi/2)\n",
+ "rsds_array_artificial[rsds_array_artificial<0]=0\n",
+ "plt.plot(time_artificial,rsds_array_artificial)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Winton model\n",
+ "\n",
+ "Initial conditions are defined here. Albedo calculation is activatred or deactivated by commenting out the set_albedo function. The model breaks if the ice thickness is below 0m, there is no handling of minimal ice thickness implemented as in the ICON sea-ice scheme!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "-7.403809721504278\n",
+ "-3.8352931389796616\n"
+ ]
+ }
+ ],
+ "source": [
+ "# run Winton model\n",
+ "\n",
+ "# initial conditions\n",
+ "Tsurf = init_Tsurf\n",
+ "T1 = init_T1\n",
+ "T2 = init_T2\n",
+ "Qbot = init_Qbot\n",
+ "Qtop = init_Qtop\n",
+ "hi = init_hi\n",
+ "hs = init_hs\n",
+ "albedo = albedo_init\n",
+ "\n",
+ "# result array\n",
+ "hi_result=[]\n",
+ "hi_result.append(hi)\n",
+ "\n",
+ "hs_result=[]\n",
+ "hs_result.append(hs)\n",
+ "\n",
+ "Tsurf_result=[]\n",
+ "Tsurf_result.append(Tsurf)\n",
+ "\n",
+ "T1_result=[]\n",
+ "T1_result.append(T1)\n",
+ "\n",
+ "T2_result=[]\n",
+ "T2_result.append(T2)\n",
+ "\n",
+ "Qbot_result=[]\n",
+ "Qbot_result.append(Qbot)\n",
+ "\n",
+ "Qtop_result=[]\n",
+ "Qtop_result.append(Qtop)\n",
+ "\n",
+ "albedo_result=[]\n",
+ "albedo_result.append(albedo)\n",
+ "\n",
+ "FS_result=[]\n",
+ "\n",
+ "SWnet_result=[]\n",
+ "\n",
+ "for i in range(1,rsds_array_artificial.size):\n",
+ " FS, dFS, SWnet, I, Tsurfmelt = surface_fluxes(Tsurf, hs, rsds_array_artificial[i], rlds, lhflx, shflx, albedo)\n",
+ " Tsurf, T1, T2, Qbot, Qtop = set_ice_temp(Tsurf, T1, T2, hi, hs, FS, dFS, SWnet, I, Tsurfmelt, True)\n",
+ " #Qtop=0\n",
+ " hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, Tsurf, T1, T2, Qbot, Qtop, prls, prcs)\n",
+ " #albedo = set_albedo(hi, hs, Tsurf)\n",
+ " #print(\"time=\", str(time_artificial[i]), \" Tsurf=\", str(Tsurf))\n",
+ " \n",
+ " \n",
+ " #hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], t1_array.values[tind+i,lind], t2_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ " \n",
+ " # assign results to final array\n",
+ " hi_result.append(hi)\n",
+ " hs_result.append(hs)\n",
+ " Tsurf_result.append(Tsurf)\n",
+ " T1_result.append(T1)\n",
+ " T2_result.append(T2)\n",
+ " Qbot_result.append(Qbot)\n",
+ " Qtop_result.append(Qtop)\n",
+ " albedo_result.append(albedo)\n",
+ " SWnet_result.append(SWnet)\n",
+ " FS_result.append(FS)\n",
+ " \n",
+ " if hi<=0: \n",
+ " break\n",
+ "print(T1)\n",
+ "print(T2)\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Semtner model\n",
+ "\n",
+ "Initial conditions are defined here. Albedo calculation is activatred or deactivated by commenting out the set_albedo function. The model breaks if the ice thickness is below 0m, there is no handling of minimal ice thickness implemented as in the ICON sea-ice scheme!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 137,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# run semtner model \n",
+ "\n",
+ "# initial conditions\n",
+ "Tsurf = init_Tsurf\n",
+ "T1 = init_T1\n",
+ "T2 = init_T2\n",
+ "Qbot = init_Qbot\n",
+ "Qtop = init_Qtop\n",
+ "hi = init_hi\n",
+ "hs = init_hs\n",
+ "albedo = albedo_init\n",
+ "\n",
+ "# result array\n",
+ "hi_result_Semtner=[]\n",
+ "hi_result_Semtner.append(hi)\n",
+ "\n",
+ "hs_result_Semtner=[]\n",
+ "hs_result_Semtner.append(hs)\n",
+ "\n",
+ "Tsurf_result_Semtner=[]\n",
+ "Tsurf_result_Semtner.append(Tsurf)\n",
+ "\n",
+ "T1_result_Semtner=[]\n",
+ "T1_result_Semtner.append(T1)\n",
+ "\n",
+ "T2_result_Semtner=[]\n",
+ "T2_result_Semtner.append(T2)\n",
+ "\n",
+ "Qbot_result_Semtner=[]\n",
+ "Qbot_result_Semtner.append(Qbot)\n",
+ "\n",
+ "Qtop_result_Semtner=[]\n",
+ "Qtop_result_Semtner.append(Qtop)\n",
+ "\n",
+ "albedo_result_Semtner=[]\n",
+ "albedo_result_Semtner.append(albedo)\n",
+ "\n",
+ "FS_result_Semtner=[]\n",
+ "FA_result_Semtner=[]\n",
+ "\n",
+ "SWnet_result_Semtner=[]\n",
+ "\n",
+ "for i in range(1,rsds_array_artificial.size):\n",
+ " nonsolar_ice, dnonsolarT, SWnet = surface_fluxes_semtner(Tsurf, rsds_array_artificial[i], rlds, lhflx, shflx, albedo)\n",
+ " Tsurf, Qbot, Qtop, FA, FS = set_ice_temp_semtner(Tsurf, hi, hs, nonsolar_ice, dnonsolarT, SWnet, True)\n",
+ " #Qtop=0\n",
+ " hi, hs = ice_growth_semtner(hi, hs, Tsurf, Qbot, Qtop, prls, prcs)\n",
+ " #albedo = set_albedo(hi, hs, Tsurf)\n",
+ " #hi, hs = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ "\n",
+ " \n",
+ " \n",
+ " #hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], t1_array.values[tind+i,lind], t2_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ " \n",
+ " # assign results to final array\n",
+ " hi_result_Semtner.append(hi)\n",
+ " hs_result_Semtner.append(hs)\n",
+ " Tsurf_result_Semtner.append(Tsurf)\n",
+ " Qbot_result_Semtner.append(Qbot)\n",
+ " Qtop_result_Semtner.append(Qtop)\n",
+ " albedo_result_Semtner.append(albedo)\n",
+ " SWnet_result_Semtner.append(SWnet)\n",
+ " FS_result_Semtner.append(FS)\n",
+ " FA_result_Semtner.append(FA)\n",
+ " if hi<=0: \n",
+ " break"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "(0, 1)"
+ ]
+ },
+ "execution_count": 138,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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p60wrp9BwUG7x8r5qevtt3KZdSi5zz1U5VDV38XpxndWlKB+g4aDc4sU9leSlxZCXrgv6uMqy6SmMj4/gse06W6saOw0H5XJl9W3sr2zhlnm6GqwrBQYIdy3KZs+pZvaeOmN1OcrLaTgol3thTxWBAcLaORoOrvaFgiyiQ4N4bLteFKfGRsNBudSAzfDSniqumZJEUrSuO+BqUaFBrJufxeaiWqqbu6wuR3kxZ60E97iI1ItI0aBt8SLypoiUOr6Pc2wXEfmFiJSJyAERmeeMGpRn+vBYI7Wt3dw6L9PqUvzGHQuzMcbw1M6TVpeivJizWg5PAKs+s+37wFZjTC6w1XEfYDX2daNzgfXAb5xUg/JAL+6pIiYsiGXTdY1od8mKj2BFXipPf3yKrl5d60GNjlPCwRjzHvDZaSHXAk86bj8J3DRo+x+M3U4gTkT0qigf1N7Tz5aiWq6fnU5YcKDV5fiVuxZl09zZx0t7q6wuRXkpV55zSDHG1AA4vp/90zEDqBi0X6Vjm/Ixmw7W0NU3oF1KFpifE8+M9Bie+FDXelCjY8UJaRli25A/vSKyXkQKRaSwoaHBxWUpZ3txTyU5iZHMGx9ndSl+R0S4a1EOR+va+aCsyepylBdyZTjUne0ucnyvd2yvBLIG7ZcJVA/1AsaYDcaYAmNMQVJSkgtLVc5WcbqTneWnuWVuBiJD/T2gXO2G2WkkRulaD2p0XBkOG4E7HbfvBF4etP0Ox6ilBUDL2e4n5Tv+4ujrvlkvfLNMaFAgt18xgbcP13Nc13pQl8hZQ1mfBnYAU0WkUkTuAX4CLBeRUmC54z7AJqAcKAMeBe5zRg3KcxhjeHFvFQsmxpM5LsLqcvza7QvGExwoPKlrPahL5JTpMY0xt13goWVD7GuA+53xvsozFVW1cryxg68tnmh1KX4vOTqMG2an83xhBd9ZMYWYsGCrS1JeQq+QVk73yoFqggOF1fk6QtkT3L0oh47eAZ7bVTH8zko5aDgop7LZDK/sr+aaKUnERuhfqZ4gPyOWyyaM408fn9JhrWrENByUU+0+dYaalm5umJ1udSlqkNvmj6e8oYOPjn/2WlWlhqbhoJzqlf3VhAUHcN30FKtLUYN8bmYa0WFBPP2xLiOqRkbDQTlN/4CNTQdrWDYthchQXQrUk4SHBHLrvEw2H6zlTEev1eUoL6DhoJxmZ/lpGtt7uWG2noj2ROvmZ9E7YOOFPZVWl6K8gIaDcpqN+6uICg1iyVSdgdUTTUuNYd74OJ7WE9NqBDQclFP09A+wpaiWFTNSdAZWD3bb/PEca+hg1wldRlRdnIaDcor3jzbS2t2vo5Q83PWz0okOC+JPH+lCQOriNByUU7xyoJpxEcFcNTnR6lLURYSHBHLz3Aw2FemJaXVxGg5qzLp6B3jzUB2rZ6YRHKg/Up5u3eXj6e238aIuBKQuQj/Jasy2Hq6js3eAG2Zpl5I3yEuPYU6WnphWF6fhoMbstQM1JEWHMj8n3upS1Ah9ef54yurb2X1ST0yroWk4qDHp6h1g25EGVs1IJTBAF/XxFmtmpREeHKjXPKgL0nBQY/Lu0Xq6+gZYnZ9qdSnqEkSFBrE6P5VX99fQ3TdgdTnKA2k4qDHZXFTLuIhg7VLyQrdelklbTz9vHKqzuhTlgTQc1Kj19A+wtaSeFXmpBOkoJa+zcGIC6bFhvLBbu5bU+Vz+iRaREyJyUET2iUihY1u8iLwpIqWO7+NcXYdyvu2ljbT39LNqpnYpeaOAAOHmeRm8X9pAXWu31eUoD+OuP/eWGmPmGGMKHPe/D2w1xuQCWx33lZfZXFRLdFgQiybphW/e6pZ5mdgM/EWveVCfYVVfwFrgScftJ4GbLKpDjVLfgI03D9WxfHoKIUHapeStJiVFMXd8HC/sqdRrHtSnuONTbYA3RGS3iKx3bEsxxtQAOL7rNJ5eZmd5Ey1dfazSUUpe79Z5mRyta6eoqtXqUpQHcUc4LDLGzANWA/eLyOKRPlFE1otIoYgUNjQ0uK5Cdck2F9USERLI4ilJVpeixuiGWemEBAboNQ/qU1weDsaYasf3euAlYD5QJyJpAI7v9Rd47gZjTIExpiApSX8JeYoBm+GN4lqWTkvW6bl9QGxEMNflJfPyvip6+21Wl6M8hEvDQUQiRST67G1gBVAEbATudOx2J/CyK+tQzrXrhH3FN73wzXfcOi+TM519bDsy5N9pyg+5uuWQAmwXkf3Ax8BrxpgtwE+A5SJSCix33FdeYktRLaFBASzVFd98xuIpSSRGhWjXkvqES1eBN8aUA7OH2N4ELHPleyvXsNkMW4pquWZKEpGhLv3xUW4UHBjAjbMzeGrnCVo6+4iNCLa6JGUxHYOoLsn+ymZqW7t1lJIPWjsnnb4Bw5biGqtLUR5Aw0FdkjcO1REYICyblmJ1KcrJZmXGMiEhgo37q60uRXkADQd1Sd48VMcVOfHa7eCDRIS1s9PZcayJep1Ow+9pOKgRO97YQVl9OyvytNXgq26ck47NwKsHtGvJ32k4qBF781AtANdpOPisycnRTE+L0a4lpeGgRu6N4jry0mLIHBdhdSnKhdbOSWdfRTOnmjqtLkVZSMNBjUhjew+7T51hubYafN4Ns9MBeOWAth78mYaDGpG3S+oxBlbM0HDwdRlx4RRMGMfGfRoO/kzDQY3IG4fqyIgLJy8txupSlBusnZPOkbo2DtfqTK3+SsNBDauzt5/3SxtYnpeCiFhdjnKDNTPTCAwQbT34MQ0HNaz3Sxvp6bfp+QY/khAVyqLJibxyoFoXAfJTGg5qWG8eqiMmLIj5OfFWl6LcaO3sdCpOd7G3otnqUpQFNBzURQ3YDG8frufaackEB+qPiz9ZMcO+BKx2Lfkn/bSri9p98gynO3pZnqcT7fmb6LBglkxJYktRLTabdi35Gw0HdVFvFNcSEhjANVN1JT5/tGZmGrWt3eytOGN1KcrNNBzUBRljeKukjoWTEojStRv80rLpyYQEBfDagVqrS1FuZlk4iMgqETkiImUi8n2r6lAXVt7YwYmmTp1LyY9FhwWzODeJzUU12rXkZywJBxEJBH4FrAbygNtEJM+KWtSFvV1iX0/42mm6HKg/+9ysVGpaunXUkp+xquUwHygzxpQbY3qBZ4C1FtWiLuCtkjqmpUaTERdudSnKQsumpxASGMCmgzqNtz+xKhwygIpB9ysd25SHaOnso/DkGZZN11aDv4sJC+bq3EQ2H6zRC+L8iFXhMNQcDOf91InIehEpFJHChoYGN5Slznq3tIEBm2HZdD3foOyjlqpbutmnXUt+w6pwqASyBt3PBM670sYYs8EYU2CMKUhK0qGU7vR2SR0JkSHMzoyzuhTlAa7LSyE4ULRryY9YFQ67gFwRyRGREGAdsNGiWtRn9A/Y2Ha0gSVTkwkM0In2FMSGB3N1bhKbDtZq15KfsCQcjDH9wAPA60AJ8JwxptiKWtT59lY009zZp+cb1KesmZlGVXMX+ytbrC5FuYFlVzYZYzYBm6x6f3VhW0vqCQoQrs5NtLoU5UGWTz/XtTQnS7sbfZ1eIa3Os7WkjismxhMdFmx1KcqDxEYEs2hyIq8d0FFL/kDDQX3KqaZOSuvbuXaajlJS5zvbtXSwSruWfJ2Gg/qUtw/XAXCdnm9QQ1iRl0JQgLC5SOda8nUaDupTth6uZ1JSJBMSIq0uRXmguIgQFk5K0Avi/ICGg/pEe08/H5Wf1gvf1EWtzk/jRFMnh2vbrC5FuZCGg/rE9tJGegdsOtGeuqgVM1IIENisF8T5NA0H9Yl3DtcTHRbEZRPGWV2K8mCJUaFcnh2v5x18nIaDAuwL+2w7Ws/i3CRdK1oNa83MNErr2ymr164lX6W/BRQAJTVt1LX26HKgakRWzrCvKb75oLYefJWGgwJg21H7wj5Lpmg4qOGlxoYxb3ycdi35MA0HBcC2ww3MSI8hOSbM6lKUl1gzM41DNa2cbOqwuhTlAhoOipauPnafOsMS7VJSl+CTriVtPfgkDQfFB2WNDNgMS6bqEFY1clnxEczKjNVw8FEaDoptR+qJCQtirs60qS7RqvxU9lc0U9XcZXUpysk0HPycMYZtRxq4ekoSQTqEVV2i1flpAGzR1oPP0d8Gfu5QTSv1bT06SkmNSk5iJNNSo9lSpFdL+xqXhYOIPCQiVSKyz/G1ZtBjD4pImYgcEZGVrqpBDW/bkQYAvb5Bjdrq/DQKT56hvrXb6lKUE7m65fBzY8wcx9cmABHJw75m9AxgFfBrEQl0cR3qArYdqSc/I4bkaB3CqkZn9cxUjIHXi7VryZdY0a20FnjGGNNjjDkOlAHzLajD77V09bHnVDNLpugoJTV6uclRTEqK1FFLPsbV4fCAiBwQkcdF5OxsbhlAxaB9Kh3blJttLz07hFW7lNToiQir89PYWd5EU3uP1eUoJxlTOIjIWyJSNMTXWuA3wCRgDlADPHL2aUO81JCrhojIehEpFJHChoaGsZSqhvDOkXpiw4N1sXg1ZqtnpmIz8OahOqtLUU4SNJYnG2OuG8l+IvIo8KrjbiWQNejhTKD6Aq+/AdgAUFBQoMtOOZHNZnj3aANX5ybqEFY1ZnlpMYyPj2BTUS3r5o+3uhzlBK4crZQ26O7NQJHj9kZgnYiEikgOkAt87Ko61NAO1bTS0NajV0Urp7B3LaXyYVkjLZ19VpejnMCVfzL+VEQOisgBYCnwbQBjTDHwHHAI2ALcb4wZcGEdagjvHnUMYdXrG5STrJ6ZRr/N8FaJdi35gjF1K12MMeYrF3nsYeBhV723Gt47h+uZmRFLUnSo1aUoHzE7M5b02DA2F9Vw62WZVpejxkg7m/1QS2cfe3QWVuVkIsKq/DTeK22kvaff6nLUGGk4+KH3yxqwGTQclNOtnplKb7+Ntw/XW12KGiMNBz/0zuEG4iKCmZM1bvidlboEl40fR1J0KJsP6lxL3k7Dwc+cG8KaRGDAUJecKDV6AQHCqhmpbDvSQGevdi15Mw0HP7OvspnGdp2FVbnO6vxUuvoGePeIXrjqzVw2WklZp627j+ONHRxv7KC8oYOTTR2cPN3JyaZOTnf0EiCwWMNBucj8nHjGRQSzuaiW1TPThn+C8kgaDl6qp3+AitOdlDd0nAsCRxg0DprfRgTSY8PJToxg5YxUshMimJMVp0NYlcsEBQawckYqrx6oobtvgLBgnXTZG2k4eDCbzVDd0vWpVsDZ25VnOrENmlAkMSqEnMRIrp2WRE5iFDmJkUxKiiQrPkI/nMrtVuWn8syuCraXNnJdXorV5ahR0HDwAAM2w6nTnZTWtVFa386x+nZK69spq2+nq+/cxeMRIYHkJEYyKzOWm+ZmMDExkpzESLITI4kND7bwX6DUp105KZGYsCA2F9VqOHgpDQc36u23cbKp45Nf/KX17ZTWtVHe2EFvv+2T/dJiw5icHMW6+VlMTo5iYmIUE5MiSY4ORURHGCnPFxIUwHV5Kbx5qJbe/pmEBOnYF2+j4eACNpuhqrmLw7VtHK5p5XBtG0fq2jjR2EG/oy9IBDLHhZObHM01U5KYlBxlXzQlOYqYMG0FKO+3Oj+NF/dUsaO8Sefw8kIaDmPU0tXHkdo2Dte2fhIGR+vaPzV9wPj4CKamRrNyRgq5ydFMTo5iUlIU4SF6LkD5rqtzE4kMCWRLUY2GgxfScBihAZvheGMHxdUt9paAIwiqW84tqh4bHszU1GhunZfBtLQYpqZGMzUlmshQPczK/4QFB3Lt9BReL67jx2ttum6Il9HfWkPoG7BRVt9OUVULxdWtFFW1cKimlc5e+8nhoABhcnIUl+fEMy01hmlp0UxLjSY1JkzPCSg1yOr8VF7ZX83HJ05z5aREq8tRl8Dvw6G7b4AjtW0UVbdQVNX6Scvg7AniiJBAZqTH8MWCLGakxzAjPZbJyVF6gk2pEVgyNYmw4AC2FNVqOHgZvwqH3n4bR2rb2FfZzP6KZoqqWiitb2fAcZI4JiyI/IxYvnplNjPSY8jPiCU7IVLnIFJqlCJCglgyJZktRbU8dMMMAvSz5DV8NhyMMZxs6mR/ZTN7TzWzv7KZ4urWT1oECZEhzMyM5brpKeRn2FsEmePCtVtIKSdbPRRE6JsAAA1+SURBVDOVLcW17Dl1hoLseKvLUSM0pnAQkS8ADwHTgfnGmMJBjz0I3AMMAN8wxrzu2L4K+C8gEPgfY8xPxlLDWU3tPeyvbGZfRQv7Kuwtg5Yu+1q24cGBzHS0CGZnxjE7K5aMOA0Cpdzh2mnJhAQGsLmoVsPBi4y15VAE3AL8bvBGEckD1gEzgHTgLRGZ4nj4V8ByoBLYJSIbjTGHLuVNbTbDsYZ2dp88Q+HJM+w+eYbjjR0ABAhMSYlmdX4qc7LimJ0VR25ylI6UUMoi0WHBXJ2byJaiWv7xc9P1jzIvMaZwMMaUAEP9Z68FnjHG9ADHRaQMmO94rMwYU+543jOOfYcNh46efn71ThmFJ06z59S5VkF8ZAjzxo/jS5dnMTcrjpmZsUSE+GxvmVJeafXMNLYerudAZQuzs+KsLkeNgKt+i2YAOwfdr3RsA6j4zPYrRvKC5Y0d/MfrR5icHMXq/FTmTRhHwYRx5CRG6l8iSnm45dNTCAoQNhXVaDi4iDH2mRl2nTjNrhNnKDxxekyvN2w4iMhbQOoQD/3AGPPyhZ42xDbD0IsLmSG2nX3v9cB6gJTMbPb+cDnjIkOGqVgp5WliI4K5crK9a+n7q6bpH3ROUnG6kx3lTew81sTO8qZPLsqNDg3isuyxLQM8bDgYY64bxetWAlmD7mcC1Y7bF9o+1HtvADYAFBQUGA0GpbzX6vxUHnzxICU1beSlx1hdjleqau5ihyMIdhxroqq5C7CPvlwwMYGv5cRzeXY8U1OjCQwQnrx79O/lqm6ljcCfRORn2E9I5wIfY29R5IpIDlCF/aT1l11Ug1LKg6zIS+EHLx1kc1GNhsMI1bZ0s6O80REIpzl1uhOAcRHBLJiYwPrFE1k4KYHc5Cint8bGOpT1ZuCXQBLwmojsM8asNMYUi8hz2E809wP3G2MGHM95AHgd+1DWx40xxWP6FyilvEJCVChX5CSwuaiW766YanU5Hqmjp5+Pjjfx3tFG3ittoLzBPgozNjyYK3Li+eqV2SyclMDUlGiXX1A41tFKLwEvXeCxh4GHh9i+Cdg0lvdVSnmn1TNT+dHLxZTWtZGbEm11OZaz2QzF1a28V9rA+6UN7D55hr4BQ1hwAAsmJvDl+eNZMDGB6Wkxbp+pQcd8KqXcZuUMezhsLqr123Cobenm/dIG3i9tZHtZI6c7egHIS4vh7qtyuCY3iXkTxlm+vK+Gg1LKbVJiwiiYMI7NRbV8Y1mu1eW4Rf+Ajd0nz/D2kXreOVzP0bp2AJKiQ1kyNYnFuUksmpxIUnSoxZV+moaDUsqtVuWn8i+vlXCisYPsxEiry3GJ5s5e3j3awNaSet492kBLVx/BgcL8nHg+f1kmV+cmMS012qOH9Go4KKXcavXMNP7ltRI2F9Vy75JJVpfjFMYYSuvb2VpSz9uH69h98gw2Yx9iujwvhWXTkrkqN5FoL1oCWMNBKeVWGXHhzM6MZUtRjVeHg81m2Ftxhi1FtbxeXPfJMNO8tBjuXzqZa6clMzszzmunKddwUEq53ar8NP59y2Eqz3SSOS7C6nJGrLffxs7yJrYU1/LmoToa2noIDhQWTkpk/eKJLJueTFpsuNVlOoWGg1LK7Vbnp/LvWw6zpaiWv756otXlXFRnbz/vHW3g9eI63iqpo627n/DgQJZOS2LljFSWTksmxou6i0ZKw0Ep5XbZiZFMT4vx2HDo7htg25EGXj1QzdaSerr6BoiLCGbljFRWzkjl6txEy4eaupqGg1LKEqvzU/nZm0epa+0mJSbM6nLo7bexvayBV/fX8MahOtp7+omPDOGWeRl8bmYa83Pi/WpdGA0HpZQl1sy0h8PrxbXcsTDbkhr6B2zsKG/i1f01bCmupaWrj5iwINbMTOWG2eksnJjgV4EwmIaDUsoSk5OjmZwcxaaDNW4NB2PsU1a8sKeSV/ZX09jeS1RoEMvzUrh+VhpX5yYREuSfgTCYhoNSyjJr8lP573fKaGrvISHKtVcI17R08Ze91by4p5LS+nZCAgNYNj2ZtXPSWTI12efPIVwqDQellGVW5afxi7fLeONQHbfNH+/01+/o6ef14lpe3FPFB8caMQYumzCOh2/O5/qZ6cRG+N4oI2fRcFBKWWZ6WjQTEiLYdLDGaeFgjGFn+Wme313BlqJaOnsHyIoP52+vzeWWuRk+O2WHs2k4KKUsIyKszk/jf94vp6Wzb0x/yTe29/DC7kqe3VVBeWMH0aFB3Dg7nVsvy6RgwjiPnsfIE2k4KKUstTo/ld++e4w3S+r4/GWZl/Rcm83wwbFGnvm4gjcO1dI3YCiYMI77l05mzcw0wkP0PMJojXUluC8ADwHTgfnGmELH9mygBDji2HWnMebrjscuA54AwrEv+vNNY4wZSx1KKe81KzOWjLhwNh+sGXE41Ld28/zuSp7ZdYqK013ERQRzx8Js1l2e5bfrRDjbWFsORcAtwO+GeOyYMWbOENt/A6wHdmIPh1XA5jHWoZTyUiLCqvxUntpxkrbuvgvOXHr2XMITHx7nrZJ6BmyGBRPj+bsVU1k5I1VHGznZWJcJLQFG3JcnImlAjDFmh+P+H4Cb0HBQyq+tzk/lse3HeftwPWvnZHzqsa7eAV7aW8WTH57gSF0bcRHB/PVVOXzp8iwmJkVZVLHvc+U5hxwR2Qu0Av9ojHkfyAAqB+1T6dimlPJj88aPIzk6lM0Haz8Jh4rTnTy18yTP7qqgpauP6Wkx/PTWWdw4J11bCW4wbDiIyFtA6hAP/cAY8/IFnlYDjDfGNDnOMfxFRGYAQzUxLni+QUTWY++CYvx454+BVkp5hoAAe9fSc4UVvHO4nqc/PsVbJXX2LqcZqdx5ZTaXZ+uII3caNhyMMddd6osaY3qAHsft3SJyDJiCvaUw+IxTJlB9kdfZAGwAKCgo0JPWSvmwVfmp/GHHSe56YhfxkSHcu2QSt18xgfQ431gfwdu4pFtJRJKA08aYARGZCOQC5caY0yLSJiILgI+AO4BfuqIGpZR3uSIngXuXTGJiYiQ3zNauI6uNdSjrzdh/uScBr4nIPmPMSmAx8M8i0g8MAF83xpx2PO1ezg1l3YyejFZKAYEBwt+vmmZ1GcpBvOUSg4KCAlNYWGh1GUop5TVEZLcxpmA0z9V5aZVSSp1Hw0EppdR5NByUUkqdR8NBKaXUeTQclFJKnUfDQSml1Hk0HJRSSp3Ha65zEJE2zq0P4e8SgUari/AAehzO0WNxjh6Lc6YaY0a1wIU3rQR3ZLQXc/gaESnUY6HHYTA9FufosThHREZ95bB2KymllDqPhoNSSqnzeFM4bLC6AA+ix8JOj8M5eizO0WNxzqiPhdeckFZKKeU+3tRyUEop5SYeFQ4iskpEjohImYh8f4jHQ0XkWcfjH4lItvurdI8RHIvviMghETkgIltFZIIVdbrDcMdi0H6fFxEjIj47UmUkx0JEvuj42SgWkT+5u0Z3GcFnZLyIvCMiex2fkzVW1OkOIvK4iNSLSNEFHhcR+YXjWB0QkXnDvqgxxiO+gEDgGDARCAH2A3mf2ec+4LeO2+uAZ62u28JjsRSIcNy+15+PhWO/aOA9YCdQYHXdFv5c5AJ7gXGO+8lW123hsdgA3Ou4nQecsLpuFx6PxcA8oOgCj6/BvrCaAAuAj4Z7TU9qOcwHyowx5caYXuAZYO1n9lkLPOm4/WdgmfjmiuPDHgtjzDvGmE7H3Z18em1uXzKSnwuAHwM/BbrdWZybjeRY/A3wK2PMGQBjTL2ba3SXkRwLA8Q4bsdykfXqvZ0x5j3g9EV2WQv8wdjtBOJEJO1ir+lJ4ZABVAy6X+nYNuQ+xph+oAVIcEt17jWSYzHYPfjucqvDHgsRmQtkGWNedWdhFhjJz8UUYIqIfCAiO0Vklduqc6+RHIuHgL8SkUpgE/C37inNI13q7xSPukJ6qBbAZ4dSjWQfXzDif6eI/BVQAFzj0oqsc9FjISIBwM+Br7qrIAuN5OciCHvX0hLsrcn3RSTfGNPs4trcbSTH4jbgCWPMIyKyEHjKcSxsri/P41zy705PajlUAlmD7mdyfjPwk31EJAh7U/FiTSlvNZJjgYhcB/wAuNEY0+Om2txtuGMRDeQD20TkBPb+1I0+elJ6pJ+Rl40xfcaY49jnI8t1U33uNJJjcQ/wHIAxZgcQhn3eJX80ot8pg3lSOOwCckUkR0RCsJ9w3viZfTYCdzpufx542zjOtviYYY+Foyvld9iDwVf7lWGYY2GMaTHGJBpjso0x2djPv9xojBn1nDIebCSfkb9gH6yAiCRi72Yqd2uV7jGSY3EKWAYgItOxh0ODW6v0HBuBOxyjlhYALcaYmos9wWO6lYwx/SLyAPA69pEIjxtjikXkn4FCY8xG4DHsTcMy7C2GddZV7DojPBb/AUQBzzvOyZ8yxtxoWdEuMsJj4RdGeCxeB1aIyCFgAPieMabJuqpdY4TH4rvAoyLybexdKF/10T8mEZGnsXclJjrOsfwTEAxgjPkt9nMua4AyoBO4a9jX9NFjpZRSagw8qVtJKaWUh9BwUEopdR4NB6WUUufRcFBKKXUeDQellFLn0XBQSil1Hg0HpZRS59FwUEopdZ7/D6uvUWw6VtqNAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "l0, = plt.plot(time_artificial[1:],-np.array(FS_result_Semtner)-np.array(FA_result_Semtner))\n",
+ "l1, = plt.plot(time_artificial,Qtop_result_Semtner)\n",
+ "#l2, = plt.plot(time_artificial,Qbot_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "plt.legend([l0, l1],[\"F$_S$ +F$_A$\", \"Qtop\"])\n",
+ "plt.xlabel(\"time [days]\")\n",
+ "plt.ylabel(\"F [Wm$^2$]\")\n",
+ "plt.title(\"Semtner surface fluxes\")\n",
+ "plt.show()\n",
+ "\n",
+ "#plt.plot(time_artificial,rsds_array_artificial)\n",
+ "plt.plot(time_artificial,Tsurf_result)\n",
+ "plt.plot(time_artificial,Tsurf_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(time_artificial,Qtop_result)\n",
+ "plt.plot(time_artificial,Qtop_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "\n",
+ "plt.show()\n",
+ "#plt.plot(time_artificial[1:],FA_result_Semtner)\n",
+ "#plt.plot(time_artificial[1:],SWnet_result)\n",
+ "#plt.plot(time_artificial[1:],SWnet_result_Semtner)\n",
+ "plt.plot(time_artificial[1:],-np.array(FS_result_Semtner)-np.array(FA_result_Semtner))\n",
+ "plt.xlim(0,1)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plt.plot(hi_result)\n",
+ "#plt.plot(hi_array[0:10,lind])\n",
+ "\n",
+ "\n",
+ "titlestr = \"\"\n",
+ "\n",
+ "# temperatures\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "plt.grid()\n",
+ "ax1.hlines(-1,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.annotate(\"wet surface\",[25,-0.7])\n",
+ "ax1.plot(time_artificial,Tsurf_result,'b-')\n",
+ "ax1.plot(time_artificial,Tsurf_result_Semtner,'b--')\n",
+ "ax1.plot(time_artificial,T1_result,'g-')\n",
+ "ax1.plot(time_artificial,T2_result,'r-')\n",
+ "ax1.legend([\"Tsurf Winton\",\"Tsurf Semtner\", \"T1\", \"T2\"])\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24],\"\")\n",
+ "ax1.set_ylabel(\"T [°C]\")\n",
+ "ax1.set_title(titlestr)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hi\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,hi_result,'b-')\n",
+ "ax1.plot(time_artificial,hi_result_Semtner,'b--')\n",
+ "ax1.legend([\"hi Winton\", \"hi Semtner\"])\n",
+ "ax1.set_ylabel(\"hi [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# hs\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,hs_result,'b-')\n",
+ "ax1.plot(time_artificial,hs_result_Semtner,'b--')\n",
+ "ax1.legend([\"hs Winton\", \"hs Semtner\"])\n",
+ "ax1.set_ylabel(\"hs [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# Fluxes\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.annotate(\"melting\",[-1,30])\n",
+ "ax1.annotate(\"freezing\",[-1,-30])\n",
+ "\n",
+ "ax1.plot(time_artificial,Qbot_result,'b-')\n",
+ "ax1.plot(time_artificial,Qtop_result,'g-')\n",
+ "ax1.plot(time_artificial,Qbot_result_Semtner,'b--')\n",
+ "ax1.plot(time_artificial,Qtop_result_Semtner,'g--')\n",
+ "ax1.legend([\"Qbot Winton\", \"Qtop Winton\", \"Qbot Semtner\", \"Qtop Semtner\"])\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_ylabel('F [W/m$^2$]')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# albedo\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,albedo_result,'b-')\n",
+ "ax1.plot(time_artificial,albedo_result_Semtner,'b--')\n",
+ "ax1.legend([\"albedo Winton\", \"albedo Semtner\"])\n",
+ "ax1.set_ylabel(\"albedo []\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# rsds\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rsds_array_artificial,'r-')\n",
+ "plt.hlines(rlds,time_artificial[0],time_artificial[-1],'y') #\n",
+ "plt.hlines(shflx,time_artificial[0],time_artificial[-1],'g') # shflx\n",
+ "plt.hlines(lhflx,time_artificial[0],time_artificial[-1],'b') #lhflx\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"F [W/m²]\")\n",
+ "plt.legend([\"rsds\", \"rlds\", \"shflx\", \"lhflx\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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FNm60f2bPjzNn3LnxwAOcr/Fxx3bfo+3HK0A9F4aNv6ODZ1yxqDs7eV9gY9ra+IWE+pPG8JnC2Gx27uQZVxxmnZ3pAHUK9haNO5Yu5X0BkN+5w+s1cQ28fDl/sOFdwH4w4w8Qh+CBOdwAgsGkMAARaxsHOJNxj4MRASlziICF9xPaWF8Ye4YlxdoG0GHmKwIh7BFMbV/8LuY8MycQGKH7H1PZyd/vRThwjvMihS8RC863brV/TnXTI+JutrQ2OVlc41qbmnLjxX5G3xfLuC5fbs/HFL58Rv/73+d8Xbrk9q0UlXJwy8MGRg2yClDPhQGsrlzJJ/89+qg9cFMAxJRgE+Wrrl/nGVdsEMuW8UAfvnbt4jOrcSW5YAHPuOJz+bVJtfb6687n9DS3keEA7+iwc4Jhb+Hr4Yftk6n+AqCTAoiBQVm+nPcFRj9FuTusR4BzhnEFQAGoY26N8JkQGDEHOOY7gBgD6gBc8X0yjCuCBoAmv0FFWQsDSWYPgy+QH37lg7KGtQx5HhOUomkKGtcwvqan7frGd4CzRGtZ5uYZC4KzzLVDxz6mtdZWF1yxIHhiwq1t1tepU26vYX35QQPLnENS1NzMy4AaZBWgngtbscKywA8+yG2IInYhdXTYQ4QFwc8/b58dHeky97u70/k6e5Yv+QVw0tfHM6441LApMqD60CH7xBUg8244sAE2GZACXzjcGH03mAqwHwzjihKRTzxhn8wcC1tMM4AawSO+RwZQ4zCDxpUJTH0tvAjX/Q8s3zPP2CcCS41hbWMfZMYLtyn4rAx4AiDEGkrhC8bUc8d4oSkVc35gLwQQY0Aw1gxuI5nxAtDH2DOgDvsC1tAPf6j3BQM4Z8+PlhaRxx6zf2Y7aA4OurnByiGmp50WniWwpqfdXpgCULe22j0sRUfbBlgFqOfCenstqOjq4ifG0aN20j7+OA/OsSA7OnjGFb46O9P5amnhwfnevfZpjKt8oDUcIgB1jMYVyS4AdcwVMw4kMGIMeML8hC/mvXBwwyfDuIbAgvke0dAIhy6zJnGYYbwYcB76SlEqCnODAXXQMaKMFTNeqI4D/ScDLAC8MF4MQw1wCV9MUOrnuYhw1TQAdMCOMusxZM4ZxhWfEbcDDAjGWOO9GKCPNYSzMQU4f/pp+2QbXY2NufkOrb7WRkacvIzFFL6uPgU4b2215y37Xp2dtsDByEi+Uto9ZBWgngu7fdtO2EOHOJ2fiEu4WL6cT0ocH7cTv7c3XR1RMGIM4Onttdc8AJuM7ABADK3RGZDyyiv2CSaF2TDwmZ580j7ZEmkiLsmUAXV4D/hixgvMNL5Hhu1+6y37xGdl2Ft8b3v22Cejs4QvjBcDxEJGn/GFK1Jc7zMMIlhIAB3crmgMgBDX6IzkCWAJIIVhEOEL3yMD6vD9PfII78snF0S4cmuo/IKAm9m/MJ+wdphbC/jC2DOgDp8JDVmYz4j5hM/GNKeCRObAARuEpCgD195u18/u3ZwfAGpj+KZsKX11dIjs2GH/XDHUlf3YXnnFHkop6vFOTNjJeuNGGh2WMZbFZbW38JUiaWzlSusHvhhW5t137binuN7HBotSfEzZKWw2mzbZJxMcAWSiXCGzkYG1AoPCAGoA6BRSFIA6PJlSUSEIZjZr/O62bfYJoKgxfH/IuGfGC3MVn5E5wMEqA4gxpADAEoA0ExjB15Yt9ongQWMgFMDCM3srfCGoYQAiGnkBDDO+8LvYC3FTozHs7whmIIdjfIFVZtYjxv7RR3lfWDOY9ynySZqb7dpkpCg4K9ra7DpK0fW1rc3KNVkpSnu7yOc+Z89cFlCPjtpAEmN2D1oFqOfCJibsBGNLwIm4Yvpnz1oAzFT6AAjGezELc+9eG8lDDsEwrgMD9tooxXXi+fN2nFL4wgYB7ToDUrBBwCcj04AMAleTfpe2sob3ScHCo5QWxj4FcE3BYuFgBGBFYqHGUJYO3wHTGAFABxp95tbowAH7xPfJgAGMNcY+hS/sW3hPjYWSD+bQRTUU7F9MZQ6AX3x/DLDwKwuxvkJZC0MIwBcCIyb4Q7L4k09aAIVbO41hfLDnMGcaCIHz5+13ycwvjE9HB99kzJfbjI3luyeXNazDvj4bFDHzPsvsGHV3W4zCViG7dUvkzTfT+GqQVYB6LgwgGIucBcG+LwZYrFplD0lcpzOgbnzcbhZg6JjPuG+fPUjAkjK+IGuBFpEB1KGsJUVtzHPn7JM53JYssXMCBxOz8R88aJ+7dtknKmFoLJSiMGMPX2BQUshtsIaYee83NBLhGFcAMTCuSMTUGMAAAA8DgjHWGPuUvhiACAYYwQzDuGLNgGllbhpOnrRPAB/m5m8uZC1ggpmxR/4BGH1GioLxWbLE7tPMZ0SFkHfesfs0o1X2SxamBMHGcGcafHV02O+Urb8uYgsmtLVxa3t83ILqS5fsHvbgg3pffv315ma+AEODrALUc2GTk/ki+AywmJrK+2KkFcuWWWYGTArzXkeO2IWOg5yRViBogAaRKTUIFj5FAJISnD/yiD3YUmRXX7tmGX3III4c0fsCqEOTBSSkaQwHNg5dsLmML2g2mfGCzAasJOML74V1yCQuhYAwReUXyEeYslMpQTDmE+YX4wt7III+zF2N7d9vnwiImCDLL/sp4uQHGgt19cx4hZIPBiAiSH7oId4XJEQDA/asZG6MADZbW+3+ynT+80uIsiDY99XUxI0X5v0zz/DsLQB0W5sF5vv26X3hNuXKFTvHUuQFtbfb4Ja5dW2gVYB6LgwgOIXGdedOG/kBIDKAemjIvlcKX5cu2YMETCvT3CWUyDDAAm17cagxGrF16+zBBhDMgPOxMTvuKXy98UZ+jJjr17AUE9OoBO+EQ5cBdWFVCGa8cOUNFpJhZVADHN8j4wu/C3aGkUPAFxg6piIQADVYeEaKgmQxMPvMeGGvwT7B7KvIFcBeiO9VY34ZS1YqAHA+b17+DNEYrvNx+8S8ly+tYD8jbumuXLF+mNs6v1xkc3Oa8oednfYWhAmMfF09C4IBxhcs4H0hWX//fp4J9pnzmzc55tyXyGzcyCW9NtAqQD0XtnixZelwBdJEDHMIxBgQ/PbbNsEuhb4YspYU7C18ge1j6lkaY8EY2zFLxH6Pixa5xc0wrm+/bccohXwEzHmKLlzwBaaOGXscuikCowcftKwT5BBgXjUGRixF4w3USU/BnIf1eJka7GEpRYa9RRMWdGZDgKQxzIkUEoaQyWQAdUoW3k+8NMZJ6jSGNb1smWX9GAkWQN3ChXZ/ZRhEMPrHj/NyCOxXXV3pfHV22j3stdd4X+j7wMxVSK8eeMAG8sz3iLXc32/PoJTMeSopyvXrIhcv8r7a2+2+zwTeDbQKUM+FLVxoAQCAK7NZnzljFxISNxjmCcx5ChCc0hckMgCsTNCwc6fVouI6iqlQcOOG3fABLJi2zlev2g0aByYDxMIKKyl8pShZuHmz1XWD5X7zTb2v8XG7fgBcmeQ/ABxcIzLJwiFATFHiEQEb4wvjgycD6jAXMPYMsHj1VfsEqQD5jcZCXX0KiUyKPAS/C+r0NBfMgJHessXuh0zFI9TDHhmxcwxlIzWGPRkMNQOC/QCEBXU+OGd9gdF//HHLuDKVhXwJQ29vGkB97RrPKoeMPuPLB+ctLWl0z5s320pdjIyxgdbS6Bf4VNrt23Zx4wr39GmnKy1r16/bzQtAmpm0U1MWTKABRwvx9U9O2t9PIWFYudJ1hBThNa7t7U6CcuaM3tc779irqBSMK2QtuPresIH3lQIEt7RYRgC+mLHv6bFsKwIjpgTfG2/Y7xLzHVeVGsP3hgMTJe8YX2CVmWA5JXuLzwTJR4oreYBzJjDy25g3NTltsMYwz7u7LahjboxCQM0ARIz9xo082PSlFUNDrnKOxlANAnsYMyd8ELx4sTtDGF8pQDCY4N5e3hf2mp4eO2bMeCE/4vBh+14M4eQHDY88ws0vX9bS0sLt976v5mYuGRdYZNu2NA3eGmQVQz0Xdvq0jbJSJCVOT9sJhuQ/hnGdmrK+HnjA/p0V/re1pWFJe3rsBg1Qx4DzDz5wSRLse0GKAlDOAAv4Anhig5mmJqcJZtjbHTuszi9FdQgw0wApjK+PP7bzFd8fk/wHWQtujFiNvohLQGMqc2zbZtdQKnDe3JymogMaueB7ZCqZ+FKUlhYu18KXyMyf77TBGsOYL1rEg2Cs5Z4e3teLL9rnjRs8QPSDhsFBbg35LPzy5VxVFOzv3d127BgpCpjfLVv48UK/gYEBnr31g4Zjxywe0JoPqDs60slt1qzhAlwkgH72szwI9ut2V4C6spyhe1AKjStae+JQY3RKAOcpGNe+PlvDFV2bUMpKY4OD9t1SgPMbN+ziTAWoweCKcAkvkLUAFDDtidets5shWG5GXwxGPwXb/e67FginAOdg4VP4AqDGQQQZgsY6O+18wHsBdGp9dXU5X7ih0dgrr+RbCqdIQANQTOGru9v6YRIv/ZrpLOMK6cnSpU6ipzWUbhPhKzoAWKTQF/uAemQkTTCD+c7cPqEb3n33WXIHkjrmvdrbeRAMQD08nBZQp/LV2WnlH7hB0hj2mvXrrbyCkZD6ZWVZEIzcncOH7f5aAerKfmwAwSkkDPCVIpmtp8cuInRCQ6KJxqBxRRIUYydPinz4odMoM+2JwcKnANTQiaeSVnR2ugPzww/1vrq7LTOTAjy9+65lliFJYrrPhSCYYUnhCwd4Cl9YQwwYuP9+q0dFkMVIUfC7qL2KmyONDQ7mmb4ULDwshYShpYUHiABe3d2WpEANdY3hM7a3W1DBMHXYT5ua7Lxgbp98Fj5VibQUvjA+S5faag5MO3rM0xSB0Usv2efFi1bSxWiVfRae1QT7EpmUvj7+mNPV43vcvNnOCeZ8RABy7ZrIZz7D5RjhPbq6+FuLBloFqOfCQoaabQjS0ZHGV1ubZWZS6J4vXbJSCLC2WFwaA3MO1ogpzg9fGC8GBAOcp5AwbNhgr6hTAH3o6jH2OFQ0NjBgPxeuwJmEPUhREGQx7C184b2YQ3fzZjunUgB9MPrQ777zjt7X4cPuO2xr494LLLyInWOMFMX3xZZI6+lxY8UC6tZWO05ggSGD09jzz9snmDWmworPnG/a5BhYxleKhD2fVWZZUuQfrFzJ+4K2e2LCniMnTuh9+UBs3TqO4PFZZaYev+8LgJphXEFyPPww7wv7TUuL1XkzbDcIgVu37JilKBeJkoUpukw3wCpAPVfW2uo2IYACjXV3izz7bBo5xJ07diNMwbjevm1ZMdSP9K89yxpY+BSMKwA16t8yh9uyZbaEWIrxAqOfgnE9ccIGMwiMGCkKWHhUYWCSOBGAgAVhQF17uz2MMPbMnOjqslpZHJKMr/3785riFImq8MOU/EK1FhE7bkww4/tqa+OkKFu2uGtlFiCeOePGiwXnuClqarJSCIZxxVru6OAZV/jq6bHnB9MaGo2yli7lQbCfLMkyrgDQWWbPD4Zx9WUt09NchShfnvTUU1wNcGjMV67kQTDWDIA+w94iD+jsWd6XXzP9/Hnu5s/Xdm/fziUcN9AqQJ3aMEHvv98xrkxNZDBiKbSkAwM2MSUFSwoWPgXYhC9o/F54Qe8LMgEEMUxTirY2e6AheZPRm50+bf9JAainpuxmmMqXrxM/elTvK+wQyrzXxo0u47u5mQuMLl/OvwsDeG7dcgccC+p8QD09zR1Ivi+0A9ba9u2ulF9vLycDwv4lwuuL33/ffY9sPV5/DqQCm01Ndq4xJb+QtNzRYZO+mMAI1tnp6g5r7Qc/sM/p6XTjNX8+DzZ9WcvRo9xNqQ/O2TrUkD/09rpyolqDpOj2bV4O4X9GFlD7EpmrV9N19Wxu5nw10CpAndqwyW/d6rR0WmnF9LSdWKdPO30lo7MUSQ+CU1yjZ1leJ86818KFIk8/7b6Hkyf1voaG7OeCLo8pdXf7tv0nxXiBhU9RQzfUnDO+enstK40gBhULNOYDMb+xkcZOnHAAs6WFuzFC0ABjACJkLSI82OzuzieMMe2cW1vzEiBmTrzyimMge3u55D9fitLUxIG60FcqcH7nDhcY9fW5fXBiwtZD1tqxY6684O7d3P7lM+epQHBKXxZ7zGwAACAASURBVPPn88lsqNO9dq3ViTNJnGDK29osoGYkDLg1RNnbTwqg9mUtrEQDVZPWr7e3gJOT92RiYgWoUxsm2fS0a6mqvcqFr4EBB3i0hwgmZ3u7A4hMW26RPKBmQHBrqw0UUjCuAGLYKKDX09i1azb7OEW5NQQNkEMwJb8gkUkBgltbXUvbFL78xBTm+vWDD5yMyBiuKgqqtYjYOc9IUXxAzYJg35cxHKjr63NglQWI58659XzlCtck5s4dtxaXLOESjn0WvquLO8R9Xyzj+vDD7hYyBXuL/ebkSY4QOHbMjT3LuPrJpVu2cGeHL61gATXOsgULePYWa6az0waBTI4RbllHRuznS9VR9Ytf5Mqk+oCaBcGYT74v7XeJ+dTb63yxuWcNsApQp7aPP7bPQ4d4Jhi6orY2txC0raHx+21trn6kttkMFk13dxpAnWUWEKTwdeuWraCRApyLWJAIJuu55/R+AKj962/GV0uL9WEMV6Fg2TKRRx91f2cO3YEBB6JTlPzCdzcywklRcE0twif/+b5WrLDSLq1t3Oh+nwXnExPuIGJ9nTzpEv7Gx12ehMZ8Fn5sjKtp7fvasYNjuxcvdvsNC4Kbmx3IYQHi88+78WabZUxOur3r1CkuAc2fT+vWuX2M8YXmVIwsDzpn6ItTlG5rbubZW+yj8+bZ5D8mz8X3lUqjP2+evUUX0c99MPpbtri9R0uiYM43NTlfzJg1yKpOiakNwNW/RtcCRPxea6uLnrVJY4j2fL2sNmrGAnzmGQfOtW1tp6ftBnvnTho5xNSUXYgpADWAK+QGbNDQ3GwPj6YmLrN9/nxXQqyri2vnPDHh2Fu2osPly+mSxqan0/oCCL5+nUv+6+x0c6unh5Oi+JWA5s3j2NtDhxwAYOUQ09MO5LBgc2rK+Tp/ngM8vq+2Nu7A7etzcor77uMqhpw+7fZSdrz8ec4m//m3FMPDXD8E39f4OHf79NhjrpPgZz7DBVkjI45YYOUQOFtbW/kqH/gekajKGPbkjg471yYn87duZQwdLhcscIA6lLHVa/iMfm+L4WFdpZXXX7fP69ddsMbM1wZZxVCnNp8JZhlXgGD/ep9lXHfscO+D0lFlDQvJr7WtPSixWRw+7BYiU0tUJA+CGYAIXwB2DKjz2y5PT4scP875QiDDMhb9/S6JavFikYce0vtCACLCg+DQFyNhQDAjYsee2ahXr3Z5DKOjXKOlq1dtpRwRGxSxDXoAvtiEPVR+SeUrlbRixw4XPJ46xcm5JiYcaFq5kmNcT592DBsS7bTmBw0sS+oz1CxzvmKF21OPHOECEL8BEbt/vfii+1zbtnFAOAYQWV++NEn7ObFmurpcPoI2oMG5sWCBGzctsYbOm2NjVooiol9HfpMY+GCCtgZZBahTG8BqCkDta5TY9sTYWNev59lbJN18+KHbwFgpCuQQxujLFWG8WlvTaILhK/Sv9fPEE/bPLBM8MuLYuaEhfWAkYjf+sKGB1nwQ3N3NVUXxWWVWE7xihQsUWF8+ELt2jbtpuHjR5VmwGlcfuN53H5eA5t8OsCB4wQKnj2RBXXNzviY8o7F8/XXHSI6McImEPgh+/HGXYKUxX9aSotxaKnC+bp0jBFgm+MMPHeA8cYK7afCD9o0b05SnE3Fnt5YUwO+1tTmAqJ2vODfmz3dBDSutaGlxpSK1NdhBJhjDE1g+ow/mnDmLGmQVoE5tPqDGQaJtVIJybU8/zcshsJhHRvjqEGD4hobcpNfWofYlMsbYjV8bMfvgXMSOma8PLmPYmAHEWMbVv6JLoS9GKSURPlkS7zU6ytWh9png3l4O1LW1uUQvFgQ3N7u1mKI9MZgZ9r184HrypO1ayfjC2C9ZwjF1vq9FizhZy5o1jnlnAeKFCw74pqrtK2Jvi65c0fvygxmWcfXB+YMPcuXW9uxxV/wsCB4ddXOClUOcPevOsaGhdEHD+LgdP+2a9H/v2WftU7tXrF3r5gTLuOK9/JKk2lu2V191f2alFTjDOjudPv/yZd7Xli3597uHrALUqQ1M8n33OYYO1yxlzZdWsKwyJvqRI/wVlB80sEywL5GBHy3jirHBuHd06A8RbGIIhrq6XLH+sjY9bf0BiLESBhF3qLEJaCIOUA8OclUFfF8ssJg/3zWm2LqVq8wxOOj0sikYav+AY8C5H8xMTvJ14QF4bt3iOv9t2GDBnIgNKJmWwj6jz4Lg8+ddKTO2ooMPgtlkNt/X++9zY790qSNSAIa1lmUuGOrp4ZL/Xn3VjT0rh/BBMHsW+WsZ+ysDXFO91+rVbuy3bdP5gL33nn0vY3gQjPHq6EgHqLu63P6KogxlzZd8wCoNtTNjzFpjzAvGmA+MMUeNMb858/M/MMZcNMYcmvnn73q/818bY04aY44ZY35mrt5tTg0TYt26PFDRGKK+kyfdAsf1T1nDYd3ens+6Z3z5G2sqQM3IIXBwP/mke6cPP+TeC9eRS5bou5YhAIFPhqHGwZ9KXyzixo311d5u692KWCb3jTf0vnwgNn8+VxVlYMDdoCxezLF+PnBlAbXPBLMVHbq6nNTgo484bbcxLp+htZXL2zh82NXEfughrtyaP14sOPdBMAvO/ZuGO3e4ALe311VfGh7mgqxTp9wV/9NP6/2IFOUjIpwmOPSlBcExX9qqNE884W7FkOOiDY5u3XJzFTd12oDmwgU3P3FTrZWP+BVWWObcZ5VZXxij+fNdTg9T2alBNpcM9aSI/E6WZdtE5HER+ZIxBi23/jjLsodn/vmeiMjMv/tlEdkhIj8rIv+HMebe6z+JxTw+7haUf81SxhD13b5tF0Brq/4AD4Fra6ueAfEZahEOiCEAQdUKY/SfEe+AjfXOHX39Yl8nLmIPXe0Bgs0P49XXZ2vXaszXiYvwFR1EHPPe1MSBlCxzCaVZxgGLwUGRd96xfx4Y0F8l4l0wXlu36stFwheCGRYEh+Cc8bV4sUuWZH1dv+6Szg4ftge61nwgtmwZ11LYB66LF3MayxCcM4B6+3Y39qzuc3zc+Xj/fW4N+RIZaKi188IPQHB7wezTIQjW5hmtXu1uJNkOrZOTzgfOcS1A3LfP/S72bJZVFrFVUURcJ9Oy5s8ndrz8PAuW0ce54YNz9ua1ATZngDrLsstZlr098+dbIvKBiNztJPsFEflGlmVjWZadEZGTIrJ3rt5vzgyZ58ePuwmnBZuY6H7RdG3UFgKxri49oMam7JfH0W6uONR8nbl2vKCDRITLgHNs8DjcLlywmyTjC2PPtAEOdeKLFulb22NsoDNP0X0OV34sOJ+ednP28mUO1PnAtaWFrxiCOfHgg/oEWhELCvfObHHNzRyo88sfsr6uXXPJkuPjfLUWzPWbN7nMfR8E79nDlRlcuNCBEhYEZ1m+DjVjBw/mg3iRNCAYeyLTtRcgGAFpivfCGaKdY6tWuf0Pe6IWIL7/vpufLND3mXPc0Gj3MN+XLxHTmP970Cpr+xg8+mi+m62IfuxRvQTEIeOrgfYT0VAbY/pEZJeIvDnzo98wxrxnjPlzY8yMYEx6ReS892sX5O4A/JNpmAS+oF47+bGY4Wtqyh10rK/mZv3miqvlxx6zz5UrbXa7xiCHQfTOgDqwCvisDKCOSVFYX9goBgfttTxjkFasW6cPjHyNvggHgicnLbCABpsF1P57sQBRxB1Ehw/rK9LAD4DYwoUc45pl7jBbtoxL/rtwwYIxvCMzXiELz8ohMEZsRQffl1+bX2NLl9qW0CJWq88k2l244KQBbMJeqO0W4aQV8IX9lQGIoS/t+bF7t8uJeOop+0RZ2LI2PFzUPWtlMhcvFm8TGbYb78WCzYkJ5wtJ49qb1w0b3FiDDNBK4HxZHgJK7Zr05YGpSt42wOYcUBtjukXkWyLyW1mWDYnIvxSRTSLysIhcFpH/Ff9p5NcLO7kx5teMMQeNMQevMckfc2XYsPzDMRWgZkAdrvWRIDEwoJeihECMkaJgY0D5sQUL9Emc4Xgx4DwE1Iwv/B6YlBs39IERQKrPrmk3HlwHQ1qxc6c++c+vmS7CAWr8XgpfMPhCgijjB23jr1/XJ+GIWDCAphY7d7pkNI3545MSBH+SwPnatS6If+cdju32pRXLl3M3M/397nvEd8jkSPjabhGOVQ7BOUOiYM9BhSGwimXNl1bgM2rH68ABt5dun1GUam8uYsGMFpzHZC1MyVu8F0gj7dgvW+YKJ2DMtZrzQ4fc2YNbTrDeZc3fkzE3mEZqDbI5BdTGmFaxYPrfZVn2bRGRLMv6syybyrJsWkT+lThZxwUR8bO+1ojIpdBnlmVfzbJsT5Zle5Yx9T7nyjDBUuiLsYgQQabQKiNjn/EF8IvnrVv6JgvheC1fri8ziA3LT7LTHpSh3MYYPajDBu9LK7S+wPBBX3/0qOs6VtZwWGBjnTdPnzgTSmRWrNB1zIr5YjTBAHAAYqy+2JdWnDvHAerRUXdTwTKuIu69Hn2UqwHu+2IBdWenW88sezs97di18XHuvU6ccIz+wID1rd0rfFkLbuqYYDIsT6cFFjFfWlC3fLm7CWPf6+RJF4BA3qJNovWDBr9EoMZ8aQX2LkbWkoqh9ssfsr5u3nTrBue3X4K1jPX3F8m1FFKU9evtk6ku1CCbyyofRkT+TEQ+yLLsj7yf+/TjL4nIjLhLvisiv2yMaTfGbBCRLSKyf67eb84slHzMm6fXWaIrGBLYGBCMiDaFHAJgzk+20G6IsQRHLYsSssrbtumT/3AV7zcESZUsyfjCrQyqVjC+Qlb56lWRS4UYtj4Lx37rVn2ZQcwrbKgMs4mx8etQa30h0XL/ft4XDMD14EGuFrLPBC9alI5VZhMJ581zzCGrL75xwyWnsvpiH2yCDNCykSGjL8Ix1PCFmxDt+N93nwVjIjwI9vdk1tfVq+52DH61UiAfuMKXtqqWz1Ajt0FL7qxZ4xLt2PHypRUsoD540JEA8MWULMTY49zQVtXyfeGGmrmxa5DNZSuap0TkV0TksDFmpiWP/DMR+U+MMQ+LlXN8JCL/mYhIlmVHjTF/KSLvi60Q8qUsy8jyBQ0wgGeUgVmwQB9pxTSuWoNuFNdjKdjbFFKUUKZx5oy+rS0OHoCn9nb9getfB4vY71A7/qdP2ycSg5hayCFwZUBd6OvKFX3HuBCcM4wrNlbUod6717GJ2vdCIMIwruHBkwJQ+1IUVtaCOXvtGlduravLaVt37xZ56SW9r/HxfB1qkTyrWMaGhtzB7TOufu3aes0PGnzAo9GT+r7QnOfGDZ2vBQtceU7/NlFjk5NuXwU40c6xo0edjJG9kveDBlarPDWV1+iL2Fsf5JiUMWOKc0K7hy1d6tYgOv/hLClrR486EJxivMKGMynKH+Kz4uahrPmAGnuqNjBqoM1llY9XsywzWZY96JfIy7LsV7Is2znz8/8oy7LL3u/8D1mWbcqy7L4sy/52rt5tTg1XRb4cRTsxUKgeh8j69Y5xKGshCGaYTSzAT5ovsAlgdq5e1Xf+wwYG5mTdOn1LYWg9/YYg2oMtlLUw8pFQ1sIARMhaIK04cEDfJCZk9Lu79e+Fscc8WLVKn/wXJpcy4Dz8jKy0whgHxE6f5jLkp6edzrKlhavyceOGyGuv2T9jbjDSilDCoA0cYoBaezPmvxfGXetrwQJ3M4ngVqtxvXTJVZYA46qVYcVAcIoExxSyllS+HnjAlQQECaKVMvodIMG4arXd1665+cTU0BeJS1G04zU5WQTn2n1n0yZHhOG2+623dL4aaPdes/RPuoEJwyHU32/BhcbA1OIAYli/EFAvXaq/zoolS2pBHbRh999vnwxAxJjjoLxxQ+8rzKY2Rr/xhLKWPXv01/sxhlr7GbEZgjlh9cUijglratIDRFzrg5W+fFnPnIcg+IEH9NeSONRS6ItjvrSWZfafVLWQx8bcoXbggPU9Oan3G94cTU3p9NShFEVED/bDUooinL4Y9YFZsOn/HhjX/n5XkaSMDQy4PZott+YDavQM0DbpiYFzpn4xbihYX35+BL4H7b5z+LB7D8wrSCXLWqwGuDZ53AfBGC/tGmptLUpRtL4WLXLBXlWHurIf26EZdYvf6lgLUrAgwahdv64v+RX6WrlSfwWFhYjEJ4bZxPukaC4CRt/XF2t9hUEDU24t9NXRke691qzRs07QiUNnznyP0OiD2Wd8hQ0QLlzQayzDAIRhXMPA6IkndHIDEccSoYMdA4LDGvO+jKSsQXoCZhPBPJNxj/cBQaBlb0XcOOFKX5uA1t5uGyz5PhimDvsYm/x38aJj5tjrfR+4IvEMzGtZ8wMQnBvasTfGjRP2IK2czpfIsCzpqVNu3qeQQ2C8ILPUJv/FGH0mMIIvyFO1HYAfeMDdprCl7q5fd3sNfFWAurIfL2ZMCiaRMATBfpkt1tf0tB6kgC0Bq/zww44dK2tgagF8GBCMq1EAuRTSCl+KksrXxYv6zn+hrGXzZj2gDjX6DAjG5zl3jvcVY+G1Fvp6/XU96wTDrUpPD5+oiu8O36tmzDDvIa0IWbYyFkqKGDlEWP4QYI7RRoZ6bO2h29zs9i+Ac+2V/OCgu8liwbkPXFP4CsdJW2rQB+fwoS3dtn69yJNP2j8jmNfW0h8edmuJDUBu3nRrKYVOPGSCmcAIvnBeQqtf1taudQAaJJa2sYufLInqO1q9/+HD7rOxgVEDrQLUqQ0bF4BrSoaa8YVIEovp1CnH6JY1bGC+BlEbNOD6vb/fvZ9WqxwCVwbUpdQX431Qh9rPci9rGHOf2dGyAmDc0cnr6af1lTlC9hatjj8pvlIk9uJ7RPB4+bIe0AFUIj8C1WQ06xtBQyzJTusLPhhgEUqwWI2riMjnPmefqJ2urS7kf2/+7ZjGxsbc/oW9S+vLB8EsEEsJznt63BmCUo9attuXVrCM60cfue7BSP7TMq5++UOWofZBMMvetrTkm7uJ6Mt19vS4OYq9Ruvr/ffd+tu40T61VbV8Fr5iqCv7sWHR4CqYSbLDxEIiAuMLPnwgpgXn0ITjELlwQZ/8FzL669bpa+iGvlIAat8XqxNH+bAUTDAA2f79elABaQVYhc7OdNVa1q7V1x2OBTNaA1hCfWBGWhEy+ufOOX1xWQO7h++OYVxDEAz2TwPqamm7Ncl/+CyoeMQAasxL7Kv4u1Y+Mj4u8uZM495QrqQxjBMCI62+OAaomQAEPlhw3tHhvkfWV3+/Oy/w1JI7PnOOta7tuuj7ws2Rdg9LWclk0yZ3I8nqxAcG3O9ivmv7GAwMFPcLLQj2ATWIJ8y3e8gqQJ3aMKGw8a9Zo7/O2rHDPnEdzIBgADEc/owvsKtYAAMD+oSLMACZntZn7ocVQ55+2hWJL2uQtYD1YEBwWNGB8QVWCNdjTGJcyASfP6+XAYW3A9u368ErfCA7nmkIgrEJD0jN3Ic2HwElAxDDsUfrXc3NRcjCIyDVfMbwvXp77VNzlYuxR3dWBiBiT4C0gqlQEN6wwae2BrtIUSLDNOnBeyEBTZs8Pn++yOc/b//MMq6jo+4zgWTQAsTbt10Qg8BIW8nED0DwPlpZpA+CkfSnTf5btsydITjbtGDTl1awbPeJE24fw3ul0IkDWGvBuc/oY//S3pY20CpAndqgywMTvGKFnnENgVhbm/4qEQwADiCGcY2x8KlkLe+9p79KhAYSY88koOF94GvDBn3JIjQCARvDAOpwvBj2NvR1+bL+kIxpzrUbNTZSMPqf/ax9asYMgYdfh1okjRyC0ReHwBXrOgU4x2fWgHPMcYw5Kjpoki/x/acoawbdLm7FmOS/MABhGETse5hXkB/gWdaamlz7ZrDc2oByctL9LnxpEwlv3nQymxRSlLmQtWBuaJP/mprcPGcZ164uR6QhIIJkpqx99JE7E1k5hA9c2Woavi88tcGMz1AjeNf2o2igVYA6tYEJ86M/bfT9+uv2ic1m92632Za1lNru0FcKgJhC9wxGAKz0mTMOSJU1ZGYDLG3apK9fDGmFX6aLlaL45bBYhtofe63heg5X3q+9pmfpQu1teM1fxsA6AmRibmjeLQSuDDiv5UtzOwPQhM+GuatJGsO4hMBCM14Yc0grHn3UPjXMU0ptd9iEiAF1YRIn9lRNkJVl9vexj+HcAFAsayMjrhY8bgm0XXt9EMyy3SJur2F9xXTiTAk+yKVwbmgbSg0Pu7kJUkabPD487G4OQRppAyOfhU8BzsPvUbvnr13rAg6sIW254QZaBahTGw5wbD4nTogcP67zBRmFD56YayMRt4g2bdIn/8VYUi04BwuJKJ7xFWpcr18vlmCr15AsiUNtelrPooRBw7PP6jfXGKDWGpp3YB4w0gqwC/DJXH3jEAPLB4CoAZshcMV801io7WaAWPhejC8csrgdY9hbMExhcwVcE5exEAQzJdJCVnnFCvvUBLm1wLlmvBDMfvGL+ffR+MJaQeCIgER7Yzc97XSyKaUoAPxaxjXL0tUv7ux0wQILEH1pBVhSbfL45ctu/8L3qQ2M/KABMjjIgRhfrBSlrc3tPayvzk5XjhEa+CopsbIf16HG5sMwrphQmGBnzji9X1kDqIOvNWv0yRu4FsazvV1fLgcLEb4YxvXVV+0TgUiKNtN4v4MH9TrxMMGxtVW/WYTBzKZNehkQriRxMGLOaphglMtDsiR8pZBDIEjVlPyCr1Aioxn/kNFHDWlNuTVUInjiCftkOv/5Mi4Rjr0FMwdgjbmVIpjBFa6mqVFY/hCBkYYUwF6F2z4GUIdBPOMLLGRYh1rzPYa1yVGZg2H94AvNm5ga7PhdyCG1t39NTe5mhi23duOG64yYgjkPb52ADcqazwSzUpRY4iXyhMra6tWu5CQLqG/edOQX5j0T/DXIKkCd2sJJwEgrwvqag4P6OqJhsuT4uD5DHowANtann3aMUVkD+4gxYmQHWJBhrVqNhYx+Sl+nT3PtcUXySZPT07rAIVb+UET3btCHI+hgfIWMPuMrZJWR/KepAw72HYl6ANKa9Y3vC+sRV/GaWwLcpqTQuM4lC48x11SlCRlqhnHF72INQaaE0l9lDPMdDD4D6kLmnGFcQ18IIjTnR7hP4LtAE5Sy1tTkNPporqNN/hsfd5+VBXW+PJP15TPBLHPug3N8F5BRlbXFi10wCkIN53hZ87un4jNi/pe18+fzDdng/x6zClCntnDRpJAwYIIxbDeAGCb+4cP6rPaQlWGkKEeO2Cc+19aterYiZJVTMNQpADVYGFx5X7umnxPYpAHmwCZrNp9XXrFPHIzPPmufmtuGUIrCMK4pfYXgnGH9wIaC0Qcw1CTi4KYJvwu5BkB7GaslH0mh7f6kyFpwHYyqFUg801QVwDzCGsSYa4J5ADDo1aEP1yQwp0yWDGuTM9UhsLcAiOEWCoFcGcuyfOt5lnEdG3MJ9yB1QPhoLNQEM7KDcOyZJkShlE57W9rSkpdXiuhujETsuYFeBs3NFqdo61D7AQisknxUVgA2DAiePz9/nc+A83nz7GKCPwZsvvyy8yFideLaBR7KWjZs0IPXEFBro+WYLwZQA4CtXGmfDLsGPSUOWeiNNVrxUMLAJJaEshawfQw4hy8GIAIEgIVM0UUwrCqgqV8MMO7Lk0R0gCf8HvfutU9Ng4tac0IzXgj6MBeYpLHwto75HhHM4AoeoFjDuIZSFKx1TbnO0BcjO8Bcxb7K+ELQDjaZ8YXvC9IKaJTR5bOMhZ04ATq1HS99X/Ch9eXrxFm2u7vbScNYX3fuuFsKrCHcbJW1sbH8LTfT4M2XoojYvV97a9FAqwB1apuayoOIbdv0Vyrbt+eZDgYEnzuXfy8G6AO8AZzfvKnXrWEBYuMfG0vn6/Of10tIUEgfjBM2R42+OMboi+gkNydO2CcOM8ZXyMKHso0yFkqKoMvTSBgw5mGyJNPgIgyyNHMM16yonJCCOcfYg2nVlPwKAxCAAM36Dhl9JEFpGFfczISAWvM9QhqGZwoWHp8RAZEm8bJWtRZGphGCc00iLfZAdJZkWFJ8RswzBtTh7AhzLTT170OdOOa7JjDC74Y6cW0Sc0tLseSkFgT75Q/x1PoaGHCsMiyFFAV+tFKU0Fdnp74legOtAtSpbfv2PIBevVpf4sZv0SpiD0ptAtrRo/mFk0ITnNKXHy1rATXG3ZdpTE3pgEWYhY5oWbP5PP+8fYblulLqizVjFvpCQhpzuMEXxlzzGaFRxhN6S1z7lzGAXxzgKfXYDOOaUg4RvhdkJBpggXn+2GP2CZ2xJkcC4AlzgWE2MTchrWCu5ENpRQrGFb4w5hrGNQxGmRJp4b6K4EZTXQjJpO++a5/MeIV7IAP0wy59IDsOHy7vC/9/sNxMuUgRy7hi/8JnhOyyrA0Pu8+E81/b0TYEriL6zxj6mp7W31SHko/paX1N6wZaBahTW1dX/prozh198t++fXlw8+ST+nJrk5N5hpphu8MFmBKcM6XbkLWPDR/lCjUgBdIKLHKwbEz3uZAl1YC6UCKTApzjvRjW75FH7BNX3WBcwSiWMXxfYd1bzSGC6gZg//B+mqvcWlIUBgSn8IVWvTjAw7bmZQzzC+/DMGIAAWDEwNhpWL9aUhRG2w0fDKirtR41txZ4H0gr8Nk0lZ2QAIqAEnIzTR+DWlKUFMmSKQB1KK3QAETs66jcg31/377yvqamrD9IK5qarD9tY7Asy2OIpiZO1jJXgNoYva/58/P661u3XAB3D1kFqFPbpUv5yP3oUX3Udvt2HsAxGqUQUO/YwXXgCsG51nbtypdfYrSkuBrDu2HcNQENNH4YI7wP0+rYl6L4fy9jobQCh5zmAAfjC/aK0aVizP3SgNr3eukl+wQzBlCuYVxDaQUYV0330nDsUwRGKQA1vkdUCmECIwAwsENYB2gyVcbCsdeW6RQpJqpCFqS5Fq6VqKoZe+jUn3oq71OzfwGAYW5g7WiS/3AjA0KGkaKEpOWvNwAAIABJREFUtykYe+QllLGwEQ4jhwhbtDO+wq7E8K1pyobzxpdvGaPbv0KduIgF0zt2lPcF830Zo2e7m5pcB07WlzH5WzAGnDfQKkCd2j74IN+hjGWCfeB69Ki+bF44Odeu1b/XokX5a0hE3prF1NaW98Uwri+8kN9MGV9hhRUkMGkS0ELwxCQlhr7AOGkqo4AJA7hkWD8Ar5DhTCFFwXrStKINfcFSVAxB8p+mjisYfVT3SAHEYIyvsOZ3CmkF5gLACbT6ZSwE1ACymuQ/gAB092SAWK2unhpf0HADiDGMayhFAchDsKrxhe+RKZGGccFNK4IsTWCEsxE3M8y+in0dVadgGl9hhRX4CX3XYxh735eWWAM4930tXKivitLc7PZAEQ5Qj4zkiUfGVwOtAtSpze9JL8LVVQ4THIeH9VU+wve6fdsuSo2/zZvdNbOIyGc+4/4fZe3MmfzvpWgIAksBqFP6wvjj4NSUK9qzxz5x5QdQoDncQraIAdRhQlcKQJ1CihL6AljR6CzBoCBZkpGi4ECED5Sy0iQwIxEIEg/me5xLWQtAugZQh7c8zE0WwBxAOZh9TckvJAmjsVEKPXYIXDW+ask0NIFk6AtnGuRUZQzzGy2+8Rk1FR3AvuOswP6qCWYwN8NzJ0VyqYg9x1PIWkTs59bcGGENIZgXsetJI0XJsnxnSRE7x7TNfsbG8h2lm5oqQF2ZFIErowkOfeEQ0TDLO3a4Q1vERcuazTpcSAwzcPx4fhND4oYm+TJk9BnZQfhZGEC9bFk+sEKpKFzLlrGmJqfJ899TE4D86Ef2iTFDYKQptxZqSVN0n0tRmSMlOMf6wZU3EuU01SGgK8ZBDqZVk/wXAldGl5rSV8joMwARumtU34Ek5cUXy/vCusOBjbmhIT9wa4L1B7DuEw71Wkptd+iLYc7BHoPJxDkUVouox8KKR8bYcdecHbhN8SUx7e06KUoMBIvoQF0MBGt9Ya340oqpKV3iOMYYenoR+31omlzhvfzuj2vW6KuiiKSTojTQKkCd2qan0+mLe3ry0SOTINTenk9kYJjgffvy7CpYP41WPGThAeY09YtDQI2x02rqfF8MENu4MR+5M75OnMi/FwIjaF/LWK3avowGMaxDrbnKTakvRv1W6IyZyhwhEwYJgyb5D7pwjBu+U816xHgBPEFGomFcQ18M44oABM8UzUXCRFWNLzQCAVMOH2Cbyxh+F/MKDKym62Loi5F8wLAHMoAav4vvkamAAVbbZyOnpnSBUXjDJmLHTiN/q+VLk2sR86XVBGOeo+oOfDFAH4SOiD2zNaU6EYD4e7K2wVu4tkUsDkC+yz1kFaBObSGrjGhZswA2bnQ6VxE34TSM64UL+eYfbHUInyWvdV1Wj4WAGj40jUpCX0gU0lyj79mTZwVYyUeM0ddKK/y5lKJZBsYM19aocKLxhcMMgZEGUOPgBhhgGs5A0pSiWQY6S2KOMvriMGjA2GvquIa+8F4aORd+B77AtGpKFoLJByPGjBcOfdwKMHMiTJbEXqa5aajVUZV5L3w2zP/du8v7ghQMEjHmvQDAwr1P4wu3A+EZlqKMpYjdG7GWNL586dyiRTopCogrP6DVguAwWRK+mLFHvgvzXqFGX8QSC5rOpTGd+MKFXCWTBlkFqFPbli35JCWAA+1i8q8hAQw1YODMGXcYiXAAMQSuDEAMfR09ap/oQlfGli3LL0JGitLcnN+owfppGIsXXsizAgzjGs4jhu0OxwWBkSb5D74QTAKkaJJooWnF4QZQoMlsBxADUGTkIyGjz4DzlL7CRFCMuX9w1msYazCskKCsWVPeFxj8UFqhAdTYD8ISlMx4pSjdFjZYgv3wh+V94awAGA4rTpQxzC+cH01Ndp9FkFPGcPsV3oKlGi8tQAzLa4pYoK6pioIzyN/ftcl/eB8/CF25UleHGnIMv4RcU5MuWI6Nl1arHPM1MaHb72t9jz5euUesAtSprb09Xyu6VkRej73zTv4a8vHH7VOzwYZSFEZfPJe+mDJwGza4hDERN3aaOq6nT+ffAYBCc50YBg0A/ZpNMfTFAMTw/88A/aeeyrMVOHx9jV29BtAEcM5IUcBWwQcqAmi0yiEITiFhSCGtgP4aATdTvxiHK8YLgExz+3TggH0iQMOY+5UB6rVaY89cMYfSCo0vjA/WNMPCA8xhnIyx/2ikKACV/hzo6HDdF8tY2JEQlqJrLEwDXFOytxhz/zbg2jVdHWoEkn6OzLx5usTxmLRi3jzXgKaM1QpmGG23T/hpgT58PPqo+9n58zoZY4OtAtSprb8/ryUGS6RJQBsfz092hnGdns5LUcLanWV9xUCwBog9+KBjZFhfIaMftrktYx99lI+28T6auqThJgNA4ct56rVaDLVmvFatym/yDKibns5v1IwvlPbCHAMg0zBPGC+ME1ppayQM8BWCYM16DFsdM6AOkgoE8gzYRPUTzH0kP738cnlfIXgKu2hqfIVyCD/Bql4LASIz9rg1wQ0WI63AueGv5SzTAQuUmvRvrrSMawwEL1qUrxbB+GJBsJ8Ix0orwm59mps/5FT439vIiC7XIsbe9vVxgVHIUGsrh4nkCSwt2439wJdYNjdz79UgqwB1artwIV/AnWmWEYJgHHaacmshCAaw0GS2L1qU1yWDWdEsgJaWdAl7+/blGRlWWuGPF5Jo/GQarS+GcQ2/x/BqvoytX59PemXG68MP85spw5yHmzJYGmT1a3yFFXI0gVHIKqMGOGQSZQzJkjhEmAAEnwV7BcOc44o51FJr5moYgGDsNdUhQjYS1WQ0dagRwGMPZIiKcH7BmGAmBF4Me+vL1m7dEnn++fK+QkmRiP1ONWcHxslnWLu6dFVRcG74oE4LzgF+/bmp9RULGq5d0wVGMV/a5L8YoN68WZf8hxsZVN0R0YPzmNSQBfoNsgpQp7Ysi5fNSwGo4UOjUwp9wYeGvV27Nn+QgXH1N7Z67dy5PKOfEgQzvkLgygJE3xcCLg3jundvnpUDKNAk/42MxKUoGjt3Lr/Jp7iSh6XogAZDuTVN8l/YiZABYiEjBmANSUoZQ01azE2mOkQYNKRoehJWkdHUL8Y44X0YogJjjacx1h8kdWUM2tYw5yMVENOCuphMQ1sLOWxeI2LHXVNPHMEMbkhF7G2RpioKmrH4JeS0QAw+/CBU66sWE5xKq3zqlJWDljWQYL6sZeFCnRQlVplDm0iI899PCq4Y6spEpAioGca1li8NqNuyJZ8UAV2eph3q1FSenWAY1/Pn85Epap1qwHlKKUpKQL1yZT7ZBYyrJvlPJH9IYmPTlCzcty/f1RPX15rkv5R67NAXw96GxgDE3l5XB1zE6Yo1TWLwO/CFgAgBUhkLmeAUrPJcaJUZfTHkBQg4sDZfeKG8L6wVH6i2tuqkKAB1vq+2Np0UJcYqh77L+kqhVYY0zQe9w8O6akCYX+H5wXSW9G8l+/p0yX+1ghlGX+z70gJqzAWfwZ+a0uEJnNP+7fLgoK4AAHJT/Koe27bpCIG5kKI0yCpAndpCJpipgDF/fj4rm0n+a2nJR48M4Hn7bVeNQ8TJIDTJM+F4QbqQQtsNTammSUwttlsD6tauzWt2GYB48mSekUE9Yz8LvF6rJUXRHuC+L1QsAKvLvBczXk88kZ/3bItvHwgAgGm0kZCv+FUYRLiGDfhsAOcoG1nGQq0yALVmTgCAIZhk5lctaYXGF0CAL/uZmtJVRQnHXsTu2xopSkxaoQV1OCt8SZfWF3z4oE7LnCOQ9G8pzp0Tee218r7Cut0iVj6iSdqPgeCFC3VVnWLgXAsQcW74jL7WF8gTn0S5cMGdIWUMgN5/j5aWdNVadu7UkQsNtgpQp7Ysyx+6qEWpWZgrVuRL8DEg+MoVd93t+9JKUXzDZuSXhqvXsiwPnhAsgPkp+16xGuB+0mO9tmtXfuwZhnp0NB3bff58HnQB8KRg4bHRasB5OCdw+Gq0kevWOY2sSP7PZS28TWHKre3bl2fSGLYbwAbjj7+/+qreF9Y0npr3ChunwJembB7AQHgNrDl0ccUdVhtJJa2YmNBJUWppXJkylr6vVat0dahxy+Qnr2lZUpQv84kcrS9IDMPvjZGi+OM1NKQDiDFfGzfqusZirfg3fVoQHGP0tb4Q+PuMfkpZy5EjOlItJilasoRritcgqwB1alu9Or8BgmHWtCCfnMxPKmj+NL76+/MtRtnEuFhL9BTVR3CoaRbmkiV5qQg2IW3msc864dpTwzwdOJC/Hk1ZrYVNqPIBNeaCRooSgnOMuSbIWrUqn7QEttsvq1SvHTmSDzYAEDVzIjx4UmioU7xXqGfEvPdvkeo1jHHYVVUDqBGghTdEDKgLO6gy45WizXSMob52zTUBKmNIDvOZubY23Q1bTOPa06OrboN55BMyxuiAWC0WPpWvq1d1jV3w/flyiOZm3ZyI+dqxQ5f8h7H3uxk2NXGVckLmPJWviQkdnoh1lvz4Y11+V4OtAtSprakpf80GvZ5/zVKvnTwp8tZb7u+49tFchdRKltQsgJS+agFEja9Vq/KMAiJxjcb17Nl8YXkwrZqbhrB7JhhXTWBUSyeuBeepfD3+eF7egc3w4MHyvsIumUxgdPlyno0GUNckQYWyFhycmvcKf4fxtWlTfn7hHTVSlFqMmKZzKepQ+wd2d7fI00+X9xUDrlogltJXKI1hfEGq4/cxGBrSdXCErMXfw1as0EmwYgEIC4JTyCFS+sJ+4HdGPHpUd1uHwMMHhN3dOsYVNzL+Z1q6NI8x6rVaWmUNoK7VJEbjC/kGfrWkU6d0t9QNtnuPU/+k282beZE/GFdN8l+4MTBMcAiCkfynYZ5CEMzoi7duzUfyzHX12Fj+YMM4aSLdy5fz44/PloK9BVOhSZ6pBYI147V6dTGZSusrvE1hajS/8UYeCGDz1jSJqdVUR8PUhesRcy1kTeux5uZ4cyTNeC1fXmRbRXTgHEDMf7fxcV2Dixhw1dZCjvnq6tIlQYUSGRG9vhiyMj8JUesLQMz/3Vu3dBKGWJJyc3OaTpwiFnhqui6mDGawj/qyFmN0oC7G6GeZbq4iAPJvhD/+WNf5LxY03H8/J63wfTU368YLcjd/H9X6ApbwA0lNScZPgFUMdWobHMxfOaVkglEj07/+qddCEAz5iCb5b8GCPEsO1lZTfkckD4IZKcqRI3k2mh17H1QgSDpypLyvcOwZxjUE1Eji1FwnrlyZl8gwDPWxY/lbGFbWEgOpmmz0EFDjzxopSshQY95qyq3t3ZsvdYj5oZkTtT4LI61I4SuWSDg6ytWh9veYnh4dIYDciLDbHPMZfQCgBYhgQ/3bAJaF90HwyZO6cpExX+3tOikKbud8hnXp0nxTj3oNwbEPxLQMNQJJvxQgK4fwx+vCBd3+VQsEp6o+smuXriINzh0QcyL68cKe4+89WnDeYKsA9VxYTMKgYQbCBEdsFJo2wKEv1KHWRM2LFrmmFiKuS5gG1F2+nI/kGWazFnPeaF9hYATg6Zccqtd27bIZ0DAEM5oD6fbt/KaF4EojRblyJV8fHWBTC1JiwDVFAII/799f3tfGjcXDW/teIaMvYtenJoH2wIF4EhyjCfaN7T7nz/2xMZ0UBXMgZJU1e2GMTFi/XhcYYR75+zsrh0jB3tbSKqfoUilib+o0zDnOCj8Xpa/P5UmUMVTKCZMlNZ8Re5e/V6SWomjeK1bJ5O23dSULIWsJzw8NGxwLlpcv15Fq2A/8xl3a8Wqw3VXyYYz57Tp83M6y7E8Tvc+9byFwZRjXEIjBlwacr1yZPzAwibVXR/7Gg8+rAZs3buR9xWqe1mtzqe1m5BDLluXnBDYjja4+BGLwpQmMDh3KH0ZgqzUthUNGnx37VNrupqb82DO+li3LA2pj7D8aKcp77xUbNGnrF4cBCN5NY7UARAqd+Gz/j7vZrl0i3/tefu5fvWrlQWUN0opwb9V8RkgrwuRx7fcokkarHGOVtQARrb39631tDf1Yi++mJn13VpH8PvrwwzrtbazSxCch+Q+3KL4scnqaK6Xo38z09+tu67DnHTki8jM/Y/+8c6cO6Me03Z9SycfviUi3iMy/yz+/M5cveE+aPzEYINbRkb/SZECKSL78GAMszp51CUciTuKi6d4UBiC4Bg+vY+v15R+S8OFLSrS+mPFaujSfLMmw8GfO5Bl9MHSasQ+BK+atFjzFxt4vPVjmvXxfDEP9yCMuSBPh5DaDg0VAkmW6q9xr14qBsTE6vX/ssyxerGNcQ1kL3ksDxLZuLWq7tWz31FSR0df6wlrx952bN3XkQkyKsnKljnGNMcFaEAw5hL/na31BnhHWtNYAREhOfND77rs2wCxrtXT1mmCy1veoOYdiwYxWwgAm37/91foCA+wD6LNndXsOAqAUQWnsNmXvXq5caoNstqTEr2dZ9t/d7T8wxhD9ij+FFgIxRPeaq9zOTndFJsKB84GB/BUdK0XxPyM2aU1TitAXrq6vXOF9IaMd30EZ27IlD4KZYGZkJF0wc/16PGBLIWvBXPCDpTK+YhUwNHWo167Nb674vBopSliH2v95WXv77Th4ZhqV+DYyotO4xhjq5mbde7W3F8erp0dXHWLJkuIVsBYE799f/D2WvfXn/q1b+UC1Xouxylmma74VdrwUsYnLmnbOuNb3mU3teAGI+fOpqUk3v3BG+GOfUqt8+XI6rfLWrbrvEeeNf8uq/Yy1qu5ofEEfnkKrHNNj79+vu3WN3Q4sXHhPSj7uylBnWfZfzuagnv/mp8o6OvJloXBFrNEWTUzkFxI2R80Ge/t2XqPEJI2FrDKb/Of7AnOhSbwMD36GjZyaym8WuO70A5x67dixfLJkSj02W1c5liyp2RSbmorXpSK6q+Gwnjjafftlleq199/P18+FpUyWTKHtZnzFAPXwsK5c5K5dxSBowQKdhOHateKh2NSkYxAHBopgUAsQY2PMgnN/7p88qcuPQCMQP/jWtkSPvdfKlbrKHEjE9vd3LairJUVJ5evyZZ3kA+e0XxZVG5TifXxGf+9el8hXxl5/3T79ZixaOUQsANEkltbyNTXFNYnxffX368i+BttdR9MY858bY75sjGkzxvxXP6mXuqdtejq/IaK9rQ9m67WhoXy5KpQH0uiLRdJpgkNfCBZS6MQZsNnTk78JgL5Rw/pduZKv1oLN0dfQ1mvhZ0QylLa9esqxjyX/acZ+x45ie1yRfB31eu3WreLn0ba1/fjjYg3l9na9FCUmh0gFgrW+Nm8uJqWOjcUDiXreKzywsyzfprteO3SoOPabNuk6/81FsmToi5FDpGBcsbf4gfyVK3kwVa+hlbf/Wdev50rdpdBjx6QVbBfBFO+F/cCvXvXmm7qxx02wnzDb3a2bE7ix9dfk6tXxMpmzWQwEt7Sk04lrgT5IKr+M7OnTuv2+wTZbePJ3ROT/FJH/TUQUJ9BPoY2P52tO41DTiPVF8pOUSf7LsjxbAV2pX/ZG64thu5ctE3nmGfd3BlCPjeU3BwAWjRRlcDB/NYbNWytFid00oIZtWV+pGOrly/OMPtutL8ZQa3wdPVpcL5OTOnAeBiAiNnDQSFFivpqadIdbW1v89zRgYNGiYsMhLUB8551iktLly7qxryVFScXoL1+ur6Mfmna8du6My1oYaYU/x7T1i7Hn+e+WZbrkP+zFfi7K3r35+s9lfaXQF0PW4idLsmx3iqTE48ft0086vnhRF5TGgOv27ToyplaypMZwhvk3idpW4XgH/+Yd5+U9JvuYbTQvZFl2WET+dxH5+Z/A+9zbhk3U1yqzTLA/SeFXw7iKxJPGNAuzvT1f9gjMiiaBY3o6v8AZQH35cr4zHzP2IXDF9ZPmGr1WtRYNsDAmPydwG6LRiS9cmG+MwbzXmTPxlr8ppCj4mUaKEgNiWaa7Fo4BxGXLdIzrzp3FmyYt43rjRnGOa33dvFm8amUYxHC8rl61EiiNr9BWrMgf6PXatm1F2ZwWDMQYfe14xfaWlOzte+/pxr5WHWoN2EHg5587a9bobv7gwwf6WnD+6qv26TfE0fqKjdeFC7puozFf2uS/mK8nn9TJUZFf5OcZaRlqnBv+/s40sWugzQao/0BEJMuy90Tk4TKOjTFrjTEvGGM+MMYcNcb85szPFxtjnjPGnJh5Lpr5uTHGfMUYc9IY854xRlG7q8EWE9ezlTnChgEiutqr4Xsh2UJTS7S1NX9ljmsyv21rvTY05LpJivASBn+8mGoaoa+UumcckNDHlbG+PpEnnnB/x/zStES/cyc+zpoga2Agni2eYrxE9AAxBs5v3dJVRVm/vsiIanWWsaoVixfrWL8jR4o3J4y+OFWVj9jvDA/rGNeuriKjPzlZLD1Yjy1YUJzjDz2k61z6xhtF1pcFwaEvBtSlkKLgvXzgev68LvkPN6I+gN60SQeoAcT8sdaCOpyHKUrd1ZLIaCwmkdm3T8d2Q5LnyyK7u7m56u9hqGxT1h9kNf75ge9Rc6PSQJstKfGmiIgxZqGI/ANjzB/NgN6vGGO+MovvSRH5nSzLtonI4yLyJWPMdhH5fRH5UZZlW0TkRzN/FxH5ORHZMvPPr4nIv9R+qIYZvvwUoC6W3ctIK5qaRD73Ofd3HEQaxmJiIr9oGGZzdDQPBsA4+cXn67WUcogQUDOl23p68kAJ76XZFCcni0GWMTopyunTxc6PHR22lmtZiwFX/DyVL23t1VSVJhYsKGpQBwZch7sydvRoXhomYm8MNFKUGAhubdWxrrV04o0G5w88UGwXf+qU7sboypXiHqpl/YaGip9n7Vpda/uUgDqlL+wH/nzq79eVW4vVoRbRESjouOmP/9NP624tajHBGkspa8F+EGsoVdbwefxg8uJFHZ54+WX79G8lcWaX/ZwxKQre9dMEqD37noj0ichhEXnL+6emZVl2Ocuyt2f+fEtEPhCRXhH5BRH52sx/9jUR+cWZP/+CiPxfmbU3RGShMWaV3EuGLz8FQ40N0Y8mteA8y+ym4wMLhnEdHc3LTqC5fOWV8r5E8uMF4KqtQelv1Ng4NFKUUFrByEe6uvISGeY6q7/fAgnfskwH6sKgQUTPuMZY5e5uXVWUGKDWguCtW/PJkvClAXWDg8UNfmxMJx8ZHCyW5JqYyF8512sxELxpU/Fza31px+u++4rVQRj2NlaHWgNSjhwpBrPnz+fbTtdrsc+yZk2+rXy9FpvfWiC2cGFc768Z+64u+x5hF0HNewGI+b7279d1z4wx5+3tnBzCPyPXrdPlR8R8aZlzEDF+kKD1hfnt33CfO2e/x7JjVito8P8d4wu3sNqgpkFW79t2ZFlWT9fEqBlj+kRkl4i8KSIrsiy7LGJBtzEGoXyviPj6gwszP8sVBzXG/JpYBlvWaWqjzqXFGGoAqbKHGzY+X1qhBeeYsP6BwbDdIvFukJqanSJxOUTI3tVjIUBEBj7KUZWxRYtEPvtZ93dsjloW3telMgl7w8NxLbGWhQ8P3dFRXVvumK+ODh2wWLmyyDK1tOikKCGjL6IH58ePx4G+loUPgevly7pSUbEARJv819lZHOfeXl1QOn9+8fe0IPjgwaLEQFsLOcac37ypk9LFfE1M6OtQh76efNLeZpS1bducLhimZTZjuRFaoI9xSdEVLwbEzp7VJaHHfG3dKvLSS+V9PfKIyLe+la+8w37GWHGCsgYiBpVDfF/j4+X21xirjMoyQ0PlbglivrBvfMqSEmFfN8b8p8aYVTMa6MXGmMWz/5qIMaZbRL4lIr+VZdnd7rhjxUkLo5ll2VezLNuTZdmeZZqrnbk0sKq+tAI/KxvpxkAzdLJhiazZDEDflwVoGWqAB39DZLTKoS8sIE0d6rY225Al9JuiMxv+rGH9rl+Pa3Y17yUS31A1oC7GUE9P665ym5uLG/LUlK50W3d3vnyViAXZmrE/fbpYMSSlHpsB1HMJzi9dclfiZez++4s67uXL8w1C6rVr1/KHt0i8cUw9Njxc3F+0LGlsvBhpRejryBFdVaedO4sBqFaKEmP0N2zQBUYffFB8h5RSFC04jyVeXr5cnHP1GKRc/h5mDFeH2meoP/tZXUDzwgv26QcJ2hvOGHMOX2UD+ZgvrAOtr/B7FNEFRw20ehnqcRH5n0XkvxEHcjMRuWtBZGNMq1gw/e+yLPv2zI/7jTGrZtjpVSKCE/eCiHgpo7JGRBTFmxtosU5XiMjLXieChXzjDfczLHq/DWk9djdtd1m2G4slVcKeSDpwbkxeIoMNTCNFGR4utiJuadE11RGJVwLQtlePAZJUMg0R3QG+erXIo4/mfzY4qGspfOtWkS3USlGGh4ufccWKfOBVr6VMlox9j1pA3ddXXMe3b+vkSTFGf2xMp2X88MOitOKhh3TVDmLANWX1EaZ2tC85YHx1dRV9nTmjS/579dUiGNmwwTadKWux+c1URQmNTdiLNacqa9gP/PF/7TUdOAcT7M+Bjg47V8Pa/7NZrHY0buYnJsp9D3fTiZdd3/AV0z2XBdSokoRSviLuVmRwMF9J5BNu9X4bvy0im7Msq7vtmTHGiMificgHWZb9kfevvisi/1hE/seZ53e8n/+GMeYbIvKYiAxCGnLPGPSP/hUZAHXZjexuhdPLHuAxbTdY7kdKFlPBYomB4LLvhcPwC18o+tKAp8nJYjcvEd0BPjFR7PJnjF6KEh4a8+bpqgrUAnUaYNHTU6zMwiSgxTSuGl+xRJlr13SVOWJMcE+PripKrZrWIQiqx9ra4kBM21wkppfV6otDIH7qVLra0VrGNeZrwwZdxZCYLy1Lev/9xbrdWl8XLxbByPXrukomIyPFd5ic1EmKYgHI5z6nA/q1wLlmvPbsKcrTtIAa75UCnOOs938flSwmJ/Nn+mwWY4I1vSNq+dICanR99JMltb4wt1K8V4Ot3tDwqIiUFZg9JSK/IiKc/asrAAAgAElEQVTPGmMOzfzzd8UC6S8aY06IyBdn/i5iEx9Pi8hJEflXIvLrJf9/jTdclfvSCi1AjHVIAjB88cVyvmIgOHYtVY/hwPdZcgCDslKUWCUTVqbh16EO/z9lLQSIExM6KUrMl5ZxNaYorViwQKcTb2srloHTMq79/ZaRTOErBlzHx3VSlBgTrE0kjAUzmzfrDri+vmIlG20AcuNGEXRpfd2+XWTlUspaTp/WJ/+FoG716nx753rt/vuLrFd7u44pjTH62mDm2LHiHE8prXjrLV0AUgsEa9b2kiVFQLlxYzmQCYtVstGC4Oeft09/jsF32bkfY4LRtKcs4x0DwbCyN1Axtvvpp+2zbH4KcsN8KZiWoUalMT/vQOurwVYvQz0lIoeMMS+IyI9DhizL/otav5Bl2asS10WLiHwh/EGWZZmIfKnO9/lkWowJ1sohYjWttVFbDFBj4yh7uOHQ8XWWANRl61DH2Hv41+rDYldgKbXKWl/hYT087JI4ylh3t9sEYV1dOmAxNlZMnmpv1/kaHS1e72uBWEo5RAwEX7qkY/1WrMhLikTSa1w1V+lnzsTZbk3AVqsbZCqt8tCQThcZa908Nqa7fYqtl8cf1yXjHjhQZGoZTXCMOddYLRZeY7H3OnlSt4a2bCmSHps364KZM2eKe4L2M8bAqZ+wV+YWKlaj2T+7y0j9YoAa/Qtu3ixXv/vxx0X+5m/yt3PI8So7X4Ep/O8NQWrZPcxn72Fs/44GWb2f/P+b+aeyuxkmmR9taxnqGAjW1kLGAnr2WfczbJBok1qvAczHpBVlPyN0siFr0tJSXooSY/RhWilKquoQzc1FFnN6Wq8lDTes8XHHgJSxwcFiub1Vq/Tt6FNJUUTSAeqWliJ40vrq7CzWF/7oIx27dvp0EVguWZKuWktXl07/OT1dnF9aKUpKcL5pUxHAHT3qkpfKWH9/ce1pb4xGRorf2ZYtRblYPZZSilILnGvrUIeVha5dS9fQKJTq1WsnTxYZzC98werHa9Wyr2Wxz+KD4DKAOuZL26gEZSdT6J4xHv5+hcZuN2+Wq8yBW3L/HVAitWyeUUptd4PtroDaGPNVEflbEfn2TC3pyu5mMRCsLU+HK5hYQxAtextLJCx7gOOgeCtShjyFFEXEjllZXerdfJWVomC8YtdgWglDrMSjBqSMjBSrNwwM6Co61KpDnUois2ZNkdHVvpcWBC9fXkyW1ALEoaEiCz8yotv0R0eLtwMxuUU9FhuvBx/UXe/HwLkWBG/cGAfn2u5zqaQVJ08Wx/n48XR67LVrRd5+O42v9vZySWywxYuLIFjL3ra3F/dCra+XXirKrfbvT9dZ0pcMlgHUsf//xpmaC2Xn2N3eq6yEYeNG+zn8z8JKK/z5BCKmrJwuBoLhV9tzw2fhH39c5E/+xHVfvEdsNob6z0XkZ0Xkt40x4yLyAxH5fpZlii4SPwUWk2mAHX7ssXK+cBXjAxItCMZB4cs7tKV3YrIWWNkFXsvX9LS7BqrXajHUscS72Qwb6DPP5H+uAXVTU9ZfCJ4YfXGYBJWSCb50KR1L2tOjq4rS3V3UhHd365r91KpDrRmvq1eLNzop2dvTp/Wscqrkv87OYsLmffdZJr6stbcXr7e1LOmRI+kqc8Tm6sCArnZ0bOy1VVFirPIzz+gqc2zcGGfhNXb2bLzqjsZiYMs/i8rIBWLjhQobIyPlk/9CX6j8UVaO8thjxQ60WhA8Nlb8/2t9YQ3HcpbKztdYU50DB+zz9Olylchi2m5tY7cG22ytx9/IsuwPsiz7jIj8QxE5JyK/Y4x5xxjz58aYf/gTect7xVD25TOfcT/Doi67KLG5+4ciJhwybOs1ALDYNWTZQzdWfQSWQtaCn5dtiQ4foVxBc5Ub08CJ2Cuxsi3RsVEdOpT/uQZQAzykAogi8etXTYOLWBnA27d1lQBaWop1qDdvLl8uUsQGk+HhpgXBtdjbVDpxBiCGvo4d0yX/9fYWq8+sWKGrZPLxx0XmC133ytroaBGMpdYXa3Xi4Zw4dEiXQLtjh2NF/fdKJa247z6dVvn06XglE5Hyc/9u2u6ywWRs/0Td+7J72MqVxTkO/xppRXg+ojdF2epCL75Y/P7Z2tH+HMB7pqgdrX2vGEMN5lwjZWyg1R0OZln2sYj8PzP/iDFmt1j2ujJYLDEOm0VZlgGNAXyNK65+wk13NrsbCNaW4EuhVcZ4xQ7rshs1NolQWnHjRrFj2GyGwzCUUcS6yM1mtVj4efPKN8uolXj5SdAqt7W5drGwS5fiXR1ns1iCo5ZxnZgoMnVbtuiyx1OD4Fh3Q42vFSuKjP7t2zrGNcbo376tS0C7cKEILB97TJc7UKsbZCoQrAXnPT1xoK95r9bW4o3OsWO6W4s33iiOfV9fOj2238egTKWomC8GiKXy1dcncvhw/mdgXK9fL6cvPnGi+P/X3i7H/nvcWpcNclNKUWKkkzaR8KmnRH7wgzwrjcBI0xisgTabhvpjEXlDRF4TkX0isj/LsjsiIlmWvSUiESHtT7Gh/jSE/iJu48ZVVL0WS3AUsRNYK9MIfXV2FvWl9b5X2PlRw7hC2xyTVmjLDIaHT5aVZxgARMID6c6d/Hdbj9UKQFatStOgR4Rju1OVbosxYlqweedOsd3y8eP6NrTheC1eXATs9VgMBM+fr3uvtrZiQKUd+9ZW1/QJpmXOP/qoeLh+8IHupqGWRj9VE6Jt23QMVizxUguCY7kR2kYlly4V968bN3Tf48RE8fOMjtqfTU2VCyBiAcjnPy/y3HPl3yslQ717dxG8aQHixERxTBhpRfhZcFt07Zq9BarXYkED8qq0yX++aT9jb2+6YCbWfVnLnDfYZlv5G0TkyyLSKiL/TETOG2MOGGO+XMk9IgatMhq8iLhJVxbw1ALU4+MiP/qRzld4iLS1lS9xg2v9EAx2dBQrIMxmsWRJWNlDBLW/w858GpBSi1W+ebP8TcPdAiOt3CaUVmzYUL4yB/7fYdKHFohNTKQZe1g4JyYmdIxrDNQNDenqUIsU58SDDxZreddjCxYUK9loQd3QUDwBTeNrfLx4iKVk4d9/X18DPPwee3t1ZQY3bizKWubNS1eHWttF8Ny5fA8D31cKaQUSJcsSDHcDwWWDo6VL4xp932e91tRUZMe1muCXX6499imYc8gtQ+lMPb5Cw1osG4DE5tBTT9mn36WwHlu3rjj2INnKMtQgT/wx+zSWzcuybEhsIuIPRESMMfNE5FdF5LdE5DdE5C/n+gXvKYuJ62EptcqazVWkeEU0Pl4eICIqDpmZBQvKS1HALoXvoGFcawUNKX1pwGYtVvmjj8pvrnifJ5/M/7y7u3yDHnzGsHRbT098/t7NcKiGV/lacC4yt7KWWMm6eqyry7bODn2n0rhqmvOIWDAdrqGUeuyU0oqhIR3r1NVVrNYzPKyTQ7S0FIPSJ5+MVy6azY4cKe6rWvlILRmQiJ1jZdZlzBfm2+houaSvGKBGjsvQUDmmdN264n4MMFd23D76qHjT5EtRylitxF6RtAFICnCOwOjUqXI5PU8+Wcyr0EpRbt8uzi8QC2V14rHuw59GhtoYs9oY8/eNMX9kjHlFRL4vIptF5L8VkZLo6afAarGRIvqEvdCXBiBCc/X44/mfj46WT1yCljLcZDTl1iCpCKUVq1enaYkuogNiKX3hsA0ZselpfWZ1+F6Dg0V2ZTYD+A0T9jZvdl2w6jWMVyp9cUpfxhSlFYyv8BbmyBFdBYwbN4qt1JcuLR/MwMLDbcECXX3slGXzaoFzjS1fXgw4Dh/WJdBev15kybXlIicminsC3rPsmKUEYil97djhagzDcAtb9tYoxuhjHywbHJ07VyQlIB9csqScr7nWdmsZ19WriwGL1tf0dHFPAJgtK2Xct6+49hAYlR37u0lRNGRFA222u6kLIvK2iPyxiPx+lmX3Vrjwk7a7MdRlgRgO7thVjDb5L4X2FlrwsAV3f7+tMVrGarHwHR3lr01r+erpKb/A8V2FLJYGUGPMQ2mFMeUPXFzrhyD4ypXy19W1dPUtLeUPkFoByPbt+vqmqfTYTU0ie/fmf6ZlXMfGitKKsTEdizI1VQyoBgd1yX9ZVhyvPXvKB1nwlRIEp5K1xICY9r36+4sH9dGjuuvlWAACpm56mtcqoylR2Tm2aFFtUFfWV3NzMRlby96++WYRhKMCUn9/OfnU3VhlTTOvcOwhayzT2RD/71Rjv3atTXJM4evDD4sgGPtZ2Rrssc8ISyFFwb6hvbVrkM12Cj8lIv+3iPySiLxujPmWMeZ3jTFPGWNK3jH/FBgmRgioFy4sssOz2cKF9hkDYmU3C1QMCWs7M+xtyoohIRi4das861fL1+rV5RlXJHiFtcM14wUmOIUcApth6EsDzmtJUd5/vwjY6/UVjr2GJQXQefjh/M8XLy5fYaVWApYWnE9MFMs5Mix8eIAfO6brsBfzpZWitLUVExwfeqj82OOdwutfphZy2CxFq1WupasXKb8mY4AaQVFZwBPzBY1r2XW0cmW8BJ9IeRB84UK8m61IGuYcn01zYxeOF6RPZZNVY++Fc6Ns8t+jjxaJMG1TttgNDMa+bAB44UIR7GrBeeysR1WssETsbBarAY7x0sr8GmSzaahfF5HXReSPRESMMX0i8vdE5GsiskZEFMVJP8UGPVMIBjRXr9iUwwXY1VWs0Tub4ZAO2S8NOK/FBGvAZi1fN2+WZ1zBQodXk5rkv1rSivvus4x3GQNLGDL6mvGq1bymqSldDfCpKf3miiAQduNG+QQ0gNOw1noomanHML9CaUVKKYqWcRWJV5rQWIyhfvfdfHJ0vTZvXnH/WrFCl7B361YRiC1cqOv8NzVVXMcptco+QCxTjizmC+XXbt8uF4hs2FCsAKFlXGtp9L/97fL5Fpcvp6uAEWOCtQAxBoJryQhns9gcx/uUlRVlWZFUQ95L2TyjN96w4+8bfKcAwVqgH2Ootb6MqZ3EWbY6WoNt1hDfGHO/iDw5889TIrJILMj+k7l9tXvQakkrRkbKNypB/Wmwy7BFi+Klmu5mKZMlU2q7YWGCjAZs4uAKg43jx8vrw8Dkf/hh/ueaphS1xmvJknQBCJMsGdOJlwWIOKBDacXZs+UBNa6DY1UrtKUUQ+br4Yf1jQxSSVFE0oHz9nYr8fBtZETHUMekFTdv6jr/DQ0V96/HHhN5/vnyvu4mRSnbYe9uvkZHywHqefOKwZ+2DJwxRTYUFRBu3CgGrHezI0eKUgWA9bLMfqzMIPZsTbnOVJ3/7gbOy/patar4GTH2J04U19fd7OTJuEZfpPyajAUNOP/DmySNr09CDfDHHivK03BjdI81dpktKfG6iPy/IvKYiLwiIn8vy7KVWZb9UpZl/8tP4gXvKcOVR1iM/M6deCbr3awWCG5qKr9R1wJ169eX2yj890rBUCNaD99B4wsLMJYkU3bTr+Xr44/LL/BawHXjxnL1SH1fMUBdFohBmxlWrdD4qsXoa3xh7MMW3++84+q812u1ZC2LF+sDo/D3liwpfwOFMQkTHLX1i7OsWAFDy94ODbmGFrAPPtCXr4oB1+lpvR7etwcftM9GgrpFi4olK7WM6/XrxXrfqEZTliWNgSdIxTS+wu8RjGuZhie13ks79g884OYA62tsLF0i4eXLRYYcpE4YYM5msfGCzjxc87PZ3Vjlsmto3bqinAvjpWG7w7Pj01g2T0Q2ZVmm6KH6U2rYDEMgllJacemSyOuvl/OFCR76Knv1J+I03eHV1eLF6epQaxhXaOdi5cNSVfm4ciUdq6xp0IPNMGSqHnqoPNDHZwu/Mw1LCnYh1M5pfNUCwZOT+oZG4fd4/Xr55L9ac2LXriL4n80wh3btyv+8pUWv7Q6BGCOHCMeZ8RX+Lm7exsfL7T8xX7iNKrsmly4t5kcAHJQ9wO9Wh7os8fHxx0UCRZv8V6sGuIgFfGWaSt2tnJ+mmVfIwqMOdRkGHu8VjpdWE/zOO+lafNcqFylSPkciBqgx5prSn+F7YQ8qU35PxGr0Q0DP1KEOyx9q5SMNttkokf94NgfGmF9L9C73vuHLDw8KDaCGr1hHwrIHCBZkKK24ebN8xIyDJ7zmXL26POMKGUyYgJhSj62RMPwkpBXvvlvsBjibAfyGlRO6u8uDHmxgIZOybFm5GrUiLoBM0RDkbmNf1lctEHzqVHmNJdZQeJuiKbdWi9F/5JHyQS7Y3lBrqAXBsffSNheJvQfY0bIgpbW1KOdCybSywDXL3A0NDAC7bPLlhQu2coVvWoY6FjRoQV1qXyEQQ+WJsrdGS5cWE/ZA0oTfyWx24UJRKlB274LFQDBTni4V2x17L6z1sJHWbLZ7t8jWrfmfaQOjW7eK+wHWZ9kcr/7+Ign5KWWof39G9lHLjIj8poh8Nd0r3cNWS6aRGiCWnfxI6Nq+Pf/zgYHy74VEp5AxaWoqv1FDJxseiDt3ltf51ZK1MAl7KUAdAo9w7EXSAbGrV8szHxcv2mdYkmn79vLsba2gQcNQ10q81ABE/L9DrSEDNsMSjG+9Vb6NOZil/fvzPy+riRSpHTRofMFqjX3ZhL2YL59xLVOOrL29yKIhx2FoqFhr/G42PFxM9NIm/2VZETw9+KDIN75RvjpEDLhqgUVKWUtfn2ORYZjDZQPT8fHieGHNl2Vcr10rBkAIeNGeu16L6cS1jGsMBGt9rVqVjr2NSSuQNHzsmMjP/3z9vt5+u3jm4KwLybZ63iucEyAWtHlZDbLZUMtLYqt63M2eS/Qu976lZJURxcfK5pX1dbc61GV9oaQaABnsww/1taPD8WpvTyeRWbGivGYQnyOs6KFhqLHhh1pDDTiHnCWsGHL+fHlAXWu8NMl/tXzt2VMebN7tvcqOFwBNilrICDLCqhWxxh6zGQKQcI5fv56uBvju3SJ/9Vfxw72W1Uq89EFwGUDd3Fzs6qkt3Xa3OtRlx+zOnSKzisoc/f3ldMExJhiAoux+GPOFPUiTIxHWdNbKIbKs+L1r9bLHjxf3KkimTpwQefrp+n3F5rY2+S8WgOAMXrmynK//n703DdPqus5E31NVUMVQgKAQM2IQkxAICdCAjITl2G476djxEMftxHac9pB2nI5vO8/N4CFx2rfTiePbHmI7zk3kdGJ3nDidyO1Onk7sSJaERhAIg8QkgZhHFRRDQVVR5/449ao+9rfX3mvt2kWBYD0Pzyd9VbW+8+2zz97vWvtd7wLyKZlMnCg3drHex+3b64MWZoatmvU+EMx10BoY+TL6DIjcQvfL3GKyeb94qS7kVWF8mN3FZ/58YN48my/yk1yeUgoI5tGQWyw5EH7xYFIrDh/OV3g5Z079944ZO0u6GbEUEMyMvpv1TfFFH+6inAIQpbF/+ml7AW1Ih9oqkUYepcsvnjy5PpseMymQTMlQk16Qg1ohgeAdO6r7aAHBUka/NuNqBdTuke3y5cA//7P9Xl64UJ+FTs2SdnYCjz128XsDaU/sU2KqfbWYO74EFDk4ritXVq/WrN/o0fV7TiqoO3q0XikpVTvaFzTkzMIzUNq+feDgnEDacvoBVKd8buacVBTrM3TmTP0enZqhPnas/n6lBkY+EMw6jqefBj7wAb2vkGLIFZahTiwrv2ZeYyZsxoyL308pQCMQcyfU9dfbI2ZmBNwFayDZbp/6SCqtxfV15IgdBDOb4B71FUW6XqcLeFautDeJIQh0m+qkAGoJuObkFxPQWYyLskuHOHTITh/h9bi+liyx84sZGLg61CkgOERrye3LslZIgeS6ddVrSudFVzmB9BHLHON3cKkVvK8pfGyplXaKpJ+U2UwBiO59ZG2Ie4oXs3HjgNWr/deVcmrkjhfVSKzKHB0d9RnMnCB4IJlz1xdPI61ynW1t9fs2r8dtbx4zH7WClD+rnv6WLfWSuzm53ama1jlpLU1N9esX1y1rndEQ2zVAndOkjNiRI/XqEzFbv756dR/mqVPTOEpAXhCco2CP1+MWowxEBs7N6D/zjF2Fgce/bsFmSrc46Rh96lQ7x1LyNZAsaQ5qBYslXSC2a5edbsON0KdDbc1W8LNdMHLHHen0JGnsLXM/BqgtoI5Bhqtaweu1+JLWLwbklnvJzLlbcLx8efVqmfscWykLn1K4JNFarMCiqcmfQEm5rt7e+tNN8sStxeOHD1dNQWqNz6m1cM+XVebJg3XtGWyeeGrGdezY+v4OzHZzP9Danj31lKLU4r9Q5tzajyJUeJlyXVLhpXXslyyp5+jTx6tJh/qaGY2yYe6x4cmT9oyrlAnu7bWDFG4SbobvttvsEXMoQ20FYozaXQmnFFDHTd+liqRcFwtt3EXmwAE7V5lj747XggX1Op6pvlLGi/xK9/6ngHMpo58iA8cF1AViTzxhn/dS8Dd2rH0DkTTAublZNhGOsXvSlArqgPq5lCK3xiDGleVkMsCSqZOChpSj3JBkIWCXWwNk2oF17Bsb63WoUwGij9udWrAH1I8Xnx9rB00foGbwbO38l5PyMXNmfUY/1de5c/VzMjXj2t5eP8asvWANktZ8QQNPjFI0wF1fTBJZqSjTptVz9IkvchRLXqGyeao0TVEUzQDeDmBW7d+UZfnZwbmsK9Qk0JySvZWA67Ztdl9Shrqpyc4ZJPh1eZbTptVnFWOWs1iSR0OuHm9OKsqBA/aq9lBG37pQc/FzAcRdd9UXy8WMi5/LD0wJQFgkuWUL8NM/fbEvq0njlaLPLIG6Q4f69Za1mWopQ33LLcDf/I3t+nia4nL0U0Aw56OkWmEBiPzcHI03JD1x0m/279fLbIaa6vjeDxnXAheI8TmwBpQ+akVqYNTVVU8TyUmHYJZ7507gDW8YmK9Ujuvo0fWyeaxZsWZcfc9vKgjevbs+GZOacfUpv/D+WddpHwjmmFupKI2N9esqT1d4cqS1667L13p827b6+5UKzofYtDveAwDeAqAHwJmaf9es1iQd6hSQktMXJ7p71Ld/v70tN8GcmxGbNcveuemZZ6pXd5FJybhKAchACvZyZOElX48/bq+sJn/bzYiNGmW/LgZ/rgrH9On2zn/MfLmBi5VWAchUlBQtZGnsd+26+LM0xmyQq0OdAiykjD4r2i1ccWbC3MxmCqiLjb3FlxQY8Tm1BPIcL5daQUBhARb05a6FzHZb6lNYb7B27cXvp4I6IG/HuJy+3ECDJ0jWjGtLS32dC58tV1UpZseP9z/LNFKJciispAJEn69UgOgLZvjMs05CazfeWA+cUwOjU6fq5xGxAQMkrZ04UX8C82rOUAOYXpblvxnUK3k1WE7ZvJy+li2rXt2ueMeP22XNCMTch6m3167MwYXBBYOrVvWDba3l1I7OKd3GjL57NJrii4ueu1jv3dvfVlhrVKtwOWo33QT88Ic2XyE+ttWk4/3a4iz3mZCMfFT3aLQWIGr5pPx8d9NnU4+XX9b74tg//TTw3vf2v88NyTIvpCw8n3XLUa6UVU7JnMf0xC2++Deuljszrvv31wc6seuSOK6WDVyqaeB1upKnGstFh/D5SgX6o0cDr33txe/xOU3RoXbHmPfESqc7c6Y+GUNlk8WLbb4Gu1gy9T76iiVTfV24IDdacrvcxmz79nq+P0/erB2TfVl4BiBWKsoQmzZD/VhRFMbelFehEfD4NDutE4MkfZ8WcioQy6EOwdbBLp91w4b6bEHMpKBh+PB0Woub3bvhBnsHLgIjd+wHooXs0jRSwCaDDJdfvG9fmq4v4KcBWbMCki/KVlnGTMoqp2gOS011UkAdN2530+d3S6FDuJuIdGoQMimYueWW6tXSPEWitaRs4Hx2XOmyFFAnUcNSrouZcZda8fzz1aurqBAyKQAhFcWi2c31zic9CeiDSFpDQ32mcCDqEO78SgXnJ07UZ1Z5UmdVdAh1g0yRW3N9MSCyNokpCn9vBcC+to4eXQ+oU5ue7NkjF7e6VMmY+YIG/r81yPIBaq4fd95p8zXEpgXUrwGwviiKbUVRbCqK4sdFURj7Xl4FxofIfZh8LT9jRk6fuyincILZkc09Zh0IFWUwqRW7d+cr/rvxRrs6x8KF1avL6UvhBJPb6gYgA2ku4v5dzkzwI4+kd5Z0fTGYsCz8zOS7xZIsgEnJIObIuBKAuUAsBZxL48WA1FKLoMnoa42gyS02ohyopfsi1yg3a58y9gRcrg71QDLn7nhxLbKc9EinAwyILHxZiSfOYNB6jF6W9TrUqYC6s7MeiOVsr54zC88xd6UyU66LwYxVh3ryZODuuy9+j/u4lYpy9mz9/E6lQ5w+XQ926SulQ6i7H/J6XHWZFF+pcpFDbFqE8CYA8wC8AVXnxJ9CvIPi1WfkJ/mOvq0Tltkq9yGfNcveVpjUihx0iJzcbimrfPiwXT+XG4/LgeztTTsaA+oXv3vvtWX8gP7Ml1v1nQKCY9lbi4UCI8AWtPEEwNWOpg60BfBwjrqnAzzCtXxXnqa4ma8UTjDHazD5xSnAQspQU3bTcmrEMXc5+jxdsYw9gwI3AOHaZcneSplz/n+KbreUhU85aXB9cd67TYA0dt99F/9/itzahQt+PXlmWq3KHL299RnMgRSNDSZXmT6sBfIjR9YHIPRlTe74VCu4L7ldW2N24EC9bF/qeIW0o4eSJ97UVJ/04nVyDb9CTAWoy7J8CcA4VCD63wIY1/feNas1tsd16R27d9uL/xhhuw/AjBl2UCeBJ2vxWchXCqBm9srNYqUARII6V9/2qafsiysjbHchbW7Ox4WfNcv+PUM0DatJ4DwFILJY0j0a5Zy3FKCR0+0GIClHucxGus/jXXdVrxYtZEk2LwWISaAuZeyZTZZa9FqCGc4Jd82hNrgFWPBvXPURnjxYtPSl8UqhHUggOAVYcF5J1AqLL85rd36R3mXhuPI7kt9PY2BkpcAB9WsVfVibLQH5lDmKon68Ut76Vt4AACAASURBVEHdsGH1TbuY1LHyi48fr+99kEpF8WVvGfhauy+HQHAOfexUXzfcUB9o8NmyFu4PsakAdVEU/xHAtwBc3/fvr4qi+NhgXtgVaevW+QFXe7u9+E8qeOnqskvd0ZebFbr7bnvhjJShTqEwUDbMVQdJ8UUg5j7MA6FWuAvGrl32sZeAq5UCVOtLKv6zbCLMQrogmL4sBaZSRj/FFzOqLnijkoKF6ycFICmAQspQUz7SEpzy813pyRRAzY3HDQ5SfJE/7HJcGRhZOv/lpKJIIJjg3CK3ljOY4T13n+WUIItrjnuiwP3EokMtfUeuXSnPkOuL0ndufYLGJMqHFQQ3N9cXS6ZmXLu65LbcVqB//nx9Eodjb1Xm8IFgZnPdE0GNLwkEW5MybW318z41aPBl9Gt/dgWZlvLxSwDuKMvy02VZfhrAnQA+OHiXdYXa8eN+8DYQRQfXNm3qP1K0+vJlI60TlkfvblZ57tz0zn+SEoDFKN/kLoo5qRWHDtnHSwJiQOXLkvFmZsKlQ6xZU71afHEhzQHEmNF3wUAKzzKmGJLDF7OmlgYXki8+DxbJL1bBSxxXy9gzkHRBUs7M+UCoKK4vapZbus9JY0+OqyVLShByzz0Xv8+gPuXUwn3uUkAdAbV0Hy1jLymsMEjlPRiIrxTwxD3QnfcMLN1ueTHjiXCtpWaoz5ypV5ZiAipHgSP/39oS3QeoCYqtVJTGxvp9m+O1cqXNV0tLfUKAZh2vvXv7O4IO1NcQmxZQFwBqv9mFvveuWa1JN38g/GLXBqI04UanO3faH3ACB3cTmz3bXonOjmzu4pdCYZCChoHwi3088Vy+pO8eMmYE3IYYKUdtEh2Dx56WORbbdFPaX0tUlBQKgwvEGJBaqEDc7N1mLDnl1ripWU6NGBy4TaVycrtzalpzXllOeggC3CN56k+7tJKQEfy6zyNBnvsZIePnPv30xe/nDEBSwHksMErx5T6PBHMseNcYx97lcPPExqpD3dNTT61g9tZaiA7kGS+gmuOur5ycc+5DrJPQ2oQJ/XS3Wl9FYb+us2f9nWubmuo7H8ess1OumbrCALUWudwP4MmiKP6+7//fCuDPBueSrmC7cMEvj5cTUKeAuqVLgX/5l/r3jx+3UxiYEXOvo7vbrtdJGoy7WN93nxyxSsbNy90oU8B5DNT59DwlW7oU+Na36rU5a0GKNhCRMvov9ZUznDmj30h27KheXSoSFU4sFIacfOxYwZ7FFzmjbhEvfVnAOee7m+HhEe62bXoaD//mxz++uAiNwMLyjEvgiUVQloyrBIJTOK6DIcHn0pMYREhSYD5jBvglpwQoZ0t0Xqcl43opeOIpoI73y6VWcJ9LkXh0nzuOeQoVxU0I8Vlna3SL5cp2A/n4xS0t/WsyzThXu7u7sW/fPpy7//5qPWChPO0f/7HaN9z3Q3b//dV1uH/z/e9XNV4WX9/7nt/XP/1TNf8tvjJaS0sLpk+fjmGGvVCFNsqy/EJRFA+hks8rAPxiWZZGXZqrwKQj95YWOxC+6Sb/REqlj/iAZUr2VjqqXb/exvPjdQH+rLJ1EZMUQ268sV5uK2YEYlKxZFeXHrhKGZNafrGW0/voo9Vre/vF2qTMlJ05o1eAkUAwLUUBwx371auBv/7reg1uja8c4JzcWjfrmKJpzUYgLk2Ez3WOoIEA8dChfh3pVF8E95biv5zBDLOQbkZsIADRtRRwzlMJ97icxX9PPgn81E/pfEkBCIvGLUomEqBmMGHh/fN6csjmSfURKb6YhXSpFUzqWBQdcnL0uW9LhZeu6o3G3EA2FZw3NtbrUHPNUfrat28fWltbMautDcWoUfUA/cyZ6not3/PMmWp+u3/T2VnJDFpkHs+cqcbH9XX+fOXLcmqUycqyxPHjx7Fv3z7MNnyXIMorimJM3+t4ALsB/BWAvwTwUt9716zWRo70Z/ZWrbJL3Y0Z41+QU7Ldjz/u35RycrsHQq1wF8UdO+yFIBKo48Zu4RdzwXHVVFKABTNhvmJJqy8esUmbSAoIdoEr+dCW6moJiHH+WuYYKRXuIsZNxQJScjYEIeByAXXKsbAUzDAwcrtXhkw6kk+RW2Pg41KKWPxnKaTl8yYFRpax52mVq7aQk1rBjKulgFbyxec0pYjTHS/eC0u2mz7cZygF1HG+80TL/QzL/IoprKT4cp9tzgWLFrK0D/G6LAkBoNqj3YZG9K3tpkrr6pK10ZXjde7cOUyYMAGFT0qRZsUBgP80vrfXTwVJ8TWEXRKLosCECRNwztj9OZY2/Xbf63oA62r+8f+vWa0tWeJvu5lS/CcVwC1caH8oT52SiyWtJi3GKb6kMTl2zK+jGjK2V3c3JF5vioSVu8C+7nX+90NGMOB+l4Fki9ygIQXoSwFIynWx0ItFYjTytC0NLvj57hwnmHM/I2SPPFK9um2mU75jTHpyqHSopaJXam9beJZcu6jgQGOmzjLvOeYuv5mJBct9lMYrhV+cc+wlX6RBWLoukqJz770Xvz8QuUh3XHha4TZNChmzym69QQo4lwKQFF8SOOe9sFBRuDZLHVUtyQXuW75npampf5/SWldXJUTgM8OcKC4lOLWC86Lw44cLF9LAeSZLGbMgoC7L8qf6XmeXZTmn5t/ssiyN6vBXgfmqjoGKumFRFAAq1QofhWLGDDt4lR48S7Yv5isFUI8d66fCpBzbjRhR+XL9sWDI0ijm4Yf97w+kAM0FYuRZWh5aCTyldOuLNXax+OIpwMSJF79PTqSl8JV8WDcrw3FKKUp0NzdqNluOEnPSIaQMdYovgiOpWNLiS8rGcO2yaOkThLhAjGA9h9RdCgiOATGLL55g5dChlk5TOH6UjdQYi27dboGknVkSMlImmL4sPREkXwMJjNzvkuKLgFqiVqRQUXxt1FOojPw710aMSKOiSPtNrgx1ijU2+ms9entfnZ0Si6L4oea9q97Wr/dn406csBfs9fb6J+zZs3ZfEghevdpetCcVXqZ02LvpJj8XOUW/eO/e8HVZfJHT544NO59RXUBjEk+cINSijJKTX8yunq6WaYqaBr9jDpUPAmq3WJaZVkuxqhSApFBRYjrUFoUCBh4uDSzlPtKkYlyLL46xm1llQGTpuphTM13yJbWpD5nUQCWF28177gZmKeCc9BC3wJKgztISXQok+d0tgZHkiycMFh1qyVdKhppA2qVWpABqrk/SGKf4clt8A9X3d5vthEzidgPVmFlOeUJWFPYar6KQ64is4Lws8eb3vQ8n3H21KC7y9c1vfhMHLHS4IbAYh7qljyvdVhTFdUVRjO/7NwuAsSPIVWCnTvkX0Zx0iGeftYFDQAbnjY32zn9Ll/rBA3nHFn+SWkbKpvv88/4xS2lPTD/uIsOiMcsxlASoeT0WwEMA5i5k1KF2266HjJu+BM4t4/XQQ9Wru4mkHFfHWnznOB1g9tTCcZWui9lJy9izu6Erj0fflvEiAHNPAVJ8SVzSgdxH1xdrCigbORBffA4sOtSkDt1558Xvc01zm0yFjOuAOydTxp6nABJHP0V9xF1b+b4lKJVAcEoChSDY5YMzwNUW4gJyEM8123JdpIdI1AqLL2ns6SdFFUWiQ1iodDSfL1/rb42ldFr22YUL+Mevfx3jIlz1Kx5QA/gwKr70wr5X/nsAwB8P7qVdgSYB1xSpuxAIttqYMf5N5/nnq8+xLBijRvmpIjzCtfhau9afFaB/S4ZH+tyUhiDS5pVSUCXxsZkNtCwQBAOSYkgKEHPHjUfylqPcmH5xynjlAPpSNpIbkYUbuWJF9eoe7/MZtQRGzGK5zzelvtgsRmM83nfpYQOhHUi0lhxZ5RRVFAaS7pE8Aa0rgRcyCYiRX2xp58xMvnu8n1JkFyuMs/iSQPBA6BDumsP3qTykMX6+ex95nRYlE6q0+JSwisJ2YhQCrkCeYIbXlcvX6dO25kjM9KZ0iZX8+b7LsGFefPAHf/AH+NKXvgQA+PjHP477+uRCf/jDH+LnP/UpzLrvPhw7dgy7d+/GokWL8MEPfhCLf/Zn8YYPfxidnZ347ne/i3Xr1uE973kPli1bhs7OTvzwhz/ErbfeiiVLluADH/gAzvetq7NmzcJnPvMZ3HbbbViyZAm2WiV4B2AxDvUXy7KcDeATNdzp2WVZ3lKW5Vcu0TVeOZYTBOcE54sW+YslmQ2xLLD79/s3Qx7RW8BTZ6cfCLOLmYXjHeN25wDUKb6WL/cfqQ0EILrziQoUFoBI+oprBIyWDSmWVc5RZJcyXswau98lxRefRRfos+ucKwUWMso4uhlyBr05ePUEoZb2xDkBdUxuzeKLFBlXfYR1EdJc9hkDSbfbbEpQKoFgXu+ttw7cV86ThhRwTkqTK3/I67JQURgAuXQuznfLiRE/10etGD7cRgPi+iTt05YkkRTMpPjiuLj1EfxZStOTT3+6OtGs/fdLvwS8853174f+ffjD/X/za7/W77+hwTuO99xzDx7pKxJft24dTp8+je7ubjz66KNY7TwnO3bswEc/+lFs+du/xbgxY/B3f/d3eMc73oEVK1bgW9/6FjZu3IiiKPD+978f3/nOd/DjH/8YPT09+NrXvvaKj7a2NjzzzDP45V/+ZXz+85+3j1OiqdBZWZZfLori5qIofrYoivfyX+hviqL486IojhRFsbnmvd8pimJ/URQb+/69ueZnv1kUxc6iKLYVRfHG9K80hCaB4JSo8Kab/B3TUo7aYtQKS7Zo+3b/sRULYCxa1LEAxLJgSL6Y1bVwldvawrrdFoDY3CxXfAO2sX/wwerV/Z7M1lgKX6XsLd+30IokiTRuwha5tViG2jL25La6x/gpgJqyYS6AGEhg5M4L0jYYIA3EF2klbjYwxVcKqOMm6R7jp9BHCMTcv0kZe55OuGsYnx2pINlnUiEhAyMLFSVGa7FQUfi7bse6FEAtBfGcE5Z9iIB582b/z32FfJJJ4wVU15oSgPj2yNGjbeCcmWDphM9KsQT8Lb6LwuaLv+sbl5SCRMnK0vs8Ll++HOvXr8epU6fQ3NyMu+66C+vWrcMjjzyC1Y7yyezZs7Fs2TKguRnLly7Fbs96uG3bNsyePRvz+/aW973vfXi45tl929ve9srn+v5+sExVkVYUxWcArAFwE4B/BPAmAI8C+O+BP/smgK94fuf/LcvyopChKIqbAPwcgMWouNk/KIpiflmWV1bfydZW/4a/alU/GNLaqFH+ytdaUKddsJ96yt+eNwVQx+gQFl/SgsAjmvZ2/UYi+SKosmxuCxb4jzKZMbds4Lt3+68tBZzzd6Vsd0oW3gXU5BFu29ZPc9D6ysG9vfNO4B/+oV77lQDRAiw4Hm4AklI0Rhk4N9DIKXXHohxL0ZgELDhHLNfFjdtVa2Hxn0Xyi3PenasptAPqT7/wQn+9AJBXTWMgSjlS8V/KRu6uU0zGWHSoeSKTg6PPTL6rQ837mgu4Wn2FssrnztmaeYWoFc3NNvob9+w77qj/2fDhtuQa56JUBG8B1ATNv/mb9QmO9euruaHtLtnbW53ItbbWz8vubi9AHzZsGGbNmoX7778fq1atwtKlS/Hggw/ihRdewCKHRtdcc1LX2NiITs/zXUaCAPpobGxEzyVUCtHyB94B4HUADpVl+YsAbgEQRChlWT4M4OXQ79TYWwD8dVmW58uy3AVgJ4DblX97+di8efUarkB/AxVLJHjokP84zRIt0zo7/YtVCqiLZZWt/DyfL2aLLG3Rb7216qrkGgGQJeMqZfRZUe7LGEi2Y0e4WNKahfdZzizpQKgVLkWHGSlXBzpk3KhdsEmOvo+6JNmPflS9upKJKWMvZc5TMnVSMJMCeCRf5BVbgAXntdtdkRucRRFo+/bq1e1ISGUCy33MSWGIqXxY7qMUGPEzXBAaMmaT3SA25USS890NDnidVPjRGMGcVEyXQocYbGpFWdoKxwmYfXtrd7c/GSWZlNEHqkDVsn+TzkJaWa1ZM9TEHjmk7hJ93XPPPfj85z+Pe+65B6tXr8bXv/51LFu2rNJ79vnq6roIm7S2tuJU3wn4woULsXv3buzcuRMA8Jd/+Ze419VwHwLTAurOsix7AfT0dU88AiBVh/pXiqLY1EcJIQKaBqA2LbOv770ryyQgxqyfBbju3NmvKlFr3PQs4Lwsw1SUHCA4Jds9fnxYNs/iq7nZn4VmdsuyKD78sH8DScnKSIses34W6aPB4Inn4Hbzu7jjTw1d3zyWjCDEHTderyXIkoIGZmIsqgISqBvI2OcIZqhW4RZLpgS4DODdtSWFq8znzU0KkNNtaU2cU31EAmIpvhhIupraAwmM3P2D94LBocYYzLjFWA0N1dptqU0JAdeGhrQTo5z8Yinja/HFYMqn1HP6tL/wUTKudT5aS0NDvqLESZNsOtQcjxw61IkUkdWrV+PgwYO46667MGnSJLS0tGA1k1RS18Waz3r/+9+Pj3zkI1i2bBnKssT999+Pd77znViyZAkaGhrwkY98JOm6cpo25bCuKIpxAP4UlcrHaQBPJXze1wD8HoCy7/WPAHwAgO8ue+9aURQfAvAhAJhpaQ5wKezZZ/0bK3nFXV16Lq8EXOnr/Hn9wij5uusu4G/+xib0nzNDfeONfumfFArDnj3+LHQKFaWry79o9EXD2L9fzwuWdLvJbbUcJ0qLMYGsZRO54w6/JupAdIJzgHNqHbu+CBI2bgTe9Cadr1h3w5SssuuLmVY3qxsyFte5tJacxX8p2VvOh0OHLtYXZrbPQmGINSHKQZFh4eXKlXpffBalDqGWsSeYdIFYytgzkJS6eqZQUXyyZkVhU0UJcZWbm/vlUjUWA9QpwYx07y2+GDBK9T8pfH/f6fKRIxX9UmuhsR89Op9ih1BIGDUfbnC0o2vtda97Hbprnvvt27e/Qh/Z/dRTQFsb2trasLkmGPnEe9/7CtXs7W9/O97+9rdf5G+D27wIuIgzvWLFCjxEWddLYNqixP9QluWJsiy/DuD1AN7XR/0wWVmWh8uyvNCX7f5T9NM69gGorZ6ZDsCrJ1aW5TfKslxRluWKiS7Xb6jt3LmwDrVlE5GyypTKGarivyVL/IVO3IAtepa9veFOiZbxeuEFf1Y5BZxLY8/jT19luWQSaCPAt1TJT5ni3yTZ+c8i+dXU5F9EUzjBXLBycJWlAsecvhjEMUCy+JIau/gKiCXj8+Oqj6SAOmYhc8jmSd9xIEDf9UU6lyXjGqNpWKgoPJVwpQm5blkCIwIxN1hPyVDzNMelJ+XmKvf22lqi5yz+49j6khFjxuTh6AN2OgSlSyUJvhQaUI5W2iGKTGdnfydai/nu4/DhtlMLrvPWpnA+49hK+2DOgslLYLHGLgv7Xm/jPwDjATT1/bfJiqKoJZ/+DACGIt8D8HNFUTQXRTEbwDykZcCH1iQglkJhkEBwCkAcN86fCWVVtctzDFlzsz8yJaCwqGk8/ni9fBXQH3lbHqac45VTh1pajMmLs/As58zxj31KYLRjh//aeOpjARax8copt5ZyjO76ImixaIDffXf1KjUfsFBRuKm685XUmdsN5SPkqUvNRVIK9nJylXPI5jEAceckP8MSGElUJz5Xc+fqfbEltZvxzalDTRsqX1xbfAXyZ88CfVJoKqMP39rS3GxLxvAky6cx3NIiP6c+C2XOrYA6pkOdi3N++HD/qZ3GON+NWWWv8Tv4nmGJeikZP9f3+blam19Ci4UY/wnAB1FRM1wrAdwn/WFRFP8DlTJIW1EU+wB8BsCaoiiW9f3tblSNY1CW5ZaiKP4GwHMAegB89IpT+ACqSZEr45oTnM+e7dcVZlbLEjXv3+/PBBOkWCNw34N0xx3Al79s6z4XA9Q5JPhSAOLKlfloLd3d/vnFY+IXXqgUZTS2e7f/sxkYWfSLpbElsLAs1jm53VQGkdpyp2Rv3U2XAeETTwC/8As6X2vXVq/us5LSeUw63iegsGTOYzrUKbq3Oeg2pNW4c5Lzym3XHTIGsi6vPyUolYIGzl2f0oNkIZoGkAbEJF+W55EBhq/eoCxtVBSe7Pn2iK4um7oN9y5fINvWZqOihAKQ1Ax1Dl98hn3qG1YQHCok7OpKS3r47n1jow0Ih75DSs+NIbYgoC7L8oN9r6+1Oi7L8t2et/8s8PufA/A56+dcVtbb63+QWHhmeZjmzfNPttSMa0iH2rKJ7N7tP55htvvgQb3EU6x5TQ4QTBqEBSBef70/a58y9o2N/qx9CtD/0Y/8EkoMcF7WiupAHi9+N/foOebLZ2xIYCn+y6lkwmy7BOosY08g5j6TOZUmCBIsR/ISt5ubsaXOJKYBbvmOK1cCf/In/bKVtJQMNee3+/kpyhwE0m69Bdecf/1X4FOf0vmK0SEsR+IxXxZVFGb0pcLPHMWSKb54kuA7UTh1ynZaFyuWzCXBN3WqTZmD80jKkFvmKr+bj9qamu32BTNWbewQCLYG3SGg39JyxVE+gk98URRvC/28LMv/mfdyrnBrbfUfqdx+O/BXf2Ur/pMagqRkuzdu9G9gKdluKXOeylX2GQHFnj36TIO0KJDj6juylGz2bH9WmffPEoHv2uUPQFLpI7ky59J4Uclh0ybgp396YL5SAra77wbWrat/n8fEbre8kBE0Sdxuy3gxEy3pF+cA1Mz4+GhQkkmZc35ni1wkJT/d0ywW/7nd8jTX5Y5XSgDC+eAGuTm53QPhKkvA2aKKwuvx0R5GjKhv0hIygjnet1qzAjFSKnwFqanZW6lYMhdX+eDBik5o9eW7jyNH2qgo3G98XTJHj7apOjGQ9DXsamhIk82T9tyc2W6LhXxZ58RlYLGc+r/t+/dLqLLL7+n79/8B+PnBvbQr0KZN8xdcpGy6hw/3d06rNWb9LBW+XV1hLeScoC6HLwJQSfvUZ8uW+TMyPBK0+Orp8R833dZXNmDhWe7e7c/25gTBKQV70lxMASnTpvl5cyya8fEcJStL/yaZoqYh8TsHQkXJWbAnZc5TGhFI2W4Lx5VgwK23SCk+koqnCU4sgVFMySSHBrj7c42FAOKFCzZAzSJJ3+metfgvpON/3XVpOtRSjUAuEGwFT9Kc4DVZqCic9z4ZutOnbbUWEmUNqE5rLHsHpSd9Gf1UHWqfWbnKMR3qlKyy7z6eO2dLCFwGFgTUZVn+Yp+aRwngprIs316W5dtRdTS8Zq7FdKgtVbn79/cXHNUagYWl+E/idjNatnKecgHq8eP9OqYpYLOx0V+pzMINS+HS2rX+jEzOlugE/xaOa+4Mtc9XCjifOdN/AsBN2KJDvXWr/3tw87Co20j3iWNvKf7LmXHNCaiZNXaPmFOuSwo66cMSGB065P98Bl4uFSRkEghOeR5zFuyxiFRq9JQCEH37R0dHv5KOxig75ts/hg+3cfVj2VtfFjzFF2Abe34HX22QFWwyyPN9l6NHbRx90lZ8zVisgVGI1jJvnk3VaTAau/gs4P9zn/scFi9ejKVLl2LZsmV48sknw8WSjg61aydOnMBXv/pV7VVfEtOyvmeVZVnbGeMwAKUQ71Vk27f3V37XGoGFJdqSQDALOyzAQgLBzFRYsn45M9QzZvgl+FJ1qH1HYznBJkG2heMqLewMjCzV6NJ1cTGyFHHceae/6DOFX3zuXBicW8Z+717/fWcw6qODSBZrhJMCgl1jd07fPJaM1ApJBi4HxzWF9/zEE9Wrm93jvbUUjUlBw0BafPuAYEODvhAX6B8XSSbMMl5MBvg6tFp9xZIuKWotvvHq7OxXyBior7Y2W8Y1VCxpBcEMin38Zqsv1p749lSrL3KUfdSHnTsBj26yaCFA3dpqk7oLAerGRtvewWfYQGF9/PHH8f3vfx/PPPMMNm3ahB/84AeYEVszI4WXuQF1jhbl2lF8qCiK/1MUxfuLongfgP8N4MEBf/qrzXp68rX4lkAwM66Wzn8x9RHLwr9woX8R43GZFZz7MjIpIHjfPj9FJgVYSGPPxdKiQy35IqDwFRlKNmWKPyPDsbe2pfct1CnjtXatP5hJAeexzHmOLpXcOFlIqzEp88L7YTlpmDat8idluy1HpqRWuJYCziXd7py+OI4PP2z35QNiVjoKkwhUgKm1YcNs95Fz3rdOWYEYffn2CKsviVcPVBQGS4OeEEXGmnElCPaB8BtuSCtelugjlmeIAYbEE7f4CtFaenpsHOPQqcWJE/46H8lC2tEtLbYT7wQd6oMHD6KtrQ3NfSdUbW1tmDp1KtY/+STu/dCHsPy++/DGN74RB/twzZo1a/DxP/xD3PPBD2LRokV4+umn8ba3vQ3z5s3DJz/5SQDAb/zGb+CFF17AsmXL8Ou//ut46KGHsGbNGrzjHe/AwoUL8Z73vAdl371bv3497r33Xixfvrzuc37rt34L9957L774xS/qx0Aw1YiUZfkrfQWKq/ve+kZZln8/4E9/tVlu2TyfrxSwOWaMX4eaQva7dtU3OpCssdFfpMHjMkvh5fr1/sWK9AHLZpmTinIpeOKUutuyBXjnO3W+Zszw0yc4vyyb7o4d/iN+Hl9b1CFyKnPEChxz+KIP0hI0tmpVNV8lszTo6ejwzwlmOql5rTF+B3fTzanbneIrBCysvgjAfAVdvb02Pd4Qx3XkSFtLdGYbfYE8r01rMTrEUEm3kaLjW9f37rU9j9yDfKdyVlBHWssLLwD33HPxz8aOzdcSPVVNQ/JlAech9RHr2NeezKxZc/HPOjuBN74R+Oxnq6TRm99c//fvf3/179gx4Gd+pvq95ubqntXSkUaM8O6Pb3jDG/DZz34W8+fPx0/8xE/gXe96F1atWoWPfeITeOC//ldMnDcP33nySfz2b/82/vzP/xwAMHzYMDz8p3+KLz76KN7ylrdg/fr1GD9+PObOnYuPf/zj+P3f/31s3rwZGzduBAA89NBD2LBhA7Zs2YKpU6fi7rvvxtq1a3HHHXfg8sDKPgAAIABJREFUYx/7GB544AFMnDgR3/nOdy76nBMnTuBHlkZTAVMjlj5Fj2uqHiHLrYAR0qG2+Jo82c/zIxXFAgYOHfLzZVl458tUSiZ1SmSmwrK55eQXx+6jxddtt/kzHym+pGNynlZs3gy89a06X/v2+YsluRFZuJHS2PNI0nKcKLVqT8mS3nCDn56T2nDGt7Hx1OKxx/S+nnjCv0nn1ELm2A+VbB5BuNTkweKLsmG+daenx9ZKmyDYN/eLwkZFkcYLqJ6fXDrUOdU0ANvY8/RLUhmx+GJG1SfdduJEmg61bx+cMcMvNSdZKACxqmnk9MVTFAoRuL5Siv98a2tvb5o6l+/zGxu96+ro0aOxfv16PPLII3jwwQfxrne9C5/85Cex+fnn8fqPfhRoasKFxkZMqcEpP33ffUBDA5YsWYLFixe/8rM5c+Zg7969GOcJzG6//XZM7xu3ZcuWYffu3Rg3bhw2b96M17/+9QCACxcuXPQ573rXu/TfPWIqQF0UxZ0AvgxgEYDhABoBnCnL0nP+fBWblFVm5smScZ0xwy8ZlwKoYzrUFl8SoGbhhqWAIxY05KBpMLtl4bhOnOjPwqeqMISOqi3f8ckn/dkwHiNKmTKfSePF67FQUSRATTBnURUA8lE+pk71z9UUcL55s/+4NicVhRsUs28aizXV8VEbYr6kTKEFDKxcCfz93/tPxqy+YvrqFl+U3vOBgZMnbaooITrEsGG2ArCQr9GjbVQ6Fqv56CvWLGmIdpAqwec7GTp+3EaHCGWCrVSUEAheuFA+ZfEZ9w0fr9469gxGfRl969izfquzs77A9dln+8dg5MhwAWxbG/C//ld1MjBpUv2+2tMj7o+NjY1Ys2YN1qxZgyVLluCP//iPsXjhQjz+1a9WNUVO8N/c2go0NaGhoeEVqggANDQ0iHzn2t9rbGxET08PyrLE4sWL8bggpTjKIqkbMW3q6CsA3g1gB4ARAP49KoB9zWpt5Ej/wrdsWfVqEedvbPSDgZTs2rZt/uPqFEWHnNlbKQAhKLdwXCVfbOji4x5LNnWqH4jw2NNyNLl7t79JTAo4j/GLc/hiFumZZ2y+fJYSGN11lx8IcFOxnFpIJy8pIPjQIf/45gTUnL8Wma6YL0uDHgIxH4AYPhx4zWvs15WD8sG1S+IX51BYGYgvHxA7c8amLEQgJtHpLKoofFZyKGBwHfCB4Nw61DlkLIEKuIfoWZbrGjXKporCgmNfMmzCBNs+xLXYl9ywZqhz6jkndF3ctm0bdtQ07tm4cSMWLVqEo8eO4fG+gtzu7m5sqd3zI3OitbUVpxTiDAsWLMDRo0dfAdR1n5PRLJSPnUVRNPa1BL+/KArDGedVYuPG+bUsU4DFyy/7Cw9ZeGaVW/NZThCcE5wzU2HRjl60yL9JktZiyd52dfkfZGrE+u6xZAcP+tVdUkCwNF6DAc4tc3X6dD945WLnU76R7MIF//xiptMSlD7xhD+7yXlipaL4bCDKHDl8NTWFM6EWKsr111djIp0aWa4rpGbQ3Gw7MYppR+fSL7b6CgGxM2dsFAa2l/Yp7xSFLXvLOgvf38yda2sSI3Wp5HXlGvucLb7L0jZXOR6+cTl2LI0G5Ftb5s2zFRKSyuRr9GQF1Dk7DiZI8J0+fRof+9jHcOLECTQ1NeHGG2/EN77xDXzo3/07/Oqv/ipO/tEfoQfAr/3ar2Ex67nOnQviiQkTJuDuu+/GzTffjDe96U34yZ/8Se/vDR8+HN/97nerzzl5Ej09PRd/TkbTAuqzRVEMB7CxKIo/AHAQQL48+avFJGoFK/F37OhfOGPW3u5fkMlxlbiJPovpUFt9hWgaFlA3bpz/aCyFDgH4vwcXI4uGrgQAOYZWQX3f2LOxhUV2KicIjoFzi68pU/xZePrw/Uyy55/3Z2S4iOdQWGEGz8JxlcY+VQEj9AxZ5tftt4fBq1VpQgoyurv92rqSETj41sORI/MB6lRQJ2WoLb6YhczRZjpErdizxya5yv3G96wMG2YLJEPAdfx4m+xnTn4xT299lCLrfeTJoy97fPCgDVD3Fchh505g9eqLf2b9jiFayy232OQPYx0JLZagQ718+XI85gnu2267DQ9/4xvVPliDBR566KGK+nbu3Cs0kYt+1mff/va3L/JX+3tf+cpXXvnvZcuW4WGPstBDIXpLgmmfrF/o+91fAXAGwAwAb896Ja8GO3SoX8u11vhgSN2mfCYBMYINS8YV8Pu66abqlcdUA7mulCxpW1t/c4RaSwHn+/f7M/qp2Vvfd6R/LppaX75Fhou3pGFr8cUCNAsVZflyf6Y9ZbzOnPFvFCm+Dh/2Fy0RUDz1lN6XBHJTAqNYl0pLYDRnjp/OxXtrzXaHOJ4WX08/Ld+rnp58HeOKwn+PY7588/v6622qKKRU5OCJ89n10TSsoO7pp6tXqVgyV+b85Zdtsnn05RuvadNsHP2clA92JPZRwKzZW9JZpLG3+OJJne9+bdxoS+yEApDWVhu3OwSom5psQVZI+aX2swZ6XVegRTPURVE0AvhcWZY/D+AcgN8d9Ku6Ui1na2gJuFJuzbIo5tShnjnTn2XncZkFWPT05KMwHD/uzyTkpFakFOxJvjgXLNnbyZP9QRmz3eTqa0zSAE/JUD/zjH9McmZvc/riIm4JjJqawprpvqN6ySZN8gNqmmVz27QpHKjnCBqAdH6xz06csFFRQlSBpibbdd16K/B3f+cf/7FjbS3RQ8f3VhDMbLIUgOTKwr/8chqFQWqqY9nTmMDxjbFVQz+nDjW5vb77ac0qh8artzdfa/sjR+LFurXGcZJ0qC3XxTXVsk5JxrXr7FnbacdlatER6eNMT+yjfFyzmIW0oy2LT8yXBSCOGuXnXLNohl26tOajVvBhsOhQ79zp73zH7K0v8yNZTn5xziy8dF2UF7TwiydN8ssfpgRGL7zgLzTifbS2tc059rkAdayA1tISfcUK/9gXRfXPEmSdOCF/j5aWqoul1o4eDY9vjmJJ7c8HyxdPUnzPZEeHLevHz5UKmC2AmgFZjsYuMTWNoVLmIKXCtxY/95yteHn06OrVF8y0tNiylDyp8rVXv/76vFSUXI1dcvp66SUToC5DMpap+ti+eT9qlL1/hGRDnLUuLWPSZ9pvvhvA2qIovoeK8sEP/IL5E1/tlgsEl2U4g2gB562t/UdktcaF16IEcPy4v0iCPiwgRQKupIGwCHAgvnKCuhRu9+LF/iAjJRPc2elfgFj8Z6lsP3rUX7TEzY7qKBqTMsFcvC0c/ZwZ6htu8H/HlPsYolaUpY2K8swzsl67tfgv9LvWRiWSBjhgz1CHAJIV1I0fL2/SZ8/ausbyPvnWirK00fJCmeD5821jH6JW5MxQWzOuLNzyFQNbgRgpQ75nUqJ6Scb9RpJKtcyJnFSUkC8roCZH37cPNjaqfbW0tOD4yZOYAKDwjdeZMzY8wfvn21MtNBQgTkUZIlBdliWOHz+OFkt7d+gB9YG+fw0ABGHRayaCYIITi97huHFVdzbXUsC5RK1I8dXR4edSHj5cvVq6lsWoKDmL/yzgfPx4f2OAFHB+4YIfDKT42rIlfMxmOQKUeOJc4CwcfQkEM7u1YoXeV0ODLNvGz9LaxIl+Sg2/t1WHOjQmuTLBXV1yO3HJl7TpjBzpz6qnXJd0XyS77bZ8xZJHj+YD5zxJ8M39vXvzcbubmtJkzSSeOLO7Glu8uNIA93WWzJntbmiwrV8savVJnR0+nC+YaWhIC0p9IHjlStsJCMfclyG3UiSYiPDhBgM4nz59OvY9+CCO9vRUf+POpcOHK0DNzskxO3my/5TN3XOOHKnqXbS+Ojqq5EJPT/0p38svV4GT1ldma2lpeaVJjNa0rcev8aY11tTkL9Lg8bmla1lZhpuLWCLKI0f8xZKpjUpyZuF9vniMt26dvi235IuLh0X/87rr/LqvzDRbAiOpI2EqJ9gHznPSIZh9sBzlSr5SgOstt/QHZz5fvpMWyTo68tEhjh8PKy1Y6RASQOzp8X//FF+9vTbpyQULZKm3yZMrRRGthTL6VhC8YYO83qVmb3P44u/6nskjR2xcZQafPoA4ZYptzeFa58uuWQE1m2GcOVOfZEgF5zky5yFe/bp1to69IV9WKgpriXwqNpMn26hhPAn2PcOGsR82bBhmP/oo8Hu/B3zzm8D73nfxL7zjHRVo1Y7/f/kvwG/9FvDVrwK//MsX/+zd765ojNp58d/+G/DxjwNf+EL1Wmuf+ATwta/ZOjkPsRnILtcsak1N+XSoOzv7CxBrjeDcJxwvmQQ2U46+LwW1gg+jQrT9FZs5058JJUD08YUl6+ryjwkLzywFNO3tfl+pY59Lbk26jyngfNo0/zEur9VCRZGKJRsaqn+WluibNsmAsijyUFFoOYola3+utZYWmQ5x4kS/eoTGxo+XayCsVJRnnpE3wvHjbcmFWLFkzsLLFIAoqTFZpO6WLAH+9m/9ILgsbb5CdIdbb7VpWjMZ4PuOVgpDTP4whVqRg/fM1t4+/vyBA7bTulBGf+FCGxWFDc58wYGVWhEKGqyZ8xitxWLM6PtOhJ980nZidBlYhjLNa/aKSdQK0iAsWb/z5/1cZWYyLGAACOtQS+2BfZYTUI8e7c8Ep0rd+RYZVs9bOiPt2uU/rs7ZEp1Hgqx81/oKgWDLeBWFf0FMAdTjx/s7hHK8LBvS9u3+eQ9U15yjvTpQnf5YqCi5QV0ucH7LLXKTJ+t1HTsmZ4Lb223PEI9xfSbNF8liVJQcDXoA+3jdfLP82TmpFc8/b6MBsXW9JGWZKxM8dWp/XwSLrxz8YkoWDpAOAaA/iPEFk/v327LKVK/xFUs2Ntqpmvw71+68M1/hpYGPDSBOA7IYgxhfvYG1D8VlYNcAdU7r6QEefVT+uYUjBvgnJ7O2Fk1YCYgRzFo6ZwHhYknLgjFypF9mLwUgHjvmlxJMbXriGy9ma3z0Gasv0nl8PEerL24IlmPhBQsqnqtrKYD69Gl/1iuF8tHeLp9MXLhgb4kuAVdrxjUEzkeNsqmizJkjA8oUCkMuHepNm+Sj8s5OW5e30NhfuGA7fQr5WrCgyrpqbfTofFSUMWPk7o1WCgOpFRJ1KldR4v79csBq9XXDDbbi5RigthhrYnwnVlZAzZNgH0XH6osnCb459thjtpPSWEt0i4UA9ZQptvbqPKENncZbr8v3d1Zfl4EFKR9FUXwZgDibyrL81exXdKUaH7pQ9tYacfkmFDN0lLwbiK+UjOvYscC999a/T86YhQ7R0+P/7JTxOnPGrzCSAs4l4Mr3LGBA8sX5YjkCbGvzF5kxs3LLLXpfUkY/hYqyfXt4QbZmb0Obay5qxblzNnA+fLh8KjRypI2KMn68XEDa1GTb3DZtkpV1cmbOc3KV9+61PUMhX9bAaOlSuVhyyhSbVOehQzLYsmaoQ0pLObnKR4/aOKkhX2Vpo48sWwY88IA/iXDnnTb51pAOtRUEU4fal/DKSWtJ9eUb+337bHQIBj6+E4XFiwFPF0HROOY+epIVBFN1Z9u2ernQWipjDs3rS2Cxq1wHYD2AFgC3AdjR928ZgCsvHz+YFjoGSen8J/lKKf5ravJ3Q2SWm9kRjUmFcdyILDrUx4755cboI0f2NidPPIWrLFEr6MNylDt2rL/oNSUw2rOnn6NXa/zelMvSWE4KQygTzM/K4aunx6aKsnixXBDpq3YPWXu7zImdPLnqYqm1EFfXCsRigNraAS2Xr8WL5ePtgwf7AZHGpEASqMbeEhht3iwDylSOq89S7iOQh/dMaoUP1G3YUOnZa43rus/X8OG263rkkerVF5hNn25TRYlpR1ssJ1c55Mvajp6UCh89zBqUvvRS9eqjwviUyUJGillo7K39O4bQghnqsiz/AgCKong/gNeWZdnd9/9fB/DPg351V5JxYc1FhwDyZbsbGvy0Dm54lgfz7Fk/EONxmeU4kdfmGgsUfEdKIculXyxdV0q2e/p04I478lxXZ6d8LAlURRxa6+iQF/imJhs/TwpAeG2W48kYELOM14wZ4d+3Zlyl73jihK3r4nPPyRla6+YWAsETJ9q0kHPyxEeNktt7p1ArpMxxR4dt/XrySblQtafHtnmH7tNtt6Vlgn2WmtnM4Ys1HpIyRwq1wvc3L71kq49gNtmXrLjxxqoORmsx9ZGcOtQWI5XJVyyZCs59f/foozZFGlIrfc8RA5lYYoQWGi+C/yuIS61V+ZiKSn+aaZjRfe9dM1oIUPOYhdF+zLjZrFlT/7NUHWqpQAWwt0P18cC4eVg0OyXd7tTiP58vAkNfu3TJRo8Oc7tzNATh2FuAxZ49/g2fC5dFIi0EggGbdFuMX2yhojQ1+Y8SaZbxGjs2H19269Yw2MpFazl2zHb0HRr7cePyNOgBqvlq6YC2eLFMY7CO/eHDcibYmr09dUr+7K1b81FkUgIjyWbOtDXMWrZMbjSUCs6llugWX9wbfL4OHbKtXyHd7rJMC4x8vlavtq2FPOHwZcitxX/cI3JQK0jpOHCgvt7D2jwlRGuh7GZPj466FsrCkz46xB0TLaZdIX8fwIaiKB7s+/97AfzOoFzRlWp8UHzUilAlq89CD3gKCO7t9RfSpYBzIAwQc/DECc7XrgV+5Vd0forC/1CGxPEla2nxq4/Ql4WKcuyYn++es1iSlstXT4+tJXrIlxVYzJ3rl1ACqkylRS6yoyMMzi3X1dEhgx4rQAyB4PPnbRq6IVDX1WVTKJg/X84qz59vU+aI6VBbgMVzz8nfw1qwF1MMsSoLSfbSS7axHzdODlhmzLBxlUeOlMGMFYiRWuGznPziVIqMz9dTT9kCkBCoa262zS+CVV/ybOZMG8WPJ8G+ExjreDHAkFQ+AD1XOVTgWFvgaQHUoTlxBWWoVecGZVneD+AOAH/f9+8u0kGuWZ9xcvl4ltaJweMXH7WCHFpt1i/E7R4MKkoOX3zPUnTR2urP6NMsVJTubv8RGMGZhV989qz/KDNFAaP273w2VFzl66/3Z/SBKjiyaCGHOK4jR9qoKC+8IBfvDh9u4/uHNpuhLP4bMUKmQ+zf3y+hprExY+QGSNbAaMMGueB2xgx/LYBkObWjc/LEQ63a29v7JTs1dtNNsnxpd7eN1rJvnzxmd9/tbzoiWehzUwF1Du3onIohlM/0zf3du9O6Z/rWsAULbECY+3+I5me9Ll/AbK3x0oBgbQDIlva+Ysm1a6tXS4JhiE11V4qqAfxPALilLMsHAAwvisLQNusqMEaAvoWMmpQhSb1a4yLm25C4eUqZJOm6fA8gF3DLsTCQrzV0Y6Of251KrQgtMpb2pe3tfgUI+rd8x9q/c62x0UZFiYFgy3g1NspALIUvK7W47umxHeW+9JLcvr67O59025Qp/Q0dNBbjdufKUFt9LVggS/al6FBLvN+9e6tKfK1JUopAtYlq6W9A+D42N9tASixDbQF1S5fKOswpAFH6Hps29ReCaWzrVpkT29iYT61l9mxbD4OcY09qhcR7thh9+ADigQO204EH+w7xJbpTSkt0XwBCpS3tmIV8WUFwTNPa4ovBne/0i8+8NUk3hKadeV8FcBeAd/f9/ykAfzwoV3SlGrOQPmoFJ5mW1xXiYxNs+zSXrb64GWg1dEMPZYqaBuCnwaT46uz0A7GcKh98wBk5D8QXr81SjS7xxIHqfUt79cmT/cWSNMume+aMnMWxgrrTp+WCvfZ2W8Y1JxUl5GvyZJuW+w03VFrUoc/SWk5qxfbtsr796dO2jGtMsjCXDvWyZTYN8FCBoxXUjRwZDkotvh57TKaI5Mycv/CCPSiVbPZsm8xg6Hmz8POB/pPgHNluZoJDXWi1xj3eB/TXrrWBw1BWmfRD7doayiqza6nW1+19uVTfSQfvhxbrMPALjb0loBli087iO8qyvK0oig0AUJZle1EUyhTpVWIh+RcrHSLEdyKg1upQhwC1VQaOi9R999X/jLxiX7MQyS5c8D8sqRnqY8fy+ALCC6mlej/kqyz9HbUka22VpdtaW20Z1xC1ArCN18GDeWXzclErQr4OH7YpczQ3yzz8sWNtVJTRo2Vud0uLrQvqc8+FtZBzUVFSuMqSrx07bJtkrPjPcl0LF8rP75w5tufxwAGZEmEFdZ2d8vew+gqNx7FjaRQGn3V324r/VqyQtd/XrLHR8kLrlxUEU/ovh2xeqFgylavsA8FMqJ0/r6OuTZ5cvfoSOKxL0Y4bn8UQ3UaLdZicOny4PilhBeeXgWlnS3dRFI3oa/JSFMVEAMZz71e5hbQsUwF1jsYbnOC+DBqzRA89pPMVqvjmAqIFA1x4fPxa+rC0tQXCC+JQcZWLQgZPXV02Kkpzs8w9bWiwXdfRo/JnX3edrUHPpQLBuYv/LFSUWbPkgKWz0yb5FeoGOW+eTS7y7Fm5A2uKdnSuVto5dagXLerPorn2wgs2OkQIiE2ZYqMwbN8u8zubm21gLDReKYA6l6+2NpleuG6dbd43N4c7S1rWrwcflH9/zhxbxju0r6UWS+bgKofAOU+StNx6ngT7Cuo5H7TXRd1332e/5jXVq1YEICcV5TIw7RP/JVTFiJOKovgcgEcB/D+DdlVXooUywdYsaQhQW33Rh49awcVNO2G5cYcaKeSgovA7WhQdgHwgOKevUaOqQqAcvs6fl7NrHR22Bj3nz8tH+CNG2Kko0ni1tNhACpAPUE+a1N+ieKC+Qhz9/fttcpEvveQvOAbS5Nak65o9Wwaikq9cQGz0aHkOpVArpA365EkbfeTpp/ulvVw7d86WvQ2N1513+ptoSBbrBmmxGFfZYvPny8+v9bp27ZJB286dtrEPZS3nzrVJrWkAtZVaEQKI2owrOwdKEnwWX9xvfePCfUPbnIoBrA83kAKkfb5DWXhSSrT1YpeBqcK4siy/VRTFegCv63vrrWVZGlJrV4GFaBpckFjRGjMW7Lz2tfU/s8qtcdL7HjwrOCeg9nHwuBhJBWXSdfkW5aKwNfEItaEFqjGzUFEaGsJg3grEcmkhd3TIcna9vbYNKQSCz5+3tUQP+ZoyxZZxDfHKUxQwpGfOmiXdtUsOZlLoENJ47d5tAyqhzOaECbbj0pAvC1cWqEBNaLwsY3/okFzklUKtkNaVzZtt8z63DrXka948uw51SGYwF0ff6mvnTjl5c+RIPsnCnp40rrLP7ruv0nDWfk9SK2IZV00Gl2tEjuwtT6F9xapWX6EsPGXz2tt1MpshX0yGWJI7Q2yWSoCRAEj7MK6uV4GRx+QrNmKxmCQt5lpOqTvyitetq/9Zzsy5FeiHKDJAtYBRjF7rS6JWNDXZAEFZypm9YcNsVJRz5yqeq2Q5mtek+AJkXydO2BQdQr6sYHPixH4ZK9emTbN1/jt1SqZ1WMF5KHtp9QXIgPrsWVt2LRTMnD5tb08sHckvXWorZstZLPnii/m4yjmpFSFf27b5azokmzBBpo9Mnx7WU3etuVn+/eZm2/x65BGZ1pEzc57T15NPVvdG261Pc12xmhPa3LnVPPI9k1y7tOPP5FSoYC+H1J2VqxzKwjMg1RYwh3zRXm0qH0VRfBrAXwAYD6ANwP1FUXxyMC/sijNGnL4N39qTngsxiyVqjeA8pNBQa6HMeU5AbT0aYzQcOoK0tEMFgHvu8b/f26vnWfb2VguxBJ5aW21UlN7ecPV+LiCW0xdgA+etrf0til3bvx9Yv17vKwTEWlttDXqOHJEDg1GjbDrUl4pfbAV1I0bI6i4vvihTSyRfUnGlNeO6ebN8WjV/vv60Drh8+cUhX+3tMrfdZ3Pn9mc3XevstK2Fe/bI69fq1baMX2jPStVC9lkKVzl0OgDogdidd8oJF+7B2nvZ3S2PC+uYtONG+mRov82RVbbSRziuOXyxJsg3J9nt09JGfohN+0S8G8DKsix/pyzLzwC4E8B7Bu+yrkDjguebSHwYtcV/5AT6MkKMMLVFFxo+trYDWoimQbNyu0PgVOsrxIEDqnujpaJwsdiwwf9zK7AIXVdbW3U8a7Fc9JGiyEetaGqSwUBPj00V5dgxuZvYmTO2o+8QCL7xRlkxRfKVSwEjJzifPl1uNGQFiMePy1nSbdv09RFA9cxJm/2kSfma6owaZStAC91HK6hbvFg+MUkBm9Lnb9xokyzctUsO4nO2RLc2KolRZAD9fJ00SS6At4K6hgZ5DrHtuPak58EHZSDP97XXxbH3zSU2MdOqC9FXqBmLtVgylO3W+iJP2sfTfxWrfOwGUHuG1AzAkz69io1RlE+KK5X3HNootLJ5IWpFSAHEZ7z+EH3CCqhDRVNakEJ+paRaYQGIsaChvV3foCfG7Q4dzUoW6iJoaZbR0tJf9OJaCh1C2vCtALGrS+bLHjign/c0CdhYVQVCIHjuXBsVZdIkWUXFCs5zUiv27ZNPckJa4z4LgeDTp+V77LMQCF6xwtYSfexYv9IBYB+vULfNxkabryeflAMWq68QcN261ZY5D/myFLzGfDG5owVic+aEu3oC+uztzp0yaEvNBPuMilZaKlDIlxVThCgfs2ZVr1qFrpCShzWYYbLFt1ZcgYA6GNoXRfFlVJzp8wC2FEXxL33//3pUSh/XjDYY1IpQAxXtUW4oQ833tYsYucN8oFxraekXfY8ZM/qhxd3aqj3UotQazEjj1dtr7ygl+erslBUHfFYUcjZy8mRbg4sQJ9AKqM+cAbZsyeMLyFcEFQLBO3fauKTDh8vZoOuus4GU5maZh9/aaruuXbtkoJtzvHLyi59/vio0zHFd1ozrDTfI9ImbburPSGrs4EGZo2/NUHd3y+Obwi+Wxv7ll/PpiZ87Zxv7FSvkuXrvvcAPfqD31dMTnhOAfp3evVueE1ZQFxrbVK6yz5jAO35cpyZDaoVvzFjbpaUC8TuG8IkWUzz2WPXqG5NXG6AGwEq29ahk82gPDcrVXMkJT7h5AAAgAElEQVQWaseZE1BzsdD64kMiHW9fuAD867/qfMWoFU1NclGTayx0kZprNDfreZaxoCFnhtrii9clLVQnTugzriyykRZPK7A4f15WDJk1y98FK2S5ihL5Nz7LqWnd1WXzNX48cOut/p91dNik2zo6ZImqm2+WuxX6rKtLBgNDDahDviw2d658Kvbcc/mKJadM0a9fQJXNl0Db6NH24tIQpchiMZ64xSZOlE8T2KSlp0dHu2lslCXQavc1zT14+GH5vs+fD/zTP+kDEU1RogVQ5+J2h66L1Detlv7MmfI94r6h5emzyN43l+6+G/jKV/T7h6b78hVUlBh8Csqy/Iu+hi5/UZblz1+ia7oyTdPYRQt4uHGFjmC0vngsE5rgWl/M3kh85O5ufyGlz2LAtbVVT0XRUGSsIFjyZQF1/G6rVsm+tCCFnyktoHv22LjKZSlvlCNH2qko0kbd2jp0xX9jxgC33JLHVyijH8oS++zYMVnLPScVZdEiG0Um59iPGiVn4a3gfPhwWQu5o8PW+GHTJvk+njplK/4LgeA775RrAXymAWKW65LM6mvWLHlu12aCNYB692458GTx8JkzurUntAbfcMPF16fxFaOi5MhQW8H5a14j69tbfXV2ys8264V27dJJnLKjpc8fsY5Vt9sXaE2bVr1KFK3L0KLhalmWFwBMvNZqPGIamoZW6J8LgsRxBfSbLhfDUFGFdvJzMZQKXrq67FQUaSG2ZFxjGepJk/Q61HywJdUKIF+xpAWcc6OXNmmpjbvPuOFK49XRYdPjDfmaM8fGL25okKkV1mx3Q0NV+JnD19GjcttkK0AE5PHassWmzBECwW1ttjbmIYA4dqytwcKUKXLBsXW8jh6VeadWfnFPj3zfN2+2nTSEeOI5dahvusmW7V6yRKZ/WbOkPT1xoK9dd156Sa614ImltvgvNF5cK7XBUeg+UTlKK5U6bZp8mmIdr1AQb6VDPPqo/Lk5aS2kMO7fr/MVAtTcNyZM0Pm6DExbHr0bwNqiKL4H4JU0WFmWXxiMi7oijRs3Cf6uNTbKP3MtpENN04IBFrps3jxwXzHgmtPXsWN6VRR+pkStCLW8dY3XIwU/ra0ySHON2WQJBA8VFYWbqQQGDh+WgybJQhx9C7AYPhxYudL/s4ULbbrK587J1Arr0XdPz6WhVpw/b8+SSr5OnLABxClT5Pbqt90WrlFwLdYQxGIHD4abxFgsJx0iNPabN9vm6vjxMqCZNs02vxob5SwvTyy7u3VZ5SeeCCuG0JfGctMhJF8MfI8d0xWsaq5Lu4bNmCEXS/LEVctV3rr10nC7UzWtfcbAV9uSPpR04py3yucOoWlXkAMAvt/3+601/64ZjVk1kv9da2jQL7CstJf0F0eOlGkErmkoDNZmLJfCF6AHiMweSBn906f1kl8sLpOAyOTJ+owr77dErcgNqLWbbk7OOU2iVmzdajv6DgGxMWNsGdfOTvnIdNw4GxUFyEeHyOmrpUXO4OzYYeMXNzXJx6vWwOjFF2XpyaVL7a3tczZjycXtDl1XR4dd/lBSzeD6oR3/vXtlQHP33dWrNuOtAZs5AbUleyuZFWzeeWc/vcA1UrO0cp3nzsnfkSfP2nVn3z4ZTFpVUTQa4Dl8Wcd+9mx5vJgEtOwfQ2za1uO/CwBFUbRW/1tGNY+KovhzAD8F4EhZljf3vTcewHcAzEKV9f7Zsizbi6IoAHwRwJsBnAXw/rIshfPVy9SYQZEWhO5ufec/ZoKk4zGL7moMuLa06KkoMXAO6IEYN262F3XNAupiGf2TJ/WAmhuRpFphARYxlY+5c+1jnzNDLVErUrjdUgGptQ1wd7dMrXj5ZVuWFJDHa9EifbMfINylciiL/8aOrQBqDl8nT8oA/NlnbeC8p0d+Tq6/3t5eXRqvsWNtQDinDvW8eTK3O6cO9aZN1ev58zowduCA/MxZM64hWsuiRcD3v6/fjzRjrwXUU6bky96WpXyCyRMu7UnP44/L4JvfTasIFApAVq0CvvAF/al3yJd1vIoin6+pU+Wx5/tXkMqHtlPizUVRbACwGZV83vqiKAT9rlfsmwD+jfPebwD4YVmW8wD8sO//AeBNAOb1/fsQgK/pLv8yMla+hhqIWDOI0kLV1aVvDR0DYmPG9EfOMeNDJC3qFiBGnlkIUGoBIlURpBbfObO3L7xQHYNqLNYNcsSIPA16gCpLrxX5pw9J4jBlvELUCmv2Vtpw9uyxKWDw832Ws0HPLbdUG7zWRo8Gli+3fYZkMWqFZezb22X+9tmztsAoBILb2/PRWm6/3XZqMWZMpVzhMyugbmgI61AD+jVs48Z+4Cz5sgDEWNZPqwMe8sXT2BzFf6SiaMdr2jQ5iLeO144dMq3FqjQR+o68v9rkTmgs+Dxoxyv0ewTlWp74qlVyIGkdr46OfHSby8C0q/c3APxfZVneUJblDQD+E4A/Df1BWZYPA3B32begamGOvte31rz/38vKngAwrigKww51GZiGwpCLDnH+vF6/WEPT0G5uVAqROK5Tp8o/c40Rv8SNtGRcuTlcCmoFkEf+EKiABSumY0bQIFErLFJ3sYy+pWCPtBaJWmEB57GMfs7iv2eftRX/hQocx42znRoVhdyEZ/x4W/HfsWP9DSNcy8kJtoLN0Oc//7xNFSWW2bRsuBMnyhKiUqZfssOHZd3qFApDTmqFNPas68hR/Me1W5txXbZMLlQlhVHbnCq0Z1kpDAcOyBnonI1dUnjP0tjzdE17ynbDDTLNivuGduxDQbxVIvjJJ+MnDa8W2bwaG1WW5YP8n7IsHyqKwtMmJ2qTyrI82OfjYFEUDDGnAahFiPv63jNKDQyh8SGRji8s/OKcvliUQfF2144eBdau1fkKtUIFquvVcvP27Klepe6GY8fqO6BpgoacsnlWUCdljo8c0QMxLmChrIx2TpBKJFErbr5Zn8HieIUoDEPBE6dJvrq7bUeJTU2yDvWxY3o9WKDaQCQgdssttqYnvb3yhpMSgFyOOtRTp8oqPRs32mTzQmBg8uTqNQRIa+3oUXkOsTCtu1snA6fRobao+OSiVrS1yc8vua3Hjsm1Q65pdKg1tm6dDIJJI5SyqK6FxiuFPpKr8BKQfTGjLp0MujZlijwevB5tkLtlixxE8eRNakDmWmhveLVSPgC8WBTFp4qimNX375MAhIq5JPPNGu/qXRTFh4qiWFcUxbqjFk7fYFtIoJxm1S8Otfi2cpW5WQzEFzWmJW3bjg69DnUMBE+apM+4avjF1ixpDnDOI7QVKwZ+XVzspKPJH/9YPjJ2jdkpKUs1apQe6MdAcFubfmPLmaHm70ljn6IOEaIBaTc2oALU0jNkzbiGgOttt+nHnr5Cai0Wa2mRA+IUaoWUXbNorwPVvZIy+uTnawFPTIca0H/X0H1MAXW5ughOmSKvw9bM+UsvyfxinnBpg8nQ2LPAUFv8F8oEWwuXc3KV77hDpmNafZ05I6+dHHupbsi1Q4fk+WOloly4II8X6aAh7HKZmXZX+QCAiQD+J6qOiW0AfjHh8w6TytH3yqdrH4Dap3Y6KmWROivL8htlWa4oy3LFRIkLNxQWAwOjRukBIo/FJAkrC6hjNlKKPi2+COYkXx0degqDJhOsXfRjgHrBAv1xLkGwpENtAXU5dagpRyRl9MsyX3v1o0f1Ve2x+7hggb7jJa9fUq1IGXvpGNOace3pqY4nc/gC5LFfv17WXLb6Gj/epl8MyHN1/HhbENLaKj9DVkB94oTMnbdylUP3iTUYWjqEBrhamnlJvrgPaKlA8+fLpynWY/SurnhLdK2vw4dl9RGe8GhPxkLAldnTHL5YZyIpsLg2bZq8fjHjalHTiAVZWl9PPSWv6VZfoTnN/gVS4yrXQs8t61K0+8dlYKoVsizL9rIsf7Usy9sArADw6bIsjeX2AIDvAXhf33+/D8ADNe+/t6jsTgAnSQ25YoxgWXrwxozRH4vl1KFm9ClJ8KWoQ+Rsyy3RWkKZJNe4IEiSX83NejDA41npIZ44US80z+BC0gC3ALEYcM3pa/9+mZLgWgycNzbq5wSvRzreX75cr4rC65I2Ect48fpjygkWC1FRchVLHj1qK/4bPbrKivls+XJbW+6cOtQnT/ZTxFyzZlxzZm9DvnhaJCk1uTZ2rFzYygydhacvFWpaTiyAau2S1q/BoEPkGHsGRhYVn9ic0K5hkyfLRa9z5lSvWoC4bZscgHDsLWotscx5jpMZ0nC0CZnQdXHMLfUWQ2xalY9vF0Uxpo83vQXAtqIofj3yN/8DwOMAFhRFsa8oil8C8PsAXl8UxQ4Ar+/7fwD4RwAvAtiJqtjxPyR9m6E0ZjalwqWy1B9PckGQsr0zZwJ33aXzlZPCwIc3xO22gvMc18VgZtky/8+PHJE3ZNe4AUqc2Bkz9IoOzJBIfLMUNY0QoM4ZGGmvi9X5kmrFunV6GlAskBw9Wg/GuAhL1Irrr9e3V48FDUPJVW5okOfjjh225iJAWAbOAvSPHaskxHzGuWJtVhJ6fygANSD74rOvHf8JE+Q6F54MavePQ4fkTnXMuGoL0HLyi0Pc9JwFe1aAeOutVd2Iz7h2aQuYz56V12EGRtpW2ocPy/dcu3bRQuNl5SqH1gFrFn7uXLkRDgOidet0vi4D04a8N5Vl2VEUxXtQgd//G8B6AH8o/UFZlu8WfvQ6z++WAD6qvJbL0wjEpMX4yBH5yNg1cvmkxbipya4YIoHg8ePz6VBbgBiz9VKL3Jw61MeP64EY1VMkIGahosSChltv1XNvc2aoOU6STJIlg8jflTbostTfR8576WTi0CF9xi8WNNx8s3xq41qMUmTJUHMscmVvGxpkMGD1de6cTK1Yty5ftT1PeC5c0GVdQyCYc9gC9nOBuqlT5WZS9GWhrUnPL2lex47pdIePH4/TNHJQURYtql61cp0acK6dY6GCdSu3O0StYGCk7Ry7caMMgnlapC1gDoFgqj3xHgzElzXb3dQkP7dWQD1xolwfQV+vQtm8YUVRDEMlc/dAWZbdEIoGr1p79tnqVdqQclIrXn45rHft8yU9ANdfr8+4coJLD4DlOzKzKWX0LeCcmtw5pNti4GnTJn3nJk1THS3HNXZdkyfLkb5r3AAlnqUFnPOIT+L9WnwxgJQ2wpde0m9sGipKLs75ypX98zlm/EwJiFnpIyFqhdVXd7ccZHAMLFxlCaRwruTIBLPoVEuHGDFC7oqXku2WMoVWfvHu3XImzgr0AXm8WHimrXUJgWBmXEPF864v6bq4p2iDwLY2+T5awfmLL8r7ds7MObPdUh2MaxqKjCUwiumJS+Pp2vLlcj2YdexPnJC/wxUom6cF1H+CqrPhKAAPF0VxAwCDTtRVYLFMcAqglnydPq3nuMZAXW+v/liS+q1SsdHixTJIc42ZWSmat1AYCOpClce5qCgpXGUJ2Bw4oL+P5N1JxZVz58rBiWsaHWrtdyTHT6J15OR2WwBibOyfeELmJ7rG65eyYmPG2Fo58298NmmSHlT09lbX9thj/p/n5HbnpEMwGaDVLw75sqoKjBwpd2clZUyr7HDihNwPICcVJafKB6lQlsYuMU1rbRfBhQvlZlKsm9AW/3V2xoGYdryOH8/X2CVnFj4EzknpkZJIrs2cGa4LAmz7h7ROkLuvXcM2bJA7sFqz3ZeBaYsSv1SW5bSyLN/c13zlJQCvHeRru7LsUgJqi6/Zs6tXSX7nxRdlPWLXYsfVTU3662IVsFQ4EirucE3Dx84F6iy+uLhIdIhDh/SgjhX+IZqGduHhmG/c6P/5HXfoTy1ySt3l5CrHfBGMaozPoRTMHDqkD0p57CtlxJYu1W9GHPvY8b72maz9G+l9C6DO5WvUKOA1r/H/bP366lVLnerpkUEKAYU2EDl9WuYq8znVBlqXClBbfY0bJ2cjY2u4a5rTFG3Gdds2WeaNNELtGhYaLyu/OMQTt/pqbJT3IQZG2v2jrU0upuf1aOl0zz0nFx1y7LWJtVAA8mqlfBRFMaEoii8VRfFMX9vxLwJQMuuvEtOAYO0GTvAUavFt1aGWQJ3FFyvXpQX00CF9W9UYCJ4+Xd/YJVYsmZIlzeGL3HRJ/tDii4ChXRDXeeopPSeYmUFpYR8xQg8EYsB16lT9kbCGJ641FtdJqhWNjXYJPuk7vviifpPkRijdK4sqSmzsmQ3U+Is1bbLyUosin35xb688hzgG2oCmvV3O6PMZy5G9ZcZVqwgE5Bt7DaDWgpSxY2XethWcHzggF4cTnGupjCEgxkyslgKnaYmuVbjRZKi1Y3/zzXKDFGv2tqNDvk8M7qUEi2vHj8unS9bAKDT2DHA1dQOXiWl3qL8GcBTA2wG8o++/vzNYF3VFWgzUTZyo16FmJkyaSBYQzAhW2nAsQJ8RrPRgvvyyfHzjWgy4Xrig3yRjx/srVsjHvK5xzKXfT5Fby6HowExYSP4wVxZ+7149Vznma+FCPb+YgaR0NJlSLBlSrdAaOb+SaoWFWkEAKI3X449X80bzfMcANYNpja/YSQPviXbdKQq5zbQVIJ4/LwfxObO3BHMWHfBYcWlOHWrtid3UqXJG3zr2XV0yaLNSGE6elPcHrvXagr3QeJFGKCUffL4kUEd6o3b/CDXCSaF85NKh3rJFTnZZwXloDWBQKkkt+nxJY89an1ebDjWA8WVZ/l5Zlrv6/v1nAMrS3qvEeNQhLXptbfoFMZYRa2zUZxA5sSWubgq/OEcWPuZryxZ98QazV1JGYtgw/XekLymjP326XvaI8ofS98jNL86pQ63lRWquS7tQcwGVVCtWrdLzWxn8SZ3XUkCwZBZwHgOuMc1r33VJvvjdNYEp544ExKgqoGkuwoAglzzdhQtyEV1OKkrO4j+e5mlP7EaMkBMozHJL2tKu9fbKzyOfMW3Gde9emRI4GFQUC1dZ8sXgi8XqMWtokMfDmnG97jq5sx/54dqM686dMkc/BQTHqBU5xp5zIacOtZaKchmYdid4sCiKnyuKoqHv388C+N+DeWFXnJEzJ2XEenr0R4lcwCR+1M03929wMcsJgmPt1S3gPObLcl033li9SlmEvXv7OzjFjAuBlCmZPVsvE8VMibQY527sorWchZektUjNWNau1WeKYoHkqFH2Ykkpszltmn7MNIohgG7uayX4NACR1y81jKJ2rqYxAsdVClgswIK/8+ij/p+vXFm9SmpBoc93LUUJICdXWbou3j9t4eWIEXEdau1z1N4u6ybz9FPbZEzDL84BxKx0iJzg/MYb++eka7HmXK6dPSs/u8QI2v3jxAl5H+JzqlW3yclV1oBzra85c2TZXn53bYO3y8CCO0pRFKeKougA8GEA3wbQ1ffvrwF8fPAv7woyHmVJD/GuXf1Zi5hxAZU2aEuTBf6elFmaNk2OqF3LWfzHjL4Urae0mQ610tZSGKhWIRUb9fbm06FetUqvAZ4TBHMxlqq6LdlbXk+IWqG9Lo49C81c27dP3/kvRq2QlGp8plUf0WzgOQE1Ny9Ji9aihUzgJ2XEnnqqetVknvh5EuAhoNAENLFCaM5hSxfB2NhrAfXIkcC99/p/ZgXn3d3y/CE4lu6Na52d8n2yZlxr/8Y1qj5plTlyFkuOHy/vHSmNSqTr4nqjDWZ27JBPJOlLW0AbOuWh2IA2saYpltTOieHD5dMSazAzbpwcYLzaVD7Ksmwty3JM32tDWZZNff8ayrJUMv6vEqMOtSQDlzMTvG+fvfuclKGeOlVWjnCNXFgps9TUpKei0IdE07AAsQ0bqlfpeDUFnEvjtX69fmOLnQ4MH56PbjNzpr74j9XvEsfVku1mIClxIy2+CMSke7Vnjz2QjLVE18yLGAi+++7qVeOLdKFVq+Trqv3MkHFOxCTlNGPGdUua25ynmuuKBSCxU6Bai91HZly1nf+Koh+MuJaiOSw9jyn8YgYtruXMBMc0+y2+uG9oaVhFIY8XA3ItrWX0aJmrbAWI+/fLGX2rr9B4kXap7WOg0aG26MLHiv/YGj1mixbJQTwTd9rxam+XKWlWX5eBqXe7oiiuK4ri9qIo7uG/wbywK840bblz8YtPntRHzLHMZne37kgY6H+IpIzEypVy50PXyO/M0ZabfF9pcUkZ+5wSfBIY2L1bnznnYidlVufN07ejzalDzUy+lNFP0Y7OQWuJ+SIdQQOeuMlLpwkMNC3ydBII0Z5YAP0b9Nq1/p9bst3azLlmvGIZahbWaiS/+HkxPrYF8JAi5hqlvrQndl1dcmLD2til9m+k93Nwu3lvtPTDkK9YUyfXJk/uDz5dY3Cv3T86O+XTKmswc+qUvJ9a72NOHeoQOOezo1XmmDZNzugzqWXRoZaui3uQlqO/daus/GKlAV0GppXN+/cAHgbwfwD8bt/r7wzeZV2BFqNWpPCLQ9JtWl8EwVKl7HPP9UsWxSx2/GrpPsdMibSpzpqlzzppuN25ZPMsAJFZl5AOtXSi4RpBnUStKEv9hssMicQLvOcefdZJQ0XRmpZaYeEqx65LAzZ5JCll9Mmz1ASm3LilAIQyWZriv9jYWzKugwGoc9BaCE7WrPH/nKdTmhM7rhPSGsXTAy0Y6O2Vi16thYRA3oK9XJzzELebc1i7f+TUoT50qP9U2DUmfKTAybVLxRO3ZlybmuQkCX1odajHjJExgNXX9u2y2hRB+fLlOl+hAORVnKH+jwBWAnipLMvXArgVlXTeNaPlLLJjxks6wrf4YvQpSZdZwCaPJKXj/V27ZKDgWgwMzJwpg0fJV+z4NYcvy3jxaFnakCzgnEWVUkb7iSf0klMx1YfmZjsVRfouUkMhn+XkKrPoiq2pJV8aUBfL6JMmoQmOyJ+MqVZoNpEYCGZ7c40qTYxzbgHUBBQ59Is5D6UAgz/XKJkwo/nkk/6fE1DkkM3jSZK2nTOQryFIiFph9TV8eD6ucnu7DL6ZpWSAFLMQcGUArN0/NC3Rc7RXt4LzWbPkYm9r9rajQw74uW5pG7ydOiWvdTlbohOzaE8tLgPTAupzZVmeA4CiKJrLstwKQCnMeJVYLEM9a5b+OJe8wFBXPC2oYwZFeogtvnjEJz0AL7+sl1uLAdfubr0OdSyjv3q1/hiXGUKJZ2nJuMYy+hZf5IeH5A+1Fgtmdu/OV3hJ5RXNHGPwJzX0sYA6/q4USFrAOfWJJY6rhascCxrYdETKfNZaLBNsUdGIBUbk3Wsy58zKsmjNNUuWlCBA4rhagEUsAGFgpEkKxMYrZ/EfTxm1HNeWFjmjb81Qd3fL1Aorv/jcOTlYoY8cTXW4b0hrpc8kX8x2Sw1WXJswQQaAKVJ30pzgc6j1tXu33DTHmgkOjT3XJG1gFCqW5DqilRu+DEy7C+8rimIcgH8A8C9FUTwAQOide5UaHzjpqHzSJH3nJk7s0ETTZjd5rC9Fp7ll83IV/23YILdndo3jKgEICxWFR2wSEJszR89VJgCTwIBlvAaDWiGN/YED+gx1zBe/n2b8CaSlo9p7+so2NIWvBKQSMLVQPrQ8XouvHFSUmC+eamjqLUhRkHSomXHVSH7xuqR7bgmMuG7F9MQttJYcHQljwQyVHrQFaIAMxHjCoKWPhDiupJ9pmy2dPi2r7gwGTzyH/CFBO/sAaPxIGWhrYDRypNzynMBQoo65tnevrKWds1iS64d2zQ/J5vF97SlPKEPN69VSUS4DU+3CZVn+TFmWJ8qy/B0AnwLwZwDeOpgXdsUZFz0pg3PunJ4v+8QT1au0qS5fLmdQXdNwu3OB4BRf0nVZ6BDMgkrHqzt36ov/eBQv3as5c/QbGzMlsUptjcUAtcVXLDCiL8295OYgtVdnd0GN3F2MWsFARnNdBJMSECMVRROI5OQqa31pgAWDd0ntgBlXzYbEMZXmtoW/zjGXMvqk4Wg6x8aAq2Xstb40Yx87YeM4aXSoOfbSmk4qlzbj2t0tAzHSzyQams8uBb94KLnKEyf206Nc47Ozbp3OV2envHcw4aPVoT57VqbxMQDQ1rpcrmM/c6YcSPI5lQK6y9AMaa3KyrL8UVmW3yvL0tCa6iowbiLSRHv+eTlT6RppEyHAo52wsYX/xhv1snk5+cWxdropmfOQDrWWPkKOn9SdqatLzxmMjdd99+mz3TFfFkDNBZ1ZSdc4hzULLD83luHRjBmPCSW9dhbCaALTWPaWQZiGwqDldl/qLCmDeCmjb/HFjJLUCIfNFaRj41qLjRezo5pgJgaCWWilybjGrssCLOgjRq3QrNP8PCnoZHColUotSzlDaG2JDshjT261NuMa8mUFdSNHyp9r5ReHMvrcg7T1KYcPy8Xe/G45qCg8adDqUOcs/mtulk+Drb5GjgxTWy2+LgMzA+prJhiP9kKasLkywTt26Iv/mCmRfE2bpo9yuYFL4Km5WU894GfGgJjGyDvNoYUcy96uW6fn+cXuY87AiBknzRwjL1AqGLRQGJgFlZoVpFAYpHtPYKEB1LFMsPuZGl/S2JMmoQlMmYWUMmIptAPpnluyt6SFxDj6mvsY4xdTh1oDLGL3kTxt6Zi91ugjViSsGa9YEG8Ze2axpSyoBSDG6jZYi2HpPif5YtGfRYdaWu8J0LSFhE1NcrdHK0+8vV1uxpKSvZXGi/dZ2+At5Cul+E/aB3n/JG1p12bMkIG8FVCfOBGvu7LIkQ6xXQPUuYwTKMQHygWoT57U00divjo79e1xYzzKVav0BQQEYtKGYxkv8ixDWb9cGuA5i/927NBnu1moKhUmESRoFh8tGNCAJ1bnSxkxCzjX0losyhySL9KqNC3pGUhKoM1CRYlRKwgSNKoCzBZL1fkWYJGTWqENjDRJAe3pgGYD52YvUStuvrl61agKEARIGfucY29R04j5oml7DwDymsd9Q1vrMny4rEPNea/Ndnd1yXugFdR1dcknkind+nLRIUJZZc4FSbHGtYkT481YLPMg+zoAACAASURBVDK1sWZS2iBr7974ycu1DPVVaDEgkwKocxT/MZKUJvimTbp2wsDg6FBLm8T8+Xqpopi0Vgq/OAe1ghlLSbZMO+611yONSawQrNbIa5YoSK99bfWqoUPExisFiOX0lQOIkVYgATELV5ngQwIhzLhqpO5i68RgcLtzjL0FbHLspRbfPF7XNLggpUL6DsySauY9waQUSJJOpSlEjwUgFlCnBecaX9xjJCDGuhQNDQjQ6VBrs5GdnbIONZM6WmUOIC8IztXiu6lJztjzGZICAdeam2Udao69dj/asydc8NnU1N8kKWahoIF2DVBfhRa76RYQzM00FgVqjNzCHLxndpeTMoRbt+qL/2JZ0pkz9Q0WYmCguVnfEl0TzGiNWeOYDJxmcyO3VaKbsABMk3mK8XgtVd8x8MSMukYLXJuh1oA6bqbS0aQl2x0rqGTGVaK91BppDtLmxXmqmRMxIHb77dWrpCPs85UDBBOYxvSLNRtlbJ3geGnuI+tcpCKnmEZ4rcWAK7+7png8dh9TpAGl2oyUsZeKR63KHD09MhBjYMJgX2MxCkMOHWqOo1ahC4hL3WkB4nXXVd2Hc/g6c0YG33yGpADFtfPnw/tMQ4MNBIf21JYWPRXlMrBrgDqXxSbQggVyEZhrN98cBpMpraFzgHM+RNK1tbfb9YulbNDZs3pfMcWQ1av14JxC+pJutSVDrcnoA7rvyYI8iW+WQq2QxmTnzupVU4gTC0AIqDXKKOyyFcukaAA1Nwnpcy0ZV240EhjImYUnj1ZSaag1TSAJ6ILJmC8+D5rMOcGHBCYt95GBh3SaYqFDxL5jrDCz1rTyhzn0sTmOpKSEjPecEpOuWTLU/B2JWmHxxbVQSrhwvLRURkAeL46nts6o9vNd43zXjD1QgXnpd60Z6pAONX1pM/rHj1cJr5DlyMID1XzQcvRjvoYP14smXAZ2DVDnsqVLw7yhyZP1ig4hjhJQZZ21wI4gICTdlkvqzgL0YzSNDRv03G4GKtL4WqgovB7puqgOofH38MPVq5SNHAx+saWgSgJ1vF5NtjsGzvlZmu9IHqUkf0iQIGX8a43FV9LYp9AhcvCLtffRkqGWfDEjq+G4Uilk1Sr/zxkYacaeijrSeFiy3QRgErXC4ktLrcjBVWYArMm4cq2R+MPcVzRBaayHAYMdjXQbn3+JTmPJkvL+5JJuA+KAWqtDXRRyNtta/NfQID8j3J8kiVHX2tvlrHHOokRaLl+9vfqTao0vSWzgMrRrgDqXjR4d5t6dOqUvBFm7NgxA7rjDVkAQspTOfzm1kHNwlQlypWO5rVv1iwWBmLSpUhlDkxngPZS+IzfIHEoTOQG1BegvX169StJtzLhqiv/4eVLwZ8nw8NheOubkfdR0ExwMHeocPHEGktKRPIMJzdhru3pqrovSk5KaAQtsNUe5OaXutIBaM7+YOAgF8YDuGeK+Id1HZm1ZABwyAhlJtYJgT+piWWs5+dgxXxZwHpurVpWPpibgrrv8P+P1rF2r89XdHS9w1FJRenriGfsctBZaLpqGxdfEieEA48wZPRXlMrBrgDqX7d8ffoCfe07fPejs2XCm15Jxjf3e4sW2zDmQhz5CIBbbkCzXJf0NuZGaBZZgQPpdZs1zgCcWWmkyT1ogptnAWbQjHd9bQB3Bb6wgVHNdVN5gUONaLOtcazEQzIyrpWgsNvaWY/QcWVJSZCQgZrkugjUJtLH4T1IUqbUYCOYzr1kvYr44lzXHwjl54vxcSbXCAja5pkgJF9K8SMXS+JIyhJbMJp/Z2NgvW6b3lRNQS9QKK784dCLM766lopw7B2zZ4v8ZP0NLRQnJ5gHV99Rmu4H4nqqljwwbFj7hKAqbr9CzWxTXihKvStu6NfzQWTPBId7j5s366t7YxJ46VQ9eJ0wIX9fo0friP4LIHNnuhx6qXqXNK0VuLdQSHdBpUWszwRapOwm4UupLo1DAgilJ4tACqCl5JPGtU8BmjOOqaaWt7WSn6eAY80VNaSlLX2sskpSq4FP0i6UNxwLOeawqAbGc95FqKDm4yqQJUVs9ZAwgJVm8nMWSFkDNQlUpo58zC8+xf+SRgftiYKRRY+K1SydC9KEJjPjsSjKWVnDe2yuPvRWcA/G9SwLcPgvhBktiLeZr1Cg9T3zMmP5aI8m0gPr06Xgx9zUd6qvQYiDYwlWOTaBTp/T6xTFfHR364r8FC8KAbdUqPRBmtjHWljsHtcLCS9WCYEshjuSLRSIavhkVGyQQTAqDJtsdU/mwbCIERRLf3TJeOakVsWJJ8kJ5IhEyFuRJ3EiLKkrsuggQNQXMPArNoYWck1oRy8IzINKoadCkeW3p6snjcYmjz+I/TcaVvHRp/ljAuZaKYlHdyVEIHfPFn2sCI4JviVpBNSqNDjWvXQriU7jdUoLE2nURiCfPLAAx5Ov8+f5TvZiNGBGe18OH65VMenvD1zVsmI5KB1RrQUh20ZLtvgzsGqDOZTm5yjl93XpreHL/+Md6QB2qOuZ1aReeGJBhExkLcA0VSwK2DHWMwqABdVSrkDI4jMw1x4n8XOm6mGnVtFhnsaSUGWDnP00BWk4+tqboFbj0nHNmwiTlFx7hajiuzOhLXQJJ39A0SNIGIBZgkaNYUntdGl+k5jCgdI2BuYbjyudMekYI+jRJAdIwpGCY4IS0nJDlpKLkDIy4bnEtdo0+NIo0sYy+hYpCaozU4pvrRyyLCsSDBpqFV5/DF1CByVCtVG+vvmtvUYTnYk+PrtYCqEBwiPrV1qbPdgP5qCiXgV0D1LkslqG2KGCMHx/mNVsAdUtLOKtsoVY8/HBYeWPz5uo7Wo5MJWMWSTNmMW43sx+WDHUOTjB1qKWAxpJxJX9S+l1mXDWKDrEMomVzi2VcOQYauTUtT1xzHwnAYsf7mrHnBi7NRQYmGm43Ny1J/pCfoQmMYmNPeomGZxkbewsQYyAZ06G2PI85CtAYzEgFewTckkRfrWm53VJnU5+vHPxizh9pzbH44n2aOnXgvngqIYFgXjeD/ZBx7Q11xgV0VJTYaR1Q7esaKkpsXaVpAWJRyDrU/LmlG2So8dSZM3pVlAsXwlQ5CxUlVix5/fXXdKivSosB6ltu0Rf/zZ8ffoAtIHjPnjD4s/g6fz4McHkEZzmSl4yRtyWzKRkLhzTjf8cd1WsOQK1toKIZL27y0mJsARaxoIHAwwLOJSBGbqumGp0bt5SV4bG/pXApB32EmqrsiOhaihayNF7M9mk6/8UywfwMS0t0aU7wtELSCK813j8JiFkANee9VKiawi+WxouAmpJ3A/FlCUpj95HgfMWKuC/+Ltcx1yzjxfGQgj8LFYVBqZRRpS9NIBkb+6Ko/mmoKJpW7c3NOlDHcYhRhrSBUexEuPYzY9bdHT9JyMUTP3pUr0MNhAH16NF6JZPLwK4B6ly2dKm8gQDVRqQt2Is9SJpsH23HjnhXI0APUmI8cUAHNmMLAYtEpMW81iZNihdvALrv2NRUfUfJH48/NdkPFktKgMZCO9C2V7cEM5IvZpM03O4Y5YNzQSMZSbqDFEwSJGiK/8jLk4p3UwKQnBz9nC2+petioSEDpJAxiy11liTtJbTG0QjEcuhQcy7GQF0O4GrJuMZAHU8tHnww7ovznfKf0nVpuo3GJOWoaa0JjHjiImUueV05ePUWepIGBJeljYoSolZoM65c50Nj29r6/7f37VFWX9d535kZmBmGAQYGhjcIhIQQAgkh9EAPx46fq4nsyE4dv+TGqbxWnUeTlaZeaVaTtM1q2jhxVrLaPNomcVeduG4S24rj5drLtSPrhQQSCAQIJBDDMAzv4T0MA6d//O7OHaH57f0d5szcC+xvLa0rzf1p33PP/f3O+c4+3/5O+TM2UrvKTvUE0vXFVhY+VyzG7k9gOZkMDJTL4+oQTqhzoaVFz4CeOMEXEj77bPVQhpGwbl0aOddwNUTMipWDUKcQi6VL9WI8qarWtrwEljWVSFEYNw2LiMnkliJryXmwSw5SJ0VGZXpr6Xum+M86yCdlYSQFb2UZLyHvDLEYC61yDlmLFDCWkVwhocxOgyWbEjAZxK1bi9eyZ0kWRNp2tiCnvpjViTO/o4y/ZYd5pWSCJUaZa4W0h1kYyS5KmaxFPotZlI5nsaQgJZa1wGB+R5mztXvx/HnOFUVkENo809ysHwAnkDlUe96am9OSazm1ylqsFHLe0qL3/eHD3MKoTuCEOhd6evQCge3beaP5Cxf0G1IcQxgixkhRgDyxUjJ199yjDwYpBWiXLukPuEhRmJMX9+zR+0J+YybjahFXsVtLKf4rI/IpxEIWBWVZ9qupbM+hcZXCsrLMuBT9lW3/D4fVX9IHjJuGRYKvxlrLItRMLFkMlBUbpcSSSausMEmI2oYNdix2AcLAiiVjSBkZTYmV8juKNrqs8C0lcy4Ln7KsnsRgtN1WLBlXcxBX+TuzMGKyygDXX6IPt2oDmO8o12gLyRg5e03pc+2I78FBzt2G6a8ZMzgpCqPtTs1QawWOKbFC0HmAu3zcoNi7V1+ZpmiVY9SJq+grmYfcIsFC5hhCPWuWLnWQynZWWlFGKuR9gMt2f//7+mLmaqQVZZCMq7aDIGAz+inFf2UEUU4+Y4pnxGKvLFOS0l8yeVjb+zlOcBT5BnNAkrWYseyyUtoli1JmK1d0sGUZwpQFiJCnsvsnJZbIQ8oWnVdjm1fWX9Lnml2WwJK1yIKI8aEW0i32eFdiLHyoGTIgmu2yTFxOWYvMBd/7nh3LItQNDcU/2jg+/FpAPxCksZFzt5H2WLtLTN/LWGLVLOTKwp85w933DKFmpShMrLlz05w5ynz0gTQSPDioSzpC4M0c6gBOqHOBzd6yq2YtlmRHc0grJBvIbOUuWaITNtG4MvriPXv0z0yVMGj9lULqckpRrFgysJYVuw2HWNmVDYqy7S+OJhqENJVlZZgtSYFlFZezWDKl+M8iwbJ9Xnagw3AIWSu7969mYVT2O6ZolUVfWZZVzkmCr0ZaURZLnnvmvpfPLRtT5Llnxi8hc2U7QpJ1k50jDfLslmWNr6ZYMscOSE4HH4ucCxgpihBlOSF3JLS0lLvyDIcsyLQDnlgHDBkLrfsnx8mS0i6GAzBZ5b4+zodanhGtqHXSJG7eZqwB29p4T+tLl/T7xzPUNyhyF+zlinXXXeVHEwPVghOm+M+SVqQM1nv36rIJ2c5jCGJOEpxTJz5vnt5f0udlBxQMh9gLld0XMjEwv6PoAcsItUx6YnmnwSqWzKlxTYklA38Ogigkt2xrUjIsTOZJdjjKiiUl68bIgFgpSsoEbskhcljdpZBNKQIu80KWZ4fRuErywMrCM7BiCTlhFkZWJvhqiiXL+j6lCF3uRU1WcPkyR6gZjT6bcWWet6lTdfIuYPTYLKmz7PwEKQWOmrTi8mVuISmxtMLLs2e5WgvZFdekX4sWcRp9QU4pSo3hhDoXLJlGChGbMUPXFaVkb5ua9IK9lFhPP109xGIkSLaP8eO1+ksIBVP8Zy1AZLXMFHJasVLI+aJFeqFqSixNlwdUt4uZyc3SDeb0oZbtdUbjapHzlAy1FEuWbQunkDprkSILQ0YGJGSgbByQPkiRopRNSLIgKjsUZaRYlg81c0+IpKjsRMIUgmh9x5RYkjwos1OTGMzCyGqXEOoyL+7hyOmAIddaGUKGpMjYZckwmFhS91DmQw0Uz5k4I2lgMucTJ3JzByPTaG1Nq7XIQc6l73NIK2TRp83LR45wc4eMW9q4yS6MGP360qVVOeM1ACfUuWARMVktM1rqRYvKJ6PhMRhi0d1dng1LjWU9JEIsUg6lKINknhj7HWtQka0uJut33326rCUlszkwwNn5MbG6u+1CVTaWlS2SyY9x5rBkGtLnWnZEIESsbOtRJhnmYCP2QBBm4Jdt1TJindPlQ+QbGzfysSwrRWbSlWvLFt/y+2m7XQJ5fspISAo5l4x+2UI+5TtahEcyeYx/sRUr5XRW656QnakHHrBjyTNk6fmZvpcsvLWDxsSSBaJV95NLEzwwkPY7arE6OzkpiixitBMaWU2wNX6lxJK+t6QVTCym719/nfPRZ2JNmcJJUeoECeXWDhUrVugSBplkWDcNq7qXjbVvn+4nnKoJZrLwOWKJ7dPBg3Yl85w5+rGpKducIegZhuXLi1fGbu3pp/VMYwo5twjD1eiLyyCLGMaHWu7Bsj6TxRUja5FFZFlWX7b9mZP/JBNW1rdX0/dW5jyHTjynP7b0OXMCmmTCygr2hCxoC32B3Ddl92IKoRY/5zJiejVSlBxaZUv3LGMOk3EVjb62Td7YyO+wyfVlaGridoyEkGruIqma4BxWd4xM4+xZLuMq/aRloBsauHZJLC0hM38+V/wn2WRtYZ3a9zl8qJmM/tAQZ5jAEGpmDqojeIY6F5qa9JWUVBMz1m0vvqhv8csKmCkeyylFYeUQLEnJJa1YuFDPgAo5Z+zWdu3Ss+JCpJm+twYoOQGK2bVgdeI5yHlK369fX632HwkyKYs3sQbJAJfdFylSFG2BBVS1rYw7RE5NsCWRSSGIYt1WNoHLM53Th5qRokh2qqx6X8iLFNpqGM/DWFJiybVlNR4p9nRiA6eRuhg5KYqMddq1ra3lC6fhyOkdnVMOwfpQM7FEo6xl9A8cqFp6apCdYHHMGQmtrZwURRIR2hg8ZQq388cQ11SduBaroYGLJc+IVgTc02MXvtcRnFDnQm+vbpsn2+ds8Z+GFGJhEVfJTDEG8TnJ+dq11e3JkZBC6gYH9XalFOz19OiLHiEUKacIlkEGcWZys5xMUjLUixZxloUsOddIWArZfO654rUsnmiURQagwcoEC3nRin4ElrQiRYoifWtlqFOKxsqO5k0hiFL/UHZfyyJTfiMNloThapwmymJJ3zNSFNbJhGmX7JqVnW4oSMnCa4uVS5e4hIDsSmjjQEMDN0ZbWXigeI4YjX5OL2TZJdF2qliXD0bHC6RZT2pH1586xbnbMIuGBQs4jT5beMnseMscNHv26GMJtKPFWXJeJ3BCnQsHD+pFSamZYO0Bf+ml6mcysTQiJsSCOWxh1ix9RSyZMibjGoK+Uk8h1M89pxdL5rS6k21EbdAcHotZgKRUfZdBspUMsZg3Ty+WTCHn27bpfXY1Eoaye1+yNsyJlxahlve1+gKBJfmQhSHjKiCHYFj64pRjucvujZRYQgbK7sWr8WguI2LyfsrCqCyWaL6Z+14kFXLC5JVIkYYxGlc2luxGamMYkC8TfOoU8NRTeWJNmMAtJOV30uaPyZM5KZ08h1osltTJaZ5btuixcskhjh3jtN0MCc7pQ718ub04BKq78NpihiXBIpHVdtDch/oGRU4Jg5UJlhiMTsmKJdkRVuOq2UDdeWfxygyKe/boPqI5td21kqJYsUSbWHZM8HCsX69X20umldlpOHNGb5dsYzM2Yr29+uCZQupYnXhKrLIJSeQIL79sxxK3jLJFSEphnEXEZFHK7FqIvrKsduNq3DTKFg05tcpCwCwCCVSJWJmcTmIxJ5eKD7V2uEhTE/Dww3YskbVYp97lyMIDfMbV6ntBCjnXYrFaZZFW3X57+TUzZnD3vSyotV3CVAcMrW9zSlFyxnrttaoXvQYZU7SdhLY23lEL0Mn59OmcD7XsGGsLjIYGJ9QWQghvhhC2hhA2hxA2Vv42PYTw3RDC7sorIQ6qI7ByiByEOsXRYeVKfRCTFTpj+WVJK1J0g729+oAoBWiMj2vOI9FzkvP58/XtrJSCvUuX9EyQTAyyQNLw/PO6/EVsirT7RsDqsVPIgBWL6Xv5zcv6LIWcWxaOkuVmDokRIlb2uaKn1bZUBazVHZNBZD3Ac2RJU04RXLWqeC3LQMuzymhcpY7FOlCKuVflmdWunTgxTaOfQxPMZElZUie7XprDxdmznMaV0eiHwDtXAToRW7RId9sQ5NRjs33PEERZSGpJlMuXuXtV+lybi44e5TiAZJO1A2VuvpkrXmb12E6oKfxIjPHOGKMc3/N5AN+LMS4D8L3Kf187kIM3ypBCqDs69CxvinwkBN2HOiXj+tJLerGkOCsISddgLRpkS1yTJggsEiwZKa0f2FgppG7ePH1bMiXWjh26xlIyZYyjgzU55NToy8Aqk/No2pWScb33XnurGuD6XhZ+ZQO/tJvxXxdphSUVYKQoFqGWe485+c+StaT0vWwdl8lacvpQX3mdBimM1Radly5xzxAjh2htzaPtFjCkToqlrQwh01+yK6Bl9FlyLn1fdrw6UGiLn33WjsX0fXNznoUkUGRcU2otcmSo5dnRkhqstEJ2grUjvg8e5HaMGM7BLkqZheSqVdyitE5QT5KPRwF8qfLvXwLwwRq2JR0WoRYvZKYqt6tL3/pKIcE9PfqDNBZSFGb71SJiQigYvay1gpVBSSuCFKxbp58QmKIvPndOb1tKrIMH9WLJnLIW0eZrusLhsTTIZMzc90uW6IsemeAZvb91qmcKoX7hheK1rM+uxuWjjDzJb6ydRMbGSlkYSb9bhZfMlrz81pJtvxIpWmXZ0raKgHNJK4aGOGLBkidmLGRizZrF+VBLNlmz4GNJncwb2m4WG0uKWrVrc8ohTpzgijiZvp83j1sYyTUifRwJtfChloW+tpPAxmKy8Fu22AeRAdzJku3t3HhfJ6gVoY4AvhNC2BRCeKLyt64Y40EAqLyOmKINITwRQtgYQth4RLOnGW/cdJNelCTaVubmuHhRJzyyDcRkXA8d0m18UrbkrWLJnPpi2c5jBsXZs7mMPqtx1X4jmaiYjOuLL+oFFylb31Z/XU3RWBnk99M07gLNMm94LEaK0tWlW09KMRmzlbtli05wU7KkOTPnllb5an7HsljSbmZhJH1atvCRdjESLBlvrH5jMojMPch8FsDpi1lSZ/U9UCQFmIyrZPQ10tbUlI+ITZ3KbckzcsCcPtQ5Yx0/zi2MJKNv+VAzi2XmlMqVK6tyRg2SyRcDgrJ2pZBgrb/YWEKCtVisFIVp15Ej3NxRJ6gVoV4fY1wD4P0APhdCIKpACsQY/zTGuDbGuHamdSTqeCIEXZ4gq0Tm5ti5Uy+Wkowr8/3rVdttxUoh+rNn66cgimUho3F94w19ASIZ1zL/2eGwJgfJ4OWQtYyFTpyZ3Nat0+9D2WFgSN3Jk/pnpmQ2jxzRr5PfkTkBjdV2pxAxS9vNxBIiVnb/yGcwUhSrXXK/MFIU+a01rfLEidXj4Zl25fBCzqlVludf86NnCaKMAxoRO31al0sIJKOvZSM7OsqdToaDPYyFIWI5YzF2fmzGVfpBc7jYvp0r/pPnTLT6I4GVojDSipkzdTmOIGe2m7U/ZGKJjEYbB/bt0/uzzlCTXHqMsbfyejiE8DUA6wAcCiHMiTEeDCHMAUDMAnWEI0d00b9kXJnJjSWurN2a9gBbRT8psVK2vlet4uzWGKI/MKDHkvYwx5gfOqRvcUoMZnfEIq4iLWHsinI6YCxerBOjVDeNXNKKjRv1vpc2a1kbgfVsCCFitJFWLNkpYlxRrMVTSoZa2p7j5D9xDLHuM0aKwkgrUnWWWia4pYXz42W1yky7JKlhZXoZQi0ZYG0Bcu4cd0CP1FlYhIY5YIzpr5tv5halrJNJykJSTq0dTSzGtYIliFLHomXGDx/m3LmY7O2SJdw8lDNDLTuI2k4VG0vmRmtR6kWJ5QghtIUQ2uXfAbwHwDYATwJ4vHLZ4wC+Md5tGxVOnNAHvBSNq0VcxSmAOTnLIuciRWEsczo79SNrxZ6HPUXQOh4X4Ca3LVv0vsgpaxF9cY6+T5GiNDTo/cVkWgRdXbq9Xgqp27ZN17fmlLXIwMrIANhYzI6R1XbJLIrHtIa779aftRQSLJNp2fdMyZxLn+bI3loFjkAxyTOnZzKEetIkTooiW+3W9j6TQWRdK5j+EttM677OJWvZv7+Qo7GxmOJeC/KMaBnVmTP1nUaB3AtlGn2AJ3WyE6wVorLFf0zm/NAhvabpylg5fKiZWHffzS1KZY7X5hm27yXzrC1AmDMt6gi1yFB3AfhaKCaBJgB/GWP8dgjhRQBfDSF8BkA3gI/UoG1Xj5wuH1Ysebi1jAYbS7bkmcz5jBn69r7YrTFVud3dugZ8LOQj4x3LInWS0di0CXjsMT3WmjVV6cpIkN0Rxv/z1Cl9IJYshKZnFhw5omdcch6JfjXFf2WQZ4fZyr3lFt0rPPVAECajL8+SBsZDO6Vdwz9/rGMNDXHEQkiTNlbEyFlPyrOhLfi7ugqHGAtiG9bfr8sncvk9p+qLxyuWJa0SSM2JRtrmzOF89CVxpe2ysd9RxgFtnK6FHIKRyGzcyJ3YK32u1Xi1tup9cGW7tO/Y1cU9j0Kor6ODXcadUMcY9wBYPcLfjwF413i3JysYQp0jQ51CLJYu1bfkZHXIeIleuKAPUilSlKNH9e1vWQFr1eoCtlgyBwlO6fv58/UBTwYK5kh0K6MvpJYhKS+/rG8VSrZPOw1LYP3WKdluq+9TsrfNzfpklBKrs1NfXMjvyJDzTZt0faS0mamPYNoOcFnEsdAqa1ll9qCSVauAL39ZXyiePMllXEVaYY1hTLtEWqHdrx0daT7UVn+Nd+El447U3592Aq12f8XIySHkQCxNW7t6dVoRZ45juZkFCJvtlvtdy9iz7ZI+1xaSBw9yWmVx79i4sTwJtHz5+EtR6gT1ZJt3bcMiwSmkbsoUPeuRWoCm3bApcojdu/XiMimaEUmKBqu/ZEBhsqSsrEXbIhRY0oqU/urs1IlRSqzXXtOPmhfizhznnFOKYsUS14jbbrNjsYsZpl1r1uh9L+SFiXXsmP4bye/IyEdOnLBPZQshjxQFKBat2glpKbHY64SIWTKyFMJjyTBSvJA10tbfz/lQM8S1o0OXyKXEamjgMogy1mlF0ywRk7E3R+GlZPS1w1h27uSKIbbcNQAAIABJREFUl3NKURgSPGdOVerAxMpBECWpoblJMdIkoJoB1txaenq4bLeQYCt5mMut5b77uDqXOsG1Y/BX77AI4l13Fa+MTqm9XfdCTinYO3xYL5bM6UMtAwUrRdFiyZaRRiKHx9L6XvqcKZ5ZsYIj1Mxi5swZvV9TYh07phdV5swEy1bqhg3AE0+UX8fEYg6HECxdqn9HIWjMIsuSVqQsZl5+Wd9FSNmZuXTJJkYxctluVnvPtKutzW7XpEncjpGQuhyHsQgR00hITqu78+fTXFE0Inbpkn4Y05WxNGKxbJk+JwhkZ087aZPtL5GkaV7aLDmXOcHSnOeSQ/T2phVearEWLeJ2/kSjr9niMYsigNsxYsm5EGrtvk614NPu+2efTfNy174jU49VR/AMdS50dgIPPVT+vmQMGB/qwUF9wJPMG6OXPXmSO9glh2NIKjnXYsnDz5y6OGuW7lKS6kOtPeCyhcscy719u97+VC/kXDaDVix5j9HBTZigD64ppwhOn65rKGVhKItTDZs361nenD7Uch+nFOxZyOEnDhRjCaO1Xr3adiBpbdX93gV9fXb2rLGRyyLKPZjjFEFWWpFre//AAc6RRpyWtGJJNuvHELGuLs6HWgqvtUUBS8RYOUSuWEeOcBIG2UHTMtAx8icEAjoJvPde7nAkcd3RdhxzkuCcntY5D4k5cIBblNYJnFDnQoz6QC2Egsm49vXpmkDJVDCDIqDfsGOh7WYG/hC44iyGNEybpktk9u8vXhnLr337dD25DJbMytnqL/aYYCZWSn9ZuwMpsVat0jNnMhExW7mWHjOl+K+/nyuWZA5ZsPpLkMPJJCXWihW2jGloiDtt1FpIyjWMFGXrVrv9XV3V02M1sLZmKYuZHPpi2XHRFiFsLBkHtFh9fZyz0DPPFK+aY0hXV5pG3yJiDFitci6pAEsQRR+uJWQ2b9YLwgUyb2h9P2FCPuI6bx4nY2T7i0HOvpd5Q5OkdXdzOw11Apd85MLp08DeveXvS5aY2QoBuALHHORJtK2ap2dqu5gM9U036WQmRQ5x/jyXQWCOAbaImGxdMr+jpV+XgpMc+uKUDPXChbqEIcVuzSqWTMkEb93KkT9mYWT1l2hSmSPRmbaHwElRJk3iMrMsqbOyyixJeeEFe+I6dYrLdjP9lepDrf2WM2ZwWb+xKNizCE2Kf7HWH6dP82MhoD+TQ0P5jkS/6y5uvGfdR5j+kqO9NfkkGyunD7Xow7VF5/79XMEeI4e4+WZuHmIWMywJlky+VhvAWt3JM605+HhR4g2KgQE9+5wzEywWXozO0oolUhTGh3rKFH3ikoeNPb0pVxHnnj26p21KAZrlGCJb0MypZTmL/5qa9N9ItosZZ46ODn17OcXJZPv2KiEYCal9z2TOGSkKkwkOgZOiMLFaWzkpyqpV+Rw8Dh3iyAwT69SpfJIV5prjx9N8qDVMm8b16eqKuZRVpM3I8sbCh9oqVk0p4tTGit27ueJlJhYrRZHxRqvnWbCA+x1lHNAWkywRe/rp4vXNN0cfiyGufX3caaOsjSUzRjPZ7vXr9TlBIEkgzfmFzXbLzrFmm3eN+VA7oc6JXMVsViyZ3JmsbAj6gySVvRopErS16Q+SbJtplcmCvr6q/dFISJGPAONvWZhDcy59/+yzdqxbb61qLUeCrPKZLcCTJ/UsvExUjCdsf7+e7UrV6FtZZTYWQ4IvX+akKLfcYh84wRb/MdKKyZO5XYtt22zLxVQ5RI5YTD8MDHC7EVOn2hP04CDnUNDWZh/ccvPNVeKt4Yc/tK9JJWI5Muc5pRVMrO5u3blDIMWsGmGeP5/bMRLyqxUws0Qsp3UbqxNPaZcW6/nnOQmpzBsrV5Zf09zMfUeGc8yfz+3CieuINg6w/VUnuLZaW+9giBiTUWJjMQRxxgzgkUfK35ftKU2uIrhwQX+gUgjP2bP6gyTFfxqJFOT07Qby+VDPnq1n9GXQZ45Et6QVMkEyW4C7dgFvvFH+vmg6tQFYYJHgnIWXAiZWa6sth2BjTZumZ9aAYqud8ULetMne8m1p4YgF019NTbwrCpPRz6UTZzOuK1fa7e/tBV55xY514IDdLlaKItIKjYjNnavXdghyFkvmjLVmTfGq2ZadOMGfXArYUhTGIUrGLk2idP/9nAwopxQlZ+GlFP9qfc+STUZasW8fV/wnRbbaDu3y5RyhZhYNnqG+gcFIGJjBeuJEPcubEouVVrBHHWsaStnCYTKuFgmWSVQbBNhYUvTHeIk2NOifmZI5b2/X7atS5BB79ugkWH4/xkOXPdUzh0RG7i9mYZS7YI+ZUNkjci198eXL3FauZaUIFL8l41DA9ENXV1VzOtpY7HV33GEvQFKypBZxYAnP9u32OHfgACfnkrZrbZs5k9tGZ45qnziRIxdCwHLoUiVGDrL5D/9QvGrk+5VX9F1LAZM5Z6UoTN8vXswVjufUKstCzNIqM7GYg3B6e7nFDOPMAXB8gtHoP/TQNUWqvSgxJ7QbQwrwmKxfYyNHqJks6enTunVb6rHc2gQi7zHbQsOvHwkiI2C2E612yaTGHOe8YIG+5ZvqQ60RsRQpyunT+gSRQvStYkkhteIYoIFxwGhosAkWUBBgq1iKjcVIK+Q6Czt2pGXhrGus/jp5ksu4MrFYKcqUKfbiddYszst98uR8xZLPPGPv4OSUopw5k+doe6DY0UspvNSeyVWruFMEZYyzDmNhiJjsWmp9yxJEmRNykHNGIrNnD+cdzRT/LV7M7eCKa422kGezytJfjATOgsg5tdqTVJcPre+feYYj5wyhbm7mF/t1ACfUuRAC8M53lr8vEwwzyQ8N6VksyUIw2Y/BQX2LOVUOkauQ0CLBQqwYH+pp0/SJPqcPtWS5ZTtUw/79OqFOyVCPp21eihSluZnLIGqFJ4L2ds4Lmcl2b9tmk/PcEoZ6jHX0KOfMsWKFXaA5ZQonRenttRfVzc2cJOf8eZtkpTo6aEjVPWtgxi4AuPvuIoOb4/Q5xod68WLO/lDabx2qwyCnBR9D6o4e5SQMUhuhZaCHhvh6JUDPdj/yCNf3ssvb01N+5kGqZeF42R+yGWXmd9y3r7j/rJ3QOkH9t/BaQIzFP9qNJHphrZpYMDio6zFlG0grEByOXJIPK1YKQQxBz4iltKulRdcqSsHSU0/ZsQ4d0rd85TsyZMAiwfL9GSnKeBZLysTA/I5Ll9q7Lpcuca4C/f02iWczrmfO2FmS9vY8OnHBePtQ33abfbT14CDnisJk9NlCwp077WLJJUu4w5FyFkvmXMzMmGH3V4q0wnIW2buXy5KKtEL7nnPmpEkYNMIzcWJa3UMOfTGjE2djifWelpzatIlzA5IFiEbkU+0itfti8WJOq1wLH2oGkpTSnKmkJoitPasxnFDngNxkmvm76Cu1Q0OGg5FWsDeZNvALKWcyrtaiIUXC0NEBPPhg+fspBPHCBc5pgtkyPXdOdwyQyZaVojDHcjMe4FaslAXI3Lnc1j1bSJhLWvHGGzZpOHcOeO45OxZDgltaOPkIQ8QmTuQcVtrb7UOBWFI3ebL9mWysF1+0HQP6+jiNPvN5LLFg+n7hQt2TOKVdbLZ7+fJ8vyMzlpw8yS2MJJOqzR8DA9zuE0OC7723WkA+2lgsCb733uJVS0SkumnkOBJdfkdtIf/GG/ZiE+CytzffzFk8MiSYzSrLAl47MZXdEZb3GXLuhPoGghA1bRXLEkSmGlqK/xiNK8BlSZkHc+JEXYcsWQ/WZzeXfOTYMd3+LNWCT+t7GViZU8tyFv81NVU9w0eCHFTCLIwmTcrnhfz661xf5ChwlGtYVxQr1sWLVesmK5ZF6rq6uGz3smU2+WOJWF9fPn3xuXP2750zE9zdzZFz5h6cMYOzeLzzTtsjv6WF8+TPWSy5a5c9zrFkk/l9tm/nEjs5failOFvb2Vu6lPsdZdzMUfwnGX1tscKSTaa/Dh/m5CPMAmRoKC3brbXrne/kdhqEUGs2ovJcWPe0zBuaJFX6nq3LqjGcUOeA/Ng5srdMkUSqTEOTVsj2lOYgIWho0LMRsm2mHUUtOH26eqDBSEjVF+fyALdIcKqvMiOtkEFdw9y5hdZSQ2MjZ5F2+rStL2xs5KQo585xp66xv2MuOQQT6+RJjtQtXWrf0zl9qGfP5nYtXn/dLryqhdUdE+v8eS7jOn26nQm2dpUELS124eUdd1Q9kzU89ZSdacxJglML9nLG0sawXbu4RakU2WuEesECbvySnWCt33JLURiMt7TihRe4XVfJ6FsWriJd1SBjvXadfI51L8qOmCWRATxDfUOBsZJhi/9yxpKbXvOhlu0pRts9NKQX2bErU7lGmwSl+Omee+xYwz97JKR4IeeMNW2afry6fA4zKLKuFUzmibEGa23lDhdhiCtL6qwFSEqs1tZ81m2TJtmZs0OHgI0b7VhbttiL18mT80lRWlv1nY3hsSzkPiSGIXXLltm7KXv2cAWA3d22rp6VogwO2u1fulS3zRQwn5ezWDJFWmGNOSdOcAtqZl4bGODcIUQWpt37Dz7IFdDm9I5mtd0M5s4tXrUdFTYWI62QMcmauzdsKF61RRQjJxz+WYwPtRPqGwiMDisl4wro0gpWPiKDQK5itqEh3TFAMk7f/74di20XI0WxiJhkRazT7qRNGgFJ+R2bm7nPZLf3rcK+oSH+SHRrMGaJBRNr2jTOCzlnhnrxYntBwJK6Y8dsj+mhIU6KMjBgTw7nz/NHolt9f9NNxSmbFtiFEdNfd9xRPTV1tLGY78gSHka/uns354XMyoAYXT0Ta9Ikbizs6rIL1dj+amqyCTUrh/jBD4pX7Xtu3sw5YDDe0SkafSvWsmWcDEhi5TioRHaCtYU8G0vmBO3eF4LMeORbny3XWOSc6a93vKN4tXap6gROqHNAbiBtO1GK/9at42JqDh6s7EAyn5q0IqfLRwo5B7iT/5jJzYolvwuzldveDtx3X/n7KadBnj/PFaAwBPHCBc4GKlcm+PRp4Omn88SaOJHbyp03T8/oA8XiyNLBAnxGny0aYzL/uaQofX28Rp85+Y9p19SptvPDTTfp/viC5mZ7Amxo4Nr13HP26Z85ZS1nzvAafQtnz+Z7Zu++u3g+LCxdyvU9g9dft9uWU4qSmgnWFhivvcb1PeumwYwlDzxQvGqZccaVA6hm/Rkfaou4ig+1RpZZrTKTVX7++eLVknQxshb5HOa+qAM4oc4ByWhq0gr2QZIbWtv6klWrZZklhFo7lIIlwWOh7dYGdnmAGG33hAm6BVdOH2qgaDezMOrv5+zicmWCAX4HxIoVIydFaW62idiFC9VB3Ypl6bZnzeL0xbt32/roFCKWqwCNjZWLIO7Zwx0Ss2SJbcM5bRqXcT1wwJ5M29q4RdbgoN0XqR66VqxcOvEdO7j7fu1a+0wBdmE0NGT3x623covSvXu5YkkGbN+nxNKI2LFjnExA7FY1bffAAF9/Y7XrHe/gduHEcECT06TWZTGZcysWW6jKxBJosSShxtRI1AGcUOcAsw0imUprS15uHE1aIYTamgCZYkmWUOeMJWCkFWyRjWjOyt4HgO99z4519iywdat+TWMjv0CyJommJs5xg4kVQj5yzpK6WbNsOcfp07qlpODkSXvgZIv/LlywFwTz5nFeyDn7K6e0Ytky+/TPwUH72HSAW0iePs35UL/5pl65D6QdDZ9To5+r72fOtLXpKdIKS1KwY4dtawgU0grrGZozxy7OBPhahVwL/dw6cQYirdD6f9MmjpzLTjBzsqT1PZlFg+y4svZ0TOGllaFmijjZbLfUR2muR1J0zez01gH8pMQcEN2XRpbl5hLLuzIwmWC5+a0CDiaWZAQ1mQPAEWpWXyzvr19ffk2K1d3QkJ4Rk0mUdWGwHt4YOSmK5T4CFNuzTBFHzgz1tGm6mX5KrJxHfB86ZBOe3t7qlqIGhjyxWVIm1uTJ3GEZkyfbn8kSxOZmu+/ZWC+/bGeU9u3jM3WMFCWXD/Wtt3IncbJHtTOk7qabbJ07S+r27LEL+06d4gr2WFkLu8iyYj3wAOejzXqTM1i/Xj/4LCWW9ANz7oMFmdu164UjDA7qixqGuDILUjaWzN3WwkGSeNpYxxJqJhGZmu2uMTxDnQOi1dKkFSzZZIz55fMsjStTWS0rYKbwB9A1rvIdtWwxUO0DxqOZnXStrPLwz7Vg9cXQECdFYWKxW7mNjbbTxIwZtrUeUAyscnx9GVgidvCg7gGeEotZNFy+zHmSMrHOnOEsv5hYixdzGv358+2sMpslPXLELuJiY128yPlQ55JD7NzJOXMwsTo7uaKl1attD/D2dr4ALVex5L59nAUfA+Y527ZNn6tSYrHj19y5dr/edhvX9/K5Gtj+YupEUg8q0b6D7PCwZFOLJTtwrAMGU/xnuQuJzFQj1Kz0U+SQjAf4NeLy4RnqHMjpQy03DnOqkXXDyvvaZCPXWFIUmdS0whhZcVsrZ8kKbNtWfo0MiNYgxqxyr7zWQq5iNsAe2Pv7qxXwGtrabAvBCRO4CencOXtCnTTJJt1Acb9amTOWiAH5Mq4MCT58mMv6zZ9v39M5fahZV4GeHnvrnm0X018sQWRinT/P9f306XZ/sacINjXpWlkAuOsuLhv29NNchjrXAiR3LAZMrG3buOK/RYtsicy8eZy+eOdO+55mXSFS5CNDQ/pzmZJxZd00LCkKUNz/WrLl/vuBr39dL5Zki+0Z6YV49lvPmiQztPE8tS6rxnBCnQNMtSqrCWYINRtLCog0aYU8SJaLgUx+2uDJ+irL+9Yk2NhYDAYamCy8IMdJiQBP6pqaiqyYhVxE7Px5bvv19Gl7AdXZyR3QA4y/vpiJ1dJiF3qxsSZMsHcHdu/mSPCuXba+uL2dIxZMf02ZwhWXXr5s27LlzFCzBHHhQtuycNcuzmawu9vWF7MZV+Y73n673XY2Vs4MNRvr3nvthffJk9wCZGCAk6Iwsfbvtwnp+vVFzYz1jDBj73AJA0OoGWcOVlrBFP+xiTVt/pAalxMn9Jqe554rXrXFsOwCWdI296F2jIgUBwxrwJMtF83JIOcx5uwKUCYiTVrBnvzHZPSlbdYgzMaaMMF2RZH+Yo6/ZVfMlg91ytHQWqEqUBBlVts9nj7UCxYAq1ZxsZiFEUPEOjttnThLEPv7gaNH9WuGhjgpysWLNmno77dJN8DJDpYv1083FeTMUC9fbhd7ppBzZnufidXTY/+Or7zCFf8xJHjWLK54mYnV3s49G3Pm2OMX218hcJ7WDJ55xl7MbNmST1efKtPQwBxwBXB9yhJEcR9hTl20xh3ZCdbaJ8+FtdvAyFpkAW/tQDFZ+IcfLl4Zy8g6gGeoc0BuVG2bSYr/HnxQjyVbuJoOmSXUMilr1m2pmfMcmWA21qVLtjsEc6gOUPw21ra9tJuxxGOLJZmDCthJxCokYsk5YPcXkwViY7W2ctnbjo5iy13D1Km8D3WuzPnRo3b7WV9luVZDTw/f9zl9qK0t+RUrOBu4xkZOisIQkE2bONu8nEeisxp95mh7pviPibVuHeeUs2CBna1nC/Z27+Z2ERmkFCVaC0Umlsx5g4N6ppSJJYcUWb/Rgw8CL72kXyNtYaQV1ucJ2bbGClkgMok1VoqiEf3Nm4vX/fv1gnsm4ZdieVsH8Ax1Dgj5vffe8mvYG0MOFdAOFxBtkpV5ktWmpntitcpMFl6Qw9NarrMkDBLDklY0NOQ5BQootsS03xqo9qd2qA6Qpi/ORRCZWDFy269NTba04uRJjog1NNjHBS9cyFW3HzxY1RiWge171jYvZ6xcOvGtW7lDYmbPtt1mOjo4u7W+PjvD3tFhayyBvBKGnLZ5DDnfvp2TfNx1ly2vYhdGFy7Y7brjDl6jbx1yk0KoWVkLWzejQbLhltxp4UL7PpR51IrFyPIkoWb5uT/3nH0fpnpHM3VZOXyo2V1v+UxtTJEdV+twpzqBZ6hzgCFiMkhYB32I9Y52KIXcsNbxvoweW5DDh1rAbrMx0grmpC7Allb09wNPPaVfI5OHrLDL0NRkT+Jsf02ezB1PzsQCxl8n3tJiZ5WPHuV0vOfO2UQspfjPmhyWL+clJuNJqNmM64IFNgm+eJHLuDJk4Ngx7oCFvj5bP3nHHbZVHMBpu1My1KybkYWZM20ixsYKwSa4mzdzBWEbNthe4ex4w0pR2FgWhmuVtd+ctWWUWBrmzbN3ZuRgpJMn9YOnXn3V/jy2+I/pL3ELsgow5bMYV60cxZJsrHXrgK99TXcMEQ0/40pTB/AMdQ5IFlXbkpOb2VppMQWOEsvKHrCEesIE4KGH8sQCeJ24Ja1gDiqRLVVromdiyWBoTfRnz9qWX2wWvrPTPqCH2RoDeFLX2Gjb66UcKZyrXefO2f26c6edeQY44trWlu+AnhkzOHLR2lpoazWw/dXQYGe6WLL52mt2v+7ZUz1oQUNOH2om1urV9s5GSruY/po7t6pzHW2sN9+0SfDZs/kKe9lCQiaWnF/AJFFykeD777etWVlSxziUsNnb3l77mp07i1crccA8G5JQs3aN2AN6mGvFGlTjAanykZynL9cYTqhzQLb1tAwCq1VOkVY8+2yeWE1N9oMkulWr2Ki52Z5oGB/qK68tgxBp65hpJhabVT571j6gh/ETl/fZbTbrWO4lS+xsMVBMlFYsNkN9/rx9yEJOCUOMeY62BwoSwxJEK9ayZVzhTEeHXeTEkuATJ2wf7RQJg4UUaYV17csvc8V/DKmbMYNb6N92m10c29HBxWI07mx/HTxo11rklFa8+mo+JxNWyjh/vl37IEXEjBc9U1QN2GPrhg129pMt/mP6VLiClbRhx97hr2Vg7mdx07LGsK6u4p7Q+l8+z+p72QnWxifWFaVO4IQ6B5isMjvw5JRpyM1oZc4uXrQJqSwIrO3CSZNsKYpMpNZhLAwRY/uLIRY5Cy9Zcr5vn70wknZbWeWJE7nJ6PJlO0MyfTrnQx2jPdixBFGu1ZBTc97by52wN22a7QGe04d69Wr7GQIKEmbZXeb0js4Za3CQmySnTSv03RqOHuXkIyHY2bw1azgP482b7TEzp99zLbTKTCw51MkidXPm2LUW8jszhwJZ2nSZ8xhpBVv8ZxHEFFkLE8tql8yf1q73unX2Pc1KUU6csO/rJUuKVytpI3OQtkso7/lJiTcQGFLHHn+dU1ohNnEWERsash9Kqfa2qr5DsAdXdmXd1VUcbauhFiSYIXWyAGGkFbkOrzl+3C7ilIHJcgyYP58jdUDeYslcFmmNjZxlIWsfZh0rvnmz7e0NFIvJDRv0a9rbOSkKQ1xnzuQIIpMJzk3OGcycWZ2gy7BrF6cv7u21M/ps8R/TX2vW8L9jLh/qFH2xtaBZu7Y41l2DSCasWOfO2feOzC1WvUVfn72AEimKlUxKIcHWd0xZGFkEcckS+7lNKSS0xlWR2lk7ry++aHMYyXJbNVKMtpspgq4jeFFiDjAG5QJrYJRVujWQAXkM3QGO8AjhthwDTpyomr+XgSWuzOTGEuqpU23dnQyGueQQAHe4CDvRbNyoX3f8uD0ZpSwamAmEiXX77dxBJWy7mL6fONHe3k/RdlvyhMuXeftD6zMPHeLsFgG7v1as4Ap6cpLgBQuAlSvtWOyR6LnI5pEjNhHbuJHT1TLFkjNm5CuWFI24dW1Xl52oGL6NrhGWS5e4glDAlkNs2mTfh+KXfPKkvjuWkoXPkaFesaJ4tch5YyMvRbHG1lmz7GJJNtaWLbYntGT8rcw/M/Yyh8AB3HgpCSmr+LpO4BnqHJBBx3oAmpvtk/+kyEg7rUhg3dxvvFG8SiHEaGKxemym+I+NdeqUnfVjCfX06ba2W7KQa9bo1zGkTiZuS1rBxJLJypq0cspatm+3PVWZDANQuCEwpCcEu1B15kzOh5p1dGAIz/nzwN69eWLJtRq6u+0iNSBv8V9bm73gvPturvgvhHwOGK+/bi8k2eI/ZtFw4QIfy+r7Y8fyFf+tXVu9VkNXl32AFVv8t2ePndGXuc+KlXLoSQ6tspBzy5ObIdTSn5YTyz332M+QxREEp07Z35Mt/jt61L4P2VhM3wvfsJJvKbsDXpR4A0EqX62T2ZiMq6ziLQeP1lbbj1dWiNbqFOAJdQ4pChuLyQxKBvjOO+12sSc3WWTz5purE1wZpFjScq1gSHDKYiZXRp9pl/SXJa04fNj+HWMs/rG2CZcutTW1QPFbWzslKSQ4l5OJfG6uWFa7XniB04lPmWLvik2dykmrjh2zfcdnzswnaxkLOUSOdgmxsJ7J22+3F/FsDc758/Y1Urhsjb+HD9sZS5bwpGiVc8SSuc/K1i9ebO8iyg6hNScz0gpJGFjEe+NGe5eK1XYzZJTt+5yxmpvt31EkjNY8WidwQp0DLBEbHKx6WpZBbhwrI9baamciWPLU0GDf2CnFf+zK2sp2pcSyBsXu7oJcaBASYB3x3dRkEx5WWtHZaRPSnNpu1n0khdRZh+r09dmZLpkULOLNuKIIrPavWWNbFg7/XOt9NrOZSyc+bZq94yVFqBaGhuzv2NdnkwqgIGEWiV+1ijvYJTehzhVrxgzbESGFbFrjqlgaWv3/6qv2YVJMsTHALUBkt8i6X1M8wBkvZ6u/WDnEzJn2PCQLI6vOaNs2mwTnlKKID7Vlw5mi7c6hE2ez3XffbWfs5X5nduzqAE6oc0AOa3nzTf26oSHbpislE2wVCLKxZs+2T/7L6aYhGUaLiAG8bZ6lz2PIuWQzrIHgyJGqnKYMbH/NnWtnXNlYzPHXQmKs35shdexCkoklk6i1kNy40ZYwyWdZ7Zo0KZ+2e/Zsbju3qYknYhZi5Kv3LRw6ZLvN7N3LEWqAq49gfait77BuHTdeMrHYTHBHh70YYy2/enrsjL7URjDSCus7CumzsrcMCZadOuveZ8g5S8TuvNO2tza7AAAUxklEQVTeTWGzt6dO8XII635l3GZEwmiNcwxxlUSM1ffMglpiWM/tsmW2ljwlc85Y+sq11wC8KDEH2OrkFEcHa4Lo77f9f9lYjBRF9MeWh25Hh+0OwfpQM/0lGU2L4KZIGKyH/ORJe2JjZRox2rEkhqWrX73aHnhkkLZcK5i+l+1gS1qRou3OkQlmtd29vXzmw4q1fLmt1wQKmYP1DKUUS9arbZ5FBjZs4Kzu5HM1TJvGtWvRIlsaJtk+i0wODvJHK1sE8fhxznqSicUQMSF1p07pu2M5FyBz59rzoxQRWzUSKT7UVn+98op9KBgbi7nv5Z63FqYMCZZYVmKtudnmAPJciHy1DJ2d9imoLAl+6SV7DGCdTOoEnqHOgZz64py2eVJEYZGnEydsT1V5iCwHjI4OO+MqA7p1DHtj4/hKUVL6Plfx344dVS/XMkhGwHKtmDDBbpfYi1k7JXPm2L+1LASsz0zJUOfMdluxenr4I23Xr7fbxWRRGGnFfffZfQ8UBMXKbLIZaubanLGGhjgS3NYGLFyoX9PXxzusWLpt2TWz2rZnT/VgijKwRXYpxNUiFimylhzSCpHHMbUulrRNpCjWb7Rrly0pkloMxpc/pw816z6SY2Ek1qeWvvjOO23NNitFOXbMvmbx4uLVMgE4ccLuU/ehvgHB2uYxpI4l50wWS/xbxfanDOfP29m1o0eLV2s1fPmyvfqW962H5JZbbB/nsTjYhZFWWLEkm5zjiG82c97ba+v8JBtjyZMWL7Yz4in9ZSGnTlyesRzSCollbas+9xxX/HfxIvD00/o1bW35pChz5/LFf8xihgETi5W1tLUVhagaZHfKGluPHrXvezbjymQj5TAgq/9zekenSCus8ffWW+1iSck6W9nns2fttsvYZM0xx4/bvuPSbqvOKKXvcxBqliAuWWIvQHJKK0SCYsnptmyxkxAyb1g7DZcu2f0liTwmyVUHcEKdAyyhbmy0rxESbE0iwPj6UO/ZU7xaxu/799t2a+yigcn6pejErVW6eLJaRTtMf0mfW64VjO5ZKp0t+7AjR6oLnzKwmfPLl+0MFlvguG5dNWtRBlYiw9rvAYV7gnUdm+227vuczhw9PZwXMmD3x4oVtt0XG4slwVOnAg8/PLrPEly8aD8fbMb1zBk7cSCH7liEjckEM/aObCwZkywC0tmZT9vNEDGW6O/caVugis0a4wg0nj7UItGydl4nTLCfNZacT59u3z+stOKVV2z7VtHTMz7UVn9JLIt4M7IW0cpbvvZ1AifUOSCrKKtAqKvLzljK9r5FxBhSJ44ijL44Z+Y8V6y+PvtEP5aIdXXZGVcZMK2MPkMGpPDHmsBTSB1DLHJJUV5+me9763ecONFul2SArZMx58+verWXgdXoM/0lmTeLUOcs4uzutgvGBLmK/5qabCJ2330cqY6RSy4AXFbZOlkyp7RC7mkr1vDPLYM8+9aOXQi8xtXaKZk61d5qZ4v/9u+3i+fYWEzf54wlEkZLDpGymLG0w3fcUXXeKIPIL5kaKSvrz/ZXf79tGSvPaw4fapGhWZLOlN2Ba6Qose4IdQjhfSGE10IIr4cQPl/r9lCQFax1RC5T/CeDsCXW7+y0P0+yXEyhGksGckgrWCJ26pSdcRUSYHmADw3ZJIUlPGvW2CtmybLkIGI5ZS05M8HSHmtbdf9++3eUdluE4eab7ZoAWcxY0gqGHLLFkjlj5dQqP/MMR84bG20y0N7OF0taREzuGWaiZLOkjM6SJXWMVtkiA5LIsCQMCxbYC8kUH2prMSByCEunf/Lk+Bbs5fShFjJqzaMLFthF9LJbYWVcmYy+zBvWDvSrr9r1ETm13Tn7Xsi5FWvSJDujL7U+W7fq19UJ6kqYEkJoBPBfALwbQA+AF0MIT8YYjYq5GoMlYseO2T7UomGyMptTp9rSBJa4NjXZ1+Qs/pNMPuNDbU3gbOGldWoTUM1qbN0K/PiPl1+XIkWx7on58+2BOsVPfDx14rKbYmX0Dx60txLlfUsDHqM9ebN67AcesIl+irbbQkrhpQX5bR55xL6WAVMk2NNT9bXW2njxor1tL8TC+sycRXYpsax7rL2dS6AwsRgiJnKvAwd06Vp3t90PIiWwxgCGBIv/v7UjkdOZo6lJPzJ9eCyLbE6dan9HWRyK7LEMO3dyhZ6APX8wfS+k3JLTjXfhJdv3K1fa0ipZGFn+3nWCuiLUANYBeD3GuAcAQghfAfAogPoh1IcOFZPY8IlfMsF9fYV9VhkuXCgqw4WITJpUHZR37y7elxvIGqAuXgS+9rW3e0IuWlT87dSp6pa9FWvZsqJYZ86ct2s3m5uL9+X7MoT6+PHiwInz50eWmwiRtjJiDQ1FrGnTqrsA3d1vzfjIAMb4UPf3V/tr9uxiQXLhQrWfZCC3Jvn9+ws94JV9LyThwIGqZs3qrwULRo4FFBKVri4+VkND8R3uv7+4T0fSzcngKwVTWqzBwaJ9soX86qtv7RtZODEEcWio+h2XLSvuq6NHqwe+yARjZWU2bCiK/4b315QpVSeIHTv4BUhLS3F/jdT3S5YUzyfb9wsXFovl++8vtpmv3GJta6tmwixphbT79tuL73b6dFVHfyVYYtHeXn2WgYIcDM/eXbpk2x9KG6ZMqU6q8+YVz/PZs2/NSrNZ5enT3zpBNzVVx1D5PCvW/fcD3/oW8N73jkx65swpiF+M/IEgP/ETxe/f2/v2yTyE4ve1iIzEuu++4jmePbvo5ysPXjlzxi5AE3LyyCPVuMuXF9+nr6+6MLx40SauYhW5cuVb+6Ojo/g9Yyye9QsX7FiyM/jTPz0y6bnlliLpMTBgyxilLb/2a8AXv1gQ1CtJ2dSpxbhk+ehLrM9+Fvjd3y2evxMn3r5gHxiwZZgS6xd/EfiVXxl53gaK39FK7Mh8+K53vVUiOnze7u4uYlm7dTKPfvazwGc+89b3WlqqFnh9fbZcRWR0f/7nwJNPjjxvz59fJD6sHUnhG3/wB8APf1j8+5XzNlD0m/UMSaw//uOibTJvA8DXv24/N+OMeiPU8wAM3yPvAfCWJyeE8ASAJwBgoWWnNBZoaChuvuETWXNz8TBYx1G/5z3A889X/7u1tfoAyoEbzc3Fg2RlnlavHjnr19ZWxLx8uXidNAl497v1WD/zM8VDtHv327MD0sYpU4rv+P7367EefbSYMKZMKQb+kSb8WbOKQjVLpvGhDwHf/GYRR/qptfWt2rLm5uIfOU63DB/+cLEAEUyaVMQcGKi2sbm5mOA/9CE91rveNXJmU9p4/HjxO3R0AB/5iB7rE58oFh4jnc4obWxtLQjLRz+qx/rYx4pM1oQJxYA80lZzV1cxGbzrXXqsj38c+JM/qbYBKPrnysXGkiXAQw/psT71KeAP/7D63+3txf1+7txb74/29uJzNXzyk8VkOxxXPkdNTcUz+qlP6bEee6zwch+JhLW3F7/hhQvF/frJT+qxfvmXi8n/8uWiDVf2U2trcW994APA5z6nx/r0p4s2ybMc48jP0apV9vP46U8XCzZp1/DnaHiWrLUVePxxO9a2bW/dgZI2NjRU29jSYsd63/uAv/iLtz9HEya8tY2dnfbv+Oijxbh65szI/SRtfO97C0Kk4fHHgaeeKp6TEAoSdmXMhoZid+Oxx/RYn/wk8N3vFv0sz9HQ0NvjNTcX/aHhE58oFg3DCeaUKcW9furUW8cw6xm6556CmFw51ksb5X5rbi7GFA3331/0/759I2vFZSG3cqU95vzkTwLf+EZ1Ad/SMvJ8dPvt9vP42GMFCRscLNoweXIRa6S+t+ahD34Q+P3fr847I83bEuvHfkyP9e53F4uWKxfckydX523p+/e+V491++3F/PLii2/P9A5/1hcutBcg739/0f/9/cXvONJzNHly8Xt/4AN6rB/5keIzBwbK522g+F2eeEKPtX59Qbrl+w2fj1KkceOEENnK9HFACOEjAN4bY/yZyn9/EsC6GOPPjXT92rVr40bL+cDhcDgcDofD4RglQgibYowjZk/rjeL3ABheITAfAGHu6nA4HA6Hw+Fw1Ab1RqhfBLAshHBTCGEigI8CeLLGbXI4HA6Hw+FwOEpRVxrqGONQCOFnAfxfAI0A/izGaJgZOhwOh8PhcDgctUNdEWoAiDF+C8C3at0Oh8PhcDgcDoeDQb1JPhwOh8PhcDgcjmsKTqgdDofD4XA4HI5RwAm1w+FwOBwOh8MxCjihdjgcDofD4XA4RgEn1A6Hw+FwOBwOxyjghNrhcDgcDofD4RgFnFA7HA6Hw+FwOByjgBNqh8PhcDgcDodjFHBC7XA4HA6Hw+FwjAIhxljrNlw1QghHAOyrdTsyoBPA0Vo34gaF933t4H1fO3jf1w7e97WD933tcL30/aIY48yR3rimCfX1ghDCxhjj2lq340aE933t4H1fO3jf1w7e97WD933tcCP0vUs+HA6Hw+FwOByOUcAJtcPhcDgcDofDMQo4oa4P/GmtG3ADw/u+dvC+rx2872sH7/vawfu+drju+9411A6Hw+FwOBwOxyjgGWqHw+FwOBwOh2MUcEJdQ4QQ3hdCeC2E8HoI4fO1bs+NhBDCmyGErSGEzSGEjbVuz/WOEMKfhRAOhxC2Dfvb9BDCd0MIuyuvHbVs4/WKkr7/jRDCgcr9vzmE8IFatvF6RQhhQQjh+yGEHSGEV0MIv1D5u9/7Ywyl7/3eH2OEEFpCCC+EELZU+v43K3+/KYSwoXLf/+8QwsRatzUnXPJRI4QQGgHsAvBuAD0AXgTwUzHG7TVt2A2CEMKbANbGGK8HX8y6RwjhYQBnAPzPGOPKyt/+M4DjMcbfriwoO2KM/7qW7bweUdL3vwHgTIzxC7Vs2/WOEMIcAHNijC+FENoBbALwQQCfht/7Ywql738Sfu+PKUIIAUBbjPFMCGECgKcB/AKAXwLwtzHGr4QQ/hjAlhjjH9WyrTnhGeraYR2A12OMe2KMgwC+AuDRGrfJ4RgTxBifAnD8ij8/CuBLlX//EorJzpEZJX3vGAfEGA/GGF+q/PtpADsAzIPf+2MOpe8dY4xY4EzlPydU/okA3gngryt/v+7ueyfUtcM8APuH/XcP/GEfT0QA3wkhbAohPFHrxtyg6IoxHgSKyQ/ArBq350bDz4YQXqlIQlxyMMYIISwGcBeADfB7f1xxRd8Dfu+POUIIjSGEzQAOA/gugDcA9McYhyqXXHecxwl17RBG+Jvrb8YP62OMawC8H8DnKtviDseNgj8CsBTAnQAOAvjd2jbn+kYIYTKAvwHwL2OMp2rdnhsJI/S93/vjgBjjpRjjnQDmo9iRv22ky8a3VWMLJ9S1Qw+ABcP+ez6A3hq15YZDjLG38noYwNdQPPCO8cWhis5R9I6Ha9yeGwYxxkOVCe8ygP8Gv//HDBUN6d8A+HKM8W8rf/Z7fxwwUt/7vT++iDH2A/gBgPsATAshNFXeuu44jxPq2uFFAMsqVa8TAXwUwJM1btMNgRBCW6VIBSGENgDvAbBN/78cY4AnATxe+ffHAXyjhm25oSBkroIPwe//MUGlOOt/ANgRY/y9YW/5vT/GKOt7v/fHHiGEmSGEaZV/bwXwoyg07N8H8OHKZdfdfe8uHzVExa7n9wE0AvizGONv1bhJNwRCCEtQZKUBoAnAX3rfjy1CCH8F4B0AOgEcAvDrAL4O4KsAFgLoBvCRGKMXz2VGSd+/A8WWdwTwJoDPiqbXkQ8hhAcB/BDAVgCXK3/+VRRaXr/3xxBK3/8U/N4fU4QQVqEoOmxEkbj9aozx31Xm3q8AmA7gZQCfiDFeqF1L88IJtcPhcDgcDofDMQq45MPhcDgcDofD4RgFnFA7HA6Hw+FwOByjgBNqh8PhcDgcDodjFHBC7XA4HA6Hw+FwjAJOqB0Oh8PhcDgcjlHACbXD4XDUECGEaSGEfzHsv+eGEP56DD7nN0IIB0II/67k/TdDCJ0ZP+/LIYTjIYQP21c7HA7HtQ0n1A6Hw1FbTAPwj4Q6xtgbYxwrEvrFGOO/HaPYb0GM8ePww6ocDscNAifUDofDUVv8NoClIYTNIYTfCSEsDiFsA4AQwqdDCF8PIfxdCGFvCOFnQwi/FEJ4OYTwfAhheuW6pSGEb4cQNoUQfhhCWG59aAhhRgjhO5VYfwIgDHvv65VYr4YQnqj87TMhhC8Ou+afhxB+r3Ly6N+HELaEELaFEP5p7g5yOByOeocTaofD4agtPg/gjRjjnTHGfzXC+ysBfAzAOgC/BeBcjPEuAM8B+FTlmj8F8HMxxrsB/DKA/0p87q8DeLoS60kUp/YJfroSay2Anw8hzEBxwtmPhxAmVK75ZwD+HMD7APTGGFfHGFcC+Db7xR0Oh+N6QVOtG+BwOBwOFd+PMZ4GcDqEcBLA31X+vhXAqhDCZAAPAPg/IfxjkrmZiPswgJ8AgBjj34cQTgx77+dDCB+q/PsCAMtijM+HEP4fgH8SQtgBYEKMcWsI4QKAL4QQ/hOAb8YYfziK7+pwOBzXJJxQOxwOR33jwrB/vzzsvy+jGMMbAPTHGO+8itjxyj+EEN4B4EcB3B9jPBdC+AGAlsrb/x3ArwLYiSI7jRjjrhDC3QA+AOA/hhC+E2McsfDR4XA4rle45MPhcDhqi9MA2q/2f44xngKwN4TwEQAIBVYT/+tTAD5e+X/eD6Cj8vepAE5UyPRyAPcN+6wNKDLWHwPwV5X/dy4KGcr/AvAFAGuu9rs4HA7HtQon1A6Hw1FDxBiPAXimUtD3O1cZ5uMAPhNC2ALgVQCPEv/PbwJ4OITwEoD3AOiu/P3bAJpCCK8A+PcAnr/i//sqgGdijCIRuQPACyGEzQD+DYD/cJXfweFwOK5ZhBjftuPncDgcjusMIYTfAHAmxviFUcb5Jgr7ve8R1/4FCl11dl9th8PhqCd4htrhcDhuDJwB8ETZwS4WKgfQ7AJwniTTXwbwCICBq/k8h8PhuJbgGWqHw+FwOBwOh2MU8Ay1w+FwOBwOh8MxCjihdjgcDofD4XA4RgEn1A6Hw+FwOBwOxyjghNrhcDgcDofD4RgFnFA7HA6Hw+FwOByjgBNqh8PhcDgcDodjFPj/x4w2fgnMQvQAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.0\n"
+ ]
+ }
+ ],
+ "source": [
+ "# quantify radiative forcing due to change in albedo\n",
+ "rad_absorbed_winton = rsds_array_artificial * albedo_result\n",
+ "rad_absorbed_semtner = rsds_array_artificial * albedo_result_Semtner\n",
+ "\n",
+ "\n",
+ "\n",
+ "# plot absorbed radiation\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rad_absorbed_winton,'r-')\n",
+ "ax1.plot(time_artificial,rad_absorbed_semtner,'r--')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"absorbed radiation [W/m²]\")\n",
+ "plt.legend([\"winton\", \"Semtner\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "rad_forcing_dif = rad_absorbed_winton -rad_absorbed_semtner\n",
+ "\n",
+ "# plot difference \n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rad_forcing_dif,'-')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"difference in absorbed radiation [W/m²]\")\n",
+ "plt.legend([\"Winton - Semtner\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.mean(rad_forcing_dif))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 115,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "23.71732067300262\n",
+ "23.291146436809054\n",
+ "-1.8850707251400884\n",
+ "-3.237239568195957\n",
+ "5.007872629325032\n",
+ "5.014980452291748\n"
+ ]
+ }
+ ],
+ "source": [
+ "# plots for presentation\n",
+ "# qtop\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,Qtop_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,Qtop_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\",\"Winton\"],loc=1)\n",
+ "ax1.set_ylabel(\"Qtop [Wm$^{-2}$]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "#ax1.set_ylim(0,400)\n",
+ "ax1.set_xlim(0,days)\n",
+ "\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_qtop_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "# plots for presentation\n",
+ "# qbot\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,Qbot_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,Qbot_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\",\"Winton\"],loc=1)\n",
+ "ax1.set_ylabel(\"Qbot [Wm$^{-2}$]\")\n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black',lw=1) \n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "\"\"\"if initial_conditions==\"melting\":\n",
+ " ax1.set_ylim(-3.2,3.2)\n",
+ "elif initial_conditions==\"freezing\":\n",
+ " ax1.set_ylim(-20,4)\"\"\"\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_qbot_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hi\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,hi_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,hi_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\", \"Winton\"])\n",
+ "ax1.set_ylabel(\"hi [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "#ax1.set_ylim(3.3,4)\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_hi_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hs\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,hs_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,hs_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\", \"Winton\"])\n",
+ "ax1.set_ylabel(\"hs [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "#ax1.set_ylim(3.3,4)\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_hs_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.nanmean(Qtop_result_Semtner))\n",
+ "print(np.nanmean(Qtop_result))\n",
+ "print(np.nanmean(Qbot_result_Semtner))\n",
+ "print(np.nanmean(Qbot_result))\n",
+ "print(np.nanmean(hi_result_Semtner))\n",
+ "print(np.nanmean(hi_result))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 3 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plots for thesis\n",
+ "\n",
+ "if initial_conditions==\"melting_icon\" or initial_conditions==\"melting\" or initial_conditions==\"melting_snow\":\n",
+ " hilim=[3.95,4]\n",
+ " qtoplim=[0,300]\n",
+ " qbotlim=[-50,4]\n",
+ "elif initial_conditions==\"freezing\" or initial_conditions==\"freezing_2\":\n",
+ " qbotlim=[-240,0]\n",
+ " qtoplim=[0,300]\n",
+ " hilim=[0,0.4]\n",
+ " \n",
+ "\n",
+ "#hi\n",
+ "fig, (ax1, ax2, ax3) = plt.subplots(3,1,figsize=(6,4))\n",
+ "#plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,hi_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,hi_result,color='C1',linestyle='-')\n",
+ "\n",
+ "legend = legend_color(ax1,['3L-Winton','0L-Semtner'],1)\n",
+ "ax1.set_ylabel(\"hi [m]\")\n",
+ "#ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "ax1.set_xlim(0,7)\n",
+ "ax1.set_ylim(hilim[0],hilim[1])\n",
+ "ax1.xaxis.set_ticks_position('none')\n",
+ "ax1.set_xticklabels('')\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "# qtop\n",
+ "ax2.plot(time_artificial,Qtop_result_Semtner,color='C0',linestyle='-')\n",
+ "ax2.plot(time_artificial,Qtop_result,color='C1',linestyle='-')\n",
+ "#ax2.legend([\"Qtop Semtner\",\"Qtop Winton\"],loc=1)\n",
+ "ax2.set_ylabel(\"Qtop [Wm$^{-2}$]\")\n",
+ "#ax2.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "ax2.set_ylim(qtoplim[0],qtoplim[1])\n",
+ "ax2.xaxis.set_ticks_position('none')\n",
+ "ax2.set_xticklabels('')\n",
+ "ax2.set_xlim(0,7)\n",
+ "#ax2.hlines(0,0,7,lw=1,color='black')\n",
+ "\n",
+ "\n",
+ "# qbot\n",
+ "ax3.hlines(0,0,7,lw=1,color='black')\n",
+ "ax3.plot(time_artificial,Qbot_result_Semtner,color='C0',linestyle='-')\n",
+ "ax3.plot(time_artificial,Qbot_result,color='C1',linestyle='-')\n",
+ "#ax3.legend([\"Qbot Semtner\",\"Qbot Winton\"],loc=1)\n",
+ "ax3.set_ylabel(\"Qbot [Wm$^{-2}$]\")\n",
+ "#ax3.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "ax3.set_ylim(qbotlim[0],qbotlim[1])\n",
+ "ax3.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "ax3.set_xlabel(\"Time [days]\")\n",
+ "ax3.set_xlim(0,7)\n",
+ "\n",
+ "ax1.spines['right'].set_color('none')\n",
+ "ax2.spines['right'].set_color('none')\n",
+ "ax3.spines['right'].set_color('none')\n",
+ "ax1.spines['top'].set_color('none')\n",
+ "ax2.spines['top'].set_color('none')\n",
+ "ax3.spines['top'].set_color('none')\n",
+ "ax1.spines['bottom'].set_color('none')\n",
+ "#ax2.spines['bottom'].set_color('none')\n",
+ "ax3.spines['bottom'].set_color('none')\n",
+ "\n",
+ "\n",
+ "plt.subplots_adjust(hspace=0.05)\n",
+ "ax1.text(-0.16,1,\"a)\", transform=ax1.transAxes, fontsize=10)\n",
+ "ax2.text(-0.16,1,\"b)\", transform=ax2.transAxes, fontsize=10)\n",
+ "ax3.text(-0.16,1,\"c)\", transform=ax3.transAxes, fontsize=10)\n",
+ "\n",
+ "plt.savefig(\"plots/model_hi_qtop_qbot_{}.pdf\".format(initial_conditions))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## compare enthalpy"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/sw/rhel6-x64/conda/anaconda3-bleeding_edge/lib/python3.6/site-packages/ipykernel_launcher.py:3: RuntimeWarning: divide by zero encountered in true_divide\n",
+ " This is separate from the ipykernel package so we can avoid doing imports until\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# example of E & E2\n",
+ "plt.subplot()\n",
+ "T_vector=np.linspace(-100,0,401)\n",
+ "plt.plot(T_vector,E(T_vector),'C3')\n",
+ "plt.plot(T_vector,E2(T_vector),'C1')\n",
+ "plt.hlines(-L,T_vector[0],T_vector[-1],'C0')\n",
+ "plt.legend(['Winton upper layer','Winton lower layer','Semtner'])\n",
+ "plt.xlabel('Ice Temperature [°C]')\n",
+ "plt.ylabel('Enthalpy [Jkg$^{-1}$]')\n",
+ "plt.xlim(-8,0)\n",
+ "plt.ylim(-360000,-200000)\n",
+ "plt.tight_layout()\n",
+ "plt.savefig(\"plots/enthalpy.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "E1_array=np.zeros(np.size(T1_result))\n",
+ "E2_array=np.zeros(np.size(T2_result))\n",
+ "for i in range(np.size(T1_result)):\n",
+ " E1_array[i]=E(T1_result[i])\n",
+ " E2_array[i]=E2(T2_result[i])\n",
+ "\n",
+ "plt.plot(E1_array)\n",
+ "plt.plot(E2_array)\n",
+ "\n",
+ "dhi_bot = Qbot_result/(rhoi*E2_array)\n",
+ "dhi_bot_Semtner = -1*np.array(Qbot_result_Semtner)/(rhoi*L)\n",
+ "\n",
+ "dhi_surf = Qtop_result/(rhoi*E1_array)\n",
+ "dhi_surf_Semtner = -1*np.array(Qtop_result_Semtner)/(rhoi*L)\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'dhi_surf_Semtner' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-90-b669873ae3d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdhi_surf_Semtner\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Semtner'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdhi_surf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Winton'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"surface ice thickness change [ms$^{-1}$]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'dhi_surf_Semtner' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "plt.plot(dhi_surf_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_surf,label='Winton')\n",
+ "plt.ylabel(\"surface ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(dhi_bot_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_bot,label='Winton')\n",
+ "plt.ylabel(\"botom ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(dhi_surf_Semtner+dhi_bot_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_surf+dhi_bot,label='Winton')\n",
+ "plt.ylabel(\"net ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/bifurcation_Semtner_unlim-lim5-checkpoint.ipynb b/.ipynb_checkpoints/bifurcation_Semtner_unlim-lim5-checkpoint.ipynb
new file mode 100644
index 0000000..1bf799b
--- /dev/null
+++ b/.ipynb_checkpoints/bifurcation_Semtner_unlim-lim5-checkpoint.ipynb
@@ -0,0 +1,370 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create CO2 - ice-edge latitude diagrams and calculate stability\n",
+ "Stability is assessed by reading simulation data and applying the stability criterion. CO2 - ice-edge latitude diagrams are created by manual input of stability and equilibrium ice-edge latitude. The actual bifurcation diagram is added afterwards as a best guess."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " if stable==2:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " else:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "def plot_simulation_merged(axes,co2, startlat, endlat, col, stable, offset=0): #plot a simulation into the bifurcation diagram\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " handle = []\n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\",clip_on=False)\n",
+ " elif stable==1: # stable from warm\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='o',clip_on=False)\n",
+ " elif stable==3: # towards Snowball\n",
+ " if endlat==0:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='v',clip_on=False)\n",
+ " else:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='v',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='^',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "def plot_co2_equivalent(co2, startlat, endlat, col, stable, heatflux):\n",
+ " CO2_fac=np.exp(heatflux/5.35)\n",
+ "\n",
+ " handle, =plt.plot([co2*CO2_fac,co2*CO2_fac],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ " \n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-limited':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend\n",
+ "\n",
+ "def stability_index(DS):\n",
+ " LW = get_var(DS,\"rlut\",True)\n",
+ " SW = get_var(DS,\"rsdt\",True)-get_var(DS,\"rsut\",True)\n",
+ " T = get_var(DS,'ts',True)\n",
+ " \n",
+ " N = np.squeeze(SW[-50*12:]-LW[-50*12:])\n",
+ " Nparm = stats.linregress(LW.time[-50*12:]-LW.time[-50*12],N)\n",
+ " \n",
+ " f=(Nparm.slope) #*np.sign(np.squeeze(SW-LW).values[-1])\n",
+ " return f\n",
+ "\n",
+ "def is_stable(f):\n",
+ " if f>0: return False\n",
+ " else: return True"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv_hice_unlim/mlo_aqua_1594ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_61sic_hice_unlim/mlo_aqua_3000ppmv_61sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_69sic_hice_unlim/mlo_aqua_3750ppmv_69sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_77sic_hice_unlim/mlo_aqua_3750ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3907ppmv_77sic_hice_unlim/mlo_aqua_3907ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4063ppmv_77sic_hice_unlim/mlo_aqua_4063ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4375ppmv_77sic_hice_unlim/mlo_aqua_4375ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_83sic_hice_unlim/mlo_aqua_5000ppmv_83sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_77sic_hice_unlim/mlo_aqua_10000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv/mlo_aqua_5000ppmv_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_1594ppmv_hice_unlim\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_1688ppmv_hice_unlim\")\n",
+ "experiment4, DS4 = load_experiment(\"mlo_aqua_1875ppmv_hice_unlim\")\n",
+ "experiment5, DS5 = load_experiment(\"mlo_aqua_2250ppmv_hice_unlim\")\n",
+ "\n",
+ "experiment1_Jor, DS1_Jor = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "experiment2_Jor, DS2_Jor = load_experiment(\"mlo_aqua_3000ppmv_61sic_hice_unlim\")\n",
+ "experiment3_Jor, DS3_Jor = load_experiment(\"mlo_aqua_3750ppmv_69sic_hice_unlim\")\n",
+ "experiment4_Jor, DS4_Jor = load_experiment(\"mlo_aqua_3750ppmv_77sic_hice_unlim\")\n",
+ "experiment5_Jor, DS5_Jor = load_experiment(\"mlo_aqua_3907ppmv_77sic_hice_unlim\")\n",
+ "experiment6_Jor, DS6_Jor = load_experiment(\"mlo_aqua_4063ppmv_77sic_hice_unlim\")\n",
+ "experiment7_Jor, DS7_Jor = load_experiment(\"mlo_aqua_4219ppmv_77sic_hice_unlim\")\n",
+ "experiment8_Jor, DS8_Jor = load_experiment(\"mlo_aqua_4375ppmv_77sic_hice_unlim\")\n",
+ "experiment9_Jor, DS9_Jor = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "experiment10_Jor, DS10_Jor = load_experiment(\"mlo_aqua_5000ppmv_83sic_hice_unlim\")\n",
+ "experiment11_Jor, DS11_Jor = load_experiment(\"mlo_aqua_10000ppmv_77sic_hice_unlim\")\n",
+ "\n",
+ "experiment1_5m, DS1_5m = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "experiment2_5m, DS2_5m = load_experiment(\"mlo_aqua_3000ppmv\")\n",
+ "experiment3_5m, DS3_5m = load_experiment(\"mlo_aqua_5000ppmv\")\n",
+ "\n",
+ "DS_array=[DS1, DS2, DS3, DS4, DS5] #, DS1_Jor, DS2_Jor, DS3_Jor, DS4_Jor, DS5_Jor, DS6_Jor\n",
+ " # , DS7_Jor, DS8_Jor, DS9_Jor, DS10_Jor, DS11_Jor"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 147,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "### %matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "save_plot = True\n",
+ "plot_unlim = True\n",
+ "plot_5m = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ax.spines['left'].set_position(('outward',5))\n",
+ "ax.spines['bottom'].set_position(('outward',5))\n",
+ " \n",
+ "# 5m simulations\n",
+ "\n",
+ "if plot_5m:\n",
+ " color_5m='C2'\n",
+ " #b=plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)\n",
+ " #plot_simulation_merged(ax,1375, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1438, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1500, 90, 46.6, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 50.3, color_5m, 1)\n",
+ " #plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_5m, 1)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_5m, 1)\n",
+ " \n",
+ " # Jormungand\n",
+ " #mlo_aqua_2000ppmv_Jor2\n",
+ " #plot_simulation_merged(ax,2000, 32.68, 29.34, color_5m, 3)\n",
+ " #mlo_aqua_2000ppmv_Jor5\n",
+ " plot_simulation_merged(ax,2000, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_2500ppmv_Jor2\n",
+ " plot_simulation_merged(ax,2500, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_2500ppmv_Jor5\n",
+ " #plot_simulation_merged(ax,2500, 32.68, 36.16, color_5m, 4)\n",
+ " #mlo_aqua_3000ppmv_Jor\n",
+ " plot_simulation_merged(ax,3000, 28.03, 36.87, color_5m, 4)\n",
+ " #mlo_aqua_3000ppmv_Jor2\n",
+ " plot_simulation_merged(ax,3000, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_3000ppmv_Jor3\n",
+ " #plot_simulation_merged(ax,3000, 16.26, 22.95, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor\n",
+ " #plot_simulation_merged(ax,5000, 28.03, 34.75, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor2\n",
+ " plot_simulation_merged(ax,5000, 13.29, 30.00, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor4\n",
+ " plot_simulation_merged(ax,5000, 7.47, 15.07, color_5m, 4, -offset)\n",
+ " #mlo_aqua_10000ppmv_Jor\n",
+ " #plot_simulation_merged(ax,10000, 28.03, 41.30, color_5m, 4)\n",
+ " \n",
+ " \n",
+ "#hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " offset=0.01\n",
+ " a=plot_simulation_merged(ax,1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 49.54, color_unlim, 1, offset)\n",
+ " plot_simulation_merged(ax,1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_unlim, 1, offset) #5m limited, but always under 5m\n",
+ " plot_simulation_merged(ax,3000, 14.46, 0, color_unlim, 3, offset)\n",
+ " #plot_simulation_merged(ax,3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation_merged(ax,3750, 14.46, 0, color_unlim, 3) \n",
+ " #plot_simulation_merged(ax,3750, 19.2, 18.7, color_unlim, 4)\n",
+ " #plot_simulation_merged(ax,3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4063, 14.46, 11.5, color_unlim, 3)\n",
+ " #plot_simulation_merged(ax,4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation_merged(ax,5000, 14.46, 24, color_unlim, 4, offset)\n",
+ " #plot_simulation_merged(ax,5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_unlim, 1, offset) # limited, but no ice at all\n",
+ " #plot_simulation_merged(ax,10000, 14.46, 18, color_unlim, 4) \n",
+ "\n",
+ "\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_ylim(-0.1,1.1)\n",
+ "ax.set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax.set_ylabel(\"Ice-Edge Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.yaxis.tick_left()\n",
+ "ax.xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "ax.set_xscale('log')\n",
+ "\n",
+ "ax.set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax.set_xticklabels([1000, 2000,3000,4000,5000,'','','','',10000] )\n",
+ "ax.set_xlim(1000,5000)\n",
+ "ax.set_ylim(0,1)\n",
+ "# extra ticks at bifurcation points\n",
+ "#semtner_bif=1641\n",
+ "#semtner_5m_bif=1547\n",
+ "semtner_bif=1547\n",
+ "semtner_5m_bif=1469\n",
+ "ax.vlines([semtner_5m_bif],-0.04,-0.01,color=color_5m,lw=1,clip_on=False)\n",
+ "ax.vlines([semtner_bif],-0.04,-0.01,color=color_unlim,lw=1,clip_on=False)\n",
+ "#ax.axvline(semtner_bif,-20,0.1)\n",
+ "ax.annotate(semtner_bif,(semtner_bif,0.02),color=color_unlim,ha='center',clip_on=False)\n",
+ "ax.annotate(semtner_5m_bif,(semtner_5m_bif,0.1),xytext=(semtner_5m_bif,-0.05),color=color_5m,ha='center',va='top',clip_on=False)\n",
+ "ax.set_yticklabels([0,10,20,30,45,60,90])\n",
+ "legend_color(ax,[\"0L-Semtner\",\"0L-Semtner-limited\"],2)\n",
+ "\n",
+ "\n",
+ "if save_plot:\n",
+ " plt.savefig(\"plots/bifurcation_5mlim_merged.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/bifurcation_Winton_Semtner_unlim-checkpoint.ipynb b/.ipynb_checkpoints/bifurcation_Winton_Semtner_unlim-checkpoint.ipynb
new file mode 100644
index 0000000..aa4d858
--- /dev/null
+++ b/.ipynb_checkpoints/bifurcation_Winton_Semtner_unlim-checkpoint.ipynb
@@ -0,0 +1,779 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create CO2 - ice-edge latitude diagrams and calculate stability\n",
+ "Stability is assessed by reading simulation data and applying the stability criterion. CO2 - ice-edge latitude diagrams are created by manual input of stability and equilibrium ice-edge latitude. The actual bifurcation diagram is added afterwards as a best guess."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "from scipy import stats\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " \n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " elif stable==1: # stable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " elif stable==3: # towards Snowball\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "\n",
+ "def plot_simulation_merged(axes,co2, startlat, endlat, col, stable, offset=0): #plot a simulation into the bifurcation diagram\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " handle = []\n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\",clip_on=False)\n",
+ " elif stable==1: # stable from warm\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='o',clip_on=False)\n",
+ " elif stable==3: # towards Snowball\n",
+ " if endlat==0:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='v',clip_on=False)\n",
+ " else:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='v',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='^',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " return handle\n",
+ "\n",
+ "def plot_co2_equivalent(co2, startlat, endlat, col, stable, heatflux):\n",
+ " CO2_fac=np.exp(heatflux/5.35)\n",
+ "\n",
+ " handle, =plt.plot([co2*CO2_fac,co2*CO2_fac],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ " \n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def stability_index(DS):\n",
+ " LW = get_var(DS,\"rlut\",True)\n",
+ " SW = get_var(DS,\"rsdt\",True)-get_var(DS,\"rsut\",True)\n",
+ " T = get_var(DS,'ts',True)\n",
+ " \n",
+ " N = np.squeeze(SW[-50*12:]-LW[-50*12:])\n",
+ " Nparm = stats.linregress(LW.time[-50*12:]-LW.time[-50*12],N)\n",
+ " \n",
+ " f=(Nparm.slope) #*np.sign(np.squeeze(SW-LW).values[-1])\n",
+ " return f"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_winton/mlo_aqua_1875ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_winton/mlo_aqua_2250ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_winton/mlo_aqua_5000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton_50sic/mlo_aqua_3000ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_74sic_winton/mlo_aqua_3000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_winton_50sic/mlo_aqua_4219ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_37sic_winton/mlo_aqua_5000ppmv_37sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_74sic_winton/mlo_aqua_5000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_winton_semtnerrestart/mlo_aqua_5000ppmv_77sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_74sic_winton/mlo_aqua_10000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_1875ppmv_winton\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_2250ppmv_winton\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_2437ppmv_winton\")\n",
+ "experiment4, DS4 = load_experiment(\"mlo_aqua_2625ppmv_winton\")\n",
+ "experiment5, DS5 = load_experiment(\"mlo_aqua_3000ppmv_winton\")\n",
+ "experiment6, DS6 = load_experiment(\"mlo_aqua_5000ppmv_winton\")\n",
+ "\n",
+ "experiment1_Jor, DS1_Jor = load_experiment(\"mlo_aqua_3000ppmv_winton_50sic\")\n",
+ "experiment2_Jor, DS2_Jor = load_experiment(\"mlo_aqua_3000ppmv_74sic_winton\")\n",
+ "experiment3_Jor, DS3_Jor = load_experiment(\"mlo_aqua_4219ppmv_winton_50sic\")\n",
+ "experiment4_Jor, DS4_Jor = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")\n",
+ "experiment5_Jor, DS5_Jor = load_experiment(\"mlo_aqua_5000ppmv_37sic_winton\")\n",
+ "experiment6_Jor, DS6_Jor = load_experiment(\"mlo_aqua_5000ppmv_74sic_winton\")\n",
+ "experiment7_Jor, DS7_Jor = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "experiment8_Jor, DS8_Jor = load_experiment(\"mlo_aqua_10000ppmv_74sic_winton\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_1875ppmv_winton f=-0.21304795919592326\n",
+ "mlo_aqua_2250ppmv_winton f=-0.10866840147621822\n",
+ "mlo_aqua_2437ppmv_winton f=0.0006746875735950412\n",
+ "mlo_aqua_2625ppmv_winton f=0.002651551595564326\n",
+ "mlo_aqua_3000ppmv_winton f=0.0004580904092328009\n"
+ ]
+ }
+ ],
+ "source": [
+ "#plot stability index\n",
+ "f1=stability_index(DS1)\n",
+ "f2=stability_index(DS2)\n",
+ "f3=stability_index(DS3)\n",
+ "f4=stability_index(DS4)\n",
+ "f5=stability_index(DS5)\n",
+ "#f6=stability_index(DS6)\n",
+ "\n",
+ "\n",
+ "\n",
+ "print(experiment1 +\" f=\" +str(f1))\n",
+ "print(experiment2 +\" f=\" +str(f2))\n",
+ "print(experiment3 +\" f=\" +str(f3))\n",
+ "print(experiment4 +\" f=\" +str(f4))\n",
+ "print(experiment5 +\" f=\" +str(f5))\n",
+ "#print(experiment6 +\" f=\" +str(f6))\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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IfE7/ypXy4mBGgVYL+bucw1CSC12G2h2Jz2kiUKqarIISNh/OZrh2HfVv5auStfH2AdBEoFQNCYmZlLoMUwd3sTsUZaf0vdZjG551tJwmAqWq2eHpOjq4m44h8GuHVlvzC0XG1V+2ldNEoFQ1O47kEhfdjvCQtt1TRNXjyGboMa7NrkpWWdv/CZU6QdtTchjYJaL+gqrtcrsgbXebH0hWThOBUpVk5JewNzWfUfFRdoei7JS+B1zF0Hmw3ZE0C00ESlWyNjEDgPG9o22ORNlqp2euzF5n2htHM9FEoFQl3+9KJSjAoV1H/d3Wj6ylKdv49NPlNBEo5WGM4cstR5gyqDPBAU67w1F2yUyElA0w5CK7I2k2mgiU8jiUUUh6fglnDdB1sf3ajs+sx8EX2BtHM9JEoJTH1uRsAIZ21x5Dfu3gKoju4xcjistpIlDKY1tKDk6HMEAXo/FvR7ZA11PsjqJZaSJQymNrcg79YtoTEqjtA36rKMeaY6hr216RrDpNBEp5bEvOYYhWC/m3lA3Wo94RKOV/PtmYzJGcIvrGhNkdirLTnq+sFcniJ9odSbPSRKAUsCDhEAAXjoy1ORJlq91fQc+JEOJfd4aaCJQCcorKmNinI3G6GI3/yj4Mx7ZCv3PtjqTZaSJQfs/tNuw+msvArtpbyK8dXGU99plkZxS20ESg/N7BjAIKSlyaCPzdvmUQ0A46D7E7kmaniUD5vb8t2QnAyDidcdRvFeXApgUwcAY4A+yOptlpIlB+LS2vmM82pQAwUAeS+a9vHgZXCZw6x+5IbKGJQPm1zYetaSVmDuuKwyE2R6NsYQysecnajhtvbyw20USg/NrChCQCHMLjlwy3OxRll5SN1uOsv4PDP0eVayJQfsvlNny59QgzhnUlKjTI7nCUXXZ8CuLwq2mnq9NEoPzWc9/sxuU2nNGvk92hKLuk7oSVz0PcBGjvv9OPayJQfmvL4RwALhjR3eZIlG12fAZlhTD9UbsjsZUmAuWXSl1uvtp+lNP7dSQs2P+6CyqPfcsgLAZiR9sdia00ESi/9Plmq8vo0O66NrHfOrQG9n8PXYbaHYntfJoIRGSGiOwUkT0icm8tZa4QkW0islVE3vFlPEoBZOSX8Nv/WtMN3zVtgM3RKNu8c6X1OPl+e+NoAXx2TywiTuAF4FwgCVgrIouMMdsqlekP/BE43RiTKSKdfRWPUuVW7U0HrJHEuki9nzIGCjOg+yiIO9XuaGznyzuCU4E9xph9xpgS4L/AhdXK3Aq8YIzJBDDGHPNhPEoBsDYxg3aBTt7/pX/NOa8qWfG09Tj2ZnvjaCF8mQhigUOV9pM8xyobAAwQkR9E5EcRmeHtQiIyR0QSRCQhNTXVR+Eqf7F6fwZjenYg0KlNZH7J7YavH7K2e51pbywthC//J3gbr2+q7QcA/YFJwNXAKyJSY+YvY8xLxpixxpixMTH+29dXnbzswlJ2HMlhXK9ou0NRdtmy0HocchFE97Y3lhbCl4kgCYirtN8DSPZS5mNjTKkxZj+wEysxKOUTt76RgDEwrncHu0NRdtn/vfV4/j/sjaMF8WUiWAv0F5HeIhIEXAUsqlbmI2AygIh0wqoq2ufDmJQfc7kNa/ZnADCmpyYCv5SfDuvfhG4jIFTvCsv5LBEYY8qAucBiYDuwwBizVUQeEpHZnmKLgXQR2QYsA+4xxqT7Kibl395ZcxCAJy4Zrr2F/FWK1W2Y4VfYG0cLI8ZUr7Zv2caOHWsSEhLsDkO1MgUlZQz582IA9j02S6ec9lfzPAMI794N7f2rt7qIrDPGjPV2TrtNKL/w/a6049uaBPzUG5V6r4dpp5PKNBEov/Dayv0AfPrrM2yORNkicQXs+9bavnUZiH4ZqEwTgWrzsgtL+XFfBoFOYViszi3kl755xHqMHeP3E8x5o4lAtXn3vG+tQPWfG3UqAb9UUgAHV1nbNy+xN5YWShOBatM2JWWxZNtRAEbE6d2AX1rimVSuXQdw6pTj3mgiUG3aLa9bPcxmj+hOeEigzdGoZpe8ARJetbZvW21vLC1YnelRRDY14BqpxpgpTRSPUk2muMzFsdxiAP50/hCbo1G2eOls67HHqRDexd5YWrD67pOcwKw6zgs1Rwsr1SIs22FNUDhjaFdiwoNtjkY1u5xKM9pc8559cbQC9SWCXxhjDtRVQERua8J4lGoyd75njSJ98tJTbI5E2SLhP9bjLd/odBL1qLONwBizor4LNKSMUs3tSHYRhaUuACJDtW3AL235AMI6Q48xdkfS4tWZCETkpfou0JAySjW3y15cCcAdU3UyW7/0/d8gYy8EhtgdSatQX9XQRSJSVMd5wTN7qFItxdrEDJIyCwG4fXI/m6NRzS4/vWIA2aX/tjeWVqK+RHBPA66xvCkCUaqp3PjqGgBevG6MrkLmj+aPtB7jT9P1iBuozkRgjHm9uQJRqimk5xWTX2K1DUwfqt0F/c7af0NxjrV9zX/tjaUV0a9Lqk35dFMKAJeMjkV0YjH/knkAPvudtX3eUxCiI8kbShOBalPe+tHq7fz4JcNtjkQ1u28ertgedb19cbRCOvGGajMu/ucP7D6WR5+YMF2BzN8UZsLm963tB1IhIMjeeFqZBt0RiMhSEYmqtN9BRBb7LiylTkxhiYv1B7MA+NtlOoDM76x4xnocdb0mgUZoaNVQJ2NMVvmOMSYT8K913lSLdvs7PwHWovRjeuooUr9hjDVw7AdPIpj5pL3xtFINTQRuEYkv3xGRnkDrWuxYtWnf7DgGwJ1TB9gciWpW2z6GhTdb21MfhKAwe+NppRraRnA/sEJEvvPsnwXM8U1ISp2YjYesm9VBXcM5o38nm6NRzaasBN7/WcX+qfqR1FgNSgTGmC9FZDQwAWs08Z3GmLR6nqaUzxljmPuuVS10w8Re9gajmtcjlRagv3sPBIXaF0srV99cQ4M8j6OBeCAZOAzEe44pZatdR/M4lGFNJ3HN+Ph6Sqs2I/twxfbkB6B9TO1lVb3quyP4HVYV0FNezhngnCaPSKkT8NrKRABuOr2XrXGoZvb8WOtx0PlwdkNmwlF1qW+KiTmeR51YTrVI7645CMDvpw+yORLVbAozobTA2p7xhL2xtBENHUdwuYiEe7YfEJH/icgo34amVN3u+3AzAKPio2gXpAPI/EJOMjzZy9oecxNExdkaTlvR0O6jfzLG5IrIGcB04HXgRd+FpVTd9hzL453V1t3AwxcOszka1Ww+/V3F9uT77YujjWloInB5Hs8D/s8Y8zGgw/eULVxuw9SnrZ7MZ/TrxLBYnVzML2QegF1fWNs3L9YG4ibU0ERwWET+BVwBfC4iwSfwXKWa1BNfbD++/c/rtPOaXyjMgmc9U4eM/TnET7A3njamoR/mVwCLgRmeqSaiadiiNUo1uZeX7z++HRGi6xH7hUVzK7anPWJfHG1UQweUFQD/q7SfAqT4KiilavPb/64HIDosiEVzT7c5GtUsinJg+yfW9qlzdOCYD2j1jmo1jDF8vCEZgLunDaRHB/1A8AtfP1SxrXcDPqGJQLUar3sGjwH079LevkBU8ynMgrUvW9t3bIaAYHvjaaM0EahW40PP3cA14+MZ10unmm7zsg/Dkz0r9iN1zICvaCJQrcKH65OOzzL62MW6DGWbd2Qz/GNIxf55T4OuQe0zPk0EIjJDRHaKyB4RubeOcpeJiBGRsb6MR7VOX25J4c73NtodhmouP70JL55RsT/iahj3c/vi8QM+SwQi4gReAGYCQ4CrRWSIl3LhwG+A1b6KRbVemfkl/PKtn47vr7l/io3RKJ8yBta/XbWraI9xMO1R+2LyE75cvP5UYI8xZh+AiPwXuBDYVq3cw8Bfgbt9GItqhUrK3Ez6+7fH95+8dDidw0PsC0j5jtsNTw2E/GMVx8QJt3xlX0x+xJdVQ7HAoUr7SZ5jx3kmroszxnxa14VEZI6IJIhIQmpqatNHqlqk3y/cSHZh6fH9WcO72RiN8pnCLHhuVNUkcMbv4M/p9sXkZ3yZCLy17Bxf51hEHMA/gLvqu5Ax5iVjzFhjzNiYGJ1fxB8s23GMjzy9hAB+uPccwnUUcdv0xoWQmVixH9UTpv5FG4ebkS+rhpKAyv29emCtcFYuHBgGfCvWL7wrsEhEZhtjEnwYl2rhCkrKuOm1tcf3H7loGLFR7WyMSPlM0jpI2VCxf97T0E/bgZqbLxPBWqC/iPTGWt7yKuCa8pPGmGzg+ErjIvItcLcmAf+2+2gu5/7j++P7f5gxiOsm9KzjGarVytgPb19asf+77RDR3b54/JjPqoaMMWXAXKzJ6rYDC4wxW0XkIRGZ7avXVa1XqctdJQkAXDVOBxG1OWXFcGAVzB9prTYGcNGLmgRs5Ms7AowxnwOfVzv251rKTvJlLKrlKip1kZiez21v/1Tl+MJfTqRDmC570aYUZMBfe9c8PvLq5o9FHefTRKBUQ/z63fUs3Xa0yrHfnNOPsTqNRNvz1V9qHps4t+Yx1aw0EShb/XvF/hpJYO9js3A6tMdIm7BrMRRlw9pXoM8k+OmNqueHXgLTdcCY3TQRKNu43YaHP606vvD5a0ZpEmgrdi2Gd66o2D9UbfKAcbfAeU81b0zKK00Eqtmt2pvOkG4R3Pfh5irHb5/cl5nDdNBYq2cMLL4ffnzB+/mLXoSYgdBVJw9sKTQRqGbz3a5U/vrlDrYm59Q4t//xWYgOIGobUnfUngQAep8JkT2aLx5VL00Eqlm43YafvbrG67lPf32GJoG2ICcFnh7k/dwVb0JkLLSL1iTQAmkiUD5njOHyf63yem7BLyYyLDaymSNSTcrtgo3vwse31zz3hwMQFAZOnR6kJdNEoHym1OXm9ZWJJGUWsu5AZo3zQU4Hp/bWLqKtVspGSPwBFv/R+/lrF0K7qOaNSTWKJgLlE/nFZQz9y2Kv55bceRZFpS46ttf1Z1ul3V/BJ7+FnKTay1z4AvQ/t/liUidFE4Fqcm63qTUJJD5xXjNHo5pc5fmBqpvxJLjL4JSrmi8eddI0Eagmd+//Nnk9/uqNuhJpi1ZaBIFeFv4pyYfiXAjvCl/UuuIs3LMPwjr6Lj7lM5oIVJPKyC9hQUJFlcGUQZ35xdl9iWgXwKCuETZGpmpVUgCPecZv9DwdDvxgbf9yRdW1g6P7Qsbems+f8x10H+n7OJXPaCJQTcIYw9bkHM5/bsXxY1/97mz6dW5vY1SqTtsWwYLrqx4rTwJQNQlA1SRw8xLoPgpcJRCsv+PWThOBOinFZS5ueT2B5bvTqhx//5cTNQm0ZEv+BCvnN/758eOtxwCdHbYt0ESgTsp1r6xmbWLNrqHjdObQlsFVCj/+E/pOsSZ827MUAkLg2Lb6n+tN/2lw1u+bNkZlO00E6oSl5xXjMobLX1zFgfSCGucvHa0jR5udMVCSBzs+h86DoX0XCIuBhz2LAC71ugxIhTPvhp6nQXA4BARD6k5r0ZjEFTB7PjgCYfX/WVNGB+qyoW2NJgLVIGUuNwczCkjJLuLaV1Z7LTOuVwcuGd2Dq0+Nb+bo/Nier2HFPyBx+Yk/d+R1kLkfhl8GY2+ueq7bCOtx/C8qjp11T+PjVC2aJgLVIE8v3cU/v/XSY8Tjw9tOY2RclM4ZdLKykyCofd0jcncvtaZ0SFwBeUdrL1efi+qYGE75FU0EqlZbDmcztHsEiekFdSaBfY/NwqFrCDSNfwy1Hu8/Ap/fDeHdrYbZRb+F6N7WaN36qnmqGzwbti+CC561uopuXwSXvNz0satWSxOBqqGwxMXaxAxueHUN5w3vxudbUmotu+a+KZoEGsPttr7V56fCgZUw7WFY8UzF+Ue71nxOTlLDq4A69LaqfaY/BhOrTQY38bbGx63aJE0Eqooj2UVMePzr4/ufba6ZBN6bM4HI0EAdINYYWQdh2eOw8Z2qx3d7n5KjQboMg7E3wSlXQmAoFGbpCF91QjQRKADmLdrKaysT6yyz5v4pdA73MgWBqp+rDN69EvZ81TTXm/MtZB2CIbNrntMkoE6QJgI/ll1QSlCAg82Hs+tNAk9fMUKTQLn9y631d8feDEe3wOGfYNvHVvfLDr1g/VuQsgHOfRiM22oATlprHauPMxiuXUUW45MAACAASURBVABvXFj1+Ky/W20GAL9aCV2GWiN7lWoCYoyxO4YTMnbsWJOQkGB3GK2ey23oe9/ndZZ5b84EYju0Y+G6JG6b1I+gAEczRddMyoqtPvN1cZVB+h7o0NPqP7/scfjuiaaNo31XyDsCnQbA+f+AXmdA2m5rLED6bnAGWev7usqsmT29TQynVD1EZJ0xxuvMj3pH4Ce+3JLC6ysPcEb/Tny785jX0cDllt55Fv27hB/fv2PqgOYI0XdK8q1v5sEVPxOrX4Iv7oFfrbIGTgWEwCvnWOeuXWg1yp72G1j+lDUytymNvgGmPQohEdZAMG9dbjv1tx5jx1QccwZY/5RqYnpH0IYlZxVy2hPfNKjs8NhInrlqJMWlboZ0b0ONwIfXwcueD/jRP4NJ98Kal6xBWM1OYNR1cOHzNry28nd6R+BHjuUW8eaqA7y6Yj/5Ja4GP+/9X04kJNDZuBctzLKqT3r4YL2BvGOwewmUFkL8BECsKp19y+Cbh60yA8+z6swBhl8O0X2sb84f3AKb36+41k+vW/9O1vTHYcn91l1GdB84508Q2tGKacU/rDuKlA0QEgXJG2DHp3D9hxA7+uRfWykf0DuCVsIYg9uA0yEYY5j77no+22R17ZzQJ5oZQ7syqFsEv353Pam5xQ265j3TBzK0ewRn9Y+pfSyAt6qLomwoKwFXMUT2gH9PsxpPp86z6rn7ngPf/RV6jLO2K9dpu8qsqpjlT1nTFw+YUZFAtn8CGfusapreZ0HMIHg8DkpyT+zNAnAEWPXpTW3C7TDjMasBOPcIdD1FZ+D0U8YY7l9xP93ad2Nr2lb+evZfiQg6ubvpnRk76RPZh0BnYBNFWaGuOwJNBK3E00t3Mf/r3Y1+/nNXj+JIdhGHMguICAnk7ukDvRd0u6yeMKk7IeFVOLjKaqj8pWedga/mNa5a5cJ/QlQcvH6B9/PlDabN6YzfwYqnrTl0jm23+uKHxcCbF1tJqHxu/t9th60fWkmt8+DmjVGdtDJ3GU5xVpn+pKisiMKyQjqEdGjUNdceWcvNi2+ucXzuyLlcOuBS8kvz6RnRk0O5hziUe4gxXcbgEAcFpQVEBkd6vd5z659j/bH1ADx2xmNc0LeW/yuNpImglTmSXURosJOIkECKSl0M+tOXjb7WWz8fz2l9O9b8xl+UYzWiRnhWpjIGvn2i6XvE2C1uPFz2H/j6QcjYD0lrrOO/3Wh19SzO876wijFQlAUB7bSXThModhWTW5JLp3admuX1Eo4kkJKfwoGcA/xr078AOLfnuSw9sLRG2esGX0fC0QRm9p5Jv6h+FJUVMa3XtCpltqRtYWD0QN7b8R6L9i5ie8b2emN4Zdor3LLklhrHrxx4JV8mfsmNQ29kUPQgxnQZw6lvn+r1GsuvXI6IkFOSw6OrH+XBiQ/SJaxLQ96CGjQRtGClLjdLtx0lPCSAM/p14u9LdvLCMmten49uP53/+3YPi7ee2MRikwfGcO6QrpwzqDNdC/dA8k/w05vQ+0yrPr04Bxb9BrIPwkX/B+l7YfnfffHjNY2z7oHhV8AL46z90TfAGXdCu2hrcrblT8HmDyB1u1VvX9l9KRAUWvVYQ7qNtkIlrhKyirPoHNr5+LHUglTmfjOXwdGD+f243xMaWPFeZBRlsD97P98c/IY5p8yp8U01qyiLHZk7GNRhEFEhVSfB25K2haMFR7lj2R0APHrGo8zuWzG4rdhVTLAzmDJ3GX/+4c98su8TwPoQvG7wdfSK7OX1Z0grTCOzKJO48DiCncGICBlFGUQERZBVnEWZu4xDuYd4OuFp5p8zn5jQGFxuFy7jYlv6NnqE9+D/NvwfC3YtOKn3sntYd5Lzk3lz5pssTlzMW9vfOqnrNZUbhtzAPeMaNwusJoIW6M1ViTz3zR6ONbA+H6B7ZAiTBnVmaPcIgpwOJg/qzK6juby56gBfbLGqVf4wYxC/mtTXesLSv8APz9RxxZNQuQ7+9N9aPXKW/Anax8C61+p//vTHYO2/qy5/GBRuTbA29GJrhs1tH1nH52Vbj64yEAc46hnPkL7XWmy96yn1l/WBw3mHAeuDdGinoVXOHc0/evwbXU5JDgdzDjKs07ATuv6BnAPkFOcwpOMQnA6rgX/9sfXc8MUNx8vcNvI2vtz/Jfuy99V4/q3Db+XyAZcz7YOq33rvGH0HMaExPLH6CXJLvbfLvHTuS3y892M+2/dZjXOnx55OaECo12/d1T07+VnOiT8Ht3GTVZxFdEg0OzJ2cPknl9e45g+Hf6jlKi1DXHgcY7uM5cM9H/r8tcrft8bQRNCCLNl6hPs+3ExaXskJP3f/47Nqnea5sMRFfkkZndoHW9Uar51Xdf3ZE9XrTKsnzIRfwavTq567ayeEe5kUrVzabojqaTWiut1WY/P8kZCZCL9Zb/W0ASvOgnQoK7IaiMOqVRuk7gRnYEV5HytzlyEIToeTpNwkFicu5tN9n1JYVsiVA6/EYLik3yU1vh0D5JXkMW/VPBYnVp0z6JHTH+GjPR+RcLTib/byAZfjEAfv7XwPgFenv0rfqL5Eh1irupW6SjlScISOIR05WnCUuV/PZVTnUfSK7MWxgmO8u+NdAK4aeBVx4XH8LeFvvnpLTprTZTACbi+dEW4edjOvbnm1WeMJcgRR4i6hXUA7CssKT+paU+Kn8NDpD1VpIB7++vBGX+/02NN58swnCXYGc/+K+1lyYEmNMpt/trnR19dE0AIUlJQx5M+Nm1jsnVvGMyq+A+2CKnXv3PIB5KfDwJmQtsv60Ny9GPZ9C/2nN34Ss+v+B/2mePkBMqwRro1dqLy00GqIbuaFzjenbuaaz68BrA/ckTEjKXYV8/S6p5nZeyYRQREM6DCAPVl7uGTRJQ2+7pmxZ/KLEb9gX9Y+Eo4msGjvIl/9CC2auA3BpVAULASXGE7bbrhkpZsfhggHOgt3fuRmazw8eG0jeqobQ79kKA2AA51h2k+GkfsMr0x3kBEhzHurjEMxwvfDHOyOFTrkGrLDKpLOpb0upEdSEWcOP5+UDhAWGEbPt76jNDmZiPPOI2zCBH48tpas7KPscR9l3aEfuWt3f+4I+YhScZEdCp1yYMY6N3u7CSuHOJgSP4V7xt2DIHRv352yzEyS77qbkBGn4M7JpSwmitxnXuDwI7dyb+arnNPxNL7IXcUD4x9gWNRgogljS/E+nOJkZ8ZO3tr+FpcPuJyrBl1F17CqX66eWPMEb29/+/j+wgsWMjC6lk4eDfld2ZUIRGQG8CzgBF4xxjxR7fzvgFuAMiAVuNkYc6Cua7bGRGCM4bz5K9iWkuP1/H/nTOD6f6+m1GX4xdl9+OPMwWxPyWHms8v562WncMXYOKtgQYb1KAJP9mrYiwdHwsAZ1gjVAysrqluueBPWvgwDZlr98xNXWL1mKo++bWW+PvA1W9K3cP2Q61mVvIrCskIeXPWg3WGdtOASQ3FQ46f6fmbyM7y7411Wp9RcWW7u4Fv5eusitjtqtkP1PGro5GrHuu5FVboRB5UaOuWA0w137OhN3Io9DYqj7PKZrBgXhvutD4hPNbx/hoOQUuiXbAgthpIAmLDDsHSUg3Y9e3HB2xXVWoejITajYT9vxqThdM92UrS+AXM71SHnlF5EbEqscizmkQfpOPsi8lb8QNrzz1O0rf61n/t8+gnB/fqR/Id7yf74Y2KffZaQwYNwFxTgCAvDFBcT1LcvuFyk//tVAmJiiLrkYgoSEihLTUUG9Scr3EFcp5O7M7YlEYiIE9gFnAskAWuBq40x2yqVmQysNsYUiMivgEnGmCvrum5rSATGGFxuw66jeSzeeoRnvXT7jA4LYkSPSO6aNpBhsZGk5haTV1xG705hVQtmHbQmIjNueHrQiQXSoTfc+g2EVlpIPicZUndYXSFbMJfbhYjgkJp1/MWuYub/NJ85p8whMSeRElcJG45tYP76+TZE2nidMw3nrncTXAqvTrfu9sbucjMwybAtXvjFF26i86yySR2hRzrs6wLr504m9n+r+XxoMTviKhLES+e+RIAjgL8n/J3tqVv5S+ZZnJoVTdQ5UwmKjSWgSxfKwoK5+OOLOZR7iM8u/gzz6z9TsLpmgki7+Aw6fbiiyrFei7/g63lz6LvqkO/elDYq6qoryfrvew0u3+2xx0i5774ax/uvWE5Ap8b1vLIrEUwE5hljpnv2/whgjHm8lvKjgOeNMafXdd3WkAh63VuzIa2yFX+YTI8OoXWWAaxZLD++vf5y3gyYAdc0/A+vJXG5XYx8cySndT+Nv539N47lH6Nfh36UucvYm7WXyz65rOoTjCG8EHJDG/atuedRQ7cMw84ewh8XuOh1DJ6d7WBrT6EoEHqkwZUjbmDEXf+h3bhxxP/rRdJyjvDi/rd4f9f7iNtwx8duRu4z7IwV/jXTwdxPXYy/72liz55O3rJvOXzb7YRMPgsevhvz5D8pW7kWV2xn2FR/t8MTUTjnMvoNOYOCn9YRFBsLAQGkf/gBZVtqfx1HaCid7/0DR/78lyaNRfleh2uvpeufHmjUc+1KBJcBM4wxt3j2rwfGG2Pm1lL+eeCIMeYRL+fmAHMA4uPjxxw4UGftUbM7lltETmEZPTuGcjSniDOeXOa1XHhIAKvvm0JoUD31pfuXwwc/r3892kn3wWlz4bHu1v6o6+HUOVYjb0R375OZ2cgYg8HgEAepBal0bNcRQY43gO/I2MGm1E08/OPDx58TVGoIK4K4yJ5sKbN+726H0POoYfZqNy/NcPDmU9ZUGvff4GR3bMXPPHKvG6cbrjkYR+j5M1j61cvEp1r12I3R4ZqrcUZFkb95E4XLW3ZPFjs42ren/eTJRF9/HQGdOxPYtSvuwkLS//0qac+f/PxK7c8+m06338bBn9+CO9fq1dTticfJ+u97FG5oeDVQj3/+k9LkZI4+Yn3UOCMjcWVbPdNChgypUt0TPHAgXe67j8y33yZ3Sc3GW+sCTrr+6QGKd+8hqE9vImbNIvfLL0l9dj6urKxG/rTe9XzrTULHNm4qF7sSweXA9GqJ4FRjzK+9lL0OmAucbYypsz9lS7sjeH1lIn9ZtLXeci9eN4ZpQ7rUHNhVmAXJ66HvZEjbA8seha3/q/tiPU6FWX+D7iNPIvLmd8939/Bl4pfcPfZu/p5gjVsILjHcstjNtnghwAU/DBEKggERLvjRzfXL3DWuU1d98aqL+vFSr/3c9T83ww62ro4QLY7DQbdHHwW3m5T7769yKuy0iZQeO0a7kSPJ+2YZATEx9P5gIRJQ+5ecrA8+oCw1laD4eIJ69eLQL39F8MCB5C9fTodrryX83KmETZhA3nffUbB2LeHnnktg9+44IyMpS08noGNHJMiazqNo1y6C4uNxhITgLi4m6733aDd6DKa0hNBRNddpyP3mG4J69Sa4T+/jxwo3byFk2FCvPfEKt27FlZVF+9OtCgpjDBn/eY2877+neO8eQkeOIubOO8n79luib7qx1t587sJCdo47FcqsrtZd583DFBcR2KMHhRs24ogIp/TgQbLeXwhA+ylTyPu6YoXA3v/7gP2XXHp8f/COxt9RtuiqIRGZCjyHlQSO1XfdlpIISl1uznnqWw5leO+CNuesPny55Qh3TRvAhSNjvV8kYx/M9/zRnv8MfHpH3S965t0w5U8nEXXzSytM490d7/LSppeqHI/MN5y5xTBlg7vGh/rKwUKZA87a2rY/yNtPmkTU5ZeRv3o12Qs/IKhXL2LnzwcMgbGxuPPyKFy/ntIjR2g3YgTBAwaQcu+9tBs1ipDBg0m88qo6r9/z3XeQwCBCBg0kdf5z5P/4I0WbNlUp03XeXwibMIHA+HgAxOGgNDmZvB9+IGLmTJztrV5erpwcjj31NKFjRhM528uqaKpO6a+9hiM0lA5XXFFv2YzXX+fo408Q968XaX/22QCUHj5M6dFjhI5u/GJEdiWCAKzG4inAYazG4muMMVsrlRkFLMSqQmrQRDp2JgKX2/D00p2s3JtOel4JBzMKai2b8MBUq09/dcnr4aVJEBJpTd5Wl4HnWQuVhDduSHlzyy7O5g/L/8Cdo+/EGEPpvL9RuHwlD17r5Lcfu4gogAducOJ0wzMvNXxm1KYW2KMHfZcuIfPtd4iYPo2ibdvIWriQvG+/w5SWEjp+PNE3/ozQ0aNJmTeP3CVLwVU13ugbb6Tz3XeRs3gxQfHxFO/dS9b7Cylct46Y3/6GyNmzKdy4kfAZM8j+3/8IHT+eoLi44883xtT6LTIvs5iwyCCktokAPXK//hp3fj5FW7cRddml5K9eQ7sRp1CWmkr4ObV3BijLzCTnk0+JuuxSHKENaKtSzcq43RTv2kXIoBPsHFIPO7uPzgKeweo++qox5lEReQhIMMYsEpGvgOFA+QrpB40xdX7dsDMR3PDqGr7flVpnmSCng09/cwYDuoRbM3S6y8DhtPrgF2XDkz0b9mI3L7FG2bYS+aX5THhnAgCxaYbbP3XRr+a6902q871/IKBTDGETJ2CKi8n++GNSn63oORT371fIfONNIi++iMC4ONx5+ThCQwkeOABHkPcZQ90uN4mb0+l1Sqcq1XjukhJcaWlkf/oZ4VOnEtynN8ZtcLsMzkDvo5cLckoICHIQFGJVl5SVuHAGOmpNAAAHtqTz6fMbAYgd2IFZvxp+/Pnl8e1cfYSSQhch7QPp1KM9HWOtb+0ZKfmsX3KAwad3p3u/moPelH/TAWVNYPW+dK586ccax4fFRvC/X51OgENwGUOg0/OhUFoIj1YaINLQQV4//8qaW7/6/Dgt1MrDK/nFV78AILDMMGWD4ealNev1GyLqvnsoWPA/SvbsxQBd//QAHa68Ene+9QHuKinF7QyidMdWVizNQDrEMPWmITicFR/EaYu+YNX7Oxl23Vn0nj6ajJR80g7lsvPHIwyb1IOO3cPYs+4YxxJzMMC0m4fiCBBKi1wYY9j2QworP7D6xfcd3ZmOsWGICMPOjuWT+RsIaR9IeHQIp0yOY/mCXSTtyOTiu0fz4d9/In5oNKOn9yQ8OoR1iw+wbXkyEZ1CmHhxPzKS81j7WSIAneLak3bI6hd67s+H0KVXJAe3prPl+8NkJOfXeF8uvHMURXmlbF+ZwsGt6TXODz0rltz0Qg5urahjG3Jmd8I7hBDVJZSdP6Yw+frBhEZYyS8jOZ93H1qNM9DBmBk9GTuzV713H6r100RwEs59+jt2H8vzeu7M/p148+devrUXZMBfe9c8Xl2fSdZIXnFYA72i4qsuTdgCFbuKmbZwGhlFng8dYxiYBON3ujl/7Yn9LQ1cl8DKD3aRnefk7KsH0K59EG5j2LwsiVUf7mXghK5MvXEIAFuXH+bbt3d6vc7ws2MpLXEREORky3eHT+rn80dX3DeOmPjWO5BQNYyuUNYIJWVu3liVWCMJrL1/KgDXvPwj82YPrfnE/HRYcEPN45XduQ0iqzUgD734JKJtHt8nfc/vP70NtwPmLAtl6vqqE5MZhJRuE3G4S9nd7zJKA9tz6nnxRO76jog+sYT27sGBfSV8vySLTnHt+eauioFMiZvSarzezh+PsPPH+tco2NwGP/zDooLJz2r4hIQnIze9SBOBn9NE4EVtawD06RRGTLjVALz0d1ZrPsV58PcBUFrzlt6rK9+qmQRasKUHlvK7ZXcycbth1P4oHk4/g139r4BI2Dh8M5HZ+wjPPURap+Ecjj27xvPXfHYQ6A27ASo6hZVXjbREZ1zen+y0QjYvS2r21x41LZ6JF/VFHEJxYRlv/3kVhbmlx89HxLRj6s8Gk7wni4NbM0jeXbWf+pUPnMqxxByWvbWjQa83+bpBxA+Lrr+gatO0asgLb43C980axLQhXelVfQqIBT+rmL+nugtfsJZwnHw/rH8Thl0G0Q2oMmoBFiR8RK+QPix9eSOjdvyE01XKnn4Nn5TNV2IHdmDSNQMpLixjzSf7vdaZD5rYlY6x7flh4R4iY9pxyT1jCI0I4r+PrKG0qIyewzsx4cI+fPzMBo4l5tBvTGdy0grp1jeKiJgQhk/qgYhQUlRGcUEZwaEB5KQVEh4dQmmxG3HA/g2pRHYOJf1wHoMmdsMZ4ODQ9gxS9mSx4atD9BzekfNuOwXg+HMdTgelJS6cAQ4cDsHtcrNo/kYO78xk7Hm9GH9BzblkjNuwa+1RHE6h3+jONeryC/NK+PHjfcQPjqbHoA4Eh1pLHO5df4w9644xdmYv9q5PJeGz/RgD3fpF0q1fFPGDo+k+IKrOhmvVtmgbwQnILSpl+LyKEYR/v3wE04Z2ISLEyxqi+76FNy70fqGr3oVBs3wTpI9l5WTz9u/XNctrzf7NSOKGRJO8O4sDW9PJTS9i3Hm9CAx24ipz89V/tiEOYfZvRhJQefZVj5KiMvIyijEYwqNDqvSwqc64jd82irpcbnLTi4jq3Do6Iaimp20EJ2DhuorqgBFxUVw2pkfFybJiePcqSN4AhV6GtgaGWVVE4rSmh25BXKVuMo7k8/Vr20k/nMdZVw2ge/8oivJK2fxdEp17RpCbUQTQ6AbXwBAnP3vsNHasOsLg07oR1C6A9MN5fPPGdgZN7EZeZhEjpsRTWlxGYV4pXXtXrIjVvX8U3fvX7PJ46e/rHk4fFBJAdPeG/Rn7axIAcDodmgRUrfSOwMMYw9NLd/HcNxVT6u55dCYB5V0Tj26D/5vo/ckd+8OvE6xFWFa/CCOvsZZQ9JG8zGKO7Mtmw1cH6T+2CyOmxFFcWIar1E3qwVxcZW6CQpwcTcwh9WAe3fpFkvB5IkV5pfVfvA4jzurM4LN70TG2PfnZxZQUlhHRqR2bv00ifmhHoruF1X8RpZQttGqoAX797no+2Zh8fH/rg9MJCw6AT++EDe9Yq2h54wi0FkL3YQNwYV4JaYfyiOgUwifzN5KdWnVaiwHju7Br9Ymta9wQxaEbmBF8mPAr7iApsYSJF/dt8tdQSjUPrRqqR3JWYZUk8OcpXQl7/yooyYeDK2t/4u1rIKbxKwbVJvNIPtt+SGHk1DicAQ5evXtFneVPJAmcflk/QsIC+fr1ismrAoKdlBVXTKEw7edD6Ts6BoezYpqCuMZPcaKUauE0EQCnPfHN8e3xMaXc9NNl3tsAhl8BM56wFnppot4W372zky3fH6bPqBj2rU+l94hO7N9o9anfsPRgk7xGuVm/Gk7vETG4XW6OHcyla+8IuvaNJKJjO8BqTHUbg9PZ/Au+K6Xs4/eJ4P2EitWW/nVRLNO/rNkXHoC790D7mHqvl5GST0ZyPotf3sLk6wfRtXckAUEOwqNDEIeQlpRHVOd2ZB0r4L1H1h5/3r71VnfV8iRQn/Gze9O1bxT7N6SSuDmN0mIX42f3IaR9IG6XYckrW5l07UAGTehGfk7x8Q97AIfTwVlXDqhxTXEITvy3QVUpf+X3bQTlq4kNlgN8EfzHmgVu+Rq6jQSn95y5bUUym79LYsKFfUnek8VPX/pm0ZxpPx9K8u4sQiODdG4YpdQJ0zaCWmw4ZI3KHCc7eD/4oaonr3gDBp1vzRzqRWmxi52rj/DdO9b8N+UzRjaV0dPjObwri6k3DiGqi9Xtr/+41jEdtVKqdfHbRFDmcnPRCz8QQ1bNJDD7ORhSdaCYq8xNYW4pi1/eQlF+KVlHa1+LoKE6dA3l7KsH0qV3BM5AB8bAkb1ZRHdvT0iYlwFsSinlA36bCBIOZALwUXC1Fb/+cKDGGICMlHzefXA1J+KC34wgJCyQ9x+vqMZq3yGY4ZN6kJdRxKkXWPX5lYlA9/4dTuh1lFLqZPltIrj6pZV8EXQfsVJprppfLD+eBIoLSkn44gD7N6TW6Ldf3fCzYxl0WjcObc+gc88IEIgbZE3kddv/TQZPM4zW6yulWiK/TARLtx1llOxhsKOie2bpvels/v4wIfuSWfZm3TM3OgMcXP7HsezflEZU51D6jekMYCWBakQE7YijlGrJ/DIR3PpGAokh83AZJw5clPaawct3fN+g517/yEQiOlldMcuXCFRKqdbM7xJBfnEZTlzkuTryeuorRASmkXO0U53P6TGoA7N/O1Kn7FVKtUl+lwj++e0e/hLwBhvyZwOQU1p7Erj0D2PAQNc+kbWWUUqp1s7vEsGHq7azVBJ4reA2r+d7De/IjF8Ox+0yBHqZ/14ppdoav0oEB9LzubXsXd5K/2eNc5f/cWyVxl6n5gCllJ/wq9nFUrKLON9socyEVDl++4vneO3xo5RS/sCv7ghKj+5gU8HFx/dHTI2jx0AdwKWU8m9+dUeQffQgxwqgKOtfhIVnMm5Wd3oNr7vHkFJKtXV+dUfw9crd9MiyJodLP/gfnr/pP8QNPYVhk89lyJmTbY5OKaXs4TeJwO02dMnNqnH80NZNHNq6ifSkg5x+xXU4tJVYKeVn/CYRJB1OITBjV63n13z0PvmZGYycfj5d+/ZvxsiUUspeftNGsHdlHWsPe2z97mvevu9OivLzmiEipZRqGfzmjqAwK/v49m2vvMNPXywiqF0oQSEhfPVK1XEFL9x8FQCnXXEtEy+9ulnjVEqp5uY3iaC0sGIq6XbhEZx+xXXH9x3OAJb8a36N56xc8DZrPnyfM6/5GaNmXIA4/OYGSinlR/zmk62ssAiAoPCa3/CHnzONX7+2wPvzSktY9vrLPH31bFb89w2KC/J9GqdSSjU3v0kEpSXFAIyeGe31fFC7UO585+M6r7H6wwU8f9OV7Fu/lrKSkiaPUSml7OA3iaCspBSAqC61zyTqcDq5+Zl/1XutD594kGevv6TJYlNKKTv5TSJwe77Bh0VF1VmuQ7dYLrv/Ec77zT31XvOpK89nzccL2bxsCWUlJeRlpHNkT+1dVJVSqiXyaWOxiMwAngWcwCvGmCeqnQ8G3gDGAOnAlcaYRF/E4iotAyA8uv65hXqeMhKAQaefzdKXn2fTQbNb6AAACQhJREFUV1/WWnb5O68BsOTFisbmc2+dS5e+/SktKqTH4GEnEbVSSvmezxKBiDiBF4BzgSRgrYgsMsZsq1Ts50CmMaafiFwFPAlc6Yt4Tr/mUg5u7EdUp44n9Lxzb51bZyLwZunLzx/fnjn3LuKHnkL76BN7XaWUai5ijPHNhUUmAvOMMdM9+38EMMY8XqnMYk+ZVSISABwBYkwdQY0dO9YkJCT4JOa6GGNY+vLzbP56caOeHxjSrlHPm33nvfQaOaZRz1VKqXIiss4YM9bbOV9WDcUChyrtJwHjaytjjCkTkWygI5BWuZCIzAHmeHbzRGRnI2PqVP3aLUStcf32jYXNHEoNre49s5nGdeJaamxtLa6etZ3wZSLwttJ79W/6DSmDMeYl4KWTDkgkobaMaKeWGhe03Ng0rhPTUuOClhubP8Xly15DSUBcpf0eQHJtZTxVQ5FAhg9jUkopVY0vE8FaoL+I9BaRIOAqYFG1MouAn3m2LwO+qat9QCmlVNPzWdWQp85/LrAYq/voq8aYrSLyEJBgjFkE/Bt4U0T2YN0JXOWreDxOunrJR1pqXNByY9O4TkxLjQtabmx+E5fPeg0ppZRqHfxmZLFSSinvNBEopZSf85tEICIzRGSniOwRkXttjCNORJaJyHYR2Soiv/Ucnycih0Vkg+ffLBtiSxSRzZ7XT/AcixaRpSKy2/NY/xwdTRvTwErvyQYRyRGRO+x6v0TkVRE5JiJbKh3z+h6JZb7nb26TiIxu5rj+JiI7PK/9oYhEeY73EpHCSu/di80cV62/OxH5o+f92iki030VVx2xvVcprkQR2eA53pzvWW2fEb77OzPGtPl/WI3Ve4E+QBCwERhiUyzdgNGe7XBgFzAEmAfcbfP7lAh0qnbsr8C9nu17gSdt/j0ewRoYY8v7BZwFjAa21PceAbOAL7DGy0wAVv9/e+cfs1VZxvHPl3Q4Q2FMa/iHiYxK5xQaw0xhaqyNfkD+nI1NXW6NFWvN/tDG5ppbWVH+mDPbVIqfUWQ5+EdwDkNhGIkgGBQEa5XvXqYuA3PEj29/3Pehw+t7Xh5efc55fc/12Z4957mf85z7eq77Pud67vs89/eq2a7PAafl7R+W7LqgvF8D/uq37fJ5sA0YCYzP5+yH6rStz/s/Ae5pwGdV14iu9bO2jAimAnts77X9X2AFMLsJQ2z32N6Stw8AO0krrIcqs4FFeXsR8OUGbfks8Ffbf2vKANvrefdalyofzQYWO7EJGCNpXF122V5r+0h+uYm0lqdWKvxVxWxghe1DtvcBe0jnbu22SRJwM/DLbtVfxQDXiK71s7YEgv7kLhq/+Eq6AJgMvJiL5uWh3cK6p2AyBtZKeklJ1gPgo7Z7IHVQ4CMN2FVwCyeemE37q6DKR0Op332V9KuxYLyklyX9XtK0Buzpr+2Gkr+mAb22d5fKavdZn2tE1/pZWwJBR1IWdSJpFPAk8C3b/wYeBSYAk4Ae0rC0bq60/SlgJvANSdMbsKFflBYlzgJW5qKh4K+TMST6naT5wBFgWS7qAc63PRm4E1gu6ewaTapquyHhr8xXOPFHR+0+6+caUblrP2Wn5Le2BIJO5C5qQ9LppAZeZvu3ALZ7bR+1fQx4jC4Oiauw/Vp+3g/8LtvQWwwz8/P+uu3KzAS22O7NNjburxJVPmq830m6DfgiMMd5QjlPvbyRt18izcV/vC6bBmi7xv0Fx+Vurgd+VZTV7bP+rhF0sZ+1JRB0IndRC3nu8Qlgp+37S+XlOb3rgB19P9tluz4s6axim3SjcQcnyoDcBgyc2Ll7nPALrWl/9aHKR6uAW/O/Oj4NvFUM7etAKTHUXcAs2/8plZ+rlC8ESRcCE4G9NdpV1XargFskjZQ0Ptv1h7rsKjED2GX7H0VBnT6rukbQzX5Wx13wofAg3Vn/CymSz2/QjqtIw7ZXgK358XlgCbA9l68CxtVs14Wkf2xsA14tfESSBX8W2J2fxzbgszNJGexGl8oa8RcpGPUAh0m/xO6o8hFpyP5I7nPbgSk127WHNHdc9LOf5X1vyG28DdgCfKlmuyrbDpif/fVnYGbdbZnLfwHM7bNvnT6rukZ0rZ+FxEQQBEHLacvUUBAEQVBBBIIgCIKWE4EgCIKg5UQgCIIgaDkRCIIgCFpOBIJg2CFpjKSvl16fJ+k3XainUNG89/0+dof1r5N0UNKQS7AefLCIQBAMR8YAxwOB7dds39iluh6wfU+Xjl2scu0X29cAf+xW3UF7iEAQDEd+AEzIuvELspb8DgBJt0t6StJqSfskzZN0ZxYT2yRpbN5vgqSnswDf85I+OVCFkkZknfhzS6/3SDonr0p9UtLm/Lgy7zNV0sZc90ZJnyjZuFLSapII4DhJ6/P32dGQSFwwjOla8vogaJC7gUtsT4LjCo5lLiEpOp5BWn17l+3Jkh4AbgUeJCUIn2t7t6TLgZ8C11ZVaPuYpKXAnPz5GcA2269LWk4aObwg6XxgDXARsAuYbvuIpBnA90krWAGuAC61/aakbwNrbH8vyxyc+Z68EwR9iEAQtJF1TjrvByS9BazO5duBS7Pq42eAlUn2BUjJUk7GQpL+y4Mk2eef5/IZwMWlY52ddZ1GA4skTSRJCpxeOtYztgut/M3AwixE9pTtraf0bYPgJEQgCNrIodL2sdLrY6RzYgTwr2JE0Sm2/y6pV9K1wOWk0QH5eFfYfqe8v6SHSUHpujxqea709tul467PkuBfAJZIWmB78anYFgQDEfcIguHIAVKKv0HhpP2+T9JNcDwn7GUdfvxxYCnwa9tHc9laYF6xg6QiwIwG/pm3b686oKSPAfttP0ZSpexa7uOgnUQgCIYdTrrxG/KN1QWDPMwc4A5JhRprp6lNVwGj+P+0EMA3gSlKGbn+BMzN5T8C7pO0gZSPuYqrga2SXibdQ3io428RBB0Q6qNBMEgkfRc4aPvHpbIppBvDdaUyfI6UCD7+RhoMmhgRBMHgOQh8rVhQJuluUlap79RRuaR1pDwSh+uoLxi+xIggCIKg5cSIIAiCoOVEIAiCIGg5EQiCIAhaTgSCIAiClhOBIAiCoOX8D7sAhn8AKwQbAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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JZmwCual60jTQVuxcwfCk4Vwy7BKrS1GqQ1gHhHG7cbmzcSS3ULR3F9veX0t2XRNJI0ae8z5LSkoAGD48/K9VL6hqYmhKHDH28A5CqxXVF3Gk7gg3T7xZr2BSQSWsA8JzZC8Qg2NIMse25WMTYVppDbF96P9w4oT/WvUh4X+tekFVMyPTdNrLQNt1chcAs7NnW1yJUqcK64BwHTgAgCNvLMW7tjOopY2UOXOwxZ37tJkVFRUMHjyYmJjw7jhmjKHgZBMj0vQbbaAV1BcgCCMGjbC6FKVOEd4BcawE8CKjRlNecJTBTS1kfu+7fdpnRUVFWI/c2u5AeQN1LS6m54TvMObBorChkCEJQ4iJCu8vHSr0hG1AeA+spaUsEUdCIw31J/EaQ3r2MGJGndtlhB6PhxUrVnDy5ElGjhzZv8UGGWMM/++VXcRHRzF/fHj3FA8Glc2VZCVkWV2GUmcI24Coe/M4LjOehMumUH3Cd2J58LBz76V66NAhTpw4wfjx45k9O7zbineX1PNRYS33XTORrEE6i1ygVTRXkB6nHRFV8AnLgDDG0Fw5jPjk3SRePIKKA/sAyBg3/pz3efjwYaKjo1m6dCkOh6O/Sg1KWwqqAfjUJP1WG2jGGCpbKsmMD/9mSxV6wjIgPNXNGBNLdJbQ2tTIrrVvk9DaRmLeuU/jWFxcTE5OTtj3fQA4VNHI4HiHzgExACqaK2hyNekc1CoohWVAuA4fBcCRm07+66/Q1FDPxBNVRJ/DuYPq6mqefvppysrKyMmJjIHUDpU3kJeZpMNrDIANJzYAMDltssWVKHWm8AyIAt85B0feWA5seI/sxEFkewXHOXzAr1+/nmPHfFOUnn/++f1aZzAyxnCoopG8LB3eO9Dq2+p5ePPDTEidwJT0KVaXo9QZ7FYXEAiu0kaipJl6ey615aXk1DQTN2sWYut9HlZX+9rj7777bpKSkvq71KBT2eCkrsVFns7/EHDvFr1Li7uF+y+8H7stLN+KKsSF3avSGIOr1o4jpoLj+/YCkFpRRcavftOr/dTV1bFz504KCwu56KKLSE+PjKtMDlU0ApCXFf5haLW3Ct4iOyGb6RnTrS5FqS6FXRNT47pjuFvTiEmvY++6d4hzuRl67XXETe5dG++mTZtYs2YNABP6ODVpKFl3sBKbwPhsDYhAamhrYMOJDSwcsVDP9aigFVYB4Sprom51MXG2DygZmsiJQ/vJqaonce7cXu+roqICgJtvvjnsO8a1q2tx8ZcPj7N4+lDSdQ7qgHrj6Bu4vC6uGnGV1aUo9YnCKiCcx+vBCMlpqzh4rIb42HjGltcQP3Nmr/dVXl7OtGnTyMvLC0ClwendAxW0uDx8Yc5Iq0sJawV1Bfxq6684P/t8bV5SQS2gASEii0TkgIgcFpHvdXH/cBFZKyLbRGSniPRpBh5PRR3gImrKJZQc2EumzYEjKwt7L0debWpqoqGhgaysyOoo9q99FaQnRjMzV8dfCqSXD72M2+vm4Ysf1uYlFdQCFhAiEgU8DlwNTAKWi8ik0zb7PvCCMWYmsAz4XV+e01VUgl3KaM6ZT3NdLfHHC4m/8IJevQmNMaxevRogYpqW2u0sruXCUWnYbPqhFUi7Tu5iYtpEHX9JBb1AHkFcABw2xhw1xrQBzwPXn7aNAQb5bycDJ871yYwxuCrAIUeobPGNH5TU0kbmvff2aj+7du1i586dzJ8/n2HDhp1rOSHH4zWU1LTo8N4B5va62Vu1l6npU60uRaluBTIghgFFnZaL/es6+yFwi4gUAyuBr3W1IxG5S0TyRSS/srKyyydr3VOFpzWa2NiDVJb6TjBnjsnDkZ3dq6Lz8/NJT09n/vz5vXpcqDtR24Lba3R60QA7UnuEFneLdoxTISGQAdFVO4U5bXk58GdjTA5wDfAXETmjJmPMCmPMbGPM7IyMM4efNm4vta8fxRFdTvzQk5w8foxYt4dB43o39lJraytFRUVMmjQJ2zl0qgtlhyoaABirHeQCqn32OD2CUKEgkJ+CxUDnEchyOLMJ6Q7gBQBjzIdALNDrHmmt+6vx1DlJjvojDJ1K+dHDJDW3Ys/u3cnpjRs3YoxhxIjIm9lre1EdAOO0g1zAeI2XFw68wJCEIQxPCv85zVXoC2RAbAHyRGSUiETjOwn92mnbFAJXAIjIRHwB0XUb0lm0nWgEMcR4t7C7fhhVJUWkN7QQO7HnHdwqKyt59913yc3NZdQ5TioUqupaXDy76TjzxqaRHBfeQ5lb6c2jb7Kveh/3zLpHr15SISFgAWGMcQN3A6uBffiuVtojIg+JyGL/Zt8EviQiO4DngNuMMac3Q3XLfbKFKEc9ZbZc/vXaOwwZnM7Ik3XETe35YXx+fj4AN9xwQ8Q1Lz27qZCTjW18d1Hk9Bi3wrridQxJGMI1o/p0NbdSAyagYzEZY1biO/nced2DnW7vBeb19XncZfU43IfY5J6GI8bJBcQio0YRldKz6/mbmprYtGkTdrud5OTkvpYTcv62pZA5o9OYpvNPB9SB6gNMSJ2gRw8qZIT8V2Wv04Or0okxxzh0vJ4Jcy/Fu207cTNm9OjxFRUVvPnmmwDcdNNNETEhUGetLg8FVc3MGZNmdSlhrbq1moL6Ar16SYWUkB/NtWlLGRhhf5Pv0tYJiYNpqKtj0LXX9ujxf/vb36iqqmLw4MERd+4B4NjJJgBGpSdYXEl421K2BYALh1xocSVK9VxIH0G4KptpeKcQR8xRPjrZyKRLr8D16j+IHjGChLlzun18dXU1VVVVpKam8oUvfCEiD/23F9UCMHHIoG62VOfKGMObR98k0ZGoM8epkBLSAdH0YSneZjc4f4vbC1mxCbTu2EnqbV/s0eRAR44cAWD58uWkpqYGutyg09Dq4ukNBQxJjmVMhh5BBMqHpR+ytmgtd0y9QycGUiElpAPCVdZEdCbUtPlmfYsrLQebjeTFi7t5JDQ0NLB+/Xqys7MjZjKg0z31fgH7yxr48WemROTR00BZc3wN8fZ4bp10q9WlKNUrIRsQxmNoK2nE4Sikui0BRHAcPUbMmNHYEs7+bdgYw6uvvkpLSwuf+cxnIvbDcf2hSmYNT+GKiTpoXKB4jZd1xeuYO3Qu0VHRVpejVK+EbEA4C+owTg8x1X+nOjaP5IxMXLv3EDul+74PRUVFHDlyhCuvvJLsXo7VFC7cHi97TtQxI3ew1aWEtU2lmyhvLufKEVdaXYpSvRayAdH4wQlsDjex3vVUe1NJTkjCU11N/IUXfOJjjDHs27ePzZs3Y7PZmNHDS2HD0cHyRlpdXqbnRl6/j4H04sEXSYlJYeGIhVaXolSvheQZs5b91bTurSIpeT2SNoWa96pIcVdji49n0FWfPIXjnj17eOmllwAYM2YMsbGxA1Vy0NlZ7Lt6STvHBc7BmoOsLVzLLZNu0eYlFZJCMiAa3i1CYqNIal1BVfqXcLflE1tUQeJll2GLP3O46tLSUlavXk1BQQEAWVlZLFiwYGCLDjI7imsZFGtnpM7/EDB/3v1nHFEO7phyh9WlKHVOQi8gDLQVNpA4rg5bQSMHquIAyKhvJvO73zll0+bmZg4cOMDmzZspLS0FYOnSpUyadPrEdpFnS0ENM4cPjtgT9IF2rO4Yrx99nVsm3kJKrB6lqdAUcgFhXB7wGqLr1nIydjyb1nxAutNN5qKrcWRmnrLtu+++y+bNmwGYNGkSM2fOJC8vz4qyg8pHhTUcrmhk2fm53W+szsmqY6sQhNun3G51KUqds5ALCFdlCwiYytd5+lAe4CWnrIq4pTM7tjl69CgfffQRu3fvxuFwMGPGDK644oqIPufQzhjDT97cR3piDMsv0DkJAsEYwz8L/sns7Nlkxmd2/wClglTIBQRATPoxVu72zSx33tTzyNzxArapU9m2bRtNTU1s27aNqqoqAD7/+c8zrpczy4WzXSV1bD1ew0PXTyYhJiT//EFve+V2jtUd45aJt1hdilJ9ctZPCBHZ2YN9VBpjruinerrlSI9j09H/o7A5hXlLbyHzmRcomTqVF15++ZTtcnNzmTx5sjYpneZf+yqwCSyePtTqUsJSm6eNb637Fnaxa98HFfK6+woZhW+u6E8inDlLXGDZ3ByuimbihKGMaXJRuXcfh790JzQ0kJycTGJiIklJSSxZsgSHQ2dHO92mo1VMHppMSrxedhkIz+x7hormCh6a+xCpsZE3vpcKL90FxL8bY46fbQMR+Y9+rKdbzoZqPGYEU664luf+uZHqZTdCQwNXXHEFl1xyyUCWEnJaXR62FdVy60WRN+f2QNlYupG8wXnckHeD1aUo1Wdn7UltjHm/ux30ZJv+1NpQT4zdywmTQnVMDABDhgxh3rw+T0wX9tbsq6DN7eWScRlWlxKWml3NbKvYxsyMmd1vrFQIOGtAiMiK7nbQk236U4stjsbxF7Bq7VrSKyuZN24cy5Yti7h5pM/F42sPMyo9gXk6e1xA/OPIP2hxt3Dt6J5NVqVUsOuuiekzItJ6lvsFuKwf6+mWibLT6oWcmhrmVFYyafly7ezVA6V1Lewtree+qydgj9Iw7W8vH3yZn276KTMyZjAzU48gVHjoLiC+3YN9vNcfhfRUVFQUF4wZw6if/JShj/xCw6GHVu0uA9ChvQOgurWaX2z5BeMGj+MnF/9EX5MqbJw1IIwxTw9UIT2VlZXFRV4v5UDCnO6nFVU+/9xVxoTsJMZmJlpdSth55dArNLubeeTSRxg+SDsfqvARkm0NrXv3Yc/IwB6hM8H1VkOri62FNVypRw/9zhjDq4df5bys8xidMtrqcpTqV6EZEPv3EzNxgtVlhIT6VhcL/2c9Hq9h/ni9eqm/7ajcwfH643xm7GesLkWpfhdyAWFcbpyHDhE3bbrVpYSEtfsrKKtv5apJWcweobPH9bdXD79KnD2Oq0Z88jwkSoWqHgWEiLwtIimdlgeLyOrAlfXJPHW14PWSfJ1eStgTB8oasNuE3940S0+e9rMWdwurClaxcMRC4h06r4YKPz09gkg3xtS2LxhjagBLhqn01NcTO2UK0SNHWvH0IWdbYS3jspKItofcwWLQW1O4hiZXkzYvqbDV008Nr4h0XJ4hIiMAE5iSzs60tJB42QIrnjrkNDrdfFRYw0WjtWNcILx6+FWGJQ7jvKzzrC5FqYDo6XjP9wPvi8g6//KlwF2BKakbBhIjfLrQnig42cQL+UU43V4WTcm2upywU9RQxKbSTfzHjP/AJnp0psJTjwLCGLNKRGYBF+HrPf0NY8zJgFb2CWwJCcTqlKHdWvTYelpdXrIHxerJ6X7mNV6+te5b2MTG4jGLrS5HqYDpbiymCf7/ZwHDgRNACTDcv27ARY8Yridbu1Fc00yrywvA/9w4HZtNf1/96Z/H/sneqr185/zvMCxxmNXlKBUw3R1B3IuvKem/u7jPAJef7cEisgh4DN+8En80xvzstPt/xcdjOcUDmcaYs8/wroPydevlrSUArPv2AkakJVhcTXhp87Txm22/YULqBJZPWG51OUoFVHdDbdzl/7/XA/KJSBTwOLAQKAa2iMhrxpi9nfb/jU7bfw3QUc76wT92lHDx2HQNhwD424G/UdJYwpMLn9RzDyrs9bQfxOdFJMl/+/si8oqIdPdhfgFw2Bhz1BjTBjwPXH+W7ZcDz/WkHvXJKupbOVrZxLyxOgxJf2toa2DFzhXMGTKHuUPnWl2OUgHX069ADxhjGkTkYuBTwNPA77t5zDCgqNNysX/dGfyXzY4C3vmE++8SkXwRya+srOxhyZFp9Z72UVst6aYS1tYUrqHWWctXZ37V6lKUGhA9DQiP//9rgSeMMf8AupvUuKszo5/Ud2IZ8JIxxtPVncaYFcaY2caY2RkZOp7Q2byxs5SxmYmMy0qyupSws754PRlxGUxLn2Z1KUoNiJ4GRImIPAksBVaKSEwPHlsM5HZazsF3FVRXlqHNS31W0dDK5oJqrpk6xOpSws6Wsi28ffxtLs25VK+iUxGjpwGxFFgNLPIPuZFK95MJbQHyRGSUiETjC4HXTt9IRMYDg4EPe1y16tLq3WUYA9dqQPS7/87/b4YlDuNrM79mdSlKDZiedpRrBl7ptFwKlHbzGIHzw6MAABvUSURBVLeI3I0vWKKAp4wxe0TkISDfGNMeFsuB540xlgzdEQ6MMXzzxR288lEJYzISGJelkwL1p90nd7Onag/3X3g/aXE6bImKHD0dauOcGGNWAitPW/fgacs/DGQNkeDDI1W88pGv78O/XzpGm0D62XP7nyPeHs91o6+zuhSlBlRAA0INjH/tq8Am8K975zM6Q48e+lNlcyWrjq3ihrwbSIzW362KLNrTJwy8s7+cS8dlaDj0M7fXzT1r78Ft3Nw4/kary1FqwGlAhLhD5Q0UVDVz+QTt99Dffr755+w6uYsfzvkheYPzrC5HqQGnTUwhzBjD/a/uJjHGzqLJOqR3f3nl0Cv8dttvqWyp5OaJN3ND3g1Wl6SUJTQgQtjukno2H6vmwesmkTko1upyQp7T46S8qZz/+vC/cBs3AF+a+iWLq1LKOhoQIeynK/eREu/g+hlDrS4l5Lk8Lj732ucoqC8A4N+n/TszMmfoZa0qomlAhKii6mY+PFrFdxaNJy0xxupyQt6qglUd4XD9mOu5e+bd1hakVBDQgAhBxhhWrD8KwFWT9NxDX7W4W/jd9t8xJnkMz133HLFR2lynFGhAhKR1Byv5y8bjfHHOCMZm6qWtffXkjicpbizmqU89RZw9zupylAoaGhAh6Ff/OsTw1Hjuv1bn5u6LOmcdIsJLh17iqhFXcX72+VaXpFRQ0YAIIW6Pl83HqtlRVMv3r51ItF27sZwrYwzL3lhGcWMxANePPdtcVkpFJg2IEPL//r6LF/J9H2iL9cqlc+bxethavrUjHADmDJ1jYUVKBScNiBBw7wvbGZuZ2BEOv1k+k8wkPZF6rp7Y8QRP7nySaFs098y6h9S4VBw2h9VlKRV0NCCCXHl9a8dIrQCv330xU3OSLawotBlj+PuhvwPw/Yu+r72klToLDYgg9/6hkwAsnJTF4ulDNRz6oLGtkR9s+AEVLRU8NPchDQeluqEBEcRezC/i2y/tZHR6Ak/ech42m87z0Bc/+vBHvHX8LSakTuBTIz9ldTlKBT29DCZIOd0eHnp9LwD/eUWehkMfFdYXsrpgNZfnXs7Ti54m3hFvdUlKBT09gghSO4rqaHC6WfGF87hKR2o9Z06Pk/veu4+3j7+Nw+bggTkPaDgo1UMaEEFo6/Fqlj75IQAXjEq1uJrQU91ajcvj4s637iQlJoXtldsBWDxmMelx6RZXp1To0IAIQve+sAOA7ywaT0p8tMXVhJZn9z3Lw5sf5rLcyzoG3xsxaAT3nnev9pRWqpc0IIJMaV0Lx6ua+cqCMfzHgrFWlxNS2jxtPLz5YQDWFq3tWH/b5Nu4fPjlVpWlVMjSgAgiW4/XsOSJDQDcdMFwi6sJLRtLN/Klt3yT+2TEZdDsbub3V/6eoYlDyYjLsLg6pUKTBkSQqG91ceufNgHw+fNyyE3VE6k90exqZkfljo7Ob2NTxvLstc9iFzuOKO0drVRfaEAEiZfyi2lq8/CPr85j6jDtDNdTv9r6K54/8DwAS/KW8P2Lvo/dpi9rpfqDvpOCwONrD/PkuiPMGp7C9NwUq8sJKfnl+YDvRPStk27VcFCqH+m7yWLFNc08svoAAN+/Tud36E55Uzl1bXW8efRNTrac5HDtYe49715un3K71aUpFXY0ICz29t5yANZ8cz5jMnR2uK4YY3j96OvkJObwjXe/QXVrdcd9CY4Erh19rYXVKRW+NCAstLukjr9tKWJCdpKGw1lsLd/K/e/f37E8PGk4eYPzuGPKHaTFpZEZn2lhdUqFLw0IC+wqrmNbUQ0P/mMPAA9o09IZypvKSYpOosZZwz1r7wF8VyiNTRnLI/Mfsbg6pSKDBsQAO9no5NO/fb9j+Y6LR3H73JHWFRSEXF4XV750JRNTJ3K07ihOj5MleUv44dwfWl2aUhEloKO5isgiETkgIodF5HufsM1SEdkrIntE5NlA1hMMVu0u67j90pfn8MB1k3Sk1tNsK98GwL7qfTg9ThaPWczXZ33d4qqUijwBO4IQkSjgcWAhUAxsEZHXjDF7O22TB9wHzDPG1IhIWDcm1zW7eOLdI4zPSmLlPZcQpcEA+I4Y1hauZd6weTy771lWHlsJQG5SLnOGzOGBOQ9YXKFSkSmQTUwXAIeNMUcBROR54Hpgb6dtvgQ8boypATDGVASwHkt5vIbvvLyDktoWnrnzQg2HTp7c8SRP7nySmKgYnB4n4Bt59ScX/8TiypSKbIEMiGFAUaflYuDC07YZByAiHwBRwA+NMatO35GI3AXcBTB8eGiOUfTajhJW7ynn0nEZzBurQ04DHKk9woMfPMjOkzsB39wNdpudC7Iv0CYlpYJAIAOiq6/IpovnzwMWADnAeyIyxRhTe8qDjFkBrACYPXv26fsIauX1rWw6Vs0LW4pJirHzh1vPs7qkoNE5HB646AE2lm7kC5O+wMzMmRZXppSCwAZEMZDbaTkHONHFNhuNMS7gmIgcwBcYWwJY14D64lOb2V/WAMA3rhxHjD3K4oqsY4yhsqUSp8fJe8XvsfPkTm6bfBuLRi1ictpklo5fanWJSqlOAhkQW4A8ERkFlADLgJtO2+ZVYDnwZxFJx9fkdDSANQ0Yl8fLidqWjnBIiXew9Pwci6uy1jP7nuHnW35OSkwKtU7fQeKnx3yacYPHWVyZUqorAQsIY4xbRO4GVuM7v/CUMWaPiDwE5BtjXvPfd5WI7AU8wLeNMVWBqmkgfFRYw/qDlbx7oJLtRb4PwVe/Oo9xWYnER0dmt5M6Zx17q/by2pHXAKh11jJ+8HgemveQhoNSQSygn1jGmJXAytPWPdjptgHu9f8LC8tWbKTN7e1YHhzvYNqw5Ijs67C5dDM7T+5kU+kmNpZu7Fg/OGYwTy58krS4NAurU0p1JzK/0gZAaV0Lb+8tPyUcHvncNC7OS4/IcDDGcMdbd5yx/s+L/sy0jGk4bDqZj1LBTgOin3zlrx91NCn97LNTyUqO5bLxYd3vr0vGGD448QHvl7x/yvrbp9xOdnw2szJnIRJ5galUKNKA6KMNR05S2eDsCIfPzhzGsgidT/rra79OrbOWreVbARCEO6feSW5SLjfk3WBxdUqp3tKA6KOb/rCp4/ZTt82OuE5wHq+Hp3Y/RZu3jTWFa0657+aJN/Ofs/7TosqUUn2lAXGOthXW4PF+3Gdvek4yl0/IsrCiwDLGsPLYShbkLiDBkUBDWwPP7nuWtLg0fr3t16dsu3DEQh646AGSopMsqlYp1R80IM5BS5uHG363oWP5vqsncMtFIyysKPA2lW3ie+99j8VjFlPeVE5VaxWHaw+fss2o5FE8f+3zxNnj9DyDUmFAA+IcbC74eMpLEbh1zkjiosO7h/Sfdv0JoKMvQ2dXDL+Ce8+7l+ioaOId8QNdmlIqQAI6H0Q42lJQzQtbirAJfPtT4/njrbPDMhyO1h7ltlW3Ud1azYaSDaf0YwDf0cKP5/2YUcmjuHPqnQwfNJzshGyLqlVKBYIeQfSA12v45os7WDA+g3ue3w7AlRMz+eplYy2uLHB+seUXbC3fyvy/ze9Y99hlj7Hy2EpGDBrB12Z+DYDrx15vVYlKqQDTgOiBjwpr+Pu2Ev6+raRj3X3XTLSwov7zxI4nePv429x73r28V/we146+ljePvsnBmoMd28RExXBpzqVclnsZlw+/3MJqlVIDSQOiB947dLLj9vkjB/Pil+daWE3f7KjcQbQtmtEpo2l2NfO77b8D4Cv/+goAz+1/DuMflf2mCTdR31bPt8//NqmxqZbVrJSyhgbEWXi9hv/7sIA3dp4gLzORrywYwxUheilrSWMJ9c56bll5CwDTMqaxs3LnGdu1h4Nd7Nw88WaGD4rMTn9KKQ2ILlU2OPnCnzZx1aQsfv2O71LO2+aO5LOzQnO4bq/xcuvKW6lo+XhG187h8Mw1z5ASk8Ltq26noqWCdTeuw4aNlNgUK8pVSgUJDYgurD9Yyf6yho65HACumBga4yrtObmH8anjefHgi8zPmU9GXAb7qvd1hMOSvCWsKVxDSkwKU9KncO3oa5mWMQ2AP1/9ZwTR5iSlFADiG3E7dMyePdvk5+cHZN/l9a3c/MdNHK5oxCbgNb4jh6nDkvnsrGFB3/krvyyf21ffzgXZF7C5bDMANrGR6EikydXEuhvXkRyTTJOrCY/xMCh6kMUVK6UGiohsNcbM7s1j9Aiik3f2V3C4ohGAhZOyWDIrh0vyMoK+n8PJlpP8YssvaHG1AHSEA/ial+rb6lmQs4DkmGQAEhwJltSplAotGhCd7CyuAyA1IZo7LxnN+SODq6nFGIPB0OZpY1/1Pv51/F+sL16PTWwcrfPN1JrgSGBa+jRunHAjxQ3FpMam8vDmh7lz2p0WV6+UCjUaEEBRdTO/XnOIf2w/wZUTs/jjF3t1FBZwJ1tOUtVSxTuF7/CXfX9hesb0M+ZbaPfSp18iJ+nUk+lXj7oau03/1Eqp3tFPDeDJ9Ud4cWsxAJ+fbf2VSk2uJmxi49Gtj+L0ONlwYgOlTaUd93cOh59e/FNqWmtYMm4J5c3lZ4QDoOGglDonEf3Jsbukjue3FLJqdxmZSTE8cN0krppkfT+Hpa8vpbCh8Kzb/PySn5Mck8y8YfM61o1OHh3o0pRSESSiA+ILf9pETbMLgN8sn8mnpw8dsOc2xlDrrGVw7OCOdWVNZQBdhsPXZ32dpOgk5ufMJ8oWRXpcZE1MpJQaeBEZEDuLa3l7b3lHOMwZnTZg/Ry2lG3hvzb+F+MGj2N1wWqWT1jOmuNruO/C+/jGu984Zdt7Zt1DVnwWbq9bp+xUSg24iOoHUdfsoqnNzZInNlBa1wrAG1+7mCnDkvuzxFP86MMfsatyF7++/Ne8VfAWK4+tZF/1vm4f9/6y9zsuS1VKqb7SfhDdWP6HjewtrWdQrO/H/sqCMUwe2r+dxQ5UH2BL2RbGDh7Ll976Usf6G/5xA83uZgBmZc4izhGHx+s5Y56FcYPHcfnwyzUclFKWi4iA+O07h2hu87C3tB6A+lY3D10/mVvnjOz357rr7buobq0mLTYNgIy4DCpbKjvCITshmxVXrSAmKoaypjKe2fcMGXEZPJL/CJflXsavL//12XavlFIDJuwDwu3x8su3Dp6yLjnOwfXTh/Xr8zyz7xleOfQK1a2+6UirWqv48vQv89UZX+XfVv8bW8q28Nhlj3HJsEtwRDkAX1h8c/Y3McaQnZDN5PTJ/VqTUkr1RVgHRJPTzY6i2o7lKJvwr3vnkxhjJzne0ad917fVYxc72yu34/a6eXz74zS0NZyyzeLRiwF45NJH+LD0QxbkLsAmZ87yKiJcNfKqPtWjlFL9LSwDYuvxaoamxLHo0feoa3ERbbfx+1tmkRIfzaj0vo1D9Mstv2RMyhge+vAhRqWM4lDNoTO2eeOGNyisLyR3UC4AaXFpXDf6uj49r1JKDbSwC4jSuhaWPPHhKetuuXAEl3cx0Y8xhjZvGw6bg4K6AkannL2jWZ2zjqf3Pt2xfHo43DHlDm4cfyNDEocwYtCIPvwUSillvbAJCGMML+YXs+dE3SnrH/ncNK6ZOqTLxzy7/1l+tvlnLBu/jOcPPM/fF/+dsYPHdrnvZ/Y9Q4Or4Yz7cpNyKWooAuCuaXcR74jvh59GKaWsFxYBUdfsYltRDd952TdL2uiMBLKSYrl8Qiafn53bsd2Gkg3srd7LpLRJfHjiQ/66768APH/geQB+v/P3uL1uluQtIb88n1sn3UpVaxWF9YX8fMvPAd+4Rt85/ztcPPRiYu2xiAhVLVU0tDVoOCilwkpAO8qJyCLgMSAK+KMx5men3X8b8AhQ4l/1W2PMH8+2z/aOcm6Pl79uPM6cMel86tH1HfenJkTz1G3nMyM3hZVHV5IZn0luUi5e4+XGN26kxlnT4/rnDp3LhhMbOpYX5C7gqhFX8ekxn+7xPpRSKhgEVUc5EYkCHgcWAsXAFhF5zRiz97RN/2aMubu3+1+1p4wfvn7qrm6fN5IffHoybq+bo3VH+e573yXOHocxhlZP6xn7GJ08mqXjl/LYR48xOW0y+eX5LByxkLePvw1wSjgsHLGQ/1nwP70tUymlQlYgm5guAA4bY44CiMjzwPXA6QFxTvaeqO+4nTfUw8JxYymP+V/eODqfxz56rGPguxZ3yymPu3H8jRypPcKjlz1KUnQSNrGxdPxS7GKnrKmMrIQsPij5gNTYVJa9uQwAh83BZ/M+2x9lK6VUyAhkQAwDijotFwMXdrHdEhG5FDgIfMMYU3T6BiJyF3AXQEbuMOb89XISm5YQnX4Yb1s6ZcnPU5e4mLeOrOKtwlVdFpMWm8bUjKl8/6Lvn3Gfw+brEzEk0Xcy+5KcSwBYvWQ1mfG+Qfx0TgWlVKQJ5KeedLHu9BMerwPPGWOcIvJl4Gng8jMeZMwKYAVA3MhE0+ippDH298TEfrzNa0de67gdExXDD+b8gAuHXMi9795Lelw6j172aK9/gKGJAzf8t1JKBZtABkQxkNtpOQc40XkDY0xVp8U/AD/vdq/iOWNVWmwaVa1VREkUeYPzuGHsDR0nkv9y9V8wZ+SSUkqp7gQyILYAeSIyCt9VSsuAmzpvICJDjDHtc2kuBrodB9uGjQcvepDdJ/fzuXGf4UjdEa4ZdQ0vHHiBucPmnjGrmoggXR7MKKWUOptAX+Z6DfAovstcnzLG/EREHgLyjTGvicjD+ILBDVQDXzHG7D/bPvsyH4RSSkWqc7nMNaImDFJKqUh1LgFx5tCiSimlFBoQSimlPoEGhFJKqS5pQCillOqSBoRSSqkuaUAopZTqkgaEUkqpLmlAKKWU6pIGhFJKqS5pQCillOqSBoRSSqkuaUAopZTqkgaEUkqpLmlAKKWU6lLIDfctIg3AAavr6IF04KTVRfSA1tl/QqFG0Dr7W6jUOd4Yk9SbBwRyRrlAOdDbMc2tICL5Wmf/CYU6Q6FG0Dr7WyjV2dvHaBOTUkqpLmlAKKWU6lIoBsQKqwvoIa2zf4VCnaFQI2id/S1s6wy5k9RKKaUGRigeQSillBoAGhBKKaW6FFIBISKLROSAiBwWke9ZXU87EXlKRCpEZHendaki8raIHPL/P9jiGnNFZK2I7BORPSJyT5DWGSsim0Vkh7/OH/nXjxKRTf46/yYi0VbW2U5EokRkm4i84V8OujpFpEBEdonI9vZLHYPt7+6vKUVEXhKR/f7X6Zxgq1NExvt/j+3/6kXk60FY5zf875/dIvKc/33V69dmyASEiEQBjwNXA5OA5SIyydqqOvwZWHTauu8Ba4wxecAa/7KV3MA3jTETgYuAr/p/f8FWpxO43BgzHZgBLBKRi4CfA7/y11kD3GFhjZ3dA+zrtBysdV5mjJnR6Xr9YPu7AzwGrDLGTACm4/u9BlWdxpgD/t/jDOA8oBn4O0FUp4gMA/4TmG2MmQJEAcs4l9emMSYk/gFzgNWdlu8D7rO6rk71jAR2d1o+AAzx3x6Cr4Of5XV2qu8fwMJgrhOIBz4CLsTXU9Xe1WvBwvpy8H0YXA68AUiQ1lkApJ+2Lqj+7sAg4Bj+C2eCtc7TarsK+CDY6gSGAUVAKr7O0G8AnzqX12bIHEHw8Q/drti/LlhlGWNKAfz/Z1pcTwcRGQnMBDYRhHX6m222AxXA28ARoNYY4/ZvEix/+0eB7wBe/3IawVmnAd4Ska0icpd/XbD93UcDlcD/+pvs/igiCQRfnZ0tA57z3w6aOo0xJcAvgUKgFKgDtnIOr81QCgjpYp1eo9tLIpIIvAx83RhTb3U9XTHGeIzvED4HuACY2NVmA1vVqUTkOqDCGLO18+ouNg2G1+g8Y8wsfM2zXxWRS60uqAt2YBbwhDFmJtBEcDR7dcnffr8YeNHqWk7nP/9xPTAKGAok4Pvbn67b12YoBUQxkNtpOQc4YVEtPVEuIkMA/P9XWFwPIuLAFw7PGGNe8a8OujrbGWNqgXfxnTNJEZH2scOC4W8/D1gsIgXA8/iamR4l+OrEGHPC/38FvvbyCwi+v3sxUGyM2eRffglfYARbne2uBj4yxpT7l4OpziuBY8aYSmOMC3gFmMs5vDZDKSC2AHn+M/HR+A7vXrO4prN5Dfii//YX8bX5W0ZEBPgTsM8Y8z+d7gq2OjNEJMV/Ow7fi30fsBb4nH8zy+s0xtxnjMkxxozE91p8xxhzM0FWp4gkiEhS+2187ea7CbK/uzGmDCgSkfH+VVcAewmyOjtZzsfNSxBcdRYCF4lIvP993/677P1r0+oTPb08+XINcBBfm/T9VtfTqa7n8LX1ufB9E7oDX3v0GuCQ//9Ui2u8GN8h5U5gu//fNUFY5zRgm7/O3cCD/vWjgc3AYXyH9TFW/9071bwAeCMY6/TXs8P/b0/7+ybY/u7+mmYA+f6//avA4CCtMx6oApI7rQuqOoEfAfv976G/ADHn8trUoTaUUkp1KZSamJRSSg0gDQillFJd0oBQSinVJQ0IpZRSXdKAUEop1SUNCBV2/KOC/ken5aEi8lIAnueHIlIiIg/19757+PxrRaRRRGZ3v7VSvacBocJRCtAREMaYE8aYz51l+774lTHmwQDtm049X89gjLkMX78BpQJCA0KFo58BY/zj9T8iIiPFP1eHiNwmIq+KyOsickxE7haRe/0DxG0UkVT/dmNEZJV/gLv3RGTC2Z5QRGz+cfYzOi0fFpF0f+/wl0Vki//fPP82F4jIBv9zb2jvReyv8UUReR3fIHtDRGS9/+fZLSKXBPKXp1S7T/x2olQI+x4wxfgG/GsfvbazKfhGs43F16v0u8aYmSLyK+BWfGMqrQC+bIw5JCIXAr/DN95Sl4wxXhH5K3Cz//FXAjuMMSdF5Fl8Rxrvi8hwYDW+AQj3A5caY9wiciXwU2CJf5dzgGnGmGoR+Sa+oZl/4p8XJb5Pvx2lekgDQkWitcaYBqBBROqA1/3rdwHT/CPezgVe9A1lA/iGKujOU/jGt3kU+Dfgf/3rrwQmddrXIP/4SMnA0yKSh28YFEenfb1tjKn2394CPOUfbPFVY8z2Xv20Sp0jDQgViZydbns7LXvxvSds+MbOn9GbnRpjikSkXEQuxzfJ0c3+u2zAHGNMS+ftReQ3+MLqBv9Rzrud7m7qtN/1/iG6rwX+IiKPGGP+rze1KXUu9ByECkcNQNK5Ptj45sk4JiKfB99IuCIyvYcP/yPwV+AFY4zHv+4t4O72DUSkPXiSgRL/7ds+aYciMgLf3BN/wDci76we1qJUn2hAqLBjjKkCPvCf0H3kHHdzM3CHiLSPgnp9Dx/3GpDIx81L4J8fWER2ishe4Mv+9b8AHhaRD/DNG/xJFgDbRWQbvnMUj/X4p1CqD3Q0V6XOkYj8EGg0xvyy07rZ+E5ID8iVRiLyLvAtY4xe7qr6nR5BKHXuGoG72jvKicj38M3Yd99APLmIrMU3xr9rIJ5PRR49glBKKdUlPYJQSinVJQ0IpZRSXdKAUEop1SUNCKWUUl3SgFBKKdWl/w+6c9i/N8LhugAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot mean sea ice cover\n",
+ "da1=get_var(DS1,\"sic\",False)\n",
+ "da2=get_var(DS2,\"sic\",False)\n",
+ "da3=get_var(DS3,\"sic\",False)\n",
+ "da4=get_var(DS4,\"sic\",False)\n",
+ "da5=get_var(DS5,\"sic\",False)\n",
+ "da6=get_var(DS6,\"sic\",False)\n",
+ "\n",
+ "da1_Jor=get_var(DS1_Jor,\"sic\",True)\n",
+ "da2_Jor=get_var(DS2_Jor,\"sic\",True)\n",
+ "da3_Jor=get_var(DS3_Jor,\"sic\",True)\n",
+ "da4_Jor=get_var(DS4_Jor,\"sic\",True)\n",
+ "da5_Jor=get_var(DS5_Jor,\"sic\",True)\n",
+ "da6_Jor=get_var(DS6_Jor,\"sic\",True)\n",
+ "da7_Jor=get_var(DS7_Jor,\"sic\",True)\n",
+ "da8_Jor=get_var(DS8_Jor,\"sic\",True)\n",
+ "\n",
+ "\n",
+ "#mean_lat = np.arcsin(1-np.mean(da1[95:150,:])) * (180./np.pi) \n",
+ "#med_lat = np.arcsin(1-np.median(da1[95:150,:])) * (180./np.pi) \n",
+ "\n",
+ "\n",
+ "da1.plot()\n",
+ "da2.plot()\n",
+ "da3.plot()\n",
+ "da4.plot()\n",
+ "da5.plot()\n",
+ "da6.plot()\n",
+ "\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"sic []\")\n",
+ "plt.title(\"winton global sea ice cover\")\n",
+ "plt.ylim(0,1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1_Jor.time,np.squeeze(da1_Jor.values),'-')\n",
+ "plt.plot(da2_Jor.time,np.squeeze(da2_Jor.values),'-')\n",
+ "plt.plot(da3_Jor.time,np.squeeze(da3_Jor.values),'-')\n",
+ "plt.plot(da4_Jor.time,np.squeeze(da4_Jor.values),'-')\n",
+ "plt.plot(da5_Jor.time,np.squeeze(da5_Jor.values),'-')\n",
+ "plt.plot(da6_Jor.time,np.squeeze(da6_Jor.values),'-')\n",
+ "plt.plot(da7_Jor.time,np.squeeze(da7_Jor.values),'-')\n",
+ "plt.plot(da8_Jor.time,np.squeeze(da8_Jor.values),'-')\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"sic []\")\n",
+ "#plt.title(\"hice_unlim global sea ice cover\")\n",
+ "plt.ylim(0.45,1)\n",
+ "plt.xlim(0,80)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "#plt.legend([experiment1, experiment2, experiment3, experiment4],loc=4)\n",
+ "\n",
+ "# sea ice latitude\n",
+ "ice_lat1 = np.arcsin(1-da1) * (180./np.pi) \n",
+ "ice_lat2 = np.arcsin(1-da2) * (180./np.pi) \n",
+ "ice_lat3 = np.arcsin(1-da3) * (180./np.pi) \n",
+ "ice_lat4 = np.arcsin(1-da4) * (180./np.pi) \n",
+ "ice_lat5 = np.arcsin(1-da5) * (180./np.pi) \n",
+ "ice_lat6 = np.arcsin(1-da6) * (180./np.pi) \n",
+ "\n",
+ "\n",
+ "\n",
+ "ice_lat1_Jor = np.arcsin(1-da1_Jor) * (180./np.pi) \n",
+ "ice_lat2_Jor = np.arcsin(1-da2_Jor) * (180./np.pi) \n",
+ "ice_lat3_Jor = np.arcsin(1-da3_Jor) * (180./np.pi) \n",
+ "ice_lat4_Jor = np.arcsin(1-da4_Jor) * (180./np.pi) \n",
+ "ice_lat5_Jor = np.arcsin(1-da5_Jor) * (180./np.pi) \n",
+ "ice_lat6_Jor = np.arcsin(1-da6_Jor) * (180./np.pi) \n",
+ "ice_lat7_Jor = np.arcsin(1-da7_Jor) * (180./np.pi) \n",
+ "ice_lat8_Jor = np.arcsin(1-da8_Jor) * (180./np.pi) \n",
+ "\n",
+ "#print(da1[0,:])\n",
+ "#print(ice_lat1[0,:])\n",
+ "\n",
+ "\n",
+ "l1,=ice_lat1.plot(color='C0')\n",
+ "l2,=ice_lat2.plot(color='C1')\n",
+ "l3,=ice_lat3.plot(color='C2')\n",
+ "l4,=ice_lat4.plot(color='C3')\n",
+ "l5,=ice_lat5.plot(color='C4')\n",
+ "l6,=ice_lat6.plot(color='C5')\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,220)\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "plt.title(\"\")\n",
+ "plt.legend(handles=[l1,l4,l2,l5,l3,l6],labels=[experiment1[9:-7], experiment4[9:-7], experiment2[9:-7], experiment5[9:-7], experiment3[9:-7], experiment6[9:-7]]\n",
+ " ,loc=1, \n",
+ " ncol=3, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"none\",\n",
+ " borderpad=0.5,borderaxespad=0.2)\n",
+ "plt.xlim(0,200)\n",
+ "plt.savefig(\"plots/winton_icelat_overview.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "lj1, = plt.plot(da1_Jor.time,np.squeeze(ice_lat1_Jor),'-',color='C0')\n",
+ "lj2, = plt.plot(da2_Jor.time,np.squeeze(ice_lat2_Jor),'-',color='C0')\n",
+ "lj3, = plt.plot(da3_Jor.time,np.squeeze(ice_lat3_Jor),'-',color='C1')\n",
+ "lj5, = plt.plot(da5_Jor.time,np.squeeze(ice_lat5_Jor),'-',color='C2')\n",
+ "lj6, = plt.plot(da6_Jor.time,np.squeeze(ice_lat6_Jor),'-',color='C2')\n",
+ "lj8, = plt.plot(da8_Jor.time,np.squeeze(ice_lat8_Jor),'-',color='C3')\n",
+ "lj4, = plt.plot(da4_Jor.time,np.squeeze(ice_lat4_Jor),'--',color='C1')\n",
+ "lj7, = plt.plot(da7_Jor.time,np.squeeze(ice_lat7_Jor),'--',color='C2')\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,62)\n",
+ "plt.xlim(0,50)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "plt.legend(handles=[lj1,lj3,lj5,lj8],\n",
+ " labels=[experiment1_Jor[9:-13], experiment3_Jor[9:-13], experiment5_Jor[9:-13], experiment8_Jor[9:-13]],loc=2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2,\n",
+ " ) # ,\n",
+ "plt.savefig(\"plots/winton_icelat_Jor_overview.svg\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'\\nf1_Jor=stability_index(DS1_Jor)\\nf2_Jor=stability_index(DS2_Jor)\\nf3_Jor=stability_index(DS3_Jor)\\nf4_Jor=stability_index(DS4_Jor)\\nf5_Jor=stability_index(DS5_Jor)\\nf6_Jor=stability_index(DS6_Jor)\\nf7_Jor=stability_index(DS7_Jor)\\nf8_Jor=stability_index(DS8_Jor)\\n\\n\\nprint(experiment1 +\" f=\" +str(f1[-1].values))\\nprint(experiment2 +\" f=\" +str(f2[-1].values))\\nprint(experiment3 +\" f=\" +str(f3[-1].values))\\nprint(experiment4 +\" f=\" +str(f4[-1].values))\\nprint(experiment5 +\" f=\" +str(f5[-1].values))\\nprint(experiment6 +\" f=\" +str(f6[-1].values))\\n\\n\\nprint(experiment1_Jor +\" f=\" +str(f1_Jor[-1].values))\\nprint(experiment2_Jor +\" f=\" +str(f2_Jor[-1].values))\\nprint(experiment3_Jor +\" f=\" +str(f3_Jor[-1].values))\\nprint(experiment4_Jor +\" f=\" +str(f4_Jor[-1].values))\\nprint(experiment5_Jor +\" f=\" +str(f5_Jor[-1].values))\\nprint(experiment6_Jor +\" f=\" +str(f6_Jor[-1].values))\\nprint(experiment7_Jor +\" f=\" +str(f7_Jor[-1].values))\\nprint(experiment8_Jor +\" f=\" +str(f8_Jor[-1].values))'"
+ ]
+ },
+ "execution_count": 32,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#plot stability index\n",
+ "f1=stability_index(DS1)\n",
+ "f2=stability_index(DS2)\n",
+ "f3=stability_index(DS3)\n",
+ "f4=stability_index(DS4)\n",
+ "f5=stability_index(DS5)\n",
+ "#f6=stability_index(DS6)\n",
+ "\"\"\"\n",
+ "f1_Jor=stability_index(DS1_Jor)\n",
+ "f2_Jor=stability_index(DS2_Jor)\n",
+ "f3_Jor=stability_index(DS3_Jor)\n",
+ "f4_Jor=stability_index(DS4_Jor)\n",
+ "f5_Jor=stability_index(DS5_Jor)\n",
+ "f6_Jor=stability_index(DS6_Jor)\n",
+ "f7_Jor=stability_index(DS7_Jor)\n",
+ "f8_Jor=stability_index(DS8_Jor)\n",
+ "\n",
+ "\n",
+ "print(experiment1 +\" f=\" +str(f1[-1].values))\n",
+ "print(experiment2 +\" f=\" +str(f2[-1].values))\n",
+ "print(experiment3 +\" f=\" +str(f3[-1].values))\n",
+ "print(experiment4 +\" f=\" +str(f4[-1].values))\n",
+ "print(experiment5 +\" f=\" +str(f5[-1].values))\n",
+ "print(experiment6 +\" f=\" +str(f6[-1].values))\n",
+ "\n",
+ "\n",
+ "print(experiment1_Jor +\" f=\" +str(f1_Jor[-1].values))\n",
+ "print(experiment2_Jor +\" f=\" +str(f2_Jor[-1].values))\n",
+ "print(experiment3_Jor +\" f=\" +str(f3_Jor[-1].values))\n",
+ "print(experiment4_Jor +\" f=\" +str(f4_Jor[-1].values))\n",
+ "print(experiment5_Jor +\" f=\" +str(f5_Jor[-1].values))\n",
+ "print(experiment6_Jor +\" f=\" +str(f6_Jor[-1].values))\n",
+ "print(experiment7_Jor +\" f=\" +str(f7_Jor[-1].values))\n",
+ "print(experiment8_Jor +\" f=\" +str(f8_Jor[-1].values))\"\"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x720 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "save_plot = True\n",
+ "plot_winton = True\n",
+ "plot_unlim = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "\n",
+ "fig, ax = plt.subplots(2,figsize=(6,10))\n",
+ "ax[0].spines['left'].set_position(('outward',5))\n",
+ "ax[1].spines['left'].set_position(('outward',5))\n",
+ " \n",
+ " \n",
+ "# color_winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='lightgray'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation(ax[0],1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation(ax[0],2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation(ax[0],3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation(ax[0],3000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 38.9, 54.3, color_winton, 4)\n",
+ " plot_simulation(ax[0],10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation(ax[0],3000, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],4219, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],4219, 16.6, 0, color_winton, 1)\n",
+ " \n",
+ " \n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " \n",
+ " a=plot_simulation(ax[0],1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[0],1594, 90, 49.54, color_unlim, 3)\n",
+ " plot_simulation(ax[0],1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation(ax[0],1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation(ax[0],2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation(ax[0],3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation(ax[0],3000, 14.46, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[0],3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation(ax[0],3750, 14.46, 0, color_unlim, 1) \n",
+ " plot_simulation(ax[0],3750, 19.2, 18.7, color_unlim, 4)\n",
+ " plot_simulation(ax[0],3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation(ax[0],4063, 14.46, 11.5, color_unlim, 3)\n",
+ " plot_simulation(ax[0],4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation(ax[0],4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation(ax[0],5000, 14.46, 24, color_unlim, 4)\n",
+ " plot_simulation(ax[0],5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation(ax[0],5000, 90, 90, color_unlim, 1) # limited, but no ice at all\n",
+ " plot_simulation(ax[0],10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ "\n",
+ "ax[0].set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax[0].set_ylim(-0.1,1.1)\n",
+ "ax[0].set_xlim(1000,10500)\n",
+ "ax[0].set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax[0].set_ylabel(\"Ice Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax[0].spines['right'].set_color('none')\n",
+ "ax[0].spines['top'].set_color('none')\n",
+ "ax[0].yaxis.tick_left()\n",
+ "ax[0].xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "\n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='lightgray'\n",
+ " \n",
+ " a=plot_simulation(ax[1],1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[1],1594, 90, 49.54, color_unlim, 3)\n",
+ " plot_simulation(ax[1],1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation(ax[1],1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation(ax[1],2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation(ax[1],3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation(ax[1],3000, 14.46, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[1],3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation(ax[1],3750, 14.46, 0, color_unlim, 1) \n",
+ " plot_simulation(ax[1],3750, 19.2, 18.7, color_unlim, 4)\n",
+ " plot_simulation(ax[1],3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation(ax[1],4063, 14.46, 11.5, color_unlim, 3)\n",
+ " plot_simulation(ax[1],4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation(ax[1],4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation(ax[1],5000, 14.46, 24, color_unlim, 4)\n",
+ " plot_simulation(ax[1],5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation(ax[1],5000, 90, 90, color_unlim, 1) # limited, but no ice at all\n",
+ " plot_simulation(ax[1],10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ " \n",
+ "# winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='C1'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation(ax[1],1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation(ax[1],2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation(ax[1],3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation(ax[1],3000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 38.9, 54.3, color_winton, 4)\n",
+ " plot_simulation(ax[1],10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation(ax[1],3000, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],4219, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],4219, 16.6, 0, color_winton, 1)\n",
+ "\n",
+ "\n",
+ "ax[1].set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax[1].set_ylim(-0.1,1.1)\n",
+ "ax[1].set_xlim(1000,10500)\n",
+ "ax[1].set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax[1].set_ylabel(\"Ice Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax[1].spines['right'].set_color('none')\n",
+ "ax[1].spines['top'].set_color('none')\n",
+ "ax[1].yaxis.tick_left()\n",
+ "ax[1].xaxis.tick_bottom()\n",
+ "\n",
+ "ax[0].text(-0.1,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.1,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "ax[0].set_xscale('log')\n",
+ "ax[1].set_xscale('log')\n",
+ "\n",
+ "ax[0].set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax[0].set_xticklabels([1000, '','','',5000,'','','','',10000] )\n",
+ "ax[1].set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax[1].set_xticklabels([1000, '','','',5000,'','','','',10000] )\n",
+ "\n",
+ "ax[0].set_yticklabels([0,10,20,30,45,60,90])\n",
+ "ax[1].set_yticklabels([0,10,20,30,45,60,90])\n",
+ "\n",
+ "#plt.legend((a,b),(\"Winton\", \"Semtner hice_unlim\"))\n",
+ "if save_plot:\n",
+ " if plot_winton:\n",
+ " plt.savefig(\"plots/bifurcation_winton.svg\",dpi=500)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "save_plot = True\n",
+ "plot_winton = True\n",
+ "plot_unlim = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "offset=0.01\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ax.spines['left'].set_position(('outward',5))\n",
+ "ax.spines['bottom'].set_position(('outward',5))\n",
+ " \n",
+ " \n",
+ "# color_winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='C1'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation_merged(ax,1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation_merged(ax,3000, 15.3, 0, color_winton, 3, -offset)\n",
+ " plot_simulation_merged(ax,5000, 15.3, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,5000, 38.9, 54.3, color_winton, 4)\n",
+ " #plot_simulation_merged(ax,10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation_merged(ax,3000, 30.2, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,4219, 30.2, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,4219, 16.6, 0, color_winton, 3, -offset)\n",
+ " \n",
+ " \n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " a=plot_simulation_merged(ax,1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 49.54, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation_merged(ax,3000, 14.46, 0, color_unlim, 3, offset)\n",
+ " plot_simulation_merged(ax,3750, 14.46, 0, color_unlim, 3) \n",
+ " #plot_simulation_merged(ax,3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4063, 14.46, 11.5, color_unlim, 3)\n",
+ " #plot_simulation_merged(ax,4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4375, 14.46, 18.2, color_unlim, 4, )\n",
+ " plot_simulation_merged(ax,5000, 14.46, 24, color_unlim, 4)\n",
+ " #plot_simulation_merged(ax,5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_unlim, 1, offset) # limited, but no ice at all\n",
+ " #plot_simulation_merged(ax,10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ "\n",
+ "#ax.hlines([np.sin(np.radians(56.3)),np.sin(np.radians(50.5)),np.sin(np.radians(52.6))],1500,3500)\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_ylim(-0.1,1.1)\n",
+ "ax.set_xlim(1000,10500)\n",
+ "ax.set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax.set_ylabel(\"Ice-Edge Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.yaxis.tick_left()\n",
+ "ax.xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "ax.set_xscale('log')\n",
+ "\n",
+ "ax.set_xticks([1000,2000,3000,4000,5000,6000,7000,8000,9000,10000] )\n",
+ "ax.set_xticklabels([1000,2000,3000,4000,5000,'','','','',10000] )\n",
+ "ax.set_xlim(1000,5000)\n",
+ "ax.set_ylim(0,1)\n",
+ "\n",
+ "# extra ticks at bifurcation points\n",
+ "winton_bif=2344\n",
+ "#semtner_bif=1641\n",
+ "semtner_bif=1547\n",
+ "\n",
+ "ax.vlines([winton_bif],-0.04,-0.01,color=color_winton,lw=1,clip_on=False)\n",
+ "ax.vlines([semtner_bif],-0.04,-0.01,color=color_unlim,lw=1,clip_on=False)\n",
+ "#ax.axvline(semtner_bif,-20,0.1)\n",
+ "ax.annotate(winton_bif,(winton_bif,0.1),xytext=(winton_bif,-0.05),color=color_winton,ha='center',va='top',clip_on=False)\n",
+ "ax.annotate(semtner_bif,(semtner_bif,0.1),xytext=(semtner_bif,-0.05),color=color_unlim,ha='center',va='top',clip_on=False)\n",
+ "\n",
+ "ax.set_yticklabels([0,10,20,30,45,60,90])\n",
+ "legend_color(ax,[\"3L-Winton\", \"0L-Semtner\"],2)\n",
+ "#plt.legend((a,b),(\"Winton\", \"Semtner hice_unlim\"))\n",
+ "if save_plot:\n",
+ " if plot_winton:\n",
+ " plt.savefig(\"plots/bifurcation_winton_merged.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/cdo_pp-checkpoint.ipynb b/.ipynb_checkpoints/cdo_pp-checkpoint.ipynb
new file mode 100644
index 0000000..7d1a67e
--- /dev/null
+++ b/.ipynb_checkpoints/cdo_pp-checkpoint.ipynb
@@ -0,0 +1,347 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Postprocessing of ICON-AES output for Snowball experiments\n",
+ "\n",
+ "This scripts merges the 2d output data of ICON into a global and zonal mean. It does that by processing custom subperiods and then merging these output files. This is done so that not all the output data has to be reprocessed if the simulation is continued at a later time, as well as for a better overview of which period is processed and which is not. For this, it is reasonable to *not* delete the output files of the subperiods (*.yXXXX_XXXX.nc) until it's certain that this simulation is not continued.\n",
+ "Additionally, 3d data is copied."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Definition of paths "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/csecfrl_experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/ exists\n"
+ ]
+ }
+ ],
+ "source": [
+ "import os, glob, sys\n",
+ "from datetime import datetime\n",
+ "\n",
+ "#experiment = \"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\" #experiment name\n",
+ "experiment = \"mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1\" #experiment name\n",
+ "\n",
+ "base_path = \"/scratch/b/b380905/experiments/)\" #base path of experiment output data\n",
+ "#base_path = \"/scratch/b/b380782/experiments/\" #Christoph\n",
+ "data_path = base_path +experiment +\"/\"\n",
+ "\n",
+ "save_path = \"/work/bb1092/pp_JH/csecfrl_experiments/\" #saving path\n",
+ "\n",
+ "if not os.path.isdir(save_path +experiment): #check if experiment folder in saving path exists\n",
+ " print(\"creating folder \" +save_path +experiment)\n",
+ " os.mkdir(save_path +experiment)\n",
+ "else:\n",
+ " print(save_path +experiment +\"/ exists\")\n",
+ " \n",
+ "filename = experiment +\"_atm_2d_ml\" #basename of input and output file"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Process subperiod of a simulation into zonal and global mean\n",
+ "Output files are *gm.y0000_9999.nc and *zm.y0000_9999.nc."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0347*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [53.82s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0348*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [50.85s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0349*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [57.53s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0350*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [49.51s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0351*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [54.46s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0352*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [56.52s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0353*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [50.91s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0354*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [44.30s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0355*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.27s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0356*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [50.75s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0357*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.14s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0358*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.34s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0359*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [47.18s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0360*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [46.44s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0361*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [38.40s 362MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0362*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.39s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0363*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [47.57s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0364*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [46.41s 364MB]\n",
+ "cdo cat: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 91cdo cat: Processed 5968281600 values from 810 variables over 6476 timesteps [294.88s 452MB]\n",
+ "cdo fldmean: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 91cdo fldmean: Processed 1673314304 values from 45 variables over 6476 timesteps [185.01s 306MB]\n",
+ "cdo remapcon: YAC first order conservative weights from unstructured (20480) to lonlat (192x96) grid\n",
+ "cdo remapcon: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 910cdo remapcon: Processed 1673314304 values from 45 variables over 6476 timesteps [228.43s 482MB]\n",
+ "cdo zonmean: Processed 1076486144 values from 45 variables over 6476 timesteps [84.30s 323MB]\n",
+ "merging and averaging took 0:28:11.264509, 0:01:33.959139per year\n",
+ "removed temporary files\n"
+ ]
+ }
+ ],
+ "source": [
+ "startyear = \"0347\"\n",
+ "endyear = \"0364\"\n",
+ "\n",
+ "currentyear = startyear\n",
+ "\n",
+ "starttime = datetime.now()\n",
+ "for year in range(int(startyear,10),int(endyear,10)+1):\n",
+ " currentyear = str(year)\n",
+ " while len(currentyear)<4:\n",
+ " currentyear = \"0\" +currentyear\n",
+ " print(data_path +filename +\"_\" +currentyear +\"*\")\n",
+ " \n",
+ " checkFileList = glob.glob(data_path +filename +\"_\" +currentyear +\"*\", recursive=True)\n",
+ " if len(checkFileList)!=12:\n",
+ " sys.exit(\"Wrong number of files for year \" +currentyear +\"! \" +len(checkFileList) +\" files\")\n",
+ " \n",
+ " !cdo -O mergetime {data_path +filename +\"_\" +currentyear +\"*\"} {data_path +\"temp_y\" +currentyear +\".nc\"}\n",
+ "\n",
+ "\n",
+ "# merge files\n",
+ "!cdo -O cat {data_path +\"temp_y*.nc\"} {data_path +\"temp_merged.nc\"}\n",
+ "!cdo -O fldmean {data_path +\"temp_merged.nc\"} {save_path +experiment +\"/\" +filename +\".gm.y\" +startyear +\"_\" +endyear +\".nc\"}\n",
+ "!cdo -O remapcon,r192x96 {data_path +\"temp_merged.nc\"} {data_path +\"temp_remap.nc\"}\n",
+ "!cdo -O zonmean {data_path +\"temp_remap.nc\"} {save_path +experiment +\"/\" +filename +\".zm.y\" +startyear +\"_\" +endyear +\".nc\"}\n",
+ "\n",
+ "endtime = datetime.now()\n",
+ "duration = endtime-starttime\n",
+ "print(\"merging and averaging took \" +str(duration) +\", \" +str(duration/(int(endyear)-int(startyear)+1)) +\"per year\")\n",
+ "\n",
+ "\n",
+ "#remove files in SCRATCH directory\n",
+ "fileList = glob.glob(data_path +\"temp_y*.nc\", recursive=True)\n",
+ "\n",
+ "#for filePath in fileList:\n",
+ "# os.remove(filePath)\n",
+ "\n",
+ "os.remove(data_path +\"temp_merged.nc\")\n",
+ "os.remove(data_path +\"temp_remap.nc\")\n",
+ "print(\"removed temporary files\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Merge subperiods\n",
+ "Ouput files are *.gm.nc and *.zm.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "cdo mergetime: Processed 1101015 values from 180 variables over 24467 timesteps [730.82s 232MB]\n",
+ "cdo mergetime: Processed 105697440 values from 180 variables over 24467 timesteps [824.56s 266MB]\n"
+ ]
+ }
+ ],
+ "source": [
+ "#merge single files\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".gm.y*.nc\"} {save_path +experiment +\"/\" +filename +\".gm.nc\"}\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".zm.y*.nc\"} {save_path +experiment +\"/\" +filename +\".zm.nc\"}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Create monthly and yearly means\n",
+ "Output files are *.mm.gm.nc, *.ym.gm.nc, *mm.zm.nc, *ym.zm.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "cdo monmean: Processed 1101015 values from 45 variables over 25282 timesteps [109.40s 209MB]\n",
+ "cdo yearmean: Processed 1101015 values from 45 variables over 24534 timesteps [105.47s 176MB]\n",
+ "cdo yearmean: Processed 105697440 values from 45 variables over 24534 timesteps [132.00s 193MB]\n",
+ "cdo monmean: Processed 105697440 values from 45 variables over 25282 timesteps [141.59s 232MB]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# monthly & yearly means\n",
+ "!cdo -O monmean {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/\" +filename +\".mm.gm.nc\"}\n",
+ "!cdo -O yearmean {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/\" +filename +\".ym.gm.nc\"}\n",
+ "!cdo -O yearmean {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/\" +filename +\".ym.zm.nc\"}\n",
+ "!cdo -O monmean {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/\" +filename +\".mm.zm.nc\"}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optional: Merge additional subperiods \n",
+ "If the subperiod files have been deleted but the simulation is continued afterwards, this is used to merge additional subperiods into the final file. It works, but it's not recommended because it's easy to skip a time period or double it."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#merge additional single files\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".zm.y0*.nc\"} {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/temp.zm.nc\"} \n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".gm.y0*.nc\"} {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/temp.gm.nc\"} "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Remove subperiod files in work directory\n",
+ "Only do this if you're certain that the simulation will not be continued."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#remove files in WORK directory\n",
+ "fileList = glob.glob(save_path +experiment +\"/\" +filename +\"*.y0*\", recursive=True)\n",
+ "\n",
+ "for filePath in fileList:\n",
+ " os.remove(filePath)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optional: copy 3D files into work directory"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/3D\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/3D/ exists\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0291*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0292*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0293*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0294*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0295*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0296*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0297*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0298*\n"
+ ]
+ }
+ ],
+ "source": [
+ "# copy 3D files\n",
+ "startyear = \"0291\"\n",
+ "endyear = \"0300\"\n",
+ "\n",
+ "currentyear = startyear\n",
+ "filename3D = experiment +\"_atm_3d_ml\"\n",
+ "filename3Dmean = experiment +\"_atm_3d_mean_ml\"\n",
+ "print(save_path +experiment +\"/3D\")\n",
+ "if not os.path.isdir(save_path +experiment +\"/3D\"): #check if experiment folder in saving path exists\n",
+ " print(\"creating folder \" +save_path +experiment +\"/3D\")\n",
+ " os.mkdir(save_path +experiment +\"/3D\")\n",
+ "else:\n",
+ " print(save_path +experiment +\"/3D/ exists\")\n",
+ " \n",
+ "\n",
+ "for year in range(int(startyear,10),int(endyear,10)+1):\n",
+ " currentyear = str(year)\n",
+ " while len(currentyear)<4:\n",
+ " currentyear = \"0\" +currentyear\n",
+ " print(data_path +filename +\"_\" +currentyear +\"*\")\n",
+ " !cp {data_path +filename3D +\"_\" +currentyear +\"*\"} {save_path +experiment +\"/3D/\"}\n",
+ " !cp {data_path +filename3Dmean +\"_\" +currentyear +\"*\"} {save_path +experiment +\"/3D/\"}\n",
+ "\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/energyflux_icelimit_comparison-checkpoint.ipynb b/.ipynb_checkpoints/energyflux_icelimit_comparison-checkpoint.ipynb
new file mode 100644
index 0000000..eaa6eae
--- /dev/null
+++ b/.ipynb_checkpoints/energyflux_icelimit_comparison-checkpoint.ipynb
@@ -0,0 +1,1459 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Calculation of the artificial heatflux out of zonal data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_1438ppmv_atm_2d_ml_0137to0338.mm.zm.nc\n",
+ "mlo_aqua_3000ppmv_Jor2_atm_2d_ml_0258to0425.mm.zm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "\n",
+ "experiment1 = \"mlo_aqua_1438ppmv\"\n",
+ "filename1 = experiment1 +\"_atm_2d_ml_0137to0338.mm.zm.nc\" \n",
+ "data_path1 = \"/work/bb1092/pp_JH/\" +experiment1 +\"/\"\n",
+ "\n",
+ "experiment2 = \"mlo_aqua_3000ppmv_Jor2\"\n",
+ "filename2 = experiment2 +\"_atm_2d_ml_0258to0425.mm.zm.nc\" \n",
+ "data_path2 = \"/work/bb1092/pp_JH/\" +experiment2 +\"/\"\n",
+ "\n",
+ "experiment3 = \"mlo_aqua_5000ppmv_Jor2\"\n",
+ "filename3 = experiment3 +\"_atm_2d_ml_0258to0306.mm.zm.nc\" \n",
+ "data_path3 = \"/work/bb1092/pp_JH/\" +experiment3 +\"/\"\n",
+ "\n",
+ "experiment4 = \"mlo_aqua_1500ppmv\"\n",
+ "filename4 = experiment4 +\"_atm_2d_ml.mm.zm.nc\" \n",
+ "data_path4 = \"/work/bb1092/pp_JH/\" +experiment4 +\"/\"\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "print(filename1)\n",
+ "print(filename2)\n",
+ "# load netcdf file\n",
+ "DS1 = xr.open_dataset(data_path1 +filename1, decode_times=False)\n",
+ "DS2 = xr.open_dataset(data_path2 +filename2, decode_times=False)\n",
+ "DS3 = xr.open_dataset(data_path3 +filename3, decode_times=False)\n",
+ "DS4 = xr.open_dataset(data_path4 +filename4, decode_times=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# qbot\n",
+ "da1 = DS1.qbot_icecl.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "\n",
+ "da2 = DS2.qbot_icecl.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "\n",
+ "da3 = DS3.qbot_icecl.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "\n",
+ "da4 = DS4.qbot_icecl.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "\n",
+ "qbot1=da1.values\n",
+ "qbot2=da2.values\n",
+ "qbot3=da3.values\n",
+ "qbot4=da4.values\n",
+ "\n",
+ "mqbot1 = np.pi/2* np.dot(da1.values,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "mqbot2 = np.pi/2* np.dot(da2.values,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "mqbot3 = np.pi/2* np.dot(da3.values,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "mqbot4 = np.pi/2* np.dot(da4.values,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(1962, 96)\n",
+ "(1962, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<xarray.DataArray 'lat' ()>\n",
+ "array(-4.6875, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float32 0.0\n",
+ " lat float32 -4.6875\n",
+ "Attributes:\n",
+ " standard_name: latitude\n",
+ " long_name: latitude\n",
+ " units: degrees_north\n",
+ " axis: Y\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# sea ice thickness tendency\n",
+ "da1 = DS1.dhidt_icecl.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "dhidt1 =da1.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da2 = DS2.dhidt_icecl.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "dhidt2 =da2.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da3 = DS3.dhidt_icecl.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "dhidt3 =da3.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da4 = DS4.dhidt_icecl.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "dhidt4 =da4.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "\n",
+ "# sea ice cover\n",
+ "da1 = DS1.sic.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "sic1 = da1.values\n",
+ "\n",
+ "da2 = DS2.sic.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "sic2 = da2.values\n",
+ "\n",
+ "da3 = DS3.sic.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "sic3 = da3.values\n",
+ "\n",
+ "da4 = DS4.sic.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "sic4 = da4.values\n",
+ "\n",
+ "# sea ice thickness\n",
+ "da1 = DS1.sit.sel()\n",
+ "da1 = da1.assign_coords(time=((da1.time-da1.time[0])/360))\n",
+ "da1 = da1.squeeze()\n",
+ "sit1 = da1.values\n",
+ "\n",
+ "da2 = DS2.sit.sel()\n",
+ "da2 = da2.assign_coords(time=((da2.time-da2.time[0])/360))\n",
+ "da2 = da2.squeeze()\n",
+ "sit2 = da2.values\n",
+ "\n",
+ "da3 = DS3.sit.sel()\n",
+ "da3 = da3.assign_coords(time=((da3.time-da3.time[0])/360))\n",
+ "da3 = da3.squeeze()\n",
+ "sit3 = da3.values\n",
+ "\n",
+ "da4 = DS4.sit.sel()\n",
+ "da4 = da4.assign_coords(time=((da4.time-da4.time[0])/360))\n",
+ "da4 = da4.squeeze()\n",
+ "sit4 = da4.values\n",
+ "\n",
+ "#temperature\n",
+ "da1 = DS1.ts.sel()\n",
+ "da1 = da1.assign_coords(time=((da1.time-da1.time[0])/360))\n",
+ "da1 = da1.squeeze()\n",
+ "ts1 = da1.values\n",
+ "\n",
+ "da2 = DS2.ts.sel()\n",
+ "da2 = da2.assign_coords(time=((da2.time-da2.time[0])/360))\n",
+ "da2 = da2.squeeze()\n",
+ "ts2 = da2.values\n",
+ "\n",
+ "da3 = DS3.ts.sel()\n",
+ "da3 = da3.assign_coords(time=((da3.time-da3.time[0])/360))\n",
+ "da3 = da3.squeeze()\n",
+ "ts3 = da3.values\n",
+ "\n",
+ "da4 = DS4.ts.sel()\n",
+ "da4 = da4.assign_coords(time=((da4.time-da4.time[0])/360))\n",
+ "da4 = da4.squeeze()\n",
+ "ts4 = da4.values\n",
+ "\n",
+ "ice_lat1 = np.arcsin(1-sic1) * (180./np.pi) \n",
+ "\n",
+ "print(dhidt2.shape)\n",
+ "print(sit2.shape)\n",
+ "\n",
+ "mdhidt1= np.pi/2* np.dot(dhidt1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, dhidt1,levels = np.linspace(-1,1,11),cmap='RdBu')\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1.time,mdhidt1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1.time,dhidt1[:,45])\n",
+ "plt.ylim(-1.5,0.3)\n",
+ "plt.xlim(199,202)\n",
+ "plt.xticks([199,200,201,202])\n",
+ "print(da1.lat[45])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(630, 96)\n",
+ "(2412, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# points where sea ice thickness exceeds the sea ice limit\n",
+ "icelim1= np.where(sit1 + dhidt1>5) # inaccurate, because yearly mean of sea ice thickness + yearly mean of sea ice growth\n",
+ "icelim2= np.where(sit2 + dhidt2>5)\n",
+ "icelim3= np.where(sit3 + dhidt3>5)\n",
+ "icelim4= np.where(sit4 + dhidt4>5)\n",
+ "\n",
+ "\n",
+ "removed_thickness1 = np.zeros([da1.sizes[\"time\"],96])\n",
+ "removed_thickness2 = np.zeros([da2.sizes[\"time\"],96])\n",
+ "removed_thickness3 = np.zeros([da3.sizes[\"time\"],96])\n",
+ "removed_thickness4 = np.zeros([da4.sizes[\"time\"],96])\n",
+ "\n",
+ "print(removed_thickness3.shape)\n",
+ "print(sit1.shape)\n",
+ "# calculate removed sea ice thickness\n",
+ "removed_thickness1[icelim1] = sit1[icelim1] + dhidt1[icelim1] - 5\n",
+ "removed_thickness2[icelim2] = sit2[icelim2] + dhidt2[icelim2] - 5\n",
+ "removed_thickness3[icelim3] = sit3[icelim3] + dhidt3[icelim3] - 5\n",
+ "removed_thickness4[icelim4] = sit4[icelim4] + dhidt4[icelim4] - 5\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, removed_thickness1)\n",
+ "\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "fig2, ax2 = plt.subplots()\n",
+ "im2=ax2.contourf(da2.lat, da2.time, removed_thickness2)\n",
+ "\n",
+ "fig2.colorbar(im2)\n",
+ "plt.show()\n",
+ "\n",
+ "fig3, ax3 = plt.subplots()\n",
+ "im3=ax3.contourf(da3.lat, da3.time, removed_thickness3)\n",
+ "\n",
+ "fig3.colorbar(im3)\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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xlBNlE+Hxw2UxzyXsra7mpaMqsG0QRQZeCEIuALpaxlV9xYbhS13Fg8rGHPtcdybgxXRajGNppeTqKzY/sTGMIleFb1RFiBC3kPWPq1+3caVDh6LTYhwq4y6WBA+LJzbg4PGfZtkhguwbVeEbUZHHigjVT6fFOE/MQuwSsmZCbOQJnZnnmwzSdlW3vOHVlThjV6IX4xirubm6JQZdMBZbbAyiSIh93RUZrot5GV3rCNI1ohdjn4PnIuBNlMbMKOOiMIyMiU2zTJNEVgxzV3ShdoUJ8WCiF+NhtJXgEUqIzU9sDKLIf+xjGVddxBt0nZQV6nC/cm0Bb2RocsEOzBVhhGXY+VQk1sPOXx+xbqvEpvmMa6TpTh/5k8ilw3NG6Lhis4qNEDRZiL4q5rI4nCjEuGqnDx8hryvduRezio26qLqQV5UqVRC/2Oez5axtc1O0Tlf8w4YRmqLFvOxGX6XEJsTXqmmYYWZuiggYVmZzGL6RE75Ypp0RkkHJIFWsZJ/Y46oibG6Kw4lSjGOLLfYJY4PBRYEsisIISdVwt7o7g5j4DicKMa66gFenpRvCRdF7UWQXjgmxEZImfcj9rrmQBYX6Yz7j2iizgDfoYLr8ZGoiuSPDFu+MJmnbOm4qMcR8xjVSR2hbCGu5qlXczyI2jKqUKUDvYymHWNSrQl4Hxs21EYUY+4a2uVrLPlYxhO9tN715r7koDG+yAvTDBLlKtIWPlexbTGjcRLcfUYhxWZqszAZh/MVmDRt1UFaQffG1jH0Eud913RWRFpHrSbpA71TVM9NtxwG3AitJWtO9TVWfHTTOC8rsSER2isjDuW2fEZFNIvITEblDRI5Jt68Ukd+KyIPpv7/x/Q/2EiKkrQ3mVsiBf3nKttYxjH6U/XXVpEEQ8lrbsGN1dJFVfbgBOL9n2+XAd1X1VOC76fOBlLGMbwC+ANyU27YBuEJV94nIX5F0Qr0sfW2zqp5VYtyhhDgQMdah2L1q0mKMjaCEjKSo4i+uo+7x4ToQVzSFqv5ARFb2bL6ApJEzwI3APRzUyELKNCQ9bEeqenfu6b3AW4aNM4iYQttCL9rlyYTahNgISeiQtqqdQdouRF+G+fkFLrqxSEQ25p7PqOrMkM+coKrbAVR1u4gcP2wnIXzGF5H4RjJOFpEfA3uAv1TVfyz6kIisB9YDTC95YWn/UJFolznwLgWB6urkYQt3Rh34VHEbRButmVz8wy2Etu1S1TV176SSGIvIx4B9wM3ppu3AclX9lYi8AviaiJyhqnt6P5veWWYAlp5xTOHZFMpfVGdSiC3QGW2TF9ve87HJ8LYqnUDcrvW43BR9eEpElqRW8RJg57APeIuxiFxIsoK4VlUVQFX3AnvTx/eLyGbgNGBj34EGUHS3dBXouutQDEp5NowmGHTuVS0mVIam61R0JOnjTuBC4Kr079eHfcBLjEXkfBJn9B+p6nO57YuBZ1R1v4icApwKPD5sPB+fcZ0i6+Oq6CfKJtZGnfRrzdSLTzGhsr7jomsxdp9xSETkFpLFukUiMgtcSSLCt4nIxcA24K3Dxhkqxn12dAUwCWwQEYB7VfUS4DXAJ0RkH7AfuERVnxm2D5906JB+4ozQpTLbrjdrjAdZzPEwfK1kF3eFr4uiKzHFRajquj4vrXUZp0w0RdGOruvz3tuB210mUIamYg2r1KHIGOS/M4y6adsA8I2kGEGfsTOdyMDL3zXr7PxsBYGMUaMJn3ForLh8i4QuFOTrTw5hGRtGGxz0HRf7jasUoHeNO3Ytr9nLcC0wy7g2BvmMfUTap+Fo3Viih9EE+VoVoazhNjtHjxNRiPEgfFotNZ0CPSxiwrp6GHUzvzppxdRPgKtaxk2V1LR6xiOGT6+7KuUyzWdsxMIg0W2ypKZvAkg5w8vcFK2R3S1dLOQmw9oGFZG3FGijCTKfcb9Y4xAuC5/MvBBuwnFxeXRCjH39xm37i81PbDTFMDdFSKoWEsozLkJbhijEOIa2S3X0ustKZc6vXmbWsVErw6IpMqqKdQjfsQlwMVGIcVE0RZNdPerudWdCbDRFHdEUeUJYxYOu0XEW6ijEuA7L2AWLLzZGgeymP8h3XJW6oyradi22SRRiHBJfX3FIQc5bJNObgwxpGCOHrxW8NfA8YiEKMe6X9OFrLfuEthmGMZyqMcfj7IYYRhRi3EuTve/MPWEYbhRdM2UFukoB+lEnKjGOpQ+eL70LdxbaZowDo9onr2miEuMqroreA1tnz7t+WCF5YxwItYjXe42OuzhHIcZtdIc294QxyiS/yuoJcfPtkTfuYjuMKMS46gKeT5W2KrUohjG3QpjaqgeSPgyjSbLOH1nMcW+9ivwvtyY6R/uKcL+iQVYoqEbaiDM2y9gYZQbFHFexlKvWp3AR5v6aEFehIBH5z8B/BBR4CHiPqj7vOk4pMRaR60k6Qe9U1TPTbccBtwIrgS3A21T1WUma4n0eeAPwHPBuVX1g0PghQ9vKxhn3nkxVqrUNy8AzjFHC6hsfRESWAn8GvFRVfysitwFvB25wHausZXwD8AXgpty2y4HvqupVInJ5+vwy4PUkXaFPBV4FXJv+7Utoy9gn8cPHbTHIwrBqbUYMZDUrpjcTrJCQr8/YhyIjLUI3xQLghSLyO+Ao4EnfQYaiqj8QkZU9my8g6RoNcCNwD4kYXwDcpKoK3Csix4jIElXd7jPBsrTdCdrKZhoxkXWL7nVRVCkyX4Uq9Y0j6By9SEQ25p7PqOoMgKo+ISJXA9uA3wJ3q+rdPjup4jM+IRNYVd0uIsen25cCv8y9bzbddogYi8h6YD3A5PFTFaaR0HbJzENP8ElYtco6fBjRULSA16Qoh17Eq4rMi4tBtktV1xSOI3IsiQF6MvBr4O9F5B2q+neuc6pjAa/oCB/mRE3vLDMAU6efWNnJ2oRbwoXFd1lRCqM9ehfw8gIcSoRdUqPDLuJFtYD3WuAXqvo0gIh8Ffg3QKNi/FTmfhCRJcDOdPsscFLufcvw9KGUoekY4zKLcxbOZsRGkQBXsZDrjjEeZBFH5jPeBvyhiBxF4qZYC2wc/JFiqojxncCFwFXp36/ntl8qIl8mWbjbPcxfXKWecdFBHibQ+RPJVZgtcsLoIoPOUx8/sk9PPF+LOAKfcV9U9T4R+QrwALAP+DHpL35Xyoa23UKyWLdIRGaBK0lE+DYRuZjk7vDW9O3fJAlre4wktO09PhPz6Qqd0YT/2ETYiJmsDROE9w3XUVQ+o0iwD9eBqNwUqOqVJJpYibLRFOv6vLS24L0KvN9lEqFC29qOqDCMWJjYNMviTVlURdjeeFZGsx6iyMCrShtRFMPaoRtGTISOoKjSfskqthUzEmLsSl0W8d7l8+xdDjDJNNaE1IiLNuKL++EbXTHKjIQYuxYKCpEKXcTBccw6NkYTFys4ZARFnsiiKYIxEmIM8fmLzSo2YiK0e6KMKLtav12JoKiLzohxKL9wE4t2FmdsxEJWmyJ0bWOf0LYyZKI9eEE/rmiKUHRGjKvSZOTE7lXmMzbiIqttHJIqi3gZ5i8+SGfEeNhBqzPRo+yYU1vV6lEYUZGPN66DOn3IefJuC/MZR0Qs/uH8uJkQmwgbMVJHJIVPSFuGT/W2g5iborOEbDpqGF2jTD88nzhkn+SPEBEWZhm3TNUFvDrcFHDwJDar2IiVvJsidFKSq9/YtSN0B6q2BSMKMe7Xdiljw47Vpe+oZeOMXQXZMuuMLpJFU+QFOQaXhS3cHU4UYhyiNoVPPeNQLZYSLILCiI+iBbwq3aEzmhZfW8DrAC4iHNpvnD8hp7YeGXRsw2gC35oVrn3wfOtRjFPyR2fFOBYRzphbIUxbcw8jMppyU5TBNfEDzGfcCbID5lKLInwNioQkrO35IGMbRmiKBDkUIRI/8oyzLzkKMc4W8Hz8xi6F5OsIccv738xfbMRGnUXm81gGXnWiEGPXBbw2u0DnsbA2o0v4tFcqi2/Bed/uH6NIFGLcVQ6e2JOwapWJshE9mSAPCtX0FezeX50+4txV4RWRY4C/Bc4kqaF7kar+s8sY3mIsIqcDt+Y2nQL8V+AY4L1A9q1+VFW/6bufIlz8xb2EdlWYdWzETJ3+4gyLMQbg88C3VPUtIjIBHOU6gLcYq+rPgLMAROQI4AngDpIGpJ9T1at9x+4lhFsitACb+BpdIPMZ91q7bXb9cLmeuyDcInI08Brg3QCqOg84/ywI5aZYC2xW1a0i7ge5KAMv70MOkX0XsrvH3AphbsVCOPdfsux7z5soG2NJGYs4lJi2nPSxSEQ25p7PqOpM7vkpJJ6A/yUifwDcD3xQVf+fy05CifHbgVtyzy8VkXcBG4EPq+qzvR8QkfXAeoDJ46cGLuCFXrALYSVberTRBbIu0YvpbyXXSahed6Grth0x73QN71LVNQNeXwC8HPiAqt4nIp8HLgf+i8ucKotx6h95E3BFuula4JMkTuxPAtcAF/V+Lr2zzAAsPeMYzd/5eoW5zEFsMsLC/MRG15hfvezA4xCdon0jJ7rgdvBgFphV1fvS518hEWMnQljGrwceUNWnALK/ACLyReAbrgMOEuZ+9B7ksi4LHys5O4nnVixkatUqwITZiJc6Yo2HXTf9xDqWsNSQqOoOEfmliJyerqWtBX7qOk4IMV5HzkUhIktUdXv69M3Aw8MGqFIoyOfgVnVThM7oM4y6yFvEmRCHiCgKkW0Hfq6LrUH2HJwPADennoLHSQIZnKgkxiJyFHAe8L7c5k+LyFkkbootPa8Fw/cO63sS9jv5zCI2YiY7NxdvgunUQp7aeiRzK/zGCyXC0I1IibKo6oPAIL/yUCqJsao+B/yLnm3vrDImVP8pE8Ji7XfS9bZaMowuUGQh+xC6FoVxkCgy8HprU/jcMfMCXuYkGSbYriUCDSNmJjbNHhDkUGnRg64hn64f404UYtxkbQpXq9n8wsYoUMYyriLSTRYKitRnXJkoxLgsTdYwHuaCyJ+086utw4cRN5llPEhsmxDisuI7qKi8dfqIgKID2U+gy/h8B1HmxEzeM8n05r0myEYnWPa95xtP/MjT73rtvbYH/1K24vJR4lLPGMIWCsqs592rJtN26IYRN7PnLgw+ZohFPfMfd1SM24gt7kcmwmYVG12g1zKuo+GC4UcUYpwvFFRmIc8l2y6jzpPOhNjoClkmXrZYF+qaaLKMpi3g1ciwaIomoyfKYLUpjC5Th7/Yp1t0nlFKAPElCjGuk5ClMzPyHT6msYU7w8jw7fZhPuOOiHGIesYZId0VB6IpSGI4TZSN2GkiiqLulGlzU0RK2Ttqfb6xCSy8zegK+fj5kMJcd6H5lovLN0InxTiWnzST2yaY2qosvmtz21MxDCdCW8hlukO71jMelPgxinRSjF0IvYDXWyjI4ouNrtGF/ncrlz09YFHfkj6iwSXRo44FPMPoMqEKBVXFIigOpZNiDH6xxqHIW8TmIzYMP2JxN8ZCZ8U4o40DavHFRlepwyKuo1DQICyaoiWarNQ2DCsmb3SdEM1Ie3FJ+Bh0PY+72yJ6Me53gIoO6rCToapYz60QprZqUhjIYouNjjGxaZbFWYDCn6yKwm8MoyHCInIEsBF4QlXf6DNGZTEWkS3AHLAf2Keqa0TkOOBWYCVJH7y3qeqzVfeVJzuATbopErFPBH1uxcLEd2wZeEZHeDoV4OQ8/l3he1wNlqZdFBHzQeBR4GjfAUJZxn+sqrtyzy8HvquqV4nI5enzywLtC/ATYZ+uzv1OtmwRz4TY6ArJovMkmUGRP7d9fzWGclF0GRFZBvwJ8Cngz33HqctNcQFwTvr4RuAeHMQ4xEEL5T8eVKs1c1eYIBtdYGLTbOpemzxQsa1qeYA2LOMWFvAWicjG3PMZVZ3JPf9r4C+AqSo7CSHGCtwtIgr8z3SSJ6jqdgBV3S4ix/d+SETWA+sBJo8/9P8w7KCVrUFRRJUTL//ZzH9sGF3igN84dVlUNVpcCsvHVKntiOedErZ2qeqaohdE5I3ATlW9X0TOqTKnEGJ8tqo+mQruBhEplcOYivYMwNTpJ9amaqG7eoAVlDe6z/TmvUxvJmgLpjIp0XmGGVUd8TGfDbxJRN4ALASOFpG/U9V3uA5UWYxV9TW5rLgAAAySSURBVMn0704RuQN4JfCUiCxJreIlwM6q+8loy++UP2GzxTtWrTK/sdFJsgalGaEyVV0FuR8dEWJU9QrgCoDUMv6IjxBDRTEWkRcBL1DVufTx64BPAHcCFwJXpX+/XmU/eVwz70J3+LDC8sYoML962YGuH3lCXCtVBLkrIlwHVS3jE4A7RCQb60uq+i0R+RFwm4hcDGwD3lpxP4W41qcIWVh+bsVCpswyNjpKPuZ4OifMcyuqj+0jxKMgwqp6D0mwgheVxFhVHwf+oGD7r4C1VcYug2usse9PsaLP2eKdMQpkFnJVv3GTPfBGlegy8EL6hOsIbwMrFGR0n/lDrOHqC3g+i3cmyIcSnRj7HKB+Al5HeFvG7lWTVsvY6Dwx1jYeV5GOTozL0Fa36Gwx0BqSGqPAwYy8cNaxD71G06hm6g2jk2LsUlw+dCW30NEZhtEGvaFtoakzM89KaEZAlXoUUF2Ys8+bz9joOv1C23rxbWDqUrPCSOiUGFelilWbD49LTsrkRDY3hdFFstC2TJT7tWKq6r4o26h0EOPiQ45CjOfnF0QZRVE0plVrM0aJrHhQJsh1MLX1yEqf/w0vCTSTuIlCjCcm9gXraVenP9dii41R4eme4vIhEqMaS/a4zv0jXSAKMS7C5SDlhbvObh/5KAqrS2EYh1J0bVV1UYwT0YpxGdroj2duCmMUmN68l7kVC2vfT6jCQeNAZ8TY5w5qIWiG0Z/8ol1d10pIIc5+LVtoW8vk3RZtFAjqZX61RVEY3aW360eIEppVhHdcIiYG0RkxjoUsrM1SoY2ukxfkrC9eFVy6foAJcC/RiXFoh765Kgyjecpcd9u3LQUsMSQjOjF2vVuWKS6fEVKYs2akYFl4RnfJrON8CyYXl0UoIXW57s1nHCFlrOi6LWMTYqPLFNUzdrlmfMLZ8pir4iCdFeMYFvEMo8uELBRUVoB9xfe8Ew/2Of6+1wjx01kx9u3yUYerwqxjo2tkQhyqO3TvddVPnH3rUGzYsTr37C6nudWNiJwE3AScCPwemFHVz7uO4y3G/SYgIh8H3gtk3+pHVfWbg8Y6esHzzvtvKuGjt2pV/rlFVBhdJpQQ5xnT9kv7gA+r6gMiMgXcLyIbVPWnLoNUsYwLJ5C+9jlVvbrsQHv2uWUCuUZc+FrFvbUoimpTmFVsdJGsattiDrWS+1FWtMtayBn5a7mrwqyq24Ht6eM5EXkUWAo0I8YDJuBFLFXbyhQDsk4fRtcJ3QMvz5haxwCIyErgZcB9rp8N4jPumcDZwKUi8i5gI4n1/GzBZ9YD6wEmj5+Kpvdd/sTMhLl3mxWXN7pOvp5xloUXiirWcS91CbU8P+9y7S4SkY255zOqOnPYmCIvBm4HPqSqe1znVFmMeycgItcCnwQ0/XsNcFHv59L/zAzA1OknetWmdGm/BO7F5fudoFYoyDAG4xt/HKmVvEtV1wx6g4gcSaKDN6vqV312UkmMiyagqk/lXv8i8I0q++jFCgYZRnhCRxu5WscZvdd3pOJ8CCIiJFWWH1XVz/qOUyWaonACIrIk9ScDvBl42HcfeepsQNrrJx70k21uhTC92XkXhhEdvXHGMVZu60i947OBdwIPiciD6bahUWS9VLGMCycArBORs0jcFFuA9w0bKGTbJZ8+d67+stlzFzKVFpcH8xsb3SQ7bw8WCxrsLXS9TurKxIstHVpV/wmo7HSvEk3RbwJOdwMobrtUliIRr7Pbhy3eGaNEUTp0KMoWlu+CK6IJos/Aq2Ix1/Wza/cqK6FpjD4u7rt+hOgODeMh2NGLsWvac91YHzxjlOhN/hiU+JHvDFIH4yC4g4hejDN8RLmu8pmGMSrU6abIKOuuGIVsvCp0RowzXGOLM3wW9oqwhqTGKHFot4/w2Xi+xPJLuEk6J8bQviAbxqhQl2VcZ03j2KIpQtEpMW4z4SNbzLCFO2OUmNg0C6tWtbLvcXRFDCJKMW4rgqJfkaC5FXLowh1YyyVjZEgMjLBuijIdQHyu81EW8KjEOISfqErL8aIiQb2PMyy8zRhFqkRM1NXtI9/lA6zTRyOEbkYK/hEVvYXke7fZIp4xCgzzGRdVLuxH1W4f5bp8QGydPkIRlRi7Umfrpd4OH0XMr7ZaxsZo42Ml190Pb1TplBg36UvudxIWWcyG0VUGLeCVMUiqkF3PJsoJnRLj3oPWZixi5jM269joOv0W8HwFuGySR4aJckKnxDjPOAaFG0adVLV+64wtHgc6Kca+CR8QLu7YKrcZo4rvtZK93zX1OWPcBbqTYpw/aD6doi0LzzAOJXNVzK2QyteHq5sCTIihY2JcZ7cPwxhH6kqHzl+DvpbyuNEpMS4byuab+FFm9diKyxvGcHxaLZW1jq02RUvEEM5WhAmxYRyOdfbwpzYxFpHzgc8DRwB/q6pX9XtviB54zTVTnAAmWbyp6N2G0S2yOON8GnSVdZUyWXijtnjnonWDqEWMReQI4L8D5wGzwI9E5E5V/WnR+3t74FWJloAwwlzk6khcFM9XHtswYuJgjZXJQwS5l2HX1Tgu2rlq3SDqsoxfCTymqo8DiMiXgQuAUhOsmtxRNYytvxBbPQpj9OjtEr13+aGvl72O+r3PpUZFBwW6ktblqUuMlwK/zD2fBV6Vf4OIrAfWp09/8/3XXvOzwHNYBOwKPGYIbF7liXFOEOe8qs9pB3APcF2A2RzEaV4lF+dWeM7lAHv2Pf3tb+34H4tKvn2hiGzMPZ9R1Zn08VCtK0tdYly0EnZIQYf0PzNT8L4wExDZqKpr6hrfF5tXeWKcE8Q5rxjnBPHOS1XPDzTUUK0rywsqTqQfs8BJuefLgCdr2pdhGEZbBNO6usT4R8CpInKyiEwAbwfurGlfhmEYbRFM62pxU6jqPhG5FPg2SbjH9ar6SB37GkBtLpCK2LzKE+OcIM55xTgniHdeQQipdaJqtXkNwzDapi43hWEYhuGAibFhGEYEjJwYi8itIvJg+m+LiDyYbl8pIr/NvfY3Dc/r4yLyRG7/b8i9doWIPCYiPxORf9vgnD4jIptE5CcicoeIHJNub/W7Sudwfvp9PCYilze9/3QOJ4nIP4jIoyLyiIh8MN3e91g2OLctIvJQuv+N6bbjRGSDiPw8/Xtsg/M5Pfd9PCgie0TkQzF8V11hpH3GInINsFtVPyEiK4FvqOqZLc3l48BvVPXqnu0vBW4hyeR5CfAd4DRV3d/AnF4HfC9dhPgrAFW9LILv6gjg/5JLMQXW+aSYVpzHEmCJqj4gIlPA/cC/B95GwbFseG5bgDWquiu37dPAM6p6VXoDO1ZVL2thbkcAT5AkP7yHlr+rrjBylnGGiAjJRXNL23MZwgXAl1V1r6r+AniMRJhrR1XvVtV96dN7SWIkY+BAiqmqzgNZimmjqOp2VX0gfTwHPEqScRUrFwA3po9vJLlxtMFaYLOqjmq1y1oYWTEGXg08pao/z207WUR+LCLfF5FXtzCnS1OXwPW5n5BF6ZRtXPAXAf8797zN7yqW7+QA6a+FlwH3pZuKjmWTKHC3iNyflhYAOEFVt0NyIwGOb2FekMTa5o2gtr+rTtBJMRaR74jIwwX/8tbTOg49IbYDy1X1ZcCfA18SkaMbnNe1wCrgrHQu12QfKxgqmO+ozHclIh8D9gE3p5tq/66GTbtgW2v+NBF5MXA78CFV3UP/Y9kkZ6vqy4HXA+8Xkde0MIfDkCTx4U3A36ebYviuOkH0xeWLUNXXDnpdRBYAfwq8IveZvcDe9PH9IrIZOA3YWDhIDfPKze+LwDfSp7Wmjpf4ri4E3gis1XQBoYnvagjRpNOLyJEkQnyzqn4VQFWfyr2eP5aNoapPpn93isgdJK6dp0RkiapuT/3dO5ueF8nN4YHsO4rhu+oKnbSMS/BaYJOqHqh3KSKL04UFROQU4FTg8aYmlF4cGW8GHk4f3wm8XUQmReTkdF4/bGhO5wOXAW9S1edy21v9rogknT5dd7gOeFRVP5vb3u9YNjWvF6ULiojIi4DXpXO4E7gwfduFwNebnFfKIb9I2/6uukQnLeMS9PqsAF4DfEJE9gH7gUtU9ZkG5/RpETmL5Of2FuB9AKr6iIjcRlL/dB/w/iYiKVK+AEwCGxLd4V5VvYSWv6tI0ukBzgbeCTwkaYgk8FFgXdGxbJATgDvSY7YA+JKqfktEfgTcJiIXA9uAtzY5KRE5iiQCJv99FJ73xuGMdGibYRhGVxhVN4VhGEanMDE2DMOIABNjwzCMCDAxNgzDiAATY8MwjAgwMTYMw4gAE2PDMIwI+P+g/M7P/xW1FgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.colorbar.Colorbar at 0x2b763088b588>"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#physical constants from icon\n",
+ "alv = 2.5008e6 # [J/kg] latent heat for vaporisation\n",
+ "als = 2.8345e6 # [J/kg] latent heat for sublimation\n",
+ "alf = als-alv # [J/kg] latent heat for fusion\n",
+ "rhoi = 917.0 # density of sea ice [kg / m**3]\n",
+ "\n",
+ "#calculate energy flux from the freezing of removed sea ice thickness, dhidt = F/(alf*rhoi) <-> F=dhidt*alf*rhoi\n",
+ "\n",
+ "energy1 = np.zeros([da1.sizes[\"time\"],96])\n",
+ "energy1 = removed_thickness1 * alf * rhoi / (60 * 60 * 24 * 30) # Joule per second per m^2 -> Watt per m^2\n",
+ "\n",
+ "energy2 = np.zeros([da2.sizes[\"time\"],96])\n",
+ "energy2 = removed_thickness2 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "energy3 = np.zeros([da3.sizes[\"time\"],96])\n",
+ "energy3 = removed_thickness3 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "energy4 = np.zeros([da4.sizes[\"time\"],96])\n",
+ "energy4 = removed_thickness4 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, energy1)\n",
+ "\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "fig2, ax2 = plt.subplots()\n",
+ "im2=ax2.contourf(da2.lat, da2.time, energy2)\n",
+ "\n",
+ "fig2.colorbar(im2)\n",
+ "plt.show()\n",
+ "\n",
+ "fig3, ax3 = plt.subplots()\n",
+ "im3=ax3.contourf(da3.lat, da3.time, energy3)\n",
+ "\n",
+ "fig3.colorbar(im3)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "fig4, ax4 = plt.subplots()\n",
+ "im4=ax4.contourf(da4.lat, da4.time, energy4)\n",
+ "\n",
+ "fig4.colorbar(im4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.5107632826463103\n"
+ ]
+ }
+ ],
+ "source": [
+ "#global mean flux \n",
+ "msit1 = np.pi/2* np.dot(sit1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "msit2 = np.pi/2* np.dot(sit2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "msit3 = np.pi/2* np.dot(sit3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "msit4 = np.pi/2* np.dot(sit4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "msic1 = np.pi/2* np.dot(sic1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "msic2 = np.pi/2* np.dot(sic2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "msic3 = np.pi/2* np.dot(sic3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "msic4 = np.pi/2* np.dot(sic4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "mts1 = np.pi/2* np.dot(ts1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "mts2 = np.pi/2* np.dot(ts2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "mts3 = np.pi/2* np.dot(ts3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "mts4 = np.pi/2* np.dot(ts4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "\n",
+ "\n",
+ "#energy1 * np.cos(np.radians(da1.lat))\n",
+ "menergy1= np.pi/2* np.dot(energy1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "menergy2= np.pi/2* np.dot(energy2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "menergy3= np.pi/2* np.dot(energy3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "menergy4= np.pi/2* np.dot(energy4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "ymenergy1=np.zeros(int(menergy1.shape[0]/12))\n",
+ "ymenergy2=np.zeros(int(menergy2.shape[0]/12))\n",
+ "ymenergy3=np.zeros(int(menergy3.shape[0]/12))\n",
+ "ymenergy4=np.zeros(int(menergy4.shape[0]/12))\n",
+ "\n",
+ "ymsic1=np.zeros(int(msic1.shape[0]/12))\n",
+ "ymsic2=np.zeros(int(msic2.shape[0]/12))\n",
+ "ymsic3=np.zeros(int(msic3.shape[0]/12))\n",
+ "ymsic4=np.zeros(int(msic4.shape[0]/12))\n",
+ "\n",
+ "for y in range(0,int(menergy1.shape[0]/12)):\n",
+ " ymenergy1[y] = np.mean(menergy1[(y*12):(y*12)+11])\n",
+ " ymsic1[y] = np.mean(msic1[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy2.shape[0]/12)):\n",
+ " ymenergy2[y] = np.mean(menergy2[(y*12):(y*12)+11])\n",
+ " ymsic2[y] = np.mean(msic2[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy3.shape[0]/12)):\n",
+ " ymenergy3[y] = np.mean(menergy3[(y*12):(y*12)+11])\n",
+ " ymsic3[y] = np.mean(msic3[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy4.shape[0]/12)):\n",
+ " ymenergy4[y] = np.mean(menergy4[(y*12):(y*12)+11])\n",
+ " ymsic4[y] = np.mean(msic4[(y*12):(y*12)+11])\n",
+ "\n",
+ "\n",
+ "print(ymenergy4[-1])\n",
+ "\n",
+ "\n",
+ "# sea ice latitude\n",
+ "ice_lat1 = np.arcsin(1-msic1) * (180./np.pi) \n",
+ "ice_lat2 = np.arcsin(1-msic2) * (180./np.pi) \n",
+ "ice_lat3 = np.arcsin(1-msic3) * (180./np.pi) \n",
+ "ice_lat4 = np.arcsin(1-msic4) * (180./np.pi) \n",
+ "\n",
+ "yice_lat1=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "menergy1m=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "msit1m=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "yice_lat2=np.zeros(int(ice_lat2.shape[0]/12))\n",
+ "yice_lat3=np.zeros(int(ice_lat3.shape[0]/12))\n",
+ "yice_lat4=np.zeros(int(ice_lat4.shape[0]/12))\n",
+ "\n",
+ "for y in range(0,int(ice_lat1.shape[0]/12)):\n",
+ " yice_lat1[y] = np.mean(ice_lat1[(y*12):(y*12)+11])\n",
+ " menergy1m[y] = np.mean(menergy1[(y*12):(y*12)+11])\n",
+ " msit1m[y] = np.mean(msit1[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat2.shape[0]/12)):\n",
+ " yice_lat2[y] = np.mean(ice_lat2[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat3.shape[0]/12)):\n",
+ " yice_lat3[y] = np.mean(ice_lat3[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat4.shape[0]/12)):\n",
+ " yice_lat4[y] = np.mean(ice_lat4[(y*12):(y*12)+11])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "5.877783718381085\n",
+ "-0.002561321\n"
+ ]
+ }
+ ],
+ "source": [
+ "\n",
+ "\n",
+ "#plt.plot(da1.time,menergy1)\n",
+ "#plt.plot(da2.time,menergy2)\n",
+ "#plt.plot(da3.time,menergy3)\n",
+ "plt.plot(ymenergy1)\n",
+ "plt.plot(ymenergy4)\n",
+ "plt.plot(ymenergy2)\n",
+ "plt.plot(ymenergy3)\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "#plt.title(\"hice_5m: heat flux from removed ice\")\n",
+ "plt.title(\"\")\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"qbot_removed [W/m²]\")\n",
+ "plt.xlim(0,210)\n",
+ "plt.ylim(0,8)\n",
+ "plt.savefig(\"plots/heatflux_comparison.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.plot(da1.time,-mqbot1)\n",
+ "plt.plot(da2.time,-mqbot2)\n",
+ "plt.plot(da3.time,-mqbot3)\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.title(\"hice_5m heat flux at ice-ocean interface\")\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"qbot [W/m²]\")\n",
+ "plt.show()\n",
+ "\n",
+ "print(ymenergy2[-1])\n",
+ "print(ice_lat2[-1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[9.97476504 9.95405141 9.91329416 9.85666766 9.78738901 9.70786213\n",
+ " 9.61864082 9.5195548 9.41147772 9.29436578 9.16798005 9.03156576\n",
+ " 8.88439149 8.72548441 8.55926759 8.38940794 8.21621948 8.037763\n",
+ " 7.8515717 7.65525129 7.44725733 7.22527701 6.98781972 6.73510113\n",
+ " 6.46956634 6.19633454 5.92231988 5.65367407 5.39498701 5.14938465\n",
+ " 4.91887989 4.70132238 4.49178427 4.28434979 4.07285187 3.85964338\n",
+ " 3.0176455 0.23082593 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0.29442812 2.75719823\n",
+ " 3.84660383 4.05760446 4.26950946 4.47652428 4.68492956 4.900759\n",
+ " 5.12918388 5.37283742 5.63050608 5.89908285 6.17299601 6.44550724\n",
+ " 6.71064504 6.96331186 7.20101106 7.42327846 7.63115569 7.82682259\n",
+ " 8.0123467 8.19025323 8.36338272 8.53355504 8.70095354 8.86200317\n",
+ " 9.0113924 9.15081557 9.28159445 9.40375439 9.51690881 9.62097496\n",
+ " 9.71453295 9.79837862 9.8704476 9.92841808 9.97077964 9.99313491]\n",
+ "(96,)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b7630986ba8>]"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# time means\n",
+ "\n",
+ "tenergy2= np.mean(energy2[0:160*12,:],axis=0)\n",
+ "print(tenergy2)\n",
+ "print(np.shape(tenergy2))\n",
+ "\n",
+ "plt.plot(da2.lat,np.squeeze(tenergy2))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b76304a5898>]"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# co2 equivalent of artifical heat flux\n",
+ "alpha = 5.35\n",
+ "mco21 = 1438 * np.exp(menergy1/alpha)\n",
+ "mco22 = 3000 * np.exp(menergy2/alpha)\n",
+ "mco23 = 5000 * np.exp(menergy3/alpha)\n",
+ "mco24 = 1500 * np.exp(menergy4/alpha)\n",
+ "\n",
+ "mco21r = np.exp(menergy1/alpha)\n",
+ "mco22r = np.exp(menergy2/alpha)\n",
+ "mco23r = np.exp(menergy3/alpha)\n",
+ "mco24r = np.exp(menergy4/alpha)\n",
+ "\n",
+ "plt.plot(da1.time,mco21)\n",
+ "plt.plot(da4.time,mco24)\n",
+ "plt.plot(da2.time,mco22)\n",
+ "plt.plot(da3.time,mco23)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(630,)\n",
+ "(630, 96)\n",
+ "(630,)\n",
+ "0.9916648749327626\n",
+ "0.9420278794069241\n",
+ "0.9797683783641139\n",
+ "(0.0, 1.0)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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9hBBXpeakMv/7+aTmuH57fGkxuMn58+eZNWsWJSUllJaWMn36dCZMmEDPnj255557eP755+nfvz9z584FYO7cufzyl7+ka9euhIWF8cknnwA152ro0aMHy5Yt4+GHHyY6Opp58+bZ719drgZHhIaG0rNnTw4fPlzlh7uN2Wy2tzomT57MDz/8QN++fVFK8frrr9O2bVt7WlGbHTt28NFHHxETE0O/fv0AePXVV7ntttucqqMQzd0bu99g29ltACy+eXEtpZ1TL/kYXKm55mNIS0tjwoQJHDx4sNK56nI1uNq+fft48MEHSUhIcMv1m8PvUYhrlZqTyhu732DBoAV0Cu5U+xsqaHD5GETj98477zBjxgz+/Oc/13dVhGiWQnxCGNR2ECE+IS6/dq1dSUqpMAeuU2pNviPqSFRUVJWtBag+V8O1yszMZMyYMZWOb9u2jZYt3ZcjWwhRPdt0VcDlg9COjDGcs37VNDXFE2iYyZfFz9ayZUuSk5PruxpCiDLqexO9I1rrSnkUylJK7XVRfYQQQjigvqerOjLX0bn5kEIIIRqsWgOD1rrAFWWEEEI0DrUGBqVUkivKCCGEcJ363kSvh1Jqfw1fBwD3TphvpKKiouwLuWJjLdOFs7KyGDt2LNHR0YwdOxaj0fJL1Vrz2GOP0bVrV/r06UNS0tVYu2zZMqKjo4mOjravjm4ooqKiuHTpksPl8/LyuP322+nevTu9evXiueeec2PthGi66ju1Z3cHyjTOBAF1YNOmTeUWmi1cuJAxY8bw3HPPsXDhQhYuXMhf/vIX1q9fz/Hjxzl+/Di7du1i3rx57Nq1i6ysLF566SUSExNRSjFw4EDuuOMOQkNdm/y7LtgWU/7mN78hLi6OoqIixowZw/r16xk/fnw9106IxsWds5IcGWM45cBXustrVsfMRiOZ77+P2ej6ZllZZfMuVMzHcN9996GUYujQoWRnZ3P+/Hn++9//MnbsWMLCwggNDWXs2LF8++23gCV72tNPP82AAQMYM2YMGRkZAIwePZonnniCYcOG0bt3b/vK5BdffJFZs2Zxyy23EBUVxapVq3jmmWeIiYlh3LhxFBcXs379eqZPn26v7+bNm5k4caJDz/bmm2/Su3dvevfuzT/+8Q/AsqaiR48ezJ8/nwEDBpCRkUFcXBwA3t7eDBgwgPT0Rv+fjxB1zjYrKdTX9X8kyspnq5xVq7j4xl/JKZOL4OdSSnHLLbcwcOBAlixZAsCFCxdo164dAO3atePixYsA1eZdqCkfg8lkYsCAASQlJTFq1CheeuklezmTycTOnTtZvHgxc+bMsR9PSUlh3bp1rFmzhpkzZxIXF8eBAwfw8/Nj3bp1jB07lvj4eEwmE+B4PoY9e/bw4YcfsmvXLuLj43nvvffYu9cyi/nYsWPcd9997N27l+uuu87+nuzsbL766qsqF88JIWpW32MMKIuOtZdsvIKnTKH1gt8Q7MJtoHfs2EFSUhLr169n0aJFbN26tdqy15KPwcPDw/6hXV0+hpEjR3L58mX7Tq/jx4/Hy8uLmJgYSkpKGDduHAAxMTGkpaVhMBgYN24cX331FWazmXXr1tl3gK3J9u3bmTx5MgEBAQQGBjJlyhS2bbNs8HXdddcxdOjQcuXNZjMzZszgscceo3PnzrVeXwhRXn2PMaC11kqp1cBAl9eggTCEhtLSutOpq9jyJrRu3ZrJkyeTkJBAmzZtOH/+PO3ateP8+fO0bt0aoNq8CxEREWzevLnc8dGjR1d5v+pyMJT9uWw+Bi8vr3JBpmw+hkWLFhEWFsagQYMICgqq9VmdyccA8NBDDxEdHV0uu5wQwnH1OsZQRrxSapDLa9BEmUwmrly5Yn+9YcMGevfuXS7vQsV8DMuXL0drTXx8PMHBwbRr145bb72VDRs2YDQaMRqNbNiwgVtvvRWA0tJSe26Hjz/+uMp8DNu3byc4OJjg4GCH6z569GiSkpJ47733nMrHsHr1avLy8jCZTHz55ZeMGDGiyrLPP/88OTk59nEIIYTz3DnG4Ew+hjjgYaXUKcCEZe8krbXu48iblVK+wFbAx3rfz7XWf6xQxgdYjqVlkgncrbVOc6KODcaFCxeYPHkyYOk2uffeexk3bhyDBg1i+vTpvP/++0RGRrJy5UoAbrvtNr755hu6du2Kv78/H374IQBhYWG88MILDBpkicl/+MMfCAuz7GsYEBDAoUOHGDhwIMHBwfZgAJacCsOGDePy5ct88MEHTtXd09OTCRMmsHTp0lqnx9pyMgwYMID777/fnr/hgQceoH///pU29EtPT+eVV16he/fuDBgwAIBf/epXPPDAA07VUQjhRlprh76A66r6cuL9Cgi0vvYCdgFDK5SZD7xjfX0P8Glt1x04cKCu6PDhw5WONUUBAQFVHh81apTevXu32+9/8eJF3b59e7ddv7n8HoW4FskXkvXEVRN18oXka3o/kKir+Vx1uCtJVzNV1Yn3a611rvVHL+tXxY7pOwHbn6ifA2OUIwmHRZ1bu3YtI0aM4LXXXqvvqgjRLL2w4wVSL6fywo4XXH5tp1J7KqX6AraO421a631Ovt8T2AN0BRZprXdVKNIBOAOgtTYrpXKAlsClCtd5CHgIIDKy+e72nZubW+XxsoPVrjJkyBAKCwvLHVu5ciUxMTEuv5cQonbz+87nDzv/wPy+811+bYcDg1LqceBBwDbR/99KqSVa6//n6DW01iVAP6VUCPClUqq31rpstpmqWgeVprtorZcAS8CS2rOae1WamSOu3a5dFWO4e+lGnnJWCHdbe3It+SX5rD25lnGdx7n02s60GOYCQ7TWJgCl1F+AHwCHA4ON1jpbKbUZGAeUDQzpQEcgXSllAIKBLGev7+vrS2ZmJi1btpTg0AhprcnMzMTX17e+qyJEg7Vg0IJy313JmcCgKL8nUgk1Z3Ur/2alwoFia1DwA24G/lKh2FpgFpaAMxXYqK/hT8eIiAjS09PtW0SIxsfX15eIiIj6roYQDVan4E4svnmxW67tTGD4ANillPrS+vMk4H0n3t8OWGYdZ/AAPtNaf62UehnL6Pha6/U+UkqdwNJSuMeJ69t5eXnRqVOna3mrEEI0CsYCI6tPrGZS10kuX8vgTGBoC8wGhmNpKczGiQ9urfV+oFKKUK31H8q8LgCmOVEnIYRolmxbYgAuT/HpTGAYq7V+FrAnClBKLQOedWmNhBBC1MqdW2LUGhiUUvOwLDzrrJTaX+ZUELDD5TUSQghRK9uWGO7gSIvhY2A98BpQNt3WFa210zOGhBBC/HxZpiJWJp5hWmxHwgK8XXrtWgOD1joHyAFmuPTOQgghrtnKxDO8tv4oAA+P6uLSazuzwG0Z8LjWOtv6cyjwN631nJrfKYQQwtWmxXYs992VnNl2u48tKABorY1UMctICCGE+2UXGknK+ZLswnrK4GYra20lAKCUCsPJvZaEEEK4xl+2f8RO4zL+sv0jl1/bmQ/2vwE7lVKfW3+eBrzi8hoJIYSo1SMD7+H0hjweGXhN64Br5My228uBu4ALwEVgitba9aFKCCFErRJOFHLk2EASThTWXthJznYFnQcSAF+glVJqpNa6+gz3Qggh3MKdg8/OzEp6AHgciACSgaFYNru7yeW1EkIIUSPlacK75VaU5yTAtesYnBl8fhwYBJzSWsdhmZEk25cKIUQ9+PjwF7y5500+PvyFy6/tTGAosG5yh1LKR2t9FOjm8hoJIYSo1ZXM6ym+0o0rmde7/NrOBIZ0a+a11cB3Sqk1wDmX10gIIUStglr+iFfQMYJa/ujyazs8xqC1nmx9+aJSahOW7GrfurxGQgghanVvz7vw9/Z0y+6qtbYYlFIfWb8/bjumtd6itV6rtS5yeY2EEELUK0e6kgYqpa4D5iilQpVSYWW/3F1BIYQQla04uoI397zJiqMrXH5tR7qS3sHSZdQZ2EP5PM/aelwIIUQdyisqKffdlRzZdvufwD+VUv/SWs9zeQ2EEEI4zZA7nIILZzB0HO76aztaUIKCEEI0HPcN6YWf58P1u/JZCCFEwxEW4O3yBD02zqxjEEII0UAYC4x8ePBDjAX1m49BCCFEA9FQtsQAQCk1Vin1nlKqn/Xnh1xeKyGEEDUqzh5IwYXxFGcPdPm1r6XFMB9YAMxUSt0E9HNtlYQQQlSUZSri3S0pZJks64onxkQzPHwqE2OiXX6vawkMGVrrbK31b4BbsOy4KoQQ4meq+OFf1srEM7y2/igrE88A8P3hC2w6lsH3hy+4vB7O5GPwBboCp5RSvlrrAq31c0qpXzv4/o7AcqAtUAos0Vq/VaHMaGANkGo9tEpr/bKjdRRCiMbM9uEPVJpxVDExjzsT9Sitdc0FlDIArwJzgFNYWhkRwIfA77XWxQ7dSKl2QDutdZJSKgjLKupJWuvDZcqMBn6jtZ7g6APExsbqxMRER4sLIYTbZZmKWJl4hmmxHQkLcDyJzrW+71oopfZorWOrOudIV9IbQBjQSWs9UGvdH+gChAB/dbQSWuvzWusk6+srwBGgg6PvF0KIxqJit09tbF1IYGkpOBIU6nu66gTgQeuHOQBa68vAPOC2a7mpUioKSwa4XVWcvkEptU8ptV4p1aua9z+klEpUSiVmZEgSOSFEw3JzzzbEdQvn5p5tHCrvbCABWH1iNW/ueZPVJ1ZfazWr5cgYg9ZV9DdprUuUUjX3Q1VBKRUIfAE8YQ0wZSUB12mtc5VSt2FJClRpyF1rvQRYApauJGfrIIQQ7rQ2+RybjmXQJ+IcT46tnGHNWGDk48NfUJw9kPuG9Lqm8QJbHoZ6yccAHFZK3VfxoFJqJnDUmZsppbywBIX/aK1XVTyvtb6stc61vv4G8FJKtXLmHkIIUf90he/lrT6xmncOvMU7h19h+a5D9u0tnBlXCPUNZXbv2YT6hrqgvuU50mJ4FFillJqDZcBYY5mi6gdMrumNZSmlFPA+cERr/WY1ZdoCF7TWWik1GEvgynT0HkIIUZeqGyyeNawT/t4Gbu7Zhne3pNjP28oPuf5GIoNWcZpjeIXswdKz3nA4su32WWCIdTFbLyz5GNZrrf/n5L1uBH4JHFBKJVuP/Q6ItN7nHWAqME8pZQbygXuq6sYSQoiGYNnONN7633HyikrsXUZZpiKW7zqEV8gevjowkH9sOAdYBpVtYwm35hzh9JU0RnQYwb0976ry2sYCI6tPrGZS10mVWgU1nXOFWgODUqor0EZrvRHYWOb4COCc1jrFkRtprbdTPslPVWXeBt525HpCCFHfjNaFaMYyC9JWJp5hUeIKfNus55GYx/nt+LhKYwhjY2LZcq5ljR/stsFlgNm9Zzt8zhUc6Ur6B5a/7CvKt56b6NIaCSFEA5OSkcufvz7M8xN60iU80H785KVclFcG3xv/w+ycV+gU3IlpsR05nz+a3XlHGB4xiL6try5UK7tVduewmj/QaxpcdufAMzg2+Byltd5f8aDWOhGIcnmNhBCintjWBqTmpJZbI/DHNYfYdCyDZ9d8z/zv55Oak0qWqYie7VrQrvMGrngc4NX41+1rES4avub0lTTe3f9utfeobf1BTYPL7hx4BsdaDL41nPNzVUWEEKK+2bpoVhz+nPP5p/lf6k7+39jX6dkuiO0nLnHG4z8cO3uU4pJiYn2f472dBxk+sAu+gQF0UTPs21ksGLSg3Peq7gHu6QZyBUdaDLuVUg9WPKiUmotllpIQQjQKWaYi/v7dMf7+3Y9kmYpIychl9ocJpGTkYiwwkm/OZ2CbgZzPP01JYSj7suJZcXQFdw+OpEt4AEZjawAK89pyc8823DLkNMlXVuPl4cX0gd347fjuTIvtSKfgTrwy/BU2n9lcqWUwqesknhr4lNu6gVzBkRbDE8CXSqlfcDUQxALeODFdVQgh6tuSnfEs/fFNSgtbk5DdgeKcvuzL2skzq27GP3wbyVdW0ze8LwCepaGA5UP9+8MXSMkwMbzbFFRgG+JTsvgq+DgLb5nL77efZNvZbfRu9QV+Lf1QnpMwFpj4/fbfs+3sNqB8y8DWDdSQOTJd9QIwTCkVB/S2Hl5nnaUkhBAN2t6z6fzm28W0buGDp98pvAJTIDCFg3nQ0h927l0AACAASURBVPcgvm2Oklq6h/yffDEEgMHDwLDQWWw40YpbBl1iXORdrNmTzeNjopk1LIoPDh0iOXcl5sDOQBS9W/WmdyvLR6Otiwhg29ltjOgwgkldJ7l9eqmrObztttZ6E7DJjXURQohrYls4dnPPNnx/+ALTYjtyxnSExzc9TmZeJhjgYh7454Xh7xlAXokJgEKdBUCxx0U6hHajU9hwHu3zJJsOaq4bWoryNPHnLcvYlBjFc7cMJCzAG39vy8fmsewDrDi6gn/t+5e9a8jP4Feui8gWCD48+GGDH1coy+HAIIQQDZVt4djWHzPYmXaazRkf8GP+txSVFpUbSc0jC0qgOLcLYf4+XOEw3gRQhIm2LXzp3yaGzUdMvPW/c8R1C2dH1jJ8Wm1lROwkpsVaPvBndJ/BwUsH2XZ2G/1b97cHhYpdRGVfu3t6qatJYBBCNHo392zDxqMXSb1kwhCyk4Om8hszlJaChzVABHq0ZlTErzhVvInUvExM+gKBHu3Zd2kf+y7t4+7oXG4d5sEvYqL4ccePXC6BzNIklKcJ8CbUN5RXhr/iVNdQYxhXKEsCgxCi0am4R9FXB46TdOUjDCE/4u1bOdWlhwf4EoJSkJNfRIJ5LRkelp7xksIQ8vHGbI7EEHCaU7nHiTfG45lyksslPxHqE8rp3NOsOLrC3lXU2D7oneVMas+/aK2fre2YEEK42/Jdh1icvJilZ1Jo5deCM7ln8Q0vqPE9BWSDBk8fKPY6hMoPI9jPQDYXKSGbYK/rmdr9UcZ2ugEvDy8e7vMwg9oOYnTH0Ww+s5l8c36jGif4OZxpMYwFKgaB8VUcE0IIt9ievp3fbFlAvrkQn5bF5JZAbq7jybrMplZ4+5m4XHgZbSgguxja+rflp7yfyMwK4/iFXPx9dlinn/bGz+BHiE8Is3vPxlhgrDS43FQ5sonePGA+0FkpVXZrjCBgp7sqJoQQtmmeozuO5p3kd/gm7RuH31t2XMHGyy+bUg+ztYAHeJQyuuNo0nLSKWzRip3GZfSNnMdTA5+q1EJo6t1HZTnSYvgYWA+8BjxX5vgVra1zvYQQwg1s00Hf2vMWJZTUXLiUcjOQygYFW5DQHmZKzb6E+ARzmQuM6DCCUN9QPjn2CfP6ziPOcHWGUXNqIVTkyAK3HCBHKTUbmIJl4zwDgFIKrfXLbq2hEKJZ2ndxH8sOLgOoPShAjRv8XA0SCg9DAeM7T6dDi1b2D/2yg8o2zamFUJEzYwyrgRws22IUuqc6QggBJ7MuMGv9HEooqr1wBVV1IQF4eXhRXFoMQJh/QLVrDoRzgSFCaz3ObTURQjRre8+ms2DDP/ALSiPtygnwcKCVUIWKQcETL6ZG38Mvek1jfep6wLJITVTPmcCwUykVo7U+4LbaCCGaJWOBkV9veJYcj/1gwrF9nx10R5cJPD/sGQDm95vvugs3Yc4EhuHAbKXUSSxdSQrQWus+bqmZEKLJsy1UyzCsJcdjf7XdQNeib3hf9mXso21gW9dcsBlxJjCMd1sthBDNkm2Po9CoPQRpzej9ms19LKnhba+v+NeYKr6SyV0m0ymkk31hWnOcVfRzORMYTgO/ADprrV9WSkUCbYFTbqmZEKLJmxbbkU3HT3LAcx/jEzS/3GSZc+pTrJm+XeNTrPh8hKfD1/P19GV2zGw6BXcCsH8XznEmMCzGMlP4JuBl4ArwBTDIDfUSQjRhWaYilu1MBRQtDDuZvq2EoHzNgY7QIk+jtQag2xlNUJ52qNVgUAYKSgrYfGazBISfyZnAMERrPUAptRdAa21USnm7qV5CiCbIbDRi/Pd/SDp+noxTV9gS0Z+Xzh2gwxFtLxNzRvPZcMWeLjAwxdK99NXQ2gPDzJ4zCfMNk64jF3AmMBQrpTwBDaCUCsfSghBCiFqlZOTy3TN/YdQPa4gEfgncmH+WDqcPc7CjZTbLuVBonQM7eir+O1CVG3OouLIZIMAQwMQuEwn1DWVG9xmNIjtaY+BMYPgn8CXQWin1CjAVeN4ttRJCNDkLV/zArUeTAbhi8CHIXIjPpZ9IGj6UE6W7mL5TU+Ct6HtKE3scNlec72gNCi28W/DCkBdYe3ItCwYtkG4jN3Amted/lFJ7gDFYgvskrfURt9VMCNFomY1Gzn+ykjVt+1McGMxtBWk8uuQZfMyWTROCzIWUtAihw+UsOLybZVMVhT6KxGg4HKnY3Edxa2Ip03dogvLgir8Hm/sounUaxJuj3yTUN5RxnWW9rbs4lahHa30UOHotN1JKdQSWY5nJVAos0Vq/VaGMAt4CbgPygPu11knXcj8hRN0zG43krFqFKScX05J36BbQip1te3H5VAKB5kJ7b9C+sM7sGzmRid/8Hx2yTCz4HBZPUMQeV1enqFp7kLpeNNA71cwN7W9k+Ow3pLuoDjiy7fYVrOMKFU9hWeDWwsF7mYGntdZJSqkgYI9S6jut9eEyZcYD0davIcC/rN+FEI1AzqpVXHzjryTHjKSX8iDCdInpKVvsW+B5ADkGPwrbtOW2zSsILTKR6xdERNYV5n+ticiyTFEt9FLs6Kko8TIQH13CU/mjGD//NQwSFOqEI7urBrniRlrr88B56+srSqkjQAegbGC4E1iuLXPV4pVSIUqpdtb3CiEaOO/oaIr8A+l2YDte1rkppUDZlQjB5nwGH7GkcskIbUvbV18l/Z+/Zb/fBXb2UKDhl5tKMSgv7nrpIzpdTGJI10kSFOqQU11JSqlQLH/N+9qOaa23OntTpVQU0B/YVeFUB+BMmZ/TrcckMAjRQNmmoILGuGYN3nm5luMoCjy9CCwpsnchFSsPtkX04YqnP1GXfyJ0YD869+uO/61TafePRfw7TrGpj8Lso5j6xCL6tu5L39Z96/PxmiVncj4/ADwORADJwFDgBywL3hymlArEsjDuCa315Yqnq3hLpW4spdRDwEMAkZGRztxeCOFCZqORs08/Td7OHwAo9vLBy3rOgCawxLJttgeWloOXLqV75mkKWrUluIUXLb9bhfH6trSdORM/Lz/m3jwQ4/ElzLlXZhvVJ2e2q3ocyyrnU1rrOCx/8TuebBVQSnlhCQr/0VqvqqJIOtCxzM8RwLmKhbTWS7TWsVrr2PDwcGeqIIRwocz33rMHBQCv4sqpWgqVpSPJA0sroiSwBZ1PH6Zl2jEA8pL2AtBy7lw6X9ePxTcvlqBQz5wJDAVa6wIApZSPdYZSN0ffbJ1x9D5wRGv9ZjXF1gL3KYuhQI6MLwjR8JiNRjL+39vkrP+2xnKFyhMfbRl6LgH23/8bimP6A5DduTv+w24g74cfyFlV1d+Jor44M8aQrpQKwZLJ7TullJEq/pqvwY1YFjseUEolW4/9DogE0Fq/A3yDZarqCSzTVSWtkhD1zDYFNXjKFAyhoZzbsJHMp5/CUEXrwKYEy4CzLShg/fmWABPqt4+zKziEIfNnERLgbb+2aDiUbbMqp96k1CggGPhWa+187j0Xio2N1YmJifVZBSGatIz/9zaXFi3Ct38/ikz5mH885lwenaAguHIFgFaPPkr4r3/llnoK5yil9mitY6s658zg85PASq11utZ6i8tqJ4RokGwtBbPRCEDBXktDv7qgUHErI0OfvoSMuJEWEyZw+et1gCZ05i/cWWXhIs50JbUA/quUygI+AT7XWl9wT7WEEPWpMDWVMw8/QvHp02RFdSMMKPTxw6cwH7B0FeWHtMI/+5J9xlHFgBEy4kbCf/1rAGklNDLO7JX0EvCSUqoPcDewRSmVrrW+2W21E0LUqcLUVC4sXEhBVg4lp08DUHrWsrQoPrQLI346iAfW8YPsTHsw8ACuhLYmqENbsvOKaD98CKEzZ9bHIwgXcGqBm9VF4CcgE2jt2uoIIerLxUPHOHffffiYLlPkacCWbKVVcR4AvXPSy7UKvMosMSrw8OT4g8/wizm3112Fhds4PIaklJqnlNoM/A9oBTyota64Ma4QohHKMhWRPO8JfEyXKQW8S8wAlJZZcxqSn13le0sB39ISRhaerYOairrgTIvhOiyrlZNrLSmEaBRsXUc7Y8bQM8PSdVT2r0UPa6ugGA/73kcAhcoDH11qL+8/7Aba3TOtrqot3MyZMYbn3FkRIUTdMhuNnJozl5Lz5+m9ZWu5je5sCj0MGH0CyfANJsZ4yn7cFhSK/APxzsvFv/8ADKGyyV1T4ci229u11sPLbL9ddj8jZ7bdFkI0IJn/93+UnLdsLFBVUChB4VNqpm1+Nq3LdCNlRnUj+qYb8fDzpcWECeRu3CgL1JoYR7bdHm797pLtt4UQ9SfLVMTKxDNMbmUme+Xn1ZazbJVt6UYyG7wwmIvtq5kjx8bR5unH7WV95s51b6VFnXNmgdsfqjqutX7ZddURQriL2Whky8J3WZUVxIBdHxBYlGc/Z1uHYPtuG2e42Lkn19/Qj+z/fMz5UbfTvd/1MpbQDDgz+Gwq89oXmABIzmchGonM996j+5plvGTwI9BsWahWcWFaKbC7yyAGXTnN5cBQerzxKmHtW+Pdvj3R1r2SRNPnzODz38r+rJT6K5bdUIUQDdCl9Avs/dMbdDyeTMCAfuRusuxkE2zOp8DDE9/SknIL1EqxfCD0P7mHn24YQ/ud3+EZvx3D3Lm0lO6iZuVaFrjZ+AOdXVURIYRr2DKqHfluOxE/7kMDuefKrzHwLS2p9D4PAKXw1qV0OLSb8AW/kUHlZsqZMYYDXM2m5gmEA39yR6WEENfGbDRy7rnnMG3ZSjiQ4ROEr7mILJ9AwgpzKVYGwsymcu8pxTLAHNT9ekKmTSfjrX/QfuFCgkaOrJdnEPXPmRbDhDKvzcAFrbXZxfURQvwM5z9ZiWnLVky+AQQUmAgvtGx3HZRny51g/a4UaG0fY8i+vg99P/83AGF3T6/zeouGxZnAcFfFA5akbBY1ZGUTQriRbXtsfesE/m5qw/iAVkSYLpHr7U9gUR7n/MI406ojfc4ewq/U+rec1hQFBvNGtwncYzzI4D+9UL8PIRoUZwJDLJacz7YB54nAVuCMqyslhKhZlqmIlV9up9un7+JdaCL0dApJ3+zi9tRDtM/LAiCwKI/LPgG0z88i7NwVfEvN/OQXwk/+YYQN7MfAZx5jREouw2I7EhbgXcsdRXPiTGBoBQzQWl8BUEq9iCVxzwPuqJgQorIsUxHLdqZy+MgZpi5/mTa5GfZz3Q/vxF+XH1RuUWjiipcfQcWW6ak/+YfRL/MkgT3upFVEGx6OaFOn9ReNgzOBIRIom8azCIhyaW2EEJXYVisPigrj9f/bwMTN/6FtqZnI3Awut2xLhtmDLjnn8NclmJXCoDW5eLEtsh+X/EIY9NMRuuek85NvCLsnP8TwgAuySE3UyJnA8BGQoJT6EsvspMnAcrfUSghhtzLxDK+tP0r34kz+uOEtQqz5EVLaR3M6sgcZGTl0yTmHGTBYc7iXGAxc8gthd98xdAnyhMR0TsXcwPPzxku3kaiVMwvcXlFKrQdGWA/N1lrvdU+1hBA2d3UJRP+0jej9W+1BAcAnJ4u4+LUUeBjIxwM/SjErD5S/H8EmE7889h39o9sRt/A5di1ux4T5syQoCIc4s45BAT2BYK31y0qpSKXUYK11gvuqJ0TzdfHQMX78459p0f16RsWvsR+/5BdMbouWRF04iRmFr3WmUYHBG19zEWlxd7D9+CU6tQxg0hNzaBXRhttffaa+HkM0Qs50JS3GshbmJuBl4ArwBZaZSkKIa2QbUPbKvcItp3fzvWdbItZ8RIusi7QxZZJz7DAenj4ElVjWILTKz6G4QyRcAAOafA8vdncayPKokfwuOIMh82dxOiWXKTLbSFwjZwLDEK31AKXUXgCttVEpJf/VCfEzZJmKePqzZPbsT+PZxH9TknGcAV5+BFtnEZWgCC7OI9fTx1LeEECRlxcnCCSh0zAici+y87bZPP3ALXD4AjdYg4HMNhI/hzOBoVgp5Yl1WwylVDiUyfUnhHBKSkYuTy7ZTHTSZqYXmRiQcRzAHhTylQE/6+YCgdbWQpjZBGZoe+IHTgeGE5mbQUD2j3QJn0KXUYH18yCiyXEmMPwT+BJorZR6BZgKPO+WWgnRhJ04ns6mhYsoycvj3lMn6Jt1khyDHwDn/MNon5fFT34htM3PpsjDgHfp1Z1njrWKokB74GtQdLuQwvFOfRjx69n19SiiiXJmVtJ/lFJ7gDFY0ntO0lpLPgYhalF2y4ol+zIxf7iEaQf/W65MsDmfywZfDodGUqoUlw2+tM3PtgeFIy2jONOpFyOeeZTdxlJi2/tw7MOPGTZ/Fq2k20i4mFPbbmutjwJHr+VGSqkPsGzEd1Fr3buK86OBNUCq9dAqyQ4nmoLzn6wk962/s33jQdqnp5HlbcmSezQ4gkJPb9qaLtGm8DItzAXcfDYZgIu+wfwUEEaWwZ+eOekktorm44g4Si8U8eTYbgB0lZlGwk1+Tj4GZy0F3qbmRXHbtNYTajgvRKNhm220PyOEMeHRdD6yi/Z5Rs75hQFg9vCkb9ZJ1kcOYnR6Mn6lxVz29KVFSQGtC3IASOvTl/VBQznd80bIKMHSWBfCveosMGittyqlourqfkLUJ7PRyPaX/8nlH89zq/EMfbNOApYxhBwvf9rnZ2Gw7msUd2YvvtrMef8wElp3x+AJw0/tJdicz02BBVz3/p/s22JMi+1Yn48lmom6bDE44gal1D7gHPAbrfWhqgoppR4CHgKIjIysw+oJUbMsUxEfb9hHn/cWEn3yMNEVzucY/OmRkw5AgadltrevdeaRqVVb7kzbScngG/BMyYfI62j7gmU77LAAbx4e1aXOnkM0bw0pMCQB12mtc5VStwGrodL/VwBorZcASwBiY2N1VWWEqEu2bqM9p7Jps34lY04eBqBAeZLtE0DbgssAtM/PBCA9oCVLe97GowfXEG08Q3rrKLq/+jJh++IJvOkmcjduJHjKFAyhofX2TKL5ajCBQWt9uczrb5RSi5VSrbTWl+qzXkLUxrZIbdOxDFoUmphhNnHBN5g2BTn46hLaFlzmom8wvuZCgovzyfbyJ8KUyW1coN/U2zG99w79pt1OeGwviO0FgM/cufX8VKI5azCBQSnVFku6UK2UGowl42BmPVdLiFq9szmFTccy8FAw9nQCk45ttp+7bPClhfnqYDJASHEeu9p0x/O2ibQf3ZWckECCp0yph5oLUbU6CwxKqRXAaKCVUiod+CPgBaC1fgfLgrl5SikzkA/co7WWbiLRoJTNjfDmd8doGeDN+oPnASjVcDCsExd9g/ErLmB7hz7kevkzLWUL+8I682NoR3y8PJk0tAslMaO5d3RvDAHetJTWgWhgVGP/7I2NjdWJiYn1XQ3RhNnGD4x5xWw6epEzxnyC/Qzk5Jsrlf3zjncZaN3aIsfgx4brBlNg8ObrzsMxhIXwf/cNYsB1Mm4g6p9Sao/WOraqcw2mK0mIhijplJE5S3eTnV9c7rgtKPh5KfKLLX9cGRScbNHeHhiCzflMS9nC3vEzuW7SQKbJbqeikZDAIEQFthYCKFYlpVcKCgAeytJ1lF+s8faAolIwa/j8+psoNHgTiJlicymtW4cw9ekHZNsK0ahIYBCijLIzjAC8Pa+uNFbArb3asPlYBgXmUnwMilaBPpzNLrCXKQoI4sitd5N0Opu4buH8ano/aSWIRkcCg2i2yrYM7ujXnk8TTvP1/vOcyylAYdlfvqjk6hicBjYeuUCRdbP5O/t2wNfLg+Xxpwnw9qRb2yDemNaXUH9v+yplCQqiMZLAIJqtlYlneOt/JwD4KD6NLNPVLqOKUzLsgaJMBpJ2Ib7Y9i56YERnnhx7vf2crFIWjZkEBtFspGTk8uevD/P8hJ6E+ntz1phH2xY+ZJqKyDIVY/CwlDNXkX6qbKBo4WtgUv8OzBrWCQB/b0/Zw0g0KRIYRJOVkpHLb7/Yj1KKV6fE8LtV+9mVamTnia306hBM0unscuWrCghldQjx5faYdjwyumu5LiJpHYimRgKDaHJsYwdrks+RlpkHwNylu8kvsuxmWliiSTqdbe8esvHyUBSXWo4E+Hhwc/c2JJ4y2geXpw6MsOdCEKIpk8AgGqWUjFx+t+oAoJk3qivvbTtJhxA/zuXk0z7Yj8/2WHYw9VTg4+VhDxA2FYMCYA8KAKbCUnq2D+aPd/Rm2c40QNu7joRo6iQwiAat7MyhWcOiCAvwJiUjl7v+tYPsPMsis12pu8u9x9M6VqCAEg15RZX7iDRX1yIABPp6EOzrTbCvAV9vA7HXhdlnFZUdVBaiOZDAIBq0ZTtT7TOHth2/CCiO/XQFk7VbqColpeDpoSixfup7KvD18sBUIUDYgkKovxedWgWQdDqb67uF8+HswW55FiEaCwkMosGxtRLOZxfw1f5z9uNJp3NqeFd5JWW6hUo0mIpKMXgozNbjg6NC6RcZip+XB7OGdcKYV2SfsSREcyeBQdS7stNIc/KKmfl/8eQV1zJFqBYtfA1cLrB0NbUP9mVCn3YM69KKP649xKhu4Txx8/XlZhaFBXhLS0EIKwkMos7ZWgT5xaUUFJlZs+8cOflmNh3b4pLrdwjx5Wx2AcO7tmTgdaHMGtbJHgS2dG/tknsI0ZRJYBBuVTGJ/UtrD7B230+VZgT9XGW3wb49ph0tA31kSwohrpEEBuEWWaYi3tl8gvUHf+KMMZ/3tqZwyVR5l9Kfa0BkCP7enjw1thtbfrQMTttmLwkhro0EBuEy9kHjnAK+TEynbBhwVVDw8lRM7t+BED9v/Lw9ywUBSYAjhGtIYBA/S9lUl/e+u5OCnzdmXK1QfwPGPDOzh0Xxu9tl5pAQ7iSBQTgky1TEwvVHWLM3ncLqlxC43PTYCF6f2rfSWIUQwn0k57MoL+M4LJsIudYE97bj1hf5GHi46Cm208+lt20d6M2MIZGczy4gIS2LFyf24tiFKzKALISbSM5nUb2M4/D1Y5CXDRnHgPLNAY8KLwIws9z7de4reuZnBwdPZVl8Fuxn4J1fxlYaIxgtU0uFqBcSGJoa2we9VjDxLQiPvnp8w+/gllfBeAq+mA2FuZRpEzjMwwMWe79Fn6IPnX7vgMgQercP5uQlE0+NvZ7daVnSKhCigZHA0NR8NhMyjlpeL6qilXh8g0tu40+hU+XD/L2YGtuRR0Z1KRcEZCaREA2PBIamIuM4rHrgalBwM49qjvt5eQCa/GJNkI8nkwdEEOrvVW71sRCiYZPA0BT8+D2smA667qYL/aQDAOgY6kdxSSntQ3x5Y1o/uoQHltv7qEt4YJ3VSQjhGhIYGrMfv4dPfgGlBXV62+KW3dja5TWSRo2oshXQJTxQNqQTohGrs8CglPoAmABc1Fr3ruK8At4CbgPygPu11kl1Vb9GJeM4fHg75F1w/bW9g6DIBOHdYeyfYMffKg1kewH3uP7OQogGoi5bDEuBt4Hl1ZwfD0Rbv4YA/7J+F7YZRddPgO9+B0V5XMtsIgCCOkBoFAx/yvKhbzJa1ixMeR+uv7ly+aqOCSGatDoLDFrrrUqpqBqK3Aks15YVd/FKqRClVDut9Xm3VKjs9E3blM7qzv34PXw6E0ryYdTvofdky/n2g2Db6xAxFE5vg67jIXWzpRwGUKUQ0B5MGaALLccwg/IGXeR8nZ2ZUeTpB3f/u+YPdvnQF0JUoSGNMXQAzpT5Od16rFJgUEo9BDwEEBkZeW132/C7qx+0v1hZ87nVD1s/7IEtr8K53Zbzx78DtCUoAJxYX+YiZkti4dz08sfg2oJCbcJ7wvTllYOcEEI4qbpZh/VBVXGsyv06tNZLtNaxWuvY8PDwa7vbLa9C9C2W77Wdm/Su5S9wgFG/u3p+1O/AwwsiR1jOdR1/tRwGUB4QGAHK5+oxsLQYron11+XX8urP4T3h0UR49AcJCkIIl6jTvZKsXUlfVzP4/C6wWWu9wvrzMWB0bV1JsleSEEI4r6a9khpSi2EtcJ+yGArkuG18QQghRLXqcrrqCmA00EoplQ78EcvMR7TW7wDfYJmqegLLdNXZdVU3IYQQV9XlrKQZtZzXwKN1VB0hhBDVaEhdSUIIIRoACQxCCCHKkcAghBCiHAkMQgghymn0OZ+VUhnAKSfe0gq45KbqNGTN8bmb4zND83zu5vjM8POe+zqtdZUrhBt9YHCWUiqxukUdTVlzfO7m+MzQPJ+7OT4zuO+5pStJCCFEORIYhBBClNMcA8OS+q5APWmOz90cnxma53M3x2cGNz13sxtjEEIIUbPm2GIQQghRAwkMQgghymmygUEpNU4pdUwpdUIp9VwV532UUp9az++qJe1oo+DAMz+llDqslNqvlPqfUuq6+qinq9X23GXKTVVKaaVUo5/W6MgzK6WmW3/fh5RSH9d1Hd3Bgf/GI5VSm5RSe63/nd9WH/V0JaXUB0qpi0qpg9WcV0qpf1r/TfYrpQb87JtqrZvcF+AJpACdAW9gH9CzQpn5wDvW1/cAn9Z3vevgmeMAf+vreY39mR19bmu5IGArEA/E1ne96+B3HQ3sBUKtP7eu73rX0XMvAeZZX/cE0uq73i547pHAAOBgNedvA9ZjyYI5FNj1c+/ZVFsMg4ETWuuTWusi4BPgzgpl7gSWWV9/DoxRSlWVXrSxqPWZtdabtNZ51h/jgYg6rqM7OPK7BvgT8DpQUJeVcxNHnvlBYJHW2gigtb5Yx3V0B0eeWwMtrK+DgXN1WD+30FpvBbJqKHInsFxbxAMhSql2P+eeTTUwdADOlPk53XqsyjJaazOQA7Sk8XLkmcuai+WvjMau1udWSvUHOmqtv67LirmRI7/r64HrlVI7lFLxSqlxdVY793HkuV8EZlqTgX0D/LpuqlavnP1/v1Z1lqinjlX1l3/FebmOlGlMHH4epdRMIBYY5dYa1Y0an1sp5QH8Hbi/ripUBxz5XRuwdCeNxtIypQUowwAAAypJREFU3KaU6q21znZz3dzJkeeeASzVWv9NKXUD8JH1uUvdX7164/LPsqbaYkgHOpb5OYLKTUp7GaWUAUuzs6bmWkPnyDOjlLoZ+D1wh9a6sI7q5k61PXcQ0BvYrJRKw9IHu7aRD0A7+t/3Gq11sdY69f+3dzevNkVxGMe/z4AUpXRNjK6BATEyuRMv5SUvZaQYcaWUMpFMKROJP4C8jJSipIt0ByQTAzclL0WiDCiXwZ0w8PIYrK3Ovimbc53dOZ7P6Jy9V+f81umcfmf91t5rAc8piaKfNen3XuAygO37wBzKQnODrNFv/08MamJ4ACyRtFjSbMrk8ti0NmPA7urxduCOq5mcPvXbPlcllTOUpDAINWf4Tb9tT9kesj1se5gyt7LN9kQ74c6IJt/va5SLDZA0RCktvepplDOvSb/fAOsAJC2lJIbJnkbZe2PArurqpBFgyva7bl5wIEtJtr9KOgCMU65kuGD7qaRjwITtMeA8ZZj5kjJS2NlexN1r2OeTwDzgSjXP/sb2ttaCngEN+z1QGvZ5HNgo6RnwDThs+2N7UXevYb8PAWclHaSUU0b7/A8fki5RSoJD1dzJUWAWgO3TlLmULcBL4BOwp+v37PPPLCIiZtiglpIiIuIvJTFERERNEkNERNQkMURERE0SQ0RE1CQxRERETRJDRJcknZO0rGHbUUmTks5Vz1dVS2P/cknliDbkPoaIHpI0Sln2+0DHsWHghu3lLYUVUZMRQ0RDkuZKuinpkaQnknZUx+/+XHup2kjmYdXmdrsRR/ydgVwSI+If2QS8tb0VQNL8zpOSFgJngdW2X0ta0EKMEV3LiCGiucfAekknJK2yPTXt/Ahwr1rNFNv9vFpv/MeSGCIasv0CWElJEMclHZnWRPT3nh4RQBJDRGOSFgGfbF8ETlH24e10H1gjaXHVPqWk6EuZY4hobgVwUtJ34Auwv/Ok7UlJ+4Cr1c5x74ENvQ8zojtJDBEN2R6n7AUw/fjajse3GIy9tOM/llJSRG99BjZ33uAGXAc+tBpVRIfc4BYRETUZMURERE0SQ0RE1CQxRERETRJDRETU/AC3hUe64CUb+wAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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Gjx4NwLTrprFsxTJfNcua6sRfeumlKKVISkoiPj6epKQkTCYTffv2JT09nbi4OLp27cratWvJzs5mx44dvmOczMqVK5k2bRpms5n4+HjGjh3L+vXrARg2bBhdunSptH1RURFXXXUV//rXv4iMjDzl/oUQDcffo2j+BcwCImraQCl1G3AbQKdOnerloDHWGG7ud3O97Kui6Ohoxo0bx9q1a8nLy8PpdGKxWCrVdvfWg+/QoQNOp5P8/HxiY2N9y72lio8dPUyvrp2ICg3yfTg4XW6OFefjcDt8dW9qqg1fsf571drwFevBf/TRR/Tq1Ysrr7zyhNry1TlZ8TmbzVbpeXl5OVdddRXXX389kydPPuW+hRANy28teKXUJCBTa/3zybbTWs/RWg/RWg+Jiwu8m4aysrLIyzOSbUlJCd999x29e/cmOTmZTz75BIB58+Zx+eWXA0Y9+Hnz5gHwySefcN5556GUOqFO/K5du7gw+VwsZhP79+9nzZo15BaX8cn8Lxg58lxf/ZuKdeJHjBjBsZJjuLW7VrFPnjyZzz//nA8++KDW9eDHjBnDhx9+iMvlIisrix9//LHS3K5eWmtuueUWevfuzR/+8Ida7VsI0bD82YIfDVymlLoYsAKRSql3tdbVT7MUoA4fPsyMGTNwuVy43W6mTp3KpEmT6NOnD9deey1//etfOfvss7nlllsAuOWWW7jhhhvo3r07sbGxzJ8/Hzh5nfjevXszb948Vq2+nc5dujLrvod8JRByCuwMGzYcrd3Mfns2R+1HKXOX1Sr2mJgY+vTpw9atW6tN0l5Op9P3X8CVV17JmjVrGDBgAEopnnvuOdq2beubKtBr1apV/O9//yMpKYmBAwcC8PTTT3PxxRfX4ewKIfypQerBK6XGAQ9prSedbLtAqAff0NLT05k0aRKbN28+YV2nzp3535fL6NOlPXERVhzOco4UZdM2vBVmk6q3qpYbN27kd7/7HSkpKWe0n5o095+hEI1J6sE3USaliI8M8d0xW1DiIr/ISkGJi5ySXI7aj5JRePCU0wuezOuvv860adP4xz/+UV9hCyECRIOUKtBaLweWN8SxmprExMRqW+9wYp34ioXPsu02tDsEe3kRGfmZJETEUVie72vRV1e3Pjs7m/Hjx59wnJ9++olWraqfv1YI0XRJLZompGLhs1Y2KyWuMOwuB4UOJ5CN3ZWN261pY4urNLesd67Z6Jho0tLSGvEdCCEakiT4JspiNtEhqg05JUFolw2n243b6aSwOIRYq5uIoAjswXbCLGEcLDpIUVkRIJOUCNGSSIJvwiwmC21scThdbvbnFKOd4didbrKKSih0ZVLuLqbMVUaZqwxbkE0mKRGihZG/9GYgt7iMIoeT8BALthALJa48yt3FaG2hzFVGkCkIh9OJvTwLe7mddrZ2FJYX1uu8skKIwCN/3c1AxYuvFrMJh7MV+/LclJYFYwrKp5xS37bF5cXsyd+DW7vJd+RjUiaCTcGUu8tJsCUQYgmp6TBCiCZGhknWQmJiou+GniFDjOGmOTk5TJgwgR49ejBhwgRyc43KlVpr7r33Xrp3707//v1JTU317WfevHn06NGDHj16+O52rQ/ei6/emaRCLEF0jWlLeLAVd3kMbmcEWpt923vvhC11llJcXkyeI4/RSaNZv3s9GYUZHLEfIbM486TDL4uLi7nkkkvo1asXffv25U9/+lO9vR8hRP2QBF9LP/zwA2lpaXhvxHr22WcZP348O3fuZPz48Tz77LMALF68mJ07d7Jz507mzJnDnXfeCRgfCE888QTr1q0jJSWFJ554wveh4A8Ws4lOsWHER4QRpKNxl7WulOSh+ro0+Y58skuyySrOYl/BvmoTvffmuIceeojt27fzyy+/sGrVKhYvXuyvtyOEOA3NMsE7c3PJfvNNnH5MoN6673BiPfgbb7wRpRQjRowgLy+Pw4cP8+233zJhwgRiY2OJiYlhwoQJfPPNN4Axm9KDDz7IoEGDGD9+PFlZWQCMGzeO+++/n1GjRtGvXz/fnaaPP/44M2bM4IILLiAxMZEFCxYwa9YskpKSmDhxIuXl5SxevJjrpl1LfKSVxNY20tat467r7gdXJG5nBC5Ha7Su/sc/79/zuOLcK5g4ciIvvvgiO3J2sCR1Cd17duf2O25n0KBBZGVlkZycDEBwcDCDBg0iIyPDb+dbCFF3zTLB5y9YQObzL5BfoR76mVBKccEFFzB48GDmzJkDwNGjR0lISAAgISGBzMxM4Hg9eC9vrfialgPY7XYGDRpEamoqY8eO5YknnvBtZ7fbWb16Na+99hozZ870Ld+9ezeLFi1i4cKFTJ8+neTkZH799VdCQ0NZtGgREyZMYO3atdjtdqxBZlYt+ZJrpl5Dp8i2KFcU6GC0KwyAisUqtmzcwucffM7737zP+4vf55N3P2HbJqM88p6dezjvyvP4dtW3tO/Y3veavLw8vvzyy2pvohJCNJ5meZE1ylO6NqqeStiuWrWKdu3akZmZyYQJE+jVq1eN256qHnzV5WCU+PVWe5w+fXql0rveevBjxoyhoKDAV9nyoosuIigoiKSkJFwuFxMnTgQgKSmJ9PR0LBYLEydO5Msvv2TKlCks/vprXnj+eSJCg2hlCyaryIF2ReDGjHIfnyQ8dW0q4y8eT5jNSP7nX3I+P6/9meSJybTr2I5+g/uRVZxFbmkuiZGJmDEzbdo07r33Xrp27Vqn8yqE8K9m2YK3xMTQ6pZbsMTE1Mv+vLXe27Rpw5VXXklKSgrx8fG+mY4OHz5MmzZtgOP14L28teJrWl6dmmrAV3xesR58UFBQpQ+LqvXgly1bxtChQ4mIMMryx0WEEB9pJTbUSjCRdI6JwoQFrS2crPZcaFio77HT7WRX3i6mzphKm05tuPzmy3E4HTW/WAjR4Jplgq9PdrudwsJC3+MlS5bQr1+/SnXfq9aDf+edd9Bas3btWqKiokhISODCCy9kyZIl5Obmkpuby5IlS7jwwgsBcLvdvtry77//Puecc47v+N568CtXriQqKoqoqKhaxz5u3DhSU1P5z3/+U6kevMVsIj7SSofYMHq2jSQiNAizSRGi2zJoyIV8//UPFBeXUGwv5vuvv2fwiMHV7v+Vp1+hML+Qh/7+EMXlxezK28XO3J2S6IUIEM2yi6Y+HT16lCuvvBIw6qZfd911TJw4kaFDhzJ16lTefPNNOnXqxMcffwzAxRdfzNdff0337t0JCwvj7bffBiA2NpZHH32UoUOHAvC3v/2N2NhYwJgpacuWLQwePJioqChfUgejpvuoUaMoKCjgrbfeqlPsZrOZSZMmMXfu3FMOy3Q6nXSJjyYqZjCXTbmBaRfcgFJOJl9/Fb379+bg/soTah85dIQ5L82hS48uXH3e1QBMu2UaU26Ywq68XVhMFjpGdCQsKKxOMQsh6k+D1IOvrZZYDx6MUTRFRUUnLB83bhwvvPCCb+y9v2RlZTFw4EAOHjyI0+Umt7iMILOJg3klmCxFuEx5NQyqPLVYayw5+3Po26dvvcYshDBIPXhRoy+++IJzzz2XZ555Bjh+01R0WDB920URa22F25GAdp/eP3s5pTlklWTxzw3/JLfUf8NWhRAnki6aAFBd6x1g+fLl9X6s4cOH43BU7iP/+OOPSUpKqnb7VjajDEJ+STwOZz7KXALKVacWvcvtYu7WuQA8OOTB0wlbCHEamkSC11qfMJpEnJ5169bVaXvvBdlWtmCy7VbsDidFjmJMwdmgjJIHFX8yQU5NqwIoC4I8m8LkchNpd5OQ7WbulrnM3TKX9mHt+fcF/6ZLVJd6fGdCiKoCPsFbrVays7Np1aqVJPlG5E30TpebbLsFiCS7yIFTFWAKKvAl+VYFEFZmfAWXuSmxl1O25wC3f+Xm556woQeM/X4f6968mGU3Xc4V9h5ETZ5cb0NahRDHBfxF1vLycjIyMigtLa3hVaKxZBaWUubUKLMdZSoDwFZqJHeXArPLjTpwAPPrb+AsKiDIDflWiPL8KI+GQ3wRhI0aSdtHH6Xgq0WAJmb6dEn4QtTSyS6yBnwLPigoiC5d5F/5QBScVcRjC7ew8XAmjtCf0EEZxFm2M/ZXzfrucN5GN70PQmIxWN3g4nhyB4ggBHBQvHoNh//2N0rWGx/u9pQUOrzyiiR5Ic5QwLfgReBL3ZfLzXNTyC85sbxw//YRBP+2jT+s+A8xZfbKKy0W8Nx1i80G9uPrY2feTPTVV3P02WeJ/9OfCJEPeSGqdbIWvCR4US9y7GXMW53OxxsOcCjfaKa3jQzhSIExYie23M7EXSsZlPkbfXP34Y6IxFRYUPMOg4IgONhI+lYrnee+TdjAgQ3xVoRoUiTBiwbz9KKtzPlpL8O7xKA1pKTnYjGB022Mtolw2JmwP4WtiQP488YPaZ2xu3Y7ttno8d1S6bYRogpJ8KLB5NjL+HjDAa4e0pHc4jJue2cDu7Ps1W4b6Un2PctyOHfnmlPu25KQgCU+HmufPlhiYoiZfr0kfNHiSYIXjaZq143ZBC5j+Dy2YBNmkwny87lu27ecn7udiGAz7sJCqMWoqdiZNxM/a5af34EQga1Jj6IRTVusLZgHJpzFZQPb8Y+vthJptbBw42FCzAp7mRtwo0JsZNlisKXnsGvyzXT9aVGtEnzOB/Mp+OZbwkaMwBIdjSk0VFr1QlQgCV40iG5x4bx98zBeWroDAIdL0yY8mKyiMjTwU7fhJERaeackkeeDIulEJm5OUSyppARnSQkFlWbu0sTdc4//3ogQTYgkeNGgZozqgnG5VbMw7RC6qAyTgkxTGK/GjwRg/rgbuOjHj+g+fSq2f7+IOz8flOKks5F4HJs7D2deHnF33y0tedHiSR+8aDSp+3K59Z315NjLiQq1kF/iJDzETJHDBUBokIn3ru5F5/XLcOzZQ/6ntZ9jN2zUSMLOHiRdNqLZk4usImB5R90czC3mnbX7iY8I4Wihw9PGhwirhVa2YF68MJH233xMwTff4jx0qNb7N3doT9SFF9Lq1lsl0YtmSRK8CHhVE/1ZbWz8lnl8eGVokIn3bh3BsrW/0fc/z5CYsaNO+w8dMgTb8OHSohfNjiR40WR4E312kYM5P+2lT9twfsu043RrYsKCyC0uJ9Jh55aizUzM2IB779467d82dgztnn1WkrxoNhplmKRSygr8CIR4jvOJ1voxfx1PNA+xtmBuH9uNHHsZrcJDKC5zsvXILgByi8sJDzFTgI0P24zFMWw0nd5+hW4UEZ6Teeqd22zYV/zI4X88RXB8G0q3baft3x6VOjei2fJbC14ZxdttWusipVQQsBK4T2u9tqbXSAteVJVjL+PeD1JZuSsbwNdHD9AmIoTMQgdDoxX3rHmHuB0b634ApYh//HFir5lan2EL0WAaZU5WbfDORRfk+Qqc/iDRJMTagnll2iDO6d4KgKOFDkIsxq9tcXk5AD/nae7uOpl3e07g88RRFMR3AFMtf7W15uhjj7FnytU46tjdI0Sg82sfvFLKDPwMdAdma63/WM02twG3AXTq1Gnwvn37/BaPaLqqtuRjwoIY06M13245SqnTjdWiKHUav8s3juzMk5f3I/PV2WS/+mqtx9AHde/m6ZtXJDz5hHTdiCah0S+yKqWigc+Ae7TWm2vaTrpoxMnk2Mt4fcVulmw5Qnp2MQDtoqy+8sTeJJ/YKow3bxrKF2kHAcU1OoP8++8Bt7vWx7J07kSX+fPlYqwIeI2e4D1BPAbYtdYv1LSNJHhRG0YBs738vC/X16KPtFooKHX6RtoM7xLLur05ACT3jOPPSTYy//F3Whfn4t6/v1bHsQ4cQPjo0UROmkTRsmUyd6wISI2S4JVScUC51jpPKRUKLAH+T2v9VU2vkQQv6qJqtw3AsMQYBnaK4auNhziUX+q7Q9ZqMVHqdPPQ8Him5WykdM8eCmp5Z6ylQwecGRm0vuv3xEyfTv6CBZLsRcBorGqSCcA8Tz+8CfjoZMldiLryXoCdtzqdkjIXGzPyWLc3h2CL2ddt0z7KSml5MaVOo3tm2eFSynucy1V5xvV/U1SUUesGjAuzbrcxm5TnAi6AMyMDgILvvif/y68o9/wH0OqWW1Hd6K4AACAASURBVBrqrQpxWvyW4LXWm4Cz/bV/IeB4OWKAl5buYN3eHLq2tpGRW0x6djFbjxRV2j51fz6p+/MJGj6ay+8LZVlsT0ZsW0XR998RlnXY2KhCcjcnJOAuKkIXFlK2w7h71tK5E1GTJ+PMzZXWvAhoUk1SNBszRnUhLNhCcZmT9OxiEluFkZ5dTP/2kWTby2hlC8ZiNpG6P481x5yUdx/Hy9/vJLnn+fw8pDvPOzeSuO473AUFYLNhMptxHfYk/fBwKDI+LFw5uZT8+iu5772HfcWP2FNS5O5YEZCkVIFodrzlDs7vE893W4+SXVTGnJ/2ANC/fSTp2cUUlDqZOrgDh/JLaRdlZV+OnZ5tI2lfmEnyuy/gSjfGxJuio3Hn5fn64X2sVigtxdyhPa6Mg4SNHEn7F/8pSV40uNO+yKqU2lSL/WdprcefbnAVSYIX/vDS0h28/P2uE5ZXHGJZ0a1JMQxdt4hu+YeIv+Vmjj77LOV79qIiI9EFBZU3DguDYmPIptS5EY3hTC6ymoGLT7Zv4IvTDUyIhuCdZKSkzEVpuYvP0w5SUOokPjKEtlFWUvfnAfhG3Hy8q5D/ho1ieN9Yrl20gl579mIbO4agDh3Ie+99Y6c2m9FX70nuKIV9xY8c/MOD0pIXAeNULfhztNYrT7qDWmxTW9KCFw1hd1YR//hqK3+d1IeHP95I6v482kSE0D7ayuECB0cqtOojHXbuLNnKhAdvZcVvmYyZ9xzOTVVq3lgs4HT6noYOHYJt2DAiJ02i4KuvACVlioXfBMSNTrUhCV40tKmvryYlPRdbiAm7w02E1Uxhqcu3vmNMKAdyS3yt+1ccG+ixeD4qJATtcGCKiqLd889x6OFZx4dbeoSNGknx6jW+x+3/KS17Uf/OuNiYUmqSUuoXpVSOUqpAKVWolCo49SuFCGzPXNWf5J5xdG1lAyAxNowIqxkw+uhHdjOKnOWXGC30TUMnsGfyzUQ+/yJBXbvQ8Y3XyX3vPV9yV1arb9/u4hJChxh/d8Wr13DwDw/izM1tsPcmRG2rSf4LmAG00lpHaq0jtNaRfoxLiAbRLS6ct28exr+mDSK5Zxz/mjaI3m2NX22zSbH9sNGOCTIrAL7eV8Jd7r58qDrQ/euvKe3Rhx/Ou46gYSMwJySgS0shOBiA0rQ0yg8fJqRvXwCK10iSFw2rVl00SqkfgPFa69pXazoN0kUjAsHurCJue2cDu7PsvpE2rW1BHLMfvwFq6uAOZBU56BEfwZwf9/DIRb24ImUBOW++dcL+zG3b4jpyxPc8dubNmEJDcZeWYrJaiZk+XbpuxGmrj1IFs4CvlVIrAId3odb6xXqIT4iA0i0unI/vGFVpjthSl9EvHx5ipsjhYvlvWWQWOlifnkP/DlF8v+0o46+Yhs0czLb0TLod20d56s8AaO9IG4/in1Mp3Vj5Qm3cPfc0zJsTLUptE/xTQBFgBYL9F44QgaHi1IEHckv4YUcWoUEmOsWEsvVIEUWOMgCKHC42ZRj977d+7iDWNoTUsDzuvuIyZoxMIe/zhTgPHvTdCWtJSKDc05pXERHowkLcJaVk/b9XAS2teVGvapvgY7XWF/g1EiECUKwtmH9OHcjVr69md5Yda7CFxFZhFJaUU1x2vMsmPMRMenaxr079wr12Zt59O5GlpeS8+RYhXRJx/LoZp7f0ARBxwQQsUVEUfvedr4CZMzcXS0wskuxFfajtRdbvlFKS4EWLFGsLZs6NQ0juGceQzjGkZxeTXWwkd+8fkNszmYjVczH2QG4J457/gQdNSZjvvBfzwMEn7NcUYqVw+XIjuYeEAJD/1SKOzZ7NsdmvcehPf5ILsuKM1PYiayFgw+h/L8e4g1XX90gaucgqAp13spGfdh7z3QFbkeLEiYe7xdm4qGMoue+9x9i8nXQ8mg5AUKdOlO/fj6VzJ0zBwZTtNMopWAcMoGzfPtx5ebR5+CEpSyxO6ozHwXuGRZq01qEyTFK0ZEZ54p6c26M1YHTN9O8QRZ+24YCR3C0mRWJsKG0iQrCFmNidZWf1MSfv9b6QFdE9ACiKS6B8/35M0dFYYmJ9yd3cti2u3FzceXmYoqNxZufg2LuX7DfflNa8qLOT9sErpdpqrY+c6TZCNDfe0sRXD+lIrC2Yl5buYOuRXb4pA9NzSogIsWB3GF03GTlG3/yXXc+h1BJMp0smMmrus4RnHqQ0Lc3oonE4UBaL0WVjteLOyyPnrbco3b6N4tVrKFq1irCzB0nZA1Frp7rI+jUwqB62EaJZ8Y6y8fIm/KGJscycl0JesZNCx/H6NJlFxqibghAbRy+agjkilPuTrufxtW/RwX4MHA6wWHBmZGDp3AnnvuPzxgZ36UL5kSMUr17jKX2gMYWFyUQj4pRO1UUzwFOaoKavQiC+IQIVIpB5E/6gzjF8eudoOsaE+tYFmanwWNEnIZJFmw9zMKIND465h02jJ1FmiwSnk6CuXQg/5xzf9tYBA3Ds+I3yPXuxDhhA2MiROHPzyHz+BXLffbch36Jogk6a4LXWZk+fe01fEVrr9g0VrBBNQbe4cBbefQ6DOkUDUH68dhnapZnz017sDmNhQYiNpzudz+9H3MH2zkm8Mfx68nccr12vgoIo8Qw8cB47RvGaNRT9+CMA+V9+hWPv3gZ6V6Ipqu0wSSFEHcTagn0XYiOtx3tCvZ02qsK2+SVODka04YGzZ+De9At6Qwqus4fS+q67COlpzDdriow0bpjCMwm4p6/+wF13+S6+OnNz5WKsqETmZBXCT7z98uf3ieeWuetJzy72lSOuOpTSBLiBpZ2GAbC557lM7t+PizZ8BYC7oABTdDRho0dj/+knY2Ypq5XyPXs9XTWK4l9SfeWJZWilAKkHL0SD8E4y0jEmlHfW7ifEDA5XzdtbMFr7tybFMDj1O7puWoX7wH6whkCpUQ4qpF8/zJERWNomULBgAQDWgQMwhYbR9m+PEtKli//fmGh0Zzzhh1Lqf1rrG0617ExJghfNnXdC8N2ZhXz088FTbm8LMWN3uBik8nl0yctY7Ub5Yu9k4FUfW9q3x3nwIGGjRtL5rRMrW4rmpz6qSfatskMzcOK910KIk6pYxMwabOH7bUfJKy7DXlZ9JW7vxdhUHcXdI+7gkW2fUe5ys++qm5lcnoHevJHiNWsI6tSJiPPPx+0oJe+997H27t2Qb0sEqFPNyfoI8GcgFPDWPFVAGTBHa/1IfQYjLXjREu3OKmLya6t8s0ZVx6TAXeVP9bYxXZk1si35Cxb4xsQ7c3MrPRfNX3100TxT38m8OpLgRUv19KKtzPnp+JDHsCATxeWVW/VV69zYQsz0TYjkmav60y0uvGECFQHntLtolFK9tNbbgY+VUifcraq1Tq2nGIVo0e4Y1x2AjRn5DOgQxcK0QxSX++bWwazAVaUtZne4SEnP5bGFWxjcORpQzBiVSKxNpmwQhlP1wf8BuA34ZzXrNHBevUckRAsUawvmz5f08T0vLXfxzlqjXEGk1ULbyBDSs4sJD7GQ4ylVbDEpQoIUmQUlvPz9MQDCgs2VSiiIlu2kCV5rfZvne3LDhCOEALh/Qk9A8ePOLCKtFjYdNEbP2CvUt3G6NU6H5rdMOwDto62c3yeel5buQFrzAmo5ikYpdTXwjda6UCn1V4ziYn/XWv/i1+iEaKFibcE8eUU/wOif9yZ4R4V+Gu/NUV7HCkt55budLNx4CJDWvKh9qYJHPcn9HOBCYB7wuv/CEkJ43TGuO/eN78GNIztXKmLmBiwmfLXoHS74dosxJWBUqHEHrWjZapvgvffcXQL8W2u9kFNMvq2U6qiU+kEptU0ptUUpdd+ZBCpES2VMMnIW7aNDOZBbQmKrMN86pxsO5pdyVhsbUaEWRnUz6t/klzh5bOFmXlr6Gzn2ssYKXTSy2t7odFAp9QZwPvB/SqkQTv3h4AQe1FqnKqUigJ+VUku11lvPIF4hWqyrh3QE4Pw+8Ty2cDMrd2UTYjGRX+L0jaHffqQQgBCLYuWubFbuymbtnmwsJsWTV/ST4ZQtTG3HwYcBE4FftdY7lVIJQJLWekmtD6TUQuBVrfXSmraRcfBC1I635ME3mw/zy4F82oQH43C5K90sFRVqIdIaxIHcEgD6d4jikqQE3yxUonk44xud6iGAROBHoJ/WuqDKutswhmLSqVOnwfv27fN7PEI0F94iZtlFDt+FWACrxUSp07gEG2RWlLs0QSYod8OgTtGc26M1M0Z1kUTfDDRqgldKhQMrgKe01gtOtq204IWouxx7GZe/utLXUg+xKBxOTbBZUebSRIdayKumDEK3OBtzbhwi3TZN3MkSvF8n/FBKBQGfAu+dKrkLIU7PxxsOcCC3hI4xobSLsuJwGo22Ms+QSm+3TXiImfbRVgAirGZ2Z9l5bOGWxglaNAi/JXillALeBLZprV/013GEaOmuHtKRRy7qxcK7z+HqIR18y9tGhhBhNfvq19iCLbTydMkkRBqJPqeolJeW7pCRNs2UP2d0Gg3cAPyqlErzLPuz1vprPx5TiBbHW4IYjFmkQLEhPYdVu7N92wSb4Wihg6OFRn2bfdnG3a9bjxSx9cguSsrd7DxayF8n9ZEum2bEbwlea72SylNPCiH8zDtmPsdexr0fpLJyVzbto60czCsFIM4WTKHDSanTTXiImfAQC+2iQ9mQnkPq/jzKXVt499bhjfwuRH2RSbeFaIZibcG8Mm0Qj1zUi/bRxt2vkVYLpS6Xb3SNUnCkwEHq/jyO5BsfAMVlTumuaUYkwQvRTHm7bp65qj/JPePo1TaCwlLjpvTwELPvcZuIYA55Enzq/jxeX7Gb3VlF3Px2CruzihotfnHm/NkHL4QIAN3iwnn75mHszirizwt+5WBuCRl5Jb71JeVGovdOKLJ29zGWbDlCenaxdNk0cdKCF6KF6BYXznm92pCRV0K7KGMUTdvIEF9L3jvaZvuRAtKzjRk6i8uc7M4q4o0Vu6XrpgmSFrwQLYi3nk12kYM5P+2lU2wYRwqMkTVBCso1lLnAGmSitNxN6v48rn59NTl2Y5IRKT/ctEiCF6IF8fbL59jLaBUewvl94rll7nqjO6bCTe2l5W4GdYomq9DBgdwSLCbF1kP5vLR0h5Q4aEIapBZNbUmpAiEa3u6sIh5buJmCkvJK9WzaRVlxubVv7LyXlDgILI1WqkAIEfi6xYXz7q0jSO7VBjBG2ERaLRzKL/Uld+8NLd4SB39e8KuMsmkCpItGCAEYd8GGBVsoLnPy8ve7MCvwzhDo/T8/xGxCWRWbD+Vhd7gpd23h3B6tpQRxgJIEL4QAKvfPf7XpMLuz7FhMxqxRXsc8F1sBIqwW9mQVsXLXMYrLnMwY1YWPNxyQZB9ApItGCFFJrC2YOTcOIblnHP+9cSihQUaa8HbTmDwPXG637wap9GPFXDl7Fc8s3s69H6TKkMoAIRdZhRAnlbovl+v/u5aScneN21Rt6d82pit/vrh3A0Qn5CKrEOK0Deocw1f3nsvwLjG0iQipdhtnldy/IT2Hl5bukEm/G5n0wQshTqlbXDgf3j6K6/+zlsxCh6+sQU1S9+eRuj8PgE0Zefxz6kDpl28E0oIXQtTak1f0I9YWdNLkXlGIRfHDjiyufn21DKlsBJLghRC11i0unI/vGMXZHaOwBZtPub13+sDdWXYmv7ZKknwDk4usQojTkmMvY97qvfy8L5eVu7JP/QLAFmKmb0Ikz1zVX+6ErSdykVUIUe+M2aN68sq0QXSODavVa+wOFynpuVz7xhqZC7YBSIIXQpyRWFswb908lEGdomv9mqyiMl7+fhfPLt4mpYj9SBK8EOKMdYsLZ8HvR3P5gLZ1et1HGzJ4ZvF2nvhii58ia9kkwQsh6s1jlyVx25iutI2sfrx8TRZuPMToZ78ndV+unyJrmSTBCyHqTawtmD9f3Juv7xvD1MHtsdQhwxzMK+WGN9dJ33w9kgQvhKh3sbZgnrt6ICl/mcDUIR0wq1O/BsBe5uLl73fx+ord/g2whZA7WYUQfhNrC+a5KQNIiLLy8ve7av26uav2kmcvIyHaKjNInQFJ8EIIv5sxqgug+GH7ETYdLDzl9mUuzUc/ZwCwMO0Qb940VMbNnwbpohFC+J0xZv4s5s4cQbc4W51em55dzAUvrmD59kw/Rdd8SYIXQjQYb6356LC6dR64NNzx7s9y8bWOJMELIRpUt7hwPr1zdJ1ujAIodboZ8o+l3PG/9VKGuJakFo0QotGk7stl+n/XUFxe9zx0Ud94/n1DtSVYWhSpRSOECEiDOsfwuzHdALDUciil1+ItR+n2yCI+WLfPD5E1DzKKRgjRqGaM6kJYsIWDucW8s3Z/nV7r0vDIZ5sZ1rWVjLKpht9a8Eqpt5RSmUqpzf46hhCi6Yu1BXP72G7cP6En943vjvXUZeZPcM/7v9R/YM2AP7to5gIT/bh/IUQz4i0/vOj+sZzTvTUhdchOWw8XyGQi1fBbgtda/wjk+Gv/QojmqVtcOO/eOpwZo7vU6XUTXlzBfR+kSi2bCqQPXggRkO4Y153dmUV8vyOrVtu7NSzceBiAdXuymX/7KH+G1yQ0+igapdRtSqkNSqkNWVm1+0EKIZq/WFswb948jO8fHMvwLrF1eu3avbmMf+GHFt9t49dx8EqpROArrXW/2mwv4+CFEDW543/r+WZL3csVdIoJ5e2Zw5rtKJuTjYOXLhohRJPw9OQBtInYwee/HKTA4fIt78Ih5gQ9Tzd1lGLMZOooOqocNAoLGrcd9s7uSN7Mj4ju1KcR30HD81sLXin1ATAOaA0cBR7TWr95stdIC14IURtDn/yWrGInz/IqU4NXY6pFZ7MbMHU+B6a+A7ZWfo+xoTTKnaxa62la6wStdZDWusOpkrsQQtTW/DtHEx8eXOvkDp5kt28lPN8V9q/3Z3gBo9EvsgohRF11iwtn3V8nUNznKtyns4P/Ta7vkAKSJHghRJMVfu1bmMb+pe5JvrwAsnb6I6SAIgleCNG0Jc/C1P2iur9u9hB4fVyzTvSS4IUQTd/0+fB4PvS6om6vO/ILfHabf2IKAJLghRDNx7Xz4LpP6/aaQ6nw97bw23f+iakRSYIXQjQvZ50PY/9St9e4SmD+Nc2uu0YSvBCi+UmeZXTZ9Lum9q9xO5tdd40keCFE8zVlTt1a84dS4fEoWPRH/8XUgCTBCyGat+RZde+XX/86vDyoyXfZSIIXQjR/Z50Pl7wC1GHi19zd8G7TviFKErwQomUYOgMez6tbos/fD6823brykuCFEC2LN9HXtm/+2BaYPbxJdtdIghdCtEzJszyt+VrI2g5L/uzfePxAErwQouUaOgPu2gBBtlNve8HT/o+nnkmCF0K0bHE9oN2AU283ewj88Jz/46lHkuCFEGLSK5AwkFNefF3xFKyf1yAh1QdJ8EIIEdcDbl8B130CynzybRfd22Tq1kiCF0IIr7POh9+vA0voybdrInVrJMELIURFcT3g9p9AnSQ9NpG6NZLghRCiqrgeMO1jsEbXvM2hVHj7ooBuyUuCF0KI6px1PnQcdvJt9q0O6PHxkuCFEKImFzwNYa1Pvk1RZsC24iXBCyFETeJ6wM3fQNuza74Z6nAavHl+QCZ5SfBCCHEycT3gjuWQOLrmbUrz4LVh8HT7gBpCKQleCCFq44KnofOomlvy2g1lRfD+lIBJ8pLghRCiNuJ6wM2La1HWQMOnNzdISKciCV4IIepi0itGSz4ksuZtHAUB0V0jCV4IIerC25K/dZlRv6am0gbe7po3xjbaBVhJ8EIIcTq89Wt+vw7i+tSwkTZG2Xx0Y4OG5iUJXgghzkRcD7hrzcmnAszaCk+2avBKlJLghRCiPgydAXetB1NQ9evdTqMS5evjGqzLRhK8EELUl7gecO18zwXYGlrzR36BN85tkDo2fk3wSqmJSqkdSqldSqk/+fNYQggREM46Hx45YLTm2w2qfhtniVHHZrZ/b47yW4JXSpmB2cBFQB9gmlKqpisRQgjRvMT1gNt+gOs+9VSlrK5F77056iq/JHl/tuCHAbu01nu01mXAfOByPx5PCCECz1nnw5/2GbNFhUSCuYbJRBbcUu+H9meCbw8cqPA8w7OsEqXUbUqpDUqpDVlZWX4MRwghGpG36+bRI0arvmrJg5jEej+kPxN8df+P6BMWaD1Haz1Eaz0kLi7Oj+EIIUSAOOt8+MshuGsDdBpt3Bk7+b/1fhhLve/xuAygY4XnHYBDfjyeEEI0LXE9YObXftu9P1vw64EeSqkuSqlg4FrgCz8eTwghRAV+a8FrrZ1KqbuBbwEz8JbWeou/jieEEKIyf3bRoLX+GvDf/x9CCCFqJHeyCiFEMyUJXgghmilJ8EII0UxJghdCiGZKaX3CvUeNRimVBeyrsKg1cKyRwjkVie30SGynR2I7PS0hts5a62rvEg2oBF+VUmqD1npIY8dRHYnt9Ehsp0diOz0tPTbpohFCiGZKErwQQjRTgZ7g5zR2ACchsZ0eie30SGynp0XHFtB98EIIIU5foLfghRBCnCZJ8EII0Uw1aoJXSnVUSv2glNqmlNqilLrPs/xqz3O3UmpIldc84pnEe4dS6sJGiO15pdR2pdQmpdRnSqnoAIrt75640pRSS5RS7TzLlVLqFU9sm5RSNcwE7L/YKqx/SCmllVKtGzK2k5yzx5VSBz3nLE0pdXGF1zTqz9Oz7h7P8bcopZ4LlNiUUh9WOGfpSqm0AIptoFJqrSe2DUqpYZ7ljf53oJQaoJRao5T6VSn1pVIqssJr6v+8aa0b7QtIAAZ5HkcAv2FM0N0b6AksB4ZU2L4PsBEIAboAuwFzA8d2AWDxLP8/4P8CKLbICtvcC7zueXwxsBhjlq0RwLqG/pl6nnfEKB+9D2jdkLGd5Jw9DjxUzfaB8PNMBr4DQjzr2gRKbFW2+Sfwt0CJDVgCXFTh92t5oPwdYMyTMdazfCbwd3+et0ZtwWutD2utUz2PC4FtQHut9Tat9Y5qXnI5MF9r7dBa7wV2YUzu3ZCxLdFaOz2brcWYqSpQYiuosJmN41MkXg68ow1rgWilVEJDxuZZ/RIwi8pTNzZIbKeIqzqN/vME7gSe1Vo7POsyAyg2wGgVA1OBDwIoNg14W8ZRHJ9JLhD+DnoCP3o2WwpcVSG2ej9vAdMHr5RKBM4G1p1ks1pN5F3fThLbTIwWQcDEppR6Sil1ALge+FugxKaUugw4qLXeWGWzBo+tmp/n3Z5/2d9SSsU0VlzVxHYWcK5Sap1SaoVSamgAxeZ1LnBUa70zgGK7H3je83fwAvBIAMW2GbjMs+pqjk9r6pfYAiLBK6XCgU+B+6u0Qk/YtJplfh3nWVNsSqm/AE7gvUCKTWv9F611R09cdwdCbBjn6S8c/8CptGk1y/wWWzXn7N9AN2AgcBiju6HB46ohNgsQg9Gd8DDwkafFHAixeU3jeOudAIntTuABz9/BA8CbARTbTOAupdTPGF03Zf6MrdETvFIqCOMEvKe1XnCKzRt0Iu+aYlNKzQAmAddrTwdaoMRWwfsc//evsWPrhtGvuFEple45fqpSqm1DxlbdOdNaH9Vau7TWbuA/HP+3uLHPmTeGBZ4uhRTAjVGgKhBiQyllASYDH1bYPBBimwF4H39MAP1MtdbbtdYXaK0HY3ww7vZrbGfaiX8mXxifWu8A/6ph/XIqX2TtS+ULEXvw3wWcamMDJgJbgbgqywMhth4VHt8DfOJ5fAmVLy6lNNbP1LNNOscvsjZIbCc5ZwkVHj+A0Q8aKD/PO4AnPY/PwvgXXgVCbJ51E4EVVZY1emwY/d3jPI/HAz835O/aKWLzXig3edbP9Od588ubq8NJOAfj35BNQJrn62LgSoxPNAdwFPi2wmv+gvGptwPPlfIGjm2X5w/Nu+z1AIrtU4w+vk3AlxgXXr2/bLM9sf1KhQ/NhoqtyjbpHE/wDRLbSc7Z/zzH3QR8QeWE39g/z2DgXc/PNBU4L1Bi86ybC9xRzWsa+7ydA/yMkTDXAYMD5e8AuA9jRM1vwLN4qgn467xJqQIhhGimGr0PXgghhH9IghdCiGZKErwQQjRTkuCFEKKZkgQvhBDNlCR4cdqUUh94bvF/wE/7v18pFeaPfdcnpdQVSqk+fty/y1MZsZ1S6j6l1L8qrHtDKfVdhef3KKVeqbJ+dB2PZ1FKLVJKHVNK9auyrtpqqkqpc5VSW5VSm0//nYr6Jgle1JknAbQFRmmt+2utX/LToe4HAiLBK6XMJ1l9BUY1wLrsz1KHzUu01gO11oeA1cCoCusGAlEV4hsFrKqwfjhGUby6+DfGWOzLgQ+VUh0qrFsK9NNa98cYy/0IgNb6J4xx3iKASIJvoZRSNk8rbaNSarNS6hrP8nR1vFb7EKXUcs/jx5VSc5RSSzDuwFsCtPG0LM9VSv1OKbXes79PvS1vpVS8p6W30fM1yrN8ulIqxfP6N6omUKXUvUA74Ael1A+eZRd4ammnKqU+9tT58Mb8tGfdBqXUIKXUt0qp3UqpOzzbjFNK/eiJZatS6nWllKkW+/2bUmolcHV179Hzfi7DKG6VppTqppRarjzzGCilWnvKM6CUusmz/y895w+l1MOefW5SSj1Rix/dL8BZSqlQpVQUUIxxE02SZ/0ojA8BlFK9gd+01i5PTC95zsE2pdRQpdQCpdROpdQ/Kpz3x4B8rfUftNargFuBDzzHQtdcTVUEIn/dySVfgf2FUafmPxWeR3m+p3P8LtMhHK+l/TjG3YGhnueJwOYKr29V4fE/gHs8jz/EKLQEYMYo39ob407bIM/y14Abq4mxYiytMcqs2jzP/8jxGuTpwJ2exy9h3D0YAcQBmZ7l44BSoKsnjqXAlFrsd1Yt3uNcYEqFdcvx3CXp2X+65/FNGHdox3qeX4Ax8bLCaGx9BYyp5jwUpnMR8wAAA2RJREFUVXm+HBgDXIhxN+QtwO8xPhD3V9juDxy/FX45x+cuuA+jzkkCxq3xGRXfWx1+h74Epld4Xul3Qr4a/6su/yaK5uVX4AWl1P8BX2njX+xT+UJrXVLDun6elmA0EI4xsQfAecCNAFprF5CvlLoBGAysV0oBhAKZJ+yxshEY3SCrPK8JBtZUjK3C+wrXRg3uQqVUqTo+61aK1noPGNcPMG4nLz3FfisW0qrpPdbFUq11jufxBZ6vXzzPw4EeHK8XXpNVGC31UE+sO4E/A1l4Wu8eFwI3V3he8Rxt0VofBlBK7cEodJVd2zehTqymKgKQJPgWSmv9m1JqMEa/6TNKqSVa6ycx/mi9XXfWKi+zn2SXc4ErtNYblVI3YbSYa6KAeVrrR06yTXWvWaq1nlbDeofnu7vCY+9z7+951bocuhb7rfie51K791jbc6iAZ7TWb9Swn5qsBm737Hs2RmLv4/m+CsDTRRatjX57r9qco1NSx6upjteeprsITNIH30IpY77WYq31uxiTInjnp0zHaF3D8XLDtREBHFZGidTrKyz/HqM+N0opszLmoPwemKKUauNZHquU6lzNPgs9+wWjv3e0Uqq75zVhSqmz6hAfwDClVBdP3/s1wMo67rem91gxTqh8DqecJJ5vgZkV+vzbe8/JKazG+I8mTmud6UmyWRgXRb0t+GTgh1rsq06UUhMxurEu01oX1/f+Rf2SBN9yJQEpypgs+S8YfcoATwAvK6V+Alx12N+jGJX7lgLbKyy/D0hWSv2K0YffV2v9/9u7Y5QIYiiM4/+v39rCStjGwsrGSrAVvIgH2M4DeAAL8QJaCJbKWtjtWq0gaOsBFASxs3gWL40yyzjijhK/Xz0veTPFS0iG5B7YA8aSbktM09VpR8C5pKuIeCTXsI9LzDWw2iE/yOWMffJ0xgfgrGO7897xBBhJupE0JAfMXUkTcg2+UUSMyXP7p+X7nPJxoJgX90wW9LtP77ZEnqAIsA1ctLX1DQdkjpdlU/lwAX3YD/FpkvYvSNoiL9fe+e1cupL0GhGDjjEzYCMi3haUVlOfK+R+zlrLo9YTz+DN/r6XMlte/mpARKz3XNw3yb9qnvrq09p5Bm9mVinP4M3MKuUCb2ZWKRd4M7NKucCbmVXKBd7MrFLvgHouv/S8vKUAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "pltsize=2\n",
+ "\n",
+ "print(msit3.shape)\n",
+ "print(sit3.shape)\n",
+ "print(menergy3.shape)\n",
+ "\n",
+ "print(np.corrcoef(msit1,menergy1)[1,0])\n",
+ "print(np.corrcoef(msit2,menergy2)[1,0])\n",
+ "print(np.corrcoef(msit3,menergy3)[1,0])\n",
+ "\n",
+ "# far - sit\n",
+ "fig, ax = plt.subplots()\n",
+ "plt.plot(msit1, menergy1,'.',markersize=pltsize)\n",
+ "plt.plot(msit4, menergy4,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, menergy2,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, menergy3,'.',markersize=pltsize)\n",
+ "plt.grid()\n",
+ "plt.xlim(0,5)\n",
+ "\n",
+ "ylim=plt.ylim(0,8.2)\n",
+ "plt.xlabel(\"$h_I$ [m]\")\n",
+ "plt.ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2,markerscale=6)\n",
+ "\n",
+ "\n",
+ "ax2 = ax.twinx()\n",
+ "co2_fac=np.linspace(1,5,9)\n",
+ "print(plt.ylim())\n",
+ "\n",
+ "np.exp(menergy1/alpha)\n",
+ "\n",
+ "ax2.set_yticks(np.log(co2_fac)*alpha)\n",
+ "ax2.set_ylim(0,8.2)\n",
+ "_=ax2.set_yticklabels(co2_fac)\n",
+ "plt.ylabel(\"equivalent CO$_2$ increase\")\n",
+ "plt.savefig(\"plots/heatflux_scatter_flux_sit.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.show() \n",
+ "\n",
+ "plt.plot(msic1, msit1,'.',markersize=pltsize)\n",
+ "plt.plot(msic4, msit4,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, msit2,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, msit3,'.',markersize=pltsize)\n",
+ "\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"sit [m]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(msic1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msic4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "#plt.ylim(1,3.1)\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(msit1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msit4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(menergy1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"heat flux [W/m^2]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(mts1, menergy1,'.',markersize=pltsize)\n",
+ "plt.plot(mts4, menergy4,'.',markersize=pltsize)\n",
+ "plt.plot(mts2, menergy2,'.',markersize=pltsize)\n",
+ "plt.plot(mts3, menergy3,'.',markersize=pltsize)\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.xlabel(\"surface temperature [K]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(mts1, msit1,'.',markersize=pltsize)\n",
+ "plt.plot(mts4, msit4,'.',markersize=pltsize)\n",
+ "plt.plot(mts2, msit2,'.',markersize=pltsize)\n",
+ "plt.plot(mts3, msit3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"surface temperature [W/m^2]\")\n",
+ "plt.ylabel(\"sit [m]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.9938529939485001\n",
+ "0.8676139722084588\n",
+ "0.9821811371639458\n",
+ "(0.0, 1.0)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "ylim=(0,6)\n",
+ "# far - icelat\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "print(np.corrcoef(msic1,menergy1)[1,0])\n",
+ "print(np.corrcoef(msic2,menergy2)[1,0])\n",
+ "print(np.corrcoef(msic3,menergy3)[1,0])\n",
+ "plt.scatter(ymsic1, ymenergy1,marker='o',s=6)\n",
+ "plt.scatter(ymsic4, ymenergy4,marker='o',s=6)\n",
+ "plt.scatter(ymsic2, ymenergy2,marker='o',s=6)\n",
+ "plt.scatter(ymsic3, ymenergy3,marker='o',s=6)\n",
+ "\n",
+ "ax.set_xticks([1-np.sin(np.radians(0)),1-np.sin(np.radians(10)),1-np.sin(np.radians(20)),1-np.sin(np.radians(30)),1-np.sin(np.radians(45)),1-np.sin(np.radians(60)),1-np.sin(np.radians(90))])\n",
+ "ax.set_xticklabels([0,10,20,30,45,60,90])\n",
+ "\n",
+ "plt.xlim(0,1.01)\n",
+ "\n",
+ "plt.ylim(ylim)\n",
+ "plt.xlabel(\"Ice-Edge Latitude [°]\")\n",
+ "plt.ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "#plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ "# ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ "# borderpad=0.5,borderaxespad=0.2,markerscale=2)\n",
+ "legend_color(ax,[\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],2)\n",
+ "\n",
+ "ax2 = ax.twinx()\n",
+ "co2_fac=np.linspace(1,5,9)\n",
+ "print(plt.ylim())\n",
+ "\n",
+ "np.exp(menergy1/alpha)\n",
+ "\n",
+ "ax2.set_yticks(np.log(co2_fac)*alpha)\n",
+ "ax2.set_ylim(ylim)\n",
+ "_=ax2.set_yticklabels(co2_fac)\n",
+ "plt.ylabel(\"Equivalent CO$_2$ Increase []\")\n",
+ "\n",
+ "#ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax2.spines['top'].set_color('none')\n",
+ "\n",
+ "plt.savefig(\"plots/heatflux_scatter_flux_icelat.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(2412, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ 48.539627 50.596096 53.38318 ... 219.82147 218.7206 217.7329 ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "ts1_sic = ts1\n",
+ "ts1_sic[sic1<1]=0\n",
+ "mts1_sic = np.pi/2* np.dot(ts1_sic,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "\n",
+ "print(np.shape(ts1_sic))\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, ts1_sic)\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "#plt.plot(da1.time,mts1)\n",
+ "#plt.plot(da1.time,mts1_sic)\n",
+ "print(mts1_sic)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.9773656235942157\n",
+ "0.9704530181574433\n",
+ "0.9820133574839562\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(msit1, -mqbot1,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, -mqbot2,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, -mqbot3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.corrcoef(msic1,-mqbot1)[1,0])\n",
+ "print(np.corrcoef(msic2,-mqbot2)[1,0])\n",
+ "print(np.corrcoef(msic3,-mqbot3)[1,0])\n",
+ "plt.plot(msic1, -mqbot1,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, -mqbot2,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, -mqbot3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show() \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b763180cda0>]"
+ ]
+ },
+ "execution_count": 16,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(da1.time,menergy1)\n",
+ "plt.plot(da2.time,menergy2)\n",
+ "plt.plot(da3.time,menergy3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 504x504 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "fig1, (ax1, ax2) = plt.subplots(2, 1, sharex=False,figsize=(7,7))\n",
+ "ax1.plot(yice_lat1)\n",
+ "ax1.plot(yice_lat4)\n",
+ "ax1.plot(yice_lat2)\n",
+ "ax1.plot(yice_lat3)\n",
+ "\n",
+ "ax1.set_ylim(0,90)\n",
+ "ax1.set_xlim(0,210)\n",
+ "ax1.set_xlabel(\"time [years]\")\n",
+ "ax1.set_ylabel(\"ice latitude [°]\")\n",
+ "ax1.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2)\n",
+ "ax1.text(-0.1,1,\"a)\", transform=ax1.transAxes, fontsize=14)\n",
+ "#plt.title(\"hice_5m: global sea ice border \")\n",
+ "\n",
+ "\n",
+ "ax2.plot(ymenergy1)\n",
+ "ax2.plot(ymenergy4)\n",
+ "ax2.plot(ymenergy2)\n",
+ "ax2.plot(ymenergy3)\n",
+ "\n",
+ "ax2.set_xlabel(\"time [years]\")\n",
+ "ax2.set_ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "ax2.set_ylim(0,6)\n",
+ "ax2.set_xlim(0,210)\n",
+ "ax2.text(-0.1,1,\"b)\", transform=ax2.transAxes, fontsize=14)\n",
+ "plt.savefig(\"plots/hice5m_sic_qbot.svg\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[3.19146303e+02 5.37758229e-01 1.06490622e+03]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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KoMruJCEmnPySKobvf4eZIW+xI3wCNxyey22DLYxLjMHhMiQnxnKXLgAMWKOTh4jcAczHXQJ9J+6qul/i7okopVSr8q8/BbBo/T7A8Hz8p8wuf4vMuBTkR68zcW0e1bUutuaWMH/KYOZMSNSih6chkJ7HfNwbNm02xqSIyDnAk80TllJKBca//lRuYSUJ0WH8wvI2V5d/wN4ePyLomj/zwr/3sCGriISYcM9VRosenqZAkke1MaZaRBCRTsaYPSIytNkiU0qpRiqutLN40z6q7C4Wb8plS7aVeRWvcHXwGj4KmcHP837MpR/vZUOWe+ZVfkkVKUPjmTNhgO8zdIZVYAJJHgc8iwT/BawWkRJ0Bz+lVBuwPC2fhWuyAAjCyRtd/8alwan8xXUFz5TfyEVJ3UiIiWB0P/c65/rjHNrjCFwgs62u9rx8QkRSga7AJ80SlVJKBWB2cgLvbt3PoaIy/hr5KhfXbOb52ut5xTmLxLhIRIQlm7+fXfXD4T11fOMMNaaq7lvGmJtFZL4xZiGAMWZt84emlFIn531cBcJTMwYS9uEtjHPuZHXCg5THXcf4I+UAbMgqJDEugouHxBMTEaqPqJpAY3oeY0SkP/AzEVlCva1ntbKuUqq1eB9XdaGCqZF/YLhjNw875rI8cywpFhsXDIxj4ZpMkuIjybZW8uPocH1E1UQakzxew/14aiCwnbrJw3jalVKqxc1OTkDKDzFj52P0qM3nT7GPEjPoSiYWHCM1w8rIvl15dMY5TB3WQ8uONLHGlGR/GXhZRF41xtzdAjEppdRxi/7812J4j83oVc6N395BJ1cZL8T/lutvuImk+Kg613rHNrTsSNMKZMBcE4dSqsV411/Y7A6+OVBGaoaVNbuPEBocxLDeXdiy/r/8JPz3VDvhx/YF7DqQwN6V6SyYOczXy9BB8eajVXGVUm3S2MRYkuIjKSitJjXDSkxECFtzSwA4t3IL74f/FqJ6sHzQi4xx9aQy00pqhhVI9/ypU3CbkyYPpVSb9MfPM8m2VuJwugsclthqSYgJZ0zZah4peZ2iyCQ+HLqQ2Zcmszwtn9wiGylD41kwcxgXDNTxjeamyUMp1eq8YxTege2xibFU1jgYPyCWuy9J4i/rcxjepyu3mJX03fZncjuPYab1birWl2AL3edbKe59VKXjG80v4OQhItOA64FXjDE7RWSuMWZR04emlDpbeMc3Pt9zhC37SujdNYxDZdVclBRHxpFyvsy28ktZTN8D7/Af5ziyR7zAqHybp9yIEBsZqo+oWtjp9DzuAW4DFnh2ExzVtCEppc423kdMn+85CoDLuB9VJXWPYtrgLiRvfpWRBzZSPWYuBzvfyU1jE7kJ6szGUi3LchrXWI0xpcaY/wEuw11pVymlTltspHvV93l9uzJxUDcuG9YTgD7B5US8cyXn2zaROuAhwq54nuvGukuol9jsrRz12S2Q/TzCgEFAnoiEGWOqjTGPiMj9AVy/Dujkue/7xphfi8gAYCkQC+wAbjbG2EWkE7AEGAMUATcYY3I9n/UocDvgBB4wxnza2N9DKdW2eEuMbM8rZUNWoW9RX9WhdG74+iEiHcXMq32QYb1v5DzPvuSpGVbW7bWyMbsIm93Bg9O0wHdLO2XPQ0SCReR3wAFgMXAdkC8ivxOREGPMHxt5rxpgsjHmPNyPuqaLyAXAc8BLxpjBQAnupIDnzxJjzCDgJc95iMgw4EZgODAd+LOIBDUyBqVUG+MtMbIhq5CUofHMTk4gfeNKFhyZT22NjafinmdYyo+5clRvX+JIGRrP8D5dPZ8gJ/181Twa0/N4HugMDDDGlAOISBfg956f+Y25kTHGABWetyGeH4N7J8KfeNoXA08ArwKzPK8B3gf+JCLiaV9qjKkB9olIFjAO966GSql2ZnZyAja7AxCuHNWbnStfZWbGbyiO6MszXZ/kX7nBpESUUmV3kpphZeKgOF643j3UGhepRQ5bS2PGPGYCd3oTB4Ax5hhwN3B5IDcTkSAR2QkcBVYD2UCpMcbhOeUA0Mfzug+Q77mfAygD4vzbG7jG/15zRSRNRNKsVmsgYSqlWkhxpZ3Xvshie14pV57Xi5L/PMXk3Y+zK2Q47418g/uvnULK0HhSM6ykF5QBMKxXV5anuf8KmKd7j7eaxvQ8jKfXUL/RKSLHtZ/ig5zAKM+mUh8C5zZ0mufPhvqi5iTt9e+1CFgEkJycHFCcSqnm47/rX3rBMTZkFRJGDdY3n+aCqnWsi5jG7cU3U7v2MNsOO32L/rxrQGx2p24b2wY0Jnmki8gtxpgl/o0ichOw5wTXnJQxplREvgAuAKJFJNjTu+jL97sTHgAScO9gGIx786liv3Yv/2uUUm1M/SKF/rv+Afwwwcn/lv6WAVVZ/Lb2x4SP+jn3iLA9r5TUDCsXDDziSxJJl7iLHkaEBunjqlbWmORxL/BPEfkZ7pLsBvf03HDg6pNd6E9E4oFaT+IIB6biHgRPxT0IvxSYA3zkuWSF5/2XnuOfG2OMiKwA3hGRF4HewGBga2PjUEq1nGK/2VE2u4OI0GCmDuvBO1v2k1ds47Ku+bxQ+jwhTht32B/CPvAyXr5oYJ3KufWThC4IbBsaU5L9IDBeRCbjnuEkwCpjzJoA79ULWOyZGWUBlhljVopIOrBURJ4GvgLe8Jz/BvCWZ0C8GPcMK4wxu0RkGZAOOIB7PY/DlFJtzPK0fN/sKBCeXbWHoooaenTpxLWhX3J32UsUOLvycvcX+fxAFyb6PYHWJNG2SQPDGXVPEBkE9DDGbKzXPgk4ZIzJbsb4mkRycrJJS0tr7TCUOmvUr1U1OzmB3MJKHn7/a6JChGlH3+C+4I840OV8rjg6j6iYHvSODmfLvmLmTxlERGiwllRvA0RkuzEmuaFjjZlt9QegvIH2Ks8xpZSqY/GmXJ5dtYdff7TLlwT++Hkmh62FPFT6DPcFf8TqsB/yj8Ev0zWuJ/klVQRbhEdnnIO3h+KdUaXapsaMeSQaY76p32iMSRORxCaPSCnVAbifaGzIKmTxpn1EhAZz13AXT+T/mn7mEO/E3M1jBRNhYz5zJw0g82gFC2YO8+0CqAPibV9jkkfYSY6FN1UgSqmOobjSXXNq7qSBAGzPKyU85xNu7vQaVa4gnu/xf1w7+6fM33mQkspa0gvKeXLWcJLi3WXUdayjfWjMY6ttInJn/UYRuR337CullPLxTsWNiwqlW2QQ43L/zF9CX6Q0vD9P9XqVP+/vy9Mr05kzYQD5JTY2ZBXy9Mr01g5bBagxPY+fAx+KyE/5PlkkA6EEMFVXKdVx+Q+Q2+wO5k4aiNNWwq0FTxMRnMp33a/k2v3XkBwTz8RBQmqGleVp+SyYOQxI9/yp2pPGTNU9AkwQkRRghKf5P8aYz5s1MqVUu+HdzGlzThGpGVamxVpZUPEMIZZi9l/4DKtlKmNDy9iQVcjcSQMICRKmDutBUnwUb942rrXDV6eh0SXZjTGpuBf0KaUUULfHATB1WA8uqPwTt1hfoNwSyfU1v+LYdyPItmYzf8ogJg3uhs1T4HBk34M6Jbcd0z3MlVIB8yYNm93JwjWZ2OwOglw1VHzwAPMKP6Ag+nys018nenMZv5o8mG25xb4k4Z1NpTWq2jdNHkqpRqufNOZOGkDK0HjCyvOYtPNhRlhyWRF5HfuGPcTN/Qbw5rnuHkVit8g69a3mXZKkU3LbOU0eSqlTqp805k8ZxKMzzsFmd9Ip8z/cHLoIE2Th9pqHWFM9BlL34bIE+Xb4846JwPe9DJ2S274Fsg3tc8aYX56qTSnVsfgXN7woKY75UwZzyZB4Xl2zi2cil9M99O985RrE/0X+L1uqokiICSe/pAr/3RO8vQvtZXQcgfQ8pgH1E8WMBtqUUh2It7hhUnwkG7OLCA22sD87nXsPPUl3Sw5be9zIK8E38cvLRrAtt7hOPSsv7WV0PKdMHiJyN3APMFBE/MuUdAY2NVdgSqnWV1xpx2Z3MH/KYK4c1ZunV6YTnLmK34b/BVeQi99H/4o/5Z1LytBOJHaLZHT/GMC974bq2BrT83gHWAU8Czzi115ujClulqiUUq2ifjVc9xhHFvOnDCL12zx+F76E+NC3qIz+AU92ephlOcEkxUf6Fv1p7+Ls0ZhFgmVAmYjcBlwDJHqvExGMMU81a4RKqWZXf0B8WVo+2dZKxiXGMHFQN6LKMpj0zaPEWw6wyPEj/llzG3sO2kkZGs+CmcOOe0ylOr5Axjz+BZThLlFS0zzhKKVaknc/8e15pWzIKmT+lEGkDI33jXFszS1mTtB/uS30XSqDI7m5+hEOxV1ItrWSpPhIXyVcfUx19gkkefQ1xkxvtkiUUi3KfxYVQMrQeK4c1QeAkX2juXpIKKXv3smo6q1kdrmINUN+xejQOJ7wjH2kZlj5LP2IJo6zVCDJY5OI/MAY822zRaOUanb1exsXJcUxvHdXwkODeG9rPovW5/DiaCuJy57BVVvGP2LuZf+gm1i0fh/zp8TyWfoRFswcxgUD9VHV2SyQ5DERuE1EcnA/thLAGGNGNktkSqkmV7+3cVFSHMmJsQAsXJNJSlJnFgS/xTXpqyiOTGLlDxby+GbD3EHunklVrYuFa7SkiAosecxotiiUUs2u/mI//6Qxf8ognhlfy2UZDxAfvI/VkVdwX9G1JEfHMn+K+zx3McOuPDrjHO1xqICSx37gp8BAY8xTItIP6AnkNUtkSqkz5p1FNTs5wbfYL2VoPC9cP8pXpDAq2MW1Vcvo8vVLFJouPBLxa5YWDSU2MoSN2UVcPCSe2ckJvjpUWgFXQWDJ48+AC5gMPAWUAx8AY5shLqVUE/CvKTU7OYGiihrSC8opsdmJjQwl1pbLbRnzCD68k385J/B65N3sLgkiMS6C3CIbFyXFYbM7AX1MpeoKJHmMN8aMFpGvAIwxJSKi/wRRqg2rX1NqzZ6jZFsr+fWH33BPxGdcmPsKtRLG/fb5rHKNZ3xMLJQWc/HgeAZ0szG4R2cWrskkIjRIk4eqI5DkUSsiQYABEJF43D0RpVQbFRsZ6ntkVVRhJ9tayQUx5fzm2PMMOPQVmV0v4vMh/48EYpkfGsSVo3r7VpYv2ZynYxzqhAJJHi8DHwLdReQZ4DpgQbNEpZQ6Lf5jHN4xDe8g+aSkGG4KWs3jNe9hgIdr55IdOosd60uZP6UbD04bArjrUvnvtaFjHKohgWxD+7aIbAem4J6me5UxZnezRaaUCtjiTbksXJPJ+sxCXv7x+b5B8mv6V/PzY4/RL+QrcqLG8WKne1iZH8r4YIvnSqnzOVoFV51KQJtBGWP2AHuaKRal1BkorrSTluuuVbohq5CHlu1kweVDODfnS8bnvU61CebZ0Pt4/eiFgGhdKnVGGlOSvRzPOEf9Q7gXCXZp8qiUUgHJtlYwd0ka2dZKEuMi6NEljIK92+lcPJ+Ly9P51JnMgtrbsNbEkBgXwcVD4omJCCUmQnsY6vRYTnWCMaazMaZLAz+dA0kcIpIgIqkisltEdonIfE/7EyJyUER2en4u97vmURHJEpEMEfmhX/t0T1uWiDzS0P2UOlsUV9p9iSM6IphDRWXcJ8v4T9gCujmtHP7ha7zR+ykS+g1g/IBYcots5BfbWLgmk+Vp+a0dvmqnAnpsJSIxwGAgzNtmjFnXyMsdwEPGmB0i0hnYLiKrPcdeMsb8vt69hgE3AsOB3sBnIjLEc/gV3DsbHgC2icgKY0x6IL+LUu1R/f02ZicnsHhTrq/H8dPeR7g44zcMPXSAmmGzeTf2bkoqOrM1L9M3a8p7vdamUmcikD3M7wDmA32BncAFwJe4Fw2ekjGmACjwvC4Xkd1An5NcMgtYaoypAfaJSBYwznMsyxiT44lrqedcTR6qw1u8aR8L12SxPtPKhqwiNucUkRATQRcqeCniPc7P/IjikHgKpi9haem5LPwsk7mTInyJw38gXKvhqjNxysdWfubjXk2eZ4xJAc4HrKdzUxFJ9Fy/xdN0n4h8IyJ/8/RuwJ1Y/PvUBzxtJ2qvf4+5IpImImlW62mFqVSbUVxp56XVGWzOcQ+I1zoNEwd1IzXjKKHpy/m80/8w0vpvPo66lomVz7HCNgLvUGV4qB2Hgz0AACAASURBVIV5lyTplFvVpAJ5bFVtjKkWEUSkkzFmj4gMDfSGIhKFu6zJz40xx0TkVeA3uP+f/hvgBeBn1J876GZoOOEdN6BvjFkELAJITk5uaMBfqXZjeVo+C9dkARAbGcKWfcU8cWEI/8/6POfW7CQ9aAi3VN1KenUiKUPdtahKbHa+OVDm26NDqaYUSM/jgIhE495RcLWIfAQcCuRmIhKCO3G8bYz5J4Ax5ogxxmmMcQF/4ftHUwcA/weyfT33O1G7Uh1StrWCdXutXJ/cl8S4CCorK3kxfiU37fwJQ0wO64Y8RvUtnxAzcAxzLx7oK3q4YudBUjOsrNh5sLV/BdUBBbJI8GrPyydEJBXoCnzS2OtFRIA3gN3GmBf92nt5xkMArga+87xeAbwjIi/iHjAfDGzF3SMZLCIDgIO4B9V/0tg4lGpvnl6ZzsbsIhLjInjw2O+YFbYJyuFD50XsP+8xtlqDcXy6ly37iklOjPGtMP++895QJ16pMxPIgPmDwHJjzAFjzNrTuNdFwM3AtyKy09P2GPBjERmF+9FTLjAPwBizS0SW4R4IdwD3GmOcnljuAz4FgoC/GWN2nUY8SrU5/uVFSmx2nl6ZzpwLE+lWW8Bdx54mKSgNgPeHv0J+9Fi255WyMbsQgKT4yDqbNc2ZkOgrMaJUUwtkzKML8KmIFANLgfeNMUcae7ExZgMN/xPo45Nc8wzwTAPtH5/sOqXaC++WsCBc6bc3OMC6vVa2Zx/ikoN/5Xd8BGIhMy6Fl0Lv4uPtTlKGlvGLaUOwO5wUlFWTba1k5khLgzOrlGpqgTy2ehJ4UkRGAjcAa0XkgDFmarNFp1QH5z8QnpZb7Hs8NfXc7sTnf8JznV6kr6OQDWGXsiz6Tnr2S+LjdTkkxUf6ksyFSd3cW8gOjWfOhAE6q0q1iIAWCXocBQ4DRUD3pg1HqY6vfm/DZndQUllLasZRAEKK9xLy9tNcU5bGkYhB/CbqEd7I7w2lMI4Sd5K4MJEn/r2L1Awrg7tH1eltKNUSAhnzuBt3jyMeeB+4U1d1K3Vq9ccxvKVEACJCg3hw2lBue3MrZSWFPB32T37Mp9grolhQexsF/W7g3inn8O2q3ThcBhHx9Thyi2wAhIcG6+Mp1eIC6Xn0x702Y+cpz1RK+Xi3grXZHaz8poBsayUJMeH0jg7nYGkVCz/dxWNxa4kP+wNdTCXvOCdTPu6X7Dto2Li3iBpXBltz3T2O1AwrSfGR3D95MCP7dgWEORMSW/tXVGehQMY8tAChUqdhdnICNruDzTnFZFsriYkI4cKkOJal5ROd9ym3Br/LQMthNjiH80bE7dhih/HbscOpDjnExuwiBnaLIiTIwv2TBwOQmmFlW24xD04LeI2uUk2mMSXZNxhjJvqVZvefMaUl2ZU6hdjIUCJCg9myz11apMRWS3DBDt4LfY3xlj1kuvrwVOdf82HFcErKHFBWzGfpR3xTbb1bwl4wMI4Xrh/lt45DqdZzyuRhjJno+bNz84ejVMdQv/rt1GE9WLP7CAdz9/JwyHtcVbSJsuCu/L+an7E1ZiaZ1mrAQWJcBJcN64nN7gRg3iVJx20Jq+Mbqi0IZMD88YbajTFPNV04SrUPDe0V7v/efzvYDVmFRJSks+zwTRAGNYTyiuNKtva+BWdoF56bNoSlW/NYvfsoT1wxnIwj5Ty7ag8RoUG+goaaMFRbE8iAeaXf6zBgJqB7mKuzkv8geERoMEUVdhatz8Fmd3DJkO4s/nIfAOdGlPGPsJ+4NzHw+MvIZWwvi2RthhUoZEz/aKwVdkpstSz+MpcXrh8FoI+mVJsWyID5C/7vReT3uOtPKXVWKa60Y7M7mD/FPYD97Ko99I+NAGB52gFeX5tDsKOC3LA7YO/31/3VMYPFneeSEhTP4O7usYwt+4rZnlfqWSnuYnAP99Nh7Wmotu50Fgl6RQADmyoQpdqD4ko7Dy3bSWqGlflTBlFld5IQE05esY2YiBCOllWQFXZLnf+yvu6UzNuDX+TL7CLyS6pY8mUeAHMnDSDYImzIcvc+Lh4Sz7Or9hCnj6lUOxDImMe3fL9vRhDuxYK/aY6glGqrFm/KJTXDSkJMOOszC9mxv9RzxPBv5tM37PvdAQ6aOFam/Jd5lw7iP/9JJ7+kqs5nhYcGk5wYy8bsIkB8j6n0cZVqDwLpecz0e+0AjhhjHE0cj1JtkndAvKTSDkB+SZUnGRgutKTzbugz4Pr+/MHVSxiX1IPkWhfFlXbSC8oBSIgJZ8aIXoSHBvkW9+lMKtUeBZI8rq3f4N6iw81/jw6lOoLiSjuvfZHF1wfKqHW62LG/lISYcADGJ8YwOSyDcXmLON+vSs/I6kUcI4rYyBCG9+nKwjWZRIQG8YtpQygoq+L5685jdP+YOvfRhKHao0CSRzLuPcy9g+RXAOuou5+4Uh2C/9iGv/ySKqaE7eYXRR8yvPY7DpsYHnfMoSDpeh65YhQ3bt3Pqu8Ok19SRVpuEaP7RfP5nqMUVdrJtlbyx88zfTv9KdWeBZI8ugGjjTHlACLyBO7Noe5ojsCUamn+C/u8+2p0ChZqHIbR/aKZ2TmbH2S/yljSOWKP5sWQ21lhmUZ1pxAO7y2jaPlOIkJDSBnanSWb89ixv8z32cEW8dWmWp6Wr70N1e4Fkjz6AXa/93YgsUmjUaqFecujV9ldpBccY0NWIa+uzaLU5iAmIoQSm505Yeu4sWQ95x5N54iJ5gnHLfwn5DKsFRbcAx01AL5kcaDExtxJ7omI1bVOcgor+cW0Iazde5SRfaN1QFx1CIEkj7eArSLyIe5ZV1cDS5olKqVaiP9mTADBFii1OQBDiuzgzrClnMs+qIUnam/hXedkhvfrztX9Y1n1XQH5JVX0jQ6nT0w4W/YV0zU8mNwiG+GhljqFC19fm83CNVk8OuMcfWSlOoRAFgk+IyKrgEmeptuMMV81T1hKtYypw3qwbq+VpO5RrNtrJb+onCstW7gvZAVDnPs5YLrxHlP5vbkJq9P9l/7hsmoWrc9hWM9IEuMiePH6USR2i2R5Wj5FlXYWrcuh/o7LOg1XdTSBrPMQYBjQ1RjzlIj0E5FxxpitzReeUs3D+7hqe14pG7OLCDF27u+ynnGV/yCBI+TQh4fsd/GRawIOv/9MEmLCfes10g+7K/Zsyy1mdP8YXxHDuMjQ45KETsNVHU0gj63+jPsB72TgKaAc+AD3DCyl2oVsawWP/+s7qmqd7NhfSiRV3B+Wyk0HV9JDStnpGsjTjgf5r2sMBgsWYFivziQnxhIWHMTXB0rJL6kiISaclKHdiamXKDRJqLNFIMljvDFmtIh8BWCMKRERfXir2gVvT+OjnYfILbIRTwkPBa/m5qDVRFPJRtdwfmnu4QvHcCJDgjEuJ52CLdQ4XNQ4XMyZkMjTK9PZsq+YlKHxOt1WnfUCSR61IhKEp0SJiMRTZ02tUm2PN2lszilmy75izpH9LAz7hOlmAyHiZJ2M5aXqmXxtBvmuiQoLprLWyZDukRyrdpJtreTXH+1iQ1ahJg6lPAJJHi8DHwLdReQZ4DpgQbNEpdQZ8CaMkspa1mVayS2q5BLLNywJ+ZiLg77FGRzO6tAZPFuSQp7pCcDIPl0osdVy4cA4sqwVHCmvIaJTCBcmxbsHx3t1ZtLgbr4yIkqd7QKZbfW2iGwHpuCeSnKVMUb381BthneRn83uZOGaLDphZ1bQRt4M/4QBJh8rsTxXeyP5fWdzyB5OXrG7qGFCTDhHK+wcLqvGlV3IwdJquoa7t409r29XHp1xjiYNpeoJqCS7MWYPsKeZYlEqYN5eBghVtU4Wrcvh7jGdWRC1glm1HxMvxyjoNIgHj93NSteFREWEU5JVQ99oCwC9u4bVqXZbWO5e8FdW5a75GR4arAPgSjXgTPbzUKpVFVfaeeDdHWzIKgIM07vs5w8h/+ZHu7YSgoPPXaPYEH8jwQMv4cMN7p39Smy1xEaGcKDUPWOq1ukethvZpwv5JVWU2Gp9+4j7V75VStXVYslDRBJwr0jviXugfZExZqGIxALv4S51kgtc75nJJcBC4HLABtxqjNnh+aw5fD/e8rQxZnFL/R6q5fnvDw7w2hdZpBeUMzA+km1ZBcwO2sRtIasZZt/HMUs4bzmmsibqCjaWxsAhuCj8GNOH9+CLDCsD4yNJLyivs14DIOWc7lw5qg9Pr0xnwcxhJMVHtdavq1S7IMaYU5/VFDcS6QX0MsbsEJHOwHbgKuBWoNgY838i8ggQY4z5pYhcDtyPO3mMBxYaY8Z7kk0a7iq/xvM5Y4wxJSe6d3JysklLS2vOX081A/+FfBuyCrkoKc63PqOvWLkn8gtm1K4mRirIcPVlY+zVFA28mtqgCN9neOtVWQRcBqI6BTE2MZayqlp27C+la3gwN4ztx12XJOmYhlL1iMh2Y0xyQ8darOdhjCkACjyvy0VkN9AHmAVc6jltMfAF8EtP+xLjzm6bRSTak4AuBVYbY4oBRGQ1MB14t6V+F9V8GqpsCxATEcKmbCsTLd/xl5DVTAnagXEI64LGsTrqSoIHXkxMZCdun5DI4k25LFyT6SsdUlBWRbbVvRp8YHwUqRlW5k4aQNfwEO1lKHWaWmXMQ0QSgfOBLUAPT2LBGFMgIt09p/Wh7l4hBzxtJ2qvf4+5wFyAfv36Ne0voJrN8rR8nl21h3V7rWzMLiIhJpyakkPMrlnLzRFr6ek6QqklmnXxt/BIXjKHiQMb9HcUkldsY3NOEVV292B3bpGNh9//muevO48X/pvB8D5dmT68J3/8PJMbxvXTpKHUGWjx5CEiUbjLmvzcGHPMfzfC+qc20GZO0l63wZhFwCJwP7Y6vWhVS8q2VrBur5W5Fw9EjJOQfZ9xj2sjY8I2E4SLb4NH8UzFbKoHzWBAjzgO5+XQu2sYCbERDO3ZmSVf5rFlX7Hv88KChWxrJWv3HuXtOy8A3NVtUzOsXDDwCEmXaPJQ6nS1aPIQkRDcieNtY8w/Pc1HRKSXp9fRCzjqaT8A+FeX6wsc8rRfWq/9i+aMWzWt+gPg3qm22/NKyMneyzTrJn4SspbQ0ENYq7uwRGayuOYSnOEDiekVyjd7y7i+S2dShsZz/+TBbMstZmiPzqzba2VcYixhIUHkFFYysFskSzbn4f/vDa1uq1TTaMnZVgK8Aeyut9/5CmAO8H+ePz/ya79PRJbiHjAv8ySYT4Hfioh3I+jLgEdb4ndQp6/Oegy7k0XrczhYYmNjdhF51jJSLDt5IHI9Y8LSCLIbtjnO42/22WwNHU9RNYSHWKgqqcJaXg3ApqwiDpRWsTO/lBJbLUnxkeQW2RjQLZI3bxvnu2efmHAtXKhUM2jJnsdFwM3AtyKy09P2GO6ksUxEbgf2A7M9xz7GPdMqC/dU3dsAjDHFIvIbYJvnvKe8g+eq7fLfdCkhJhyAg3u28ZOK/3J12EZiOcZRezSvOq9kY+cZfFnSBYDR3aMp2l/KgLgIDpZVU1bl3uFvwqA4lqUd8CWO5687jz9+nsmCmcN899REoVTzabGpuq1Jp+q2Hv9tXr8+UErmvlxmBW1kTsQmEmuzqSWIbyMn8ErJONa6zsNBMLdc0I+YyFBAuHJU7zqzrrzmThoAQHpBOU/OGq6D30o1gzYxVVd1TPXHL7yvYyNDKa6089CynWzIKCDF8hW/itvGOWFfEoyTg8Hn8LhtDiucE+gc3p18VxVdwoI5Vu0gJrITD04bQnGlnde+yMJmd3J9cl/yimzUOl3s2F9KeGgwD04b0sq/vVJnL00e6ox4p9ba7A7SckvYmF3E53uOcF6faGrytvKmdT6Euc8tLI/mDcd0PnBeTHyfUWwsKSIxLoJxibHkbz/AsWoHSfGRnJ8QzW1vbmVwj84sWu8uK1JYUUO2tZL5Uwbxw+E9dcBbqVamyUMFxL/cecaRcob27MzcSQNZn1nIjv2lDJIDTMxfxpUHN9HfctR33a32h/k6dDQlDsPEQd34xbQhhHrGKFbsPARAYlyEe++MFbvIK7ZhszuYO2kA6QXl/GLaELblFmt1W6XaCE0e6pT8Z0oBvoFvgC37irkgzkZy6RqeDt3EMEseTixsdA7nZfs17OoykT2lFvdsqWoXiXERjOkfwye7DpOaYWVf4TZevH4UVXYHXx8o47LhPamudbLkyzzO6xvDYz8613ev0f1j6oemlGolmjzOcidac+GtJvvaF1n8N/0IuUU2AEb368roftFYbEWMrFjLNcGbGVH5HYRARvBQ3oy4m1eOjqSQriTGRfiuq6p1J47Lhvdk4ZpMLkqKA9yrwP/4eSbgTkQRoUG8cP0o+kSH66MppdowTR5nucWb9rFwTRaLN+USZBFfpdm/bczBGKiocQIQFmIhvLaUwQdTucKyiYlBuwDIc/bljZCfsLhiLFZnL6oqXO5V3xbhoWlD+NVHuyitqgVg1qjeXDmqD5lHyrl/8mCGf1dAekG53/Rad0VbnWKrVNunyeMs4f/oac6ERN9sqO157mLEh8rci+86hwVhd7gor3YnjTjKmBW2gxTnl1wYlk4wLg5benIkpD9Pmnl8fKw/14/pi/WbAqpqXcRGhvg+63efZlBaVUvvrmHMPK83cyYMYPGmfaRmWBnZtyuP/WhYnRi9i/uUUm2fJo+zhP8ivbTcYob37kpaXjE79pcypHskuYWV2F1QXu0knlJ+GLSNyy1bGG/ZTRCGHOnJa44rWOUczy7Tn5Sh3RncozOsy+HLnGKqat09jp5dw5h6TiSHymqw2R3kl1QxMD6Kxy73jl1IvT+VUu2RJo8OLttawaMffIPDZZg8NJ61nmq1G7OLfOfkFVXSzVXI1KDtzAzeSjJ7sIgh29WLV5yz+Nh5AXtMAp2CLNQYQ0JMOKkZVrKOVjB+QKyvGGFosMWzR0YI/7hjPNnWCt/mSl5zJiQSERqk4xlKtXO6wrwD8R/8/ia/lAeWfoXTGCo94xaCf/lhw3DJY3rwdlJkOyMsuQBkuvrwsWs8/3GO52hYIqVVTjoFCTVO95WxkSFMPbcHy9IOAHBRUhzJiTGAcMmQeF+JEF3xrVT7d7IV5po8OojiSjt3vZXG1twSgsTdC6iqddU5JxgH4y27mWbZztSgHfSVQlwI212D+cw5htWuMZSG96OkyoExECTgyRkkxrl358stsnFRUhzDe3fR0iBKdXBanqQD8fYuxibG8sJ/M0jqHkWZzc4n3x329Q6cBl/iGCE5DJUDXBz0DSmWnXQRG9UmhPWukSx0XcPm4DHk2zt/fwObeyOlYIvgcLkfUcV37kRy/1imj+ipPQulFKDJo11w13jKJr2gjGG9u7JoXQ5hwRaqHa46YxduhgeCPuQXIe/XaS0ynfnEOZbVrjGsd/2Aajq5DziPv1//2AheumEUL67OYENWEf3jIlm0Poe4qFCdEaWUAjR5tDn+e3iv2HkQ//0vAPKKbPTuGuabDgvQV6y8H/oEPaWkwc/8yDmBB2vvwYWlTvuQ7pEcKa+hrMrd2xjdL5qI0GA2ZBWyLbeYMf1j2JBVxLBenZk0uJsOciulfDR5tAH+CePxf33Hxuwinlu1B1cD5+aXVBFsgTlBn/JkyOITfua99gf4j+uCk963e5cw9h6t9Ax6x/pWlfuvOI8IDdZ6Ukqp4+iAeSvxfxTVOzqcZWkHiAi2YHM0lDKgC5VcaEnnlZCFBMvx5+x0DeQ2+/9SQpeT3jcy1ELnsBAuG9aTORcl8ln6EU0OSqkG6YB5G+E/lfYPn+1lyZd5dY77J44QHJwvmUwM+paJlu84T7IJkrqJ/pHaO1jqnHzK+4YFC9UO46s19cCUAb7yH0mX6MC3UipwmjyaUXGlnT+szmBdZiFPXDGc332STvrhSl5es4dKe/2zDYPlIJMs3zLR8i3jLbuJlBqcRvjaJPEn51VsdI7gKzOY2kb8z9a9cyemj+hJjrWSDVmFpAyNZ8HMYb6ehlJKnQlNHs3A28Ow2R0s2bwfgFv/vs133Js4rrRs5OXQV467PtvViw+cF7PBNYLNrmEcI7LR9+7ZpRNXjurDXZck+epX+e/upz0NpVRT0ORxGrwlP0SEq0b15rerduNwOPFMWqJHVAhHKmqPq950tWU9L4W+2uBnHjHRvOCYzUbnCA4Sf9L7R4ZaiI4I5ZHp57B0Wz7dokL5Yq+VsioHN4ztV2d7Vq1Qq5RqDpo8ApBtreB/lu3kq/wyX5u3rpO/IxW1gOHaoHX8PuT1k37mCueFPFw7jxoaN2CdMjSeF64f5RvgvmJUH+D4fTmUUqo5afJoBO/MqOXb8ymx1Z7gLEOKZSdvhj5/0s/6k2MWLzmuw0nQCc/pHtWJoxU1ddrCgoVbJgzwPY6qT3sYSqmWpMnjFIor7dz9jzS27Ku7AC+UWkbIPsZY9jLWksFoSybd5Nhx17/suIqFjmtPmizqG9wjih+PT6Ckspad+SWU2GpZeOP5ug2rUqrN0ORxCos35bJlXwldqGCMJZOxlgzGWPYySrLpJO5eyD5XD75wjSLfFY+DIF53zsQR4FfrrXibGBfBU1eN0NpRSqk2TZPHybhc3PDVLTwYttvXVGuC2GUSWeKcRpprCNtdQymk6xndZsbwHvzP9HN0wZ5Sqt3Q5HEyIsRX7wPgTcs1fFI1nK/NwO+LCjaCtzptkEV4etZwdheU8+muwxhjCAm2cLC0mlH9YkiKj9JptEqpdkOTx8mIUP5QPsvT8vl012F27C9t9KUhFrht4kBuGJvA0yvTSc2wcqzawVNXjeCpq0YAOkNKKdV+WU59StMQkb+JyFER+c6v7QkROSgiOz0/l/sde1REskQkQ0R+6Nc+3dOWJSKPNHfc3llMyZ7B6vjIUEKCjt9/Oyk+kuuT+wLQNTyY9+ZN4LHLzyUpPooXrh/FozPOOS5JeD9bH1Mppdqblux5/B34E7CkXvtLxpjf+zeIyDDgRmA40Bv4TES8K99eAaYBB4BtIrLCGJPenIED3HXpIOKiOjE7OYESm53H/vktxhgemXEu23KLfYkhKT7quHELnUarlOpoWix5GGPWiUhiI0+fBSw1xtQA+0QkC/DuQpRljMkBEJGlnnObPXn4J4DYyFDem3eh75j/FFpNEkqps0GLPbY6iftE5BvPYy3v38J9gHy/cw542k7UfhwRmSsiaSKSZrVamyNupZQ6a7V28ngVSAJGAQXAC5724wcV3MsgTtR+fKMxi4wxycaY5Pj4k9eKUkopFZhWnW1ljDnifS0ifwFWet4eAPxHl/sChzyvT9SulFKqhbRqz0NEevm9vRrwzsRaAdwoIp1EZAAwGNgKbAMGi8gAEQnFPai+oiVjVkop1YI9DxF5F7gU6CYiB4BfA5eKyCjcj55ygXkAxphdIrIM90C4A7jXGOP0fM59wKdAEPA3Y8yulvodlFJKueke5koppRp0sj3MW3vAXCmlVDt0VvQ8RMQK5LXgLbsBhS14vzPV3uKF9hdze4sX2l/MGm/T62+MaXC66lmRPFqaiKSdqKvXFrW3eKH9xdze4oX2F7PG27L0sZVSSqmAafJQSikVME0ezWNRawcQoPYWL7S/mNtbvND+YtZ4W5COeSillAqY9jyUUkoFTJOHUkqpgGnyOE0N7YxY77iIyMueHQ+/EZHRLR1jAzGdKuZLRaTMb2fHx1s6xnrxJIhIqojsFpFdIjK/gXPazPfcyHjbzHcsImEislVEvvbE+2QD53QSkfc83++WAPbkaRaNjPlWEbH6fcd3tEas9WIKEpGvRGRlA8fa1HfcaMYY/TmNH+BiYDTw3QmOXw6swl1G/gJgSzuI+VJgZWvH6RdPL2C053VnYC8wrK1+z42Mt818x57vLMrzOgTYAlxQ75x7gNc8r28E3msHMd8K/Km1v996Mf0CeKeh/+3b2nfc2B/teZwmY8w6oPgkp8wClhi3zUB0vSrCLa4RMbcpxpgCY8wOz+tyYDfHb/7VZr7nRsbbZni+swrP2xDPT/0ZNLOAxZ7X7wNTRKShfXVaRCNjblNEpC/wI+CvJzilTX3HjaXJo/k0etfDNuZCzyOBVSIyvLWD8fJ05c/H/S9Nf23yez5JvNCGvmPP45SdwFFgtTHmhN+vMcYBlAFxLRtlXY2IGeBaz2PM90UkoYHjLekPwP8CrhMcb3PfcWNo8mg+jd71sA3ZgbuWzXnAH4F/tXI8AIhIFPAB8HNjzLH6hxu4pFW/51PE26a+Y2OM0xgzCvfGauNEZES9U9rc99uImP8NJBpjRgKf8f2/6luciMwEjhpjtp/stAba2vrfFZo8mtHJdkNsk4wxx7yPBIwxHwMhItKtNWMSkRDcfxG/bYz5ZwOntKnv+VTxtsXv+P+3dzchWURRGMf/D+VCCmoTVES4DqLAkEDcREErIRAS+qKlm9blUoKKoHX0sYgMoqVUtAixfbXIqAiJVrVJyZLELE+Luaa8qM00vs4Iz281Opfr4TJwvHPvnJti+QqMAEcbbv0dX0kbgS3U5NXncjFHxHhEzKQfbwLtaxzaYp1At6SPwH3gkKTBhja1HeOVOHk0zxBwOu0GOghMRsTnqoNaiaTt8+9aJXWQPR/jFcYj4DbwNiKuLdOsNuOcJ946jbGkbZK2putW4DDwrqHZEHAmXfcAw5FWdquQJ+aGNa9usrWnSkTEhYjYFRFtZIvhwxFxsqFZrcY4r0rPMF/PtPTJiC0AEXEdeEy2E2gM+AGcrSbSBTli7gH6JP0CpoHeih/iTuAUMJrecQP0A7uhluOcJ946jfEO4I6kDWRJ7EFEPJQ0ADyPiCGyZHhX0hjZf8O9FcU6L0/M5yR1k51COkG2+6pWaj7Gubg8iZmZFebXVmZmVpiTh5mZFebkYWZmhTl5mJlZYU4eZmZWmJOHmZkV5uRh1iSSbknak677V2j3O5UO31mg7y5Jb7RMeX2zZvN3HmZrCz1AFwAAASdJREFUQNJURGwueu8ffbaRlfhurO1k1nSeeZiVJGmTpEepUu5rScfT70ckHZB0GWhNs4t7OfqbknRF0gtJTyV1pL4+pC+nzSrn5GFW3lHgU0TsS7OAJ4tvRsR5YDoi9kfEiRz9bQJGIqId+A5cBI4Ax4CB1Q3d7P84eZiVNwocTrOFroiYLNnfTxYS0CjwLCJm03Vbyb7NVoWTh1lJEfGerOz3KHBJ5c8ln11ULHEOmEl/Zw4XM7Wa8INoVlLaJTUREYOSpli6iuuspJY0gzBb95w8zMrbC1yVNAfMAn1LtLkBvJL0Mue6h1mteauuWcW8VdfWI695mFXv2/98JEh2VveX5oVltjzPPMzMrDDPPMzMrDAnDzMzK8zJw8zMCnPyMDOzwv4ABCUg06JqTi8AAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ 1.39134715 -0.84883122]\n",
+ "[-0.1278794 0.54114959 0.2003112 ]\n",
+ "[0.01143275 0.01283542 0.00298047]\n",
+ "[ 2.80987065 0.272662 -3.08239936]\n",
+ "[0.06881618 0.00409829 0.07651853]\n",
+ "[-6.77852209 0.2970746 1.7242942 6.71992723]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "# fit\n",
+ "from scipy.optimize import curve_fit\n",
+ "\n",
+ "def exponential_func(x, a, b, c):\n",
+ " return a*np.exp(b*x)+c\n",
+ "def linear_func(x, a, b):\n",
+ " return a*x+b\n",
+ "def arcsin_func(x, a, b,c,d):\n",
+ " return a*np.arcsin(b*x+c)+d\n",
+ "def sin_func(x, a, b,c,d):\n",
+ " return a*np.sin(b*x+c)+d\n",
+ "def poly_func(x, a, b,c):\n",
+ " return a+b*x+c*x**2\n",
+ "\n",
+ "msit1m=msit1\n",
+ "mco21r=mco21\n",
+ "menergy1m=menergy1\n",
+ "\n",
+ "#exponential fit of equivalent co2\n",
+ "popt, pcov = curve_fit(exponential_func, msit1, mco21r, p0=(1, 1e-6, 1))\n",
+ "\n",
+ "print(popt)\n",
+ "plt.plot(msit1,mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msit1,exponential_func(msit1,popt[0],popt[1],popt[2]))\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "\n",
+ "#linear fit of heat flux\n",
+ "popt, pcov = curve_fit(linear_func, msit1m, menergy1m, p0=(1, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,linear_func(msit1m,popt[0],popt[1]))\n",
+ "\n",
+ "\n",
+ "\n",
+ "#quadratic fit of heat flux\n",
+ "popt, pcov = curve_fit(poly_func, msit1m, menergy1m, p0=(1, 1,1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,poly_func(msit1m,popt[0],popt[1],popt[2]))\n",
+ "\n",
+ "\n",
+ "#exponential fit of heat flux\n",
+ "popt, pcov = curve_fit(exponential_func, msit1m, menergy1m, p0=(1, 1e-6, 1))\n",
+ "\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "plt.plot(msit1m,exponential_func(msit1m,popt[0],popt[1],popt[2]))\n",
+ "\n",
+ "\n",
+ "\n",
+ "#sin fit of heat flux\n",
+ "popt, pcov = curve_fit(sin_func, msit1m, menergy1m, p0=(-1, 1, 0, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,sin_func(msit1m,popt[0],popt[1],popt[2],popt[3]))\n",
+ "\n",
+ "\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "\n",
+ "plt.legend([\"data\",\"linear\",\"quadratic\",\"exponential\",\"sinusoidal\"],loc = 2)\n",
+ "plt.savefig(\"plots/F_sit_fit.pdf\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-0.08474864 24.13225415]\n",
+ "[9.52501758e-05 2.55617904e-02]\n",
+ "-0.9984813316701636\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b763184dbe0>]"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "#linear fit of heat flux & surface temperature\n",
+ "popt, pcov = curve_fit(linear_func, mts1, menergy1m, p0=(1, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "print(np.corrcoef(mts1,menergy1)[1,0])\n",
+ "plt.plot(mts1,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(mts1,linear_func(mts1,popt[0],popt[1]))\n",
+ "\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "celltoolbar": "Tags",
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/overview-checkpoint.ipynb b/.ipynb_checkpoints/overview-checkpoint.ipynb
new file mode 100644
index 0000000..96aaad0
--- /dev/null
+++ b/.ipynb_checkpoints/overview-checkpoint.ipynb
@@ -0,0 +1,500 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "import cycler\n",
+ "import glob\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " DA = get_var(DS,'sic',False)\n",
+ " icelat = np.squeeze(np.arcsin(1-DA) * (180./np.pi) )\n",
+ " time=DA.time\n",
+ " return time, icelat # returns the name of the experiment & the actual dataset & icelat array\n",
+ "\n",
+ "def load_experiment2(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml*.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_icon_aes/MLO/AQUA/\" +expname +\"/\" #simulation path\n",
+ " fpath = glob.glob(dpath +fname)[0]\n",
+ " DS = xr.open_dataset(fpath, decode_times=False) #loading of dataset\n",
+ " print(fpath)\n",
+ " DA = get_var(DS,'sic',False)\n",
+ " icelat = np.squeeze(np.arcsin(1-DA) * (180./np.pi) )\n",
+ " time=DA.time\n",
+ " return time, icelat # returns the name of the experiment & the actual dataset & icelat array\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "test=glob.glob('/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml*gm.nc')[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml_0001to0150.mm.gm.nc'"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "test"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### hice_unlim experiments"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv_hice_unlim/mlo_aqua_1594ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_61sic_hice_unlim/mlo_aqua_3000ppmv_61sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_69sic_hice_unlim/mlo_aqua_3750ppmv_69sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_77sic_hice_unlim/mlo_aqua_3750ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3907ppmv_77sic_hice_unlim/mlo_aqua_3907ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4063ppmv_77sic_hice_unlim/mlo_aqua_4063ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4375ppmv_77sic_hice_unlim/mlo_aqua_4375ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_83sic_hice_unlim/mlo_aqua_5000ppmv_83sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_77sic_hice_unlim/mlo_aqua_10000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(16,dtype=object)\n",
+ "icelatarray=np.zeros(16,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "timearray[1], icelatarray[1] = load_experiment(\"mlo_aqua_1594ppmv_hice_unlim\")\n",
+ "timearray[2], icelatarray[2] = load_experiment(\"mlo_aqua_1688ppmv_hice_unlim\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_1875ppmv_hice_unlim\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_2250ppmv_hice_unlim\")\n",
+ "\n",
+ "timearray[5], icelatarray[5] = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "timearray[6], icelatarray[6] = load_experiment(\"mlo_aqua_3000ppmv_61sic_hice_unlim\")\n",
+ "timearray[7], icelatarray[7] = load_experiment(\"mlo_aqua_3750ppmv_69sic_hice_unlim\")\n",
+ "timearray[8], icelatarray[8] = load_experiment(\"mlo_aqua_3750ppmv_77sic_hice_unlim\")\n",
+ "timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_3907ppmv_77sic_hice_unlim\")\n",
+ "timearray[10], icelatarray[10] = load_experiment(\"mlo_aqua_4063ppmv_77sic_hice_unlim\")\n",
+ "timearray[11], icelatarray[11] = load_experiment(\"mlo_aqua_4219ppmv_77sic_hice_unlim\")\n",
+ "timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_4375ppmv_77sic_hice_unlim\")\n",
+ "timearray[13], icelatarray[13] = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "timearray[14], icelatarray[14] = load_experiment(\"mlo_aqua_5000ppmv_83sic_hice_unlim\")\n",
+ "timearray[15], icelatarray[15] = load_experiment(\"mlo_aqua_10000ppmv_77sic_hice_unlim\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "l1,=plt.plot(timearray[0],icelatarray[0],'-',label='1500ppmv 90°')\n",
+ "l2,=plt.plot(timearray[1],icelatarray[1],'-',label='1594ppmv 53°')\n",
+ "l3,=plt.plot(timearray[2],icelatarray[2],'-',label='1688ppmv 53°')\n",
+ "l4,=plt.plot(timearray[3],icelatarray[3],'-',label='1875ppmv 90°')\n",
+ "l5,=plt.plot(timearray[4],icelatarray[4],'-',label='2250ppmv 90°')\n",
+ "\n",
+ "\n",
+ "lj1, = plt.plot(timearray[5],icelatarray[5],'-',label='3000ppmv 14°')\n",
+ "lj2, = plt.plot(timearray[6],icelatarray[6],'-',label='3000ppmv 22°')\n",
+ "lj3, = plt.plot(timearray[7],icelatarray[7],'-',label='3750ppmv 19°')\n",
+ "lj4, = plt.plot(timearray[8],icelatarray[8],'-',label='3750ppmv 14°')\n",
+ "#lj5, = plt.plot(timearray[9],icelatarray[9],'-',label='3907ppmv 14°')\n",
+ "lj6, = plt.plot(timearray[10],icelatarray[10],'-',label='4063ppmv 14°')\n",
+ "#lj7, = plt.plot(timearray[11],icelatarray[11],'-',label='4219ppmv 14°')\n",
+ "lj8, = plt.plot(timearray[12],icelatarray[12],'-',label='4375ppmv 14°')\n",
+ "lj9, = plt.plot(timearray[13],icelatarray[13],'-',label='5000ppmv 14°')\n",
+ "#lj10, = plt.plot(timearray[14],icelatarray[14],'-',label='5000ppmv 12°')\n",
+ "lj11, = plt.plot(timearray[15],icelatarray[15],'-',label='10000ppmv 14°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,600)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=4,edgecolor='none', facecolor='none', \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_semtner_unlim.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Winton experiments"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_winton/mlo_aqua_1875ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_winton/mlo_aqua_2250ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton_50sic/mlo_aqua_3000ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_74sic_winton/mlo_aqua_3000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_winton_50sic/mlo_aqua_4219ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_winton/mlo_aqua_5000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_37sic_winton/mlo_aqua_5000ppmv_37sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_74sic_winton/mlo_aqua_5000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_74sic_winton/mlo_aqua_10000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(13,dtype=object)\n",
+ "icelatarray=np.zeros(13,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment(\"mlo_aqua_1875ppmv_winton\")\n",
+ "timearray[1], icelatarray[1] = load_experiment(\"mlo_aqua_2250ppmv_winton\")\n",
+ "timearray[2], icelatarray[2] = load_experiment(\"mlo_aqua_2437ppmv_winton\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_2625ppmv_winton\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_3000ppmv_winton\")\n",
+ "\n",
+ "timearray[5], icelatarray[5] = load_experiment(\"mlo_aqua_3000ppmv_winton_50sic\")\n",
+ "timearray[6], icelatarray[6] = load_experiment(\"mlo_aqua_3000ppmv_74sic_winton\")\n",
+ "timearray[7], icelatarray[7] = load_experiment(\"mlo_aqua_4219ppmv_winton_50sic\")\n",
+ "timearray[8], icelatarray[8] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")\n",
+ "timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_5000ppmv_winton\")\n",
+ "timearray[10], icelatarray[10] = load_experiment(\"mlo_aqua_5000ppmv_37sic_winton\")\n",
+ "timearray[11], icelatarray[11] = load_experiment(\"mlo_aqua_5000ppmv_74sic_winton\")\n",
+ "timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_10000ppmv_74sic_winton\")\n",
+ "\n",
+ "#timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "\n",
+ "#timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "_, = plt.plot(timearray[0],icelatarray[0],'-',label='1875ppmv 90°')\n",
+ "_, = plt.plot(timearray[1],icelatarray[1],'-',label='2250ppmv 90°')\n",
+ "_, = plt.plot(timearray[2],icelatarray[2],'-',label='2437ppmv 59°')\n",
+ "_, = plt.plot(timearray[3],icelatarray[3],'-',label='2625ppmv 59°')\n",
+ "_, = plt.plot(timearray[4],icelatarray[4],'-',label='3000ppmv 90°')\n",
+ "_, = plt.plot(timearray[5],icelatarray[5],'-',label='3000ppmv 30°')\n",
+ "_, = plt.plot(timearray[6],icelatarray[6],'-',label='3000ppmv 15°')\n",
+ "_, = plt.plot(timearray[7],icelatarray[7],'-',label='4219ppmv 30°')\n",
+ "_, = plt.plot(timearray[8],icelatarray[8],'-',label='4219ppmv 17°')\n",
+ "_, = plt.plot(timearray[9],icelatarray[9],'-',label='5000ppmv 90°')\n",
+ "_, = plt.plot(timearray[10],icelatarray[10],'-',label='5000ppmv 39°')\n",
+ "_, = plt.plot(timearray[11],icelatarray[11],'-',label='5000ppmv 15°')\n",
+ "_, = plt.plot(timearray[12],icelatarray[12],'-',label='10000ppmv 15°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,210)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=3,edgecolor='none', facecolor='none',loc=1, \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_winton.pdf\")\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Semtner 5m simulations"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1250ppmv/mlo_aqua_1250ppmv_atm_2d_ml_0121to0222.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1375ppmv/mlo_aqua_1375ppmv_atm_2d_ml_0136to0269.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1438ppmv/mlo_aqua_1438ppmv_atm_2d_ml_0137to0338.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv/mlo_aqua_1594ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2000ppmv_Jor2/mlo_aqua_2000ppmv_Jor2_atm_2d_ml_0258to0277.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2000ppmv_Jor5/mlo_aqua_2000ppmv_Jor5_atm_2d_ml_0318to0356.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2500ppmv_Jor2/mlo_aqua_2500ppmv_Jor2_atm_2d_ml_0258to0341.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2500ppmv_Jor5/mlo_aqua_2500ppmv_Jor5_atm_2d_ml_0318to0369.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml_0001to0089.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor/mlo_aqua_3000ppmv_Jor_atm_2d_ml_0298to0337.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor2/mlo_aqua_3000ppmv_Jor2_atm_2d_ml_0258to0425.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor3/mlo_aqua_3000ppmv_Jor3_atm_2d_ml_0253to0502.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv/mlo_aqua_5000ppmv_atm_2d_ml_0001to0079.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor/mlo_aqua_5000ppmv_Jor_atm_2d_ml_0298to0307.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor2/mlo_aqua_5000ppmv_Jor2_atm_2d_ml_0258to0306.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor4/mlo_aqua_5000ppmv_Jor4_atm_2d_ml_0421to0490.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_10000ppmv_Jor/mlo_aqua_10000ppmv_Jor_atm_2d_ml_0298to0307.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(18,dtype=object)\n",
+ "icelatarray=np.zeros(18,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment2(\"mlo_aqua_1250ppmv\")\n",
+ "timearray[1], icelatarray[1] = load_experiment2(\"mlo_aqua_1375ppmv\")\n",
+ "timearray[2], icelatarray[2] = load_experiment2(\"mlo_aqua_1438ppmv\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_1594ppmv\")\n",
+ "timearray[5], icelatarray[5] = load_experiment2(\"mlo_aqua_2000ppmv_Jor2\")\n",
+ "timearray[6], icelatarray[6] = load_experiment2(\"mlo_aqua_2000ppmv_Jor5\")\n",
+ "timearray[7], icelatarray[7] = load_experiment2(\"mlo_aqua_2500ppmv_Jor2\")\n",
+ "timearray[8], icelatarray[8] = load_experiment2(\"mlo_aqua_2500ppmv_Jor5\")\n",
+ "timearray[9], icelatarray[9] = load_experiment2(\"mlo_aqua_3000ppmv\")\n",
+ "timearray[10], icelatarray[10] = load_experiment2(\"mlo_aqua_3000ppmv_Jor\")\n",
+ "timearray[11], icelatarray[11] = load_experiment2(\"mlo_aqua_3000ppmv_Jor2\")\n",
+ "timearray[12], icelatarray[12] = load_experiment2(\"mlo_aqua_3000ppmv_Jor3\")\n",
+ "timearray[13], icelatarray[13] = load_experiment2(\"mlo_aqua_5000ppmv\")\n",
+ "timearray[14], icelatarray[14] = load_experiment2(\"mlo_aqua_5000ppmv_Jor\")\n",
+ "timearray[15], icelatarray[15] = load_experiment2(\"mlo_aqua_5000ppmv_Jor2\")\n",
+ "timearray[16], icelatarray[16] = load_experiment2(\"mlo_aqua_5000ppmv_Jor4\")\n",
+ "timearray[17], icelatarray[17] = load_experiment2(\"mlo_aqua_10000ppmv_Jor\")\n",
+ "\n",
+ "\n",
+ "#timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "\n",
+ "#timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "_, = plt.plot(timearray[0],icelatarray[0],'-',label='1250ppmv 50°')\n",
+ "_, = plt.plot(timearray[1],icelatarray[1],'-',label='1375ppmv 50°')\n",
+ "_, = plt.plot(timearray[2],icelatarray[2],'-',label='1438ppmv 50°')\n",
+ "_, = plt.plot(timearray[3],icelatarray[3],'-',label='1500ppmv 90°')\n",
+ "_, = plt.plot(timearray[4],icelatarray[4],'-',label='1594ppmv 65°')\n",
+ "_, = plt.plot(timearray[5],icelatarray[5],'-',label='2000ppmv 14°')\n",
+ "_, = plt.plot(timearray[6],icelatarray[6],'-',label='2000ppmv 30°')\n",
+ "_, = plt.plot(timearray[7],icelatarray[7],'-',label='2500ppmv 14°')\n",
+ "_, = plt.plot(timearray[8],icelatarray[8],'-',label='2500ppmv 30°')\n",
+ "_, = plt.plot(timearray[9],icelatarray[9],'-',label='3000ppmv 90°')\n",
+ "_, = plt.plot(timearray[10],icelatarray[10],'-',label='3000ppmv 30°')\n",
+ "_, = plt.plot(timearray[11],icelatarray[11],'-',label='3000ppmv 14°')\n",
+ "_, = plt.plot(timearray[12],icelatarray[12],'-',label='3000ppmv 16°')\n",
+ "_, = plt.plot(timearray[13],icelatarray[13],'-',label='5000ppmv 90°')\n",
+ "_, = plt.plot(timearray[14],icelatarray[14],'-',label='5000ppmv 30°')\n",
+ "_, = plt.plot(timearray[15],icelatarray[15],'-',label='5000ppmv 14°')\n",
+ "_, = plt.plot(timearray[16],icelatarray[16],'-',label='5000ppmv 13°')\n",
+ "_, = plt.plot(timearray[17],icelatarray[17],'-',label='10000ppmv 7°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,510)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=4,edgecolor='none', facecolor='none',loc=1, \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_semtner_5m.pdf\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 109,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<pre><xarray.DataArray 'sic' ()>\n",
+ "array(7.4343133, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float32 0.0\n",
+ " lat float32 0.0\n",
+ " time float64 420.0</pre>"
+ ],
+ "text/plain": [
+ "<xarray.DataArray 'sic' ()>\n",
+ "array(7.4343133, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float32 0.0\n",
+ " lat float32 0.0\n",
+ " time float64 420.0"
+ ]
+ },
+ "execution_count": 109,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "icelatarray[14][0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/.ipynb_checkpoints/paper_5000_and_3000ppmv_and_1500ppmv_plot-checkpoint.ipynb b/.ipynb_checkpoints/paper_5000_and_3000ppmv_and_1500ppmv_plot-checkpoint.ipynb
new file mode 100644
index 0000000..4deb366
--- /dev/null
+++ b/.ipynb_checkpoints/paper_5000_and_3000ppmv_and_1500ppmv_plot-checkpoint.ipynb
@@ -0,0 +1,207 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Temporal evolution of sea-ice edge latitude for selected simulations of 0L-Semtner unlimited and limited"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.ym.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_Jor2/mlo_aqua_3000ppmv_Jor2_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_Jor2/mlo_aqua_5000ppmv_Jor2_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.ym.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "\n",
+ "experiment1_5m, DS1_5m = load_experiment(\"mlo_aqua_3000ppmv_Jor2\")\n",
+ "experiment2_5m, DS2_5m = load_experiment(\"mlo_aqua_5000ppmv_Jor2\")\n",
+ "experiment3_5m, DS3_5m = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "da1=get_var(DS1,\"sic\",True)\n",
+ "da2=get_var(DS2,\"sic\",True)\n",
+ "da3=get_var(DS3,\"sic\",True)\n",
+ "da1_5m=get_var(DS1_5m,\"sic\",True)\n",
+ "da2_5m=get_var(DS2_5m,\"sic\",True)\n",
+ "da3_5m=get_var(DS3_5m,\"sic\",True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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C3heYvmE65ca6p4G82uNcicSCRGZumslfN/yVO767gzt73NkkiR8pZbPdgN5ADHAEWAe4Au7AdiC++t7tcvuJjIyUdfn+eJLsumSAnLrm9jrXqc/NN98sfXx8pE6nk/7+/nLJkiVy9uzZsnv37rJHjx5y8uTJMjU1tWb9F198UYaGhsqIiAi5ZcuWmuWbN2+W4eHhMjQ0VL744os1yzt06CAXLlwo+/fvL6OiomR8fLyUUsq5c+fKBQsWyKFDh8rw8HC5ceNGKaWUn3zyibzvvvt+t31WVlatr/33v/+VgExMTLyi964oSptXa05tFfX4o6KiZExMTK2vSSkZ8dGz5NlsYKbff7m191BC/zA1miUFBwcTExODh4fH75bffvvt3HDDDUyffvl+QEVRlCvUeuvx10cIweOD78BscOLLxFcY99a3TH9/N6v3X8Bcz5yaiqIo7VWrb/FftDZuJy/EPogGHY7FN5OU1IWpvf14c2bvBg8XUxRFaWPaZov/oundR7B28hp6eXWnwOEzJg46z/pDqfzv57OWDk1RFKVFaTOJHyDcNZzFoxczwGcAu/LfJ7zrVl7ffoBT6XmWDk1RFKXFaFOJH0BvpWfxmMXc2f1O0uUObDq+wM1bbuJkdqKlQ1MURWkR2kwff22i06JZf2Iv6899jtCW0cEhgr/1uo1JIZNqrphTFEVpw2rt42/Tif+iFQdieXX3KsqtY9HapmONKyPc7uG+QWOwsi4jLjsOL70XXd27YqezUyeDFUVpK9pv4gcoqzTx/MY4Np/ZicZjI2Zdeq3redl5MbnjZOb3nI/eSn9Vx1QURbGw9p34L1VmLGP1sW9ZceAYCRkmwpwj8PcqxNutgrjsoySW7UMnbPCz7s1gr0lcHz6c3oFVF2CVGkrVF4KiKK2FSvx/ZDJLVkQnsWp/EgmZJZQZqqrhWemT0DgdxMrxMEJXijRbYaNxxMEWcstzq0q8WjnQ1b0rf+vxNzq5NbzGjqIoyjWkEn99Kowmdp7KItBNT4iHPQAmWcmWMzv5+sQODiZn4Oloi6etD+klqTjqjWSbjoMw8MrwRfg7+FNhqqCXZy91jkBRlJZCJf6r8dne87y46TgONjpCPOw5klIAmiKs/D5Fa5dUM8FEsFMw08Kn4WTtxO7U3bjZujG/5/w6a44riqI0I5X4r5aUsqY1L6Ukv9TA419Hs6vgXcwGZzo6d8LaJYaEoqMA+Nn7kVOeg63Olneve5feXr0tGb6iKO3PtU/8QohzQBFgAoxSyighhBuwCggGzgEzpJT1XlrbUhJ/XVLzy1gdc4FV+y+QVlDOrUNtuTHSBR/bLuxPPsX7J58hryKLvt59GR00GmutNUP9h9ZMHK0oitJMLJb4o6SU2Zcs+w+QK6VcJIR4EnCVUj5R335aeuK/qNxg4vmNx/kyOgm9tZbSyqqTxUJXiG+HHWj05ygwVs3zOdhvMI9GPUp0ejRlxjI6OndkWMAwdBodBrOBjJIMAhwD+CnpJ1478BoDfQeqLiNFURqrxST+U8BIKWVa9dSLO6SU9Q6LaS2J/6JNR1LZFZ9NVz8nwjwdiM8sZtX+C5zKKMROn8WoyEx2ZH72p+06OHXg1s63svLUShILEung1IHzhecJcAggvSQdrUZLmEsYE0MmMqfrHHUSWVGUy7FI4k8E8gAJ/E9K+aEQIl9K6XLJOnlSStdatp0PzAcICgqKPH/+fLPFea2czynh8bVH2JeYha3/CqTRCfuysdwa1ZlCTRw/Zn5IgSEbf/sgJoSMZV/aPsYFj2NWl1lklGbw6bFPOZ57nCNZR+ji1oVbOt/C5I6TefPAm+xJ28Pi0YvxsPNAq9HWGUOFqQKT2dSmrkVIKU5BIPBz8Lv8ytUuPV/TlAwmA2klaQQ4BqARDS+FVVxZzOazm7ku6Do89Z4AnMk7Q2xmLBmlGaSXpONk7USUTxQjA0bW+zdWlEtYJPH7SSlThRBewDbg/4ANDUn8l2ptLf76mMyStQcuUFxhwsfJlpe/PUFyXlnVi5oyNNY5UOHHPSPDeXhsJ7Sa3//dpJQsj1vBxrPfEJ9/mi7uXTiecxwrjRVWGisqzZXc1/s+JoZM5P1D75NUlISLjQvXBV1HXHYcGxI2YDAZmBI2hYWDFv4u+ZUZyzibfxadRkeYSxhajZaiyiL0Oj0SSVJhEnorPT72Pk36maQUp+Bq41rzZZRekk58XjwhziFklGbwS/IvRLhG4Ovgy68pv9LFvQunck/R2a0zFaYKFu5eiEmamNN1DoGOgRjMBob4D8FL78XxnONEuEZgp7MD4FTuKR7e8TAGs4EJIRMY4DMAV1tX/B38cbZxruXvZWJXyi4CHANq5jo1mU2UGkuxt7JHIzQYTAa2JG7hh6Qf2JO6hwpTBQN8BvDPQf8k0DGQ5KJknGyccLZx5lj2MT49/ikFlQXc1uU2Ilwj+OzEZ6w/s57c8lw6u3Vm+YTlJBYmMm/rPMqMZWiFFk+9J/nl+ZSbyglzCeO1Ea8R6hLapH8HpU2y7KgeIcRCoBi4izbe1dMYBpOZ0koTx1IKyCyqYECoG29sO83qmGRmRAXw8o09a5J/an4ZR5LzeeabOGytTQj/dyg0pdJFNw8naw8q7X/AztqaX1N+BcBWa0sPzx6kFaeRXJyMRmiY2nEqJmliQ8IG3h71NqOCRgFwKPMQ87fNp8xY9SXU0bkjNjobTuScoINTB+x0dpzIPQHAMP9h3N/nfrq6d230+00vSafSVEmQUxClhlKe+OUJdlzYgZfei6cHPE1maSZvHHijJo6G6OLWBW+9NzuSd9Qs0wgN/g7+XCi6gL2VPYuGLcIszTz5y5M4WjsS4RrBntQ9mKSp5rOaGjYVJ2snig3FpJWkMbvLbN479B4HMw8C4GbrRpBjEGklaWSUZuBm68bUsKkczz7OvvR9+Nj7cF3gdXjYefDhkQ+pMFXUfBnbW9kz3H8425O2o7fSY62xJrMsEwCt0DLMfxj9fPrxasyruNq6UlhZiJedF4vHLMbfwR9bnS1Gs5Efkn7g5X0vU2GqYFrYNCZ3nIyjtSMlhhJ89D5klGbwc/LPnMw9iaO1I+M6jCO5OJnzhefp7dWb4znH8bX3ZWyHsbja1tveUtqGa5v4hRD2gEZKWVT9eBvwL2A0kHPJyV03KeXj9e2rLSf+ury+7TRvb49nRIQn13X24lxOCZ/tOY/RLOngrqfcYCKntIAgDw2VFc5kFlbgZm/NxO4+rD/1E8Wa0wzwHMPDI4eht9YQm72bzp7+9PHuicFs4Mb1N2IwG5gUMolfU38lszQTG60Nj0Y9SlFlEStOrkCv09PbqzdrTq/BZDbxcOTD5JTn8OXJLymoKGBmp5noNDru6nkXbrZuQFWXRVxOHMFOwX/6ZbDk6BLein0LgEkhk8gszSQ2M5Y7u9/JzuSdnM47DcAQ/yHM7TqXlOIUTGYT14deT1JREucKzhHlE8WJnBOEu4ZzJOsIdjo7BvsNxkprRUFFAYUVhZgxs+rUKnZe2MmsLrNYn7Ce4znHAejq3pV3rnsHL70XeeV5JBYkkleRx9bErfyQ9ANSSqy11ug0Oooqi7DR2vBU/6fIq8gjtTiVU7mncLB2YKDvQA5kHGBXyi4Anhv0HH8J+0vNL6is0izWJ6ynsKIQfwd/9qXvIy47jnDXcF4c8iJ6Kz0/Jv3IydyTTAubRrBzMAD70/ez4sQKvPRezOs+r9ZfV2nFabx24DV+TPoRg9lQ67+fIMcgssqyar5AtUKLSZoQCCQSW60tTw94mmnh067mn6nS8l3zxB8KfFP9VAeskFK+JIRwB1YDQUAScJOUMre+fbXHxC+l5PN9Sbyw6TiVRjMAN/bx56+RAfQKdEGnEVQYzDjrrQA4mlzAs+uOcji5gBERnnT2ceTDX85y6Z/XVW/FjH6B2Oq07E6JIYEPMIg8/Ow6UmTI48VBrzIyOApN9S+MwnIDtjotuRWZmKQJfwd/AIoqi3h538tsPLsRgAG+A+jp0ZMyYxnrzqyj2FBcU9IitzwXdzt3yo3lHM46zNgOYwl0DGTZsWXohI5nBz7LtPBpGMwGVp9ajaO1I5NDJzdp/3tBRQFvx75NJ7dOTO44uabbpz7nC8+zKHoR87rNo79v/zrXKzWUUmGqsEjrOb88n53JO4GqeSjOF57HzdaNYf7D8NR7kleeR3xePF56L9zt3InLjqOXZy+Si5P5/PjnzOw8k27u3a553Mo1pS7gao0qjCaKyo042Oiwtar/hN7Fi8pc7avmGkjKKeV0RhFlBhMVRjM/HM/g++PpmCV09nFEaCrJKMkgt6DmlAsaAU52VgS66jmRVoiPsy1PTOjMuG7e2Oh+f/zTWVmsi9/AZ/FvohVazNLMEP8hzIiYwecnPierLIsOTh3IL8/HVmdLkGMQj/V7DFudLaWGUmy0Nmg1WqSUfHMwhUA3Pf2C3ZBSYjRLrLRtbp4gRbnWVOJXIKOwnEqjmUC3qhOppZVGYs/n42Cr42BSHrklleSWVHIms5gIb0d2J2STkFWCq96KUZ29QEJqQVX3wd6zuYBkbJ8SXpk8noPny9iTkMeR5AJ6Bjgzf3goQgjc7K05nVHErvhsOvk4Mizco6ZFX1Bm4IVNx1l7IBmNgJsiA9l/LpeMwnK6+TujEfCfv/YiwNWO87mldHDT1/wiURTlslTiVxrPZJbsOpPN6v0XiD6Xi5QSPxc78ksNzIgKIL/UwJJdiTUXrFnrNIR7OXAstbBmH1qNwGT+7d/Z6M5e9AxwwVqnYckvZ8ktreTekR3JLKzg27h0PBys6RngwrmcEs7nlGI2SzwcbUjMLiHC24HFsyIJ83KoNd7mGqapKK2USvxK05NS8t2xqi6kwR09mNLLD2udht0J2ZxMK0KnFWQWVmBnreXGvv6sP5TKWz/E15TAjuzgyvNTutHdv2oopdksEYKa5J2QVczinxJIzS9jSJg7n/x6Dmc7K766ZzBareCX09l08nEABI+tPcyZjGJuigrkqUmdAVR3kdLeNS7xCyGONGCnWVLK0VcTVUOoxN/2GExmMgrL8XO2a1TXzb6zOcxasg9bKy3lBhNGs8Td3hohwCxhUKg7m4+m4eNkS25pJS9O7c5NUQGk5JeRnFdG70AXrLUaNh5JxcvRlkEd3Ws9TkGpASc7nfr1oLR2jU78x4BJl9nhBillz6uPrX4q8SuXOp5ayMe7EvFwsKZPkAuPrz2CRiP46p7BdPR04PO95/liXxK2VhoOJuXj52xLakE5AH2Dqk5kxyblY63V8I/JXRkU6l7TdXQht5SnvznKL/HZeDvZcM+Ijmw6ksaE7j78bZi6YEppdRqd+IdKKXfVu8cGrNMUVOJX6pOUU4oQ1JywvshoMrMq5gLfHctgUKg79jZant94HGc7Kx4ZF8Hy3ec4nVGMtVbDg2PCMVfPyFZSYeS2QR3YFZ/N4eSCmnMU948K45FxEZxIK6LMYCSyg5uF3rGiNJjq41eU+IwivBxtcdZbUWk0k5BVzLPr4jhwvqoyeIiHPYtn9aWLrxPlBhNf7Evius5e/G9nAiv3X2BgqBuxSfkg4bUZvYhLLeB0ehGjOnvhbm/DwFA33B1sLPwuFaVGo1v8XYBHq5++LqU81kyBXZZK/EpzMpklqflleDra1HmthJSSxTsSWLX/AiEe9pzJLCYlvwytRuDjZEtKfvUVshrBPSM6Mm9IMPM/O0APf2fSC8o5nVFEVLArz0zqWnPRXUOYzZLTmUVYazWEetY+kklR6tHoxL8LmEZVZc31UsohzRdb/VTiV1qac9klHEkpYHBHd9ztrUnOKyOnpJLP9pznq9hk9NZVJ5/NEqx1GkZEePLTyUw8HW24c2gIZim5rrM3QW561h1K4WxWCV18HekT6MqGwymcSC8iq6iCk2mFFJYb0QiYMyiYzj6OeDvZ4mCr42xWMedzShndxUt1Oyl1aXTiXw7spSrxj5BS3tJ8sdVPJX6lNfnuWDovbj7O/GGhBLnb4+tsS4S3I0eS81mw8hBns0sAEAIivBw5lVGEpnpU0kUhHvZ4OtgQ4mFPvxA3didk883BFOrqme3u74TJDM52OmYN6MDkXg0vUa20aZ7Yni8AACAASURBVI1O/AIYB2iB76SsLmNoASrxK21FhdFEZmEF1joNr353iq8PpvCvqd2YGRXIsdRCYs7n0S/YlZ4BLrVum1VUQWZRBQWlBkI87PFwtGHV/gtsOpKKg42O1PwyErJKuK6zF1HBrvQNcsXbyZYQD/vf7Utd6NZuqJO7itLSlFYa0Vvrmmx/RpOZ17edZsvRNM7llNYsn9LLj8cndCLAVU9cSgG3fxLN6M7ePDI+Ai9H2yY7vtLiNLrFv1BKubDePTZgnaagEr+iNF5GYdVJ5ejEXD6qrtT6t2EhrNqfjNFspqDMgJTQzc8Jg8mMu70Nf40MwFVvRTc/Z+ystexJyGFcV29VH6n1anTiTwZev8wO75JSdr762OqnEr+iXJ3U/DKe+OoIv8Rn09HTng9mRyIEfHcsg59PZ2Gt03Cy+oQygE4j8HS0Ia2gnHlDgnn2+q6UVBpxtFFXM7cyjU78zzVgp8VSyteuJqqGUIlfUa6eySyJTcqjd6BLrTWMyg0mUvPLyCs1sGJfEnvP5tA7yIXNR9Kwt9ZSUmnC09GGZ6/vwtTe/hZ4B8oVUH38iqI0jtks+f54OjtPZ+PvYssPJzI5nJzP4+M7c9ewEHSqCF5LpxK/oihXp6zSxEOrDrH1WDrjunrzwexI1f/fstX6x1Ff14qiNJidtZb3Z/fl6Umd+f54Bjd/uJfVMRcsHZbSSM2e+IUQWiHEQSHEpurnIUKIfUKIeCHEKiGEdXPHoChK0xFCcNewUO4b1ZH0wnKe/OoIsUl5lg5LaYTLJn4hRIQQYrsQIq76eU8hxLONOMaDwIlLnr8CvCGlDAfygDsbE7CiKJYnhOCx8Z3Z/MBQfJxseXTNYcoNFrvGU2mkhrT4PwKeAgwAUsojwM0N2bkQIgC4HlhS/VwA1wFrq1dZDvylcSEritJSONpaseivPTmbVcKUd3cx8a1fSM4rvfyGikU1JPHrpZTRf1hmbOD+3wQeB8zVz92BfCnlxe2TgVrHhQkh5gshYoQQMVlZWQ08nKIo19rwCE9uG9iB1PxyknNLmbVkH4nV9YiUlqkhiT9bCNGRqmJtCCGmA2mX20gIcQOQKaU8cOniWlatdViRlPJDKWWUlDLK09OzAWEqimIp/5rajUP/HMund/ansMzA1Hd3cSKt0NJhKXVoSOK/D/gf0FkIkQIsAO5pwHZDgClCiHPASqq6eN4EXIQQF4uTBACpjQ1aUZSWRQiBTquhT5ArG+4fip21ljuX7Wd1zAWKKxraQaBcKw0exy+EsAc0UsqiRh9EiJHAo1LKG4QQa4CvpJQrhRAfAEeklIvr216N41eU1iUupYC/f3aAlPwynO2s+GhOFP1D1JwBFtDokg0P17c3KWV9dXz+uK+R/Jb4Q6n6BeAGHARmSykr6tteJX5FaX2krCoR8eDKQzjY6NjywDB1sde11+gLuByrb1FUde34V9/uBro25shSyh1SyhuqH5+VUvaXUoZJKW+6XNJXFKV1EkIQ2cGNxyd05mR6EWtjky0dklKtzsQvpXxeSvk84AH0lVI+IqV8BIikqm9eURTlsm7o4UtUB1de2HSctIIyS4ej0LCTu0FA5SXPK4HgZolGUZQ2R6MRvHpTL4wmyR3LYsgtqbz8Rkqzakji/wyIFkIsrC7VvA/4tHnDUhSlLQn2sOd/t0VyNquYGxf/yqEL+ZYOqV1r0KgeIURfYFj105+llAebNao/UCd3FaVtOHA+l7s/jyWrqIKpvf146+Y+lg6prbuy6pxCiCAgG/im+pZTvUxRFKVRIju4se2h4cwaEMT6Q6nqIi8LaUhXz2ZgU/VtO3AW+LY5g1IUpe1y0Vvz2PhO2Fpp+OTXREuH0y5dNvFLKXtIKXtW38KB/sCu5g9NUZS2ykVvzU2RgXwdm8LZrGJLh9PuNLoev5QyFujXDLEoitKOPDA6HFsrLS9tPkFrmAmwLdFdboU/XMGrAfoCqlymoihXxdPRhgdGh/HvLSf5MvoCtw5Qpw6vlYa0+B0vudlQ1ec/tTmDUhSlffjb0FCGhXuwcOMxDpxXs3hdKw1J/McvXsUrpXxJSvkFMLm5A1MUpe3TaARv3dwHX2db5n8aQ1KOmsTlWmhI4n+qgcsURVEazc3emk9u74fRLJm3LFol/2ugzsQvhJgohHgH8BdCvH3JbRkNn4FLURTlskI9HfjfbZFkFFYw7s2dbDueYemQ2rT6WvypQAxQDhy45LYBGN/8oSmK0p4MDHVn28PD6eTtyL1fHGBPQo6lQ2qzLluyQQihu2SOXItQJRsUpf0oKDMwbfGvlFaY2LpgGC56a0uH1Jo1rmSDEGJ19cODQogjf7w1S4iKorR7znZWvDWzD1nFFSzekWDpcNqk+sbxP1h9f8O1CERRFOWiHgHOTOjuw8roJBaMCUdvfdlLjpRGqG8ilrTqh/dKKc9fegPuvTbhKYrSXt0xJJjCciNrYtTMXU2tIcM5x9aybGJTB6IoinKpvkGu9At25e3t8RSWGywdTptSXx//PUKIo0CnP/TvJwKqj19RlGYlhOCfN3Qjt7SShRuOYTarej5Npb6OsxVUlV9+GXjykuVFUsrcZo1KURSFqr7+/7sunLe3x+Noo+P5qd0tHVKbUGfil1IWAAXALQBCCC/AFnAQQjhIKZOuTYiKorRnD40Jp6TCyMe7EhkS5sG4bj6WDqnVa8gMXJOFEPFAIrATOEcDJmIRQtgKIaKFEIeFEMeEEM9XLw8RQuwTQsQLIVYJIdQgXUVR6iSE4IkJnenu78Qjqw8Tl1Jg6ZBavYac3H0RGAicllKGAKOBXxuwXQVwnZSyF9AbmCCEGAi8ArxRPalLHnDnFUWuKEq7Ya3T8NGcKBxtddz+STTnskssHVKr1pDEb5BS5gAaIYRGSvkTVYm8XrLKxal1rKpvErgOWFu9fDnwl8aH3TpJKckrV6VnFeVK+Drb8emdAzCZJTM/3KPq+VyFhiT+fCGEA/Az8IUQ4i0aWKRNCKEVQhwCMoFtQAKQf0kJiGTAv45t5wshYoQQMVlZbWPeFyEE+RX5lBhUa0VRrkSYlwNf/G0grnpr5n8Ww6n0IkuH1Co1JPFPBUqBh4CtVCXvBl3NK6U0SSl7AwFUzdXbpbbV6tj2QylllJQyytPTsyGHa9EqTBUAhDiHYG9lb+FoFKX16urnxMr5A3Gw0fHf705ZOpxWqSGTrZdIKc1SSqOUcrmU8m1gY2MOIqXMB3ZQda7ARQhxcTRRAFVVQNu0SlMlMzfOZMnRJZYORVHaBBe9NXeP6MgPJzJY8stZS4fT6jR6svVql50cUwjhKYRwqX5sB4wBTgA/AdOrV5sLrL/CGFqNr+K/IqEggQjXCEuHoihtxt+HhzKphw8vbj7BTyczLR1Oq3Klib8hl9D5Aj9VV/LcD2yTUm4CngAeFkKcAdyBj68whlbBYDKwNG4pvT17M8x/mKXDUZQ2Q6fV8MbM3oR7OfD0N0dVWYdGqPMCLiHEjXW9BNhdbsdSyiNAn1qWn6Wqv79dWJewjvSSdP458J8IUWtpbEVRrpCNTst/pvfkpg/28MCXB1k8q6+q5NkA9X1C9U2ovqmpA2mLzNLMJ3Gf0MuzF0P9h1o6HEVpk/oEubJwSjeeXRdH7+e3MT0qgMfGdcLVXl0bWpfLzsDVErTmGbhSi1MpMZQQ7hpu6VAUpU3bezaHDYdTWb3/An4udiy9vR9hXg6WDsvSau1mUIm/mWSXZeNu6666dxTlGjuYlMddn8ZQYTTz4W1RDOrobumQLKlxUy8qV67CVMHtW2/nhb0vWDoURWl3+gS5su6+IXg72TL/sxgSsoovv1E7oxJ/M/j46MecLzzPmA5jLB2KorRLAa56ls3rh5VWw/Vv/8Iz3xxV9X0u0ZDqnHohxD+EEB9VPw8XQqh5eOtwruAcS44uYWLIRAb7DbZ0OMo1UlZpsnQIyh8EuOr56p7BTOnlx5oDyUx6+xd2J2RbOqwW4bJ9/EKIVcABYI6Usnv1xVh7qksxXBOtpY/faDZy53d3Ep8Xz4ZpG/Cw87B0SEoz+SU+i/WHUvFytMFolny65xzbHhpBoJve0qEptUgrKGPu0mjO55Tyv9siGdnJy9IhXSu19vE3ZMBrRynlTCHELQBSyjKhzljWKq04jeSiZJ4e+LRK+m2MlJJ9ibkMDHUnr6SSuz87gEYjKKs0YTRLpvXxR/2vaLl8ne1YOX8Qt328j78tj+HekR0ZEOrOoFB3NJr294drSIt/N9U1+KWUfYUQHYEvpZTX7CKs1tLiBygxlKgibG1AucHEjlOZHE4uoMJgJjYpj0MX8jn770loNII9CTl08XXESqshv8yAv8tlr2lUWoDCcgNPfXWUzUfTABjVyZO3b+mDo62VhSNrNlc8quc5qqpyBgohvgC2A483YWCtXrmxnM+Pf06lqfJPST84OJgePXrQu3dvoqKiAMjNzWXs2LGEh4czduxY8vKqavRLKXnggQcICwujZ8+exMbG1uxn+fLlhIeHEx4ezvLly6/dm2sn8ksr2XwkjZT8MgA2HUnj7s9j+ejns3wZnYTJLHlucteaWiWDOrrjorfG3kankn4r4mRrxbu39mHXE6NYOLkrP8dn89TXR2kNw9qbUoPG8Qsh3KmqrCmAvVLKa3qGpKW3+N879B4fHP6AZROWEekd+bvXgoODiYmJwcPjt66fxx9/HDc3N5588kkWLVpEXl4er7zyClu2bOGdd95hy5Yt7Nu3jwcffJB9+/aRm5tLVFQUMTExCCGIjIzkwIEDuLq6Xuu32maYzZJXvz9FzPk8Al317DqTRUZhBU9N7MzfR3Sk3GBi/7lcBoS4Y61Tg9/aqvd+OsN/vzuFTiN49vou3D4kxNIhNbUra/ELIfoCHYA0qkooBwkhOl5SWrldSy5KZunRpUwMmfinpF+X9evXM3fuXADmzp3LunXrapbPmTMHIQQDBw4kPz+ftLQ0vvvuO8aOHYubmxuurq6MHTuWrVu3AuDg4MAjjzxC3759GT16NBcnrRk5ciQLFixg8ODBdO/enejoaAAWLlzI3LlzGTduHMHBwXz99dc8/vjj9OjRgwkTJmAwGPj222+ZMWNGTbw7duxg8uT6Kni0TnmllRSWGdidkI2Pky0r/jaAqb2r5gWytdIyLNxTJf027u4RHXn5xh70D3HjX5uO83VsMmZz22/9N+Rf9WJgL/Ah8BGwB1gJnBZCjGvG2FqF1w+8jlaj5eHIh2t9XQjBuHHjiIyM5MMPPwQgIyMDX19fAHx9fcnMrCopm5KSQmBgYM22AQEBpKSk1LkcoKSkhL59+xIbG8uIESN4/vnna9YrKSlh9+7dLF68mDvuuKNmeUJCAps3b2b9+vXMnj2bUaNGcfToUezs7Ni8eTNjx45l7969lJRUjXtetWoVM2fObIqP65qTUhKXUsCClQf5/lg67/10hoUbjmGWkn9P68G3Dw5jz1OjWX//UAaHeeDjbGvpkJVrSKsR3NI/iA/nRNHNz5mHVx/m9mX7Ka1s0CSDrVZDWu3ngDullMcAhBBdgceAF4Cvge+bLboWbnfKbrad38b9ve/Hx96n1nV+/fVX/Pz8yMzMZOzYsXTu3LnO/dXW7SaEqHM5gEajqUnKs2fP5sYbfyuqessttwAwfPhwCgsLyc/PB2DixIlYWVnRo0cPTCYTEyZMAKBHjx6cO3cOnU7HhAkT2LhxI9OnT2fz5s385z//achHYhFns4pZ9O1JMooqGB7ugVlK+gS6MqarN8UVRm54ZxdCwLpDVXP+jOvqjVYjVDkNpYaDjY519w3hi33nWbjhGNPe282rN/WiR4CzpUNrFg1J/J0vJn0AKeVxIUQfKeXZ9v4fx9XWlQnBE5jXfV6d6/j5+QHg5eXFtGnTiI6Oxtvbm7S0NHx9fUlLS8PLq2pMcUBAABcuXKjZNjk5GT8/PwICAtixY8fvlo8cObLW4136N/nj3+ficxsbG6DqS8PKyup3XyJGY1VLZ+bMmbz33nu4ubnRr18/HB0dG/KRXBNZRRXsOpPFkDAPvBxtefKro5xIK8Tf1Y53fjyDViOY2S+QMV29sdJqeG5yVyb18OXn01k42loxqrOnSvrKn2g1gjmDggly0/PkV0eZ+0k03z80HA8HG0uH1uQa0tVzSgjxvhBiRPVtMVXdPDZAu5z54GILvIt7F/474r9Ya2sv/1pSUkJRUVHN4++//57u3bszZcqUmpE5y5cvZ+rUqQBMmTKFTz/9FCkle/fuxdnZGV9fX8aPH8/3339PXl4eeXl5fP/994wfPx4As9nM2rVrAVixYgVDh/5W/nnVqlUA7Nq1C2dnZ5ydG956GTlyJLGxsXz00UcW7+bJLCxnTcwFFu84w/T3d9P/3z/w0KrDlFeaAVj01x78+OhIti4YTsK/JxH/4kT+Pa0HUNVXP29ICN5OttwUFciE7j7Y6LSWfDtKCzeykxef3tmf4nIjj6453Ca7fRrS4r8duBdYQNUZ4l3Ao1Ql/VHNFlkL9uXJL4nLjmPh4IV1Jn2o6sufNm0aAEajkVtvvZUJEybQr18/ZsyYwccff0xQUBBr1qwBYNKkSWzZsoWwsDD0ej2ffPIJAG5ubvzjH/+gX79+APzzn//Ezc0NAHt7e44dO0ZkZCTOzs41yR7A1dWVwYMHU1hYyNKlSxv1HrVaLTfccAPLli2zyPDR3JJKygwm/F3suJBXymNrjwDQzc+JBaMjuK6zFwGuVcMoQz1/K72rbYcX4yhNL8LbkX9M7so/18dx4+LdrLhrIG5tqL6/KsvcSCdzT3Lr5lsZ7DeYd657x+JdBg4ODhQX/7n64MiRI3n11Vdrrh1oiSqNZqy0v/W1G01mdp7OYk1MMttPZjA9MpCXb+xBpdFMan4ZLnorXPRt5z+f0vLtPJ3F/E9jCPGwZ+nt/fBrfddsNK5kgxDiKPXMrSul7NkEQbUqpYZSHtv5GK42rrww5AWLJ/3WbGtcOi9sOs6uJ6p+NN792QF+OJGB0Sxxt7dmzqBgbooKAMBapyHYQ10NrVx7IyI8WTI3ins+j2X8mz8zurMXT0/qgpdT6x79VV9Xz8UKnPdV339WfT8LKG22iFqoSlMlD/70IElFSXw49kNcbVvGxVO1tfaB350MbinKKk38dCqTb+PS2XI0jQEhbkgJQkBUsCuhnvb0DnRhVGcvrLRq/LzSMgwL92TdfUNY/NMZvo1LZ19iLl/eNbBVN0YaUqvnVynlkMsta04toavnaNZR7tt+H49EPcLUsKkWjaU1kFLyS3w2+WUGpvTyIymnlOvf/oWiCiNOtjpmRAXy4JjwtlwjRWmDjqUWMGvJPtztrVk2r39rqMZ6ZVMvCiEOAfdLKXdVPx8MLG6PZZnLjGXY6VpdH981IaVkwapDmMySC7mlnM0uoajcyLBwDz67cwBSSt7efoZ+Ia70D3ZDp1r0Siu192wOc5dGYzCZee/Wvkzs4WvpkOpzxYk/ElgKOFPV518A3CGljK13wyZkycS/O3U3u1J28Xi/9lmX7lx2CYnZJYzq7IWUkqziClLzyzmZVsjmo2lUGM3c0j+QaX0C2JOQw98/iyHIXU/fIFd6+DszrpsPznaqVa+0LekF5cxbtp/CMgM/PjqiJQ8RvrJ6/FLKA0AvIYQTVV8UBU0dWUu1/fx2Hvv5MUKcQyg1lKK3avE/65pMekE50edyeWLtEZztrNj79GjKDCaGvvITlcaq8fMdPe1/d3HLoI7uHFk43lIhK8o14+Nsy5MTOzN3aTRLfknkvlFhlg6pUeob1fOmlHJB9eMHpZRvXfLaMinl7dcgPotZGreUNw68QU+Pniwes7jdJP3MonIeWX2YXWeykRIivB14fUZVr57eWsfbN/dGp9Hgam9F3yBXNbJJabeGh3swqYcPr287Tb9gN/qHuFk6pAarr8U//JLHc4G3Lnl+2aGcQohA4FPABzADH0op3xJCuAGrgGCq6gDNkFLmNS7s5rX+zHreOPAGE4In8OLQF7HRtr1LtqGqX37/uTyOphQQ2cGV3oEuaIUgs7CCu0d0ZGiYB32CXNBb//bPZEL3Ft2fqSjXjBCCV/7ak7iUXTy+9jBbFwzH1qrFdvn8Tn2JX9TxuKGMwCNSylghhCNwQAixjaorgbdLKRcJIZ4EngSeuIL9NxtPO0+G+g/l30P/jZW2dfRPSykpLDPirLdCSklyXhmVJjMd3PSUVJqws9LWlBjOKa5g5+ks1h5IZndCDgAeDjZsXTAMDwcbvntoeH2HUhSlmqOtFf+e1oPZH+/jzR/ieXJi3UUYW5L6Er9GCOFKVT2fi48vfgFc9mtNSplGVQ1/pJRFQogTgD8wFRhZvdpyYActJPHnlufiZuvGYP/BDPIb1Cq6McxmSVxqAW/9EI8QgiVzoyitNDHq1R0YzRJHGx3FlUZsdVo+uC2SERGe/JqQw8OrD+Noq+P5Kd0Y09Wb3OJK3NvQJemKcq0MDffg5n6BfLAzgagOVVVhW7o6R/UIIc5R1UVTW/aTUsrQBh9EiGDgZ6A7kCSldLnktTwp5Z+uhhJCzAfmAwQFBUWeP3++oYdrNKPZyEv7XmJd/Dr+PezfTAyZ2GzHuhpSSqQEjUZQUmHkq9hklu0+x9msEmytNPzjhq7MGtABgC1H0yipMHLgfB7eTrZkFpUzJMyDG3r6UVhuIKuoAn8Xu1bz01RRWrJyg4npH+wmNb+cbQ8Nx73lVPS8suGcV31UIRyAncBLUsqvhRD5DUn8l2ru4ZxvHHiDpXFLmd1lNvf2vhdH65ZRgjitoIzkvDJOphfx5b4kErNLeGlad27sG8D7OxJ4ZetJegU4M2tgB0Z39mpJ/9gUpd05nVHE9W//wogILxbP6ttSZm+7suGcv9uDEAullAsbsb4V8BXwhZTy6+rFGUIIXyllmhDCF8hsTAxNbfWp1SyNW8r0iOk80b/5epyklKTkl5FZVEHfoKrvuXPZJWw4nMquM9kk5ZTiorfijiEhzOgXSGZROYNe/rFm+66+TswaEFRTifLmfoEMCHWr2ZeiKJYV4e3I05O68PzG49y5fD/vz47EwaZlzlDbqBa/ECJWStm3gesKqvrwcy8OC61e/l8g55KTu25SynqvjmrKFn+FqYLTuafp4t6FrNIsJnw9gaH+Q3lz5JtXfSK33GDiZHoRIe72OOut+OZgMl/uu0BxhZHs4goyiyoAOPXiBGx0Wp5Ye4RVMRfoFehCuJcD57JLMJol39w7GCEE6w6m4KK3IsDVjo6eDq3inIOitHer91/gqW+O0sPfma/uGWzpUuFX3+Kvayd1GALcBhytLvsA8DSwCFgthLgTSAJuamQMVyy9JJ0HfnyAtJI0fprxE74Ovrw64lWGBwy/bNI3myXH0wr5Ni6NAFc9k7r74qy3oqTCyD1fxOJhb83BC/kkZpew5YFhOOut0AiBROLnYktnH0d6B7kQ5KZHU53A5w4O5v7rwuqs9/GXPv5N/hkoitK8ZvQLRKMRPLrmMFuOpjG5l5+lQ/qTxrb4NVJKczPGU6umaPEnFSYxf9t8CioKeLzf40wLn9bgbb+MTuIf6+Iwmn/7rEZ28mTZvP78Z+tJPtiZgEYIHKpHyYzv5qNOmipKO2Y2S8a+sRMrrYZ19w2xZD64sha/ECICeB/wllJ2F0L0BKZIKV9s4gCbzfJjy3nv0HtYaaxYMn4J3dy7NWg7s1mi0QgqjWYGhrozvrsPU3r5cSH3t6rUD4wOp3+IG0Fueuystfg6qyJuitLeaTSCx8Z34u7PY5m9ZB+f/21Ai2oMNqRI207gMeB/Uso+1cvipJTdr0F8QONb/Pnl+XwV/xVzus3BSmPFy/teJq0kjaf6P4Wvw29Xnp5KL6pJ2OdzStiXmEtSTikd3PVEJ+ZSUmlk8axIoOrkrOpjVxSlMdYdTGHBqkM8P6UbcwcHWyKEK+7j10spo/+Q9Frs7MPRadE8tOMhCisLGeo/lE5unXhqwFM1ryfllPLl/iT2ns3hYFI+i2f1ZVIPX3adyeaZb+IQgqqx8gLuGv7bpQoq6SuK8v/t3Xl8VOX1+PHPyb6RnbAFEwIRCCCbbAKCbCJlUUDEKlKX4kattmr1W9pqVWyrP61acVdQkVVFXFAWRUQ2QSHsWwjIHhKSkG0ymTm/P+YSIyQQyCSTSZ7365XXzNy5ufc8ucnJM8+9z7kXalSnpnyw9gCvLN/L+O7Na00Vz8ok/hMi0hLrNowiMhZrRm5tUmAvYOb2mfzvp/8R5tuUP6U8w6VRl5JbZCc8yB+7w8l/l+7irZX7cDiV5LgG/G14Cj2swkrD2jehT6tYmkYG8+P+k0SE+NOmcbiHW2UYhjcTEf44KJmb3lzL3PUHmdAzwdMhAZUb6kkCXgeuAE4C+4CbVTW92qOznG+oR1W58fMb2Zq5FXtuB+zHxuAoCSLA14eEmBAWW7Vnxr66msbhQUwZ3taMxRuGUSNUlbGvruZIdiHfPNS/pnv9VZu5KyKhgI+qnnJnVJVRUeLPLspGRIgIjGBv9l4OnTrB9rQYbu2dxKItR9h2OJfGEUHc0isRX+skbS2ZTWcYRj2yYlcGt7y9jim/acsdfStd7cYdLvoOXFOB/6hqtvU6ClfVzSluD7ECZRO/qnLKVkK+rZh7lt1DTk4UDfLHMveuXrVm/MwwDKMsVeW26T+wbl8Wy/7cn8YRQTW163ITf2W6v9ecTvoAVu38Ye6K6kIt2HiIy574mKvencSeUz9SkNfQVYQs1+apkAzDMM5JRHh8ZHvsDuWFZbs9HU6lTu76ikigqtoARCQY8Fg1sGN8TXTrlyjRYobF38GT/f9gbtxtGEatd0lMCDd0a86sdQe4p3/LCmfs14TKZMz3gWUicruI3AYswVWDp0Y9+9VOPty4h3l7ZtCj6eV8NPJD/jXwqDqe/gAAHRtJREFUjybpG4bhNe69qhV+vsLD81MpcdR4EYRSlTq5KyLXAANxjRctVtWvqjuwstp17KwFw55kUt8kbu0XRWxwLH4+tbPqnWEYxrnM33CQB+dt4oqWMTxxbXtaWhV3q4ln6vG7Q0xiW42/7waWTnqIhmGhng7HMAyjSmasSufZxTvpGB/J+3f0qM5dXdjJXRE5JSK55XydEpHc6ovzbPkl2ThjPiQ1a01N7tYwDKNaTLwikYm9Elm19wQn8mr+wpQKE7+qNlDV8HK+GqhqjU5pFb9TJIZ2pG14r5rcLQAnCk+wdP9SCksKa3zfhmHUXSM6NsWpsGhzzRdC8I6BcnGwfVdbhm//nrd/141WcWGld7bJK84jLODXY2SqysaMjcQExeDv48+KgyvYl7uP2OBYxiSPISro3Het+nj3xxSWFLL+2HqW/7wcu9NOq8hWvDroVRqF1v4bKRuGUfu1btyA1o0aMHf9QW7umVCj9cC8Yow/pEWIfrxoM4/M3cvJAjvNIoNZeN/lPPfjv0nNSOXT6z7F5rCx/uh6ejfrjaoy/OPhHDh1oHQbof6h5NvzCfINYlSrUXRr3I1BlwzC18eXebvm8fJPL/PlmC9xqpNB8wdxqvgUccFxDEwYSIfYDjy19ilC/EJoE90GPx8/XrjqBUSE9Jx0wgLCiA2O5efcn/ntF7/FR3xIikhiXOtxDEoYhL+PP3anHX+fqt3hyzCMuuX9NfuZsmALc+/sRXerbpibee/J3bCkME36RxJtotpzqsCX/bmHiAr1Ia8kg0kdJ3Fvp3uZunYqC/YsYPm45YT4h7A1cyvrjqxDEK5sfiUtwluwL2cf07dO57O0z7A77TzX/zkGJwxm9eHVLN6/mAcvf5BQ/1Byi3MptBcSFxJX+l94y4kt/G/j/8gqzKJro678pftfcDgdDPtoGH3j+zKl5xRybDm89NNLONXJ2iNrOXDqAFGBUTQMaUhadhpP9HmCIQlDCPANAFyVRLs17mYqfxpGPVVY7KDXv5bRs0UMr07oWh278N7EH9IiRP8x5x8sPbCUopIibAUNybOfwnZ0FM+Nuo5RnZrxc84RZm9ax53dhxEedO6edY4th51ZO+ncqHOVeuF2p53lPy+nSWgT2sf++vYETnWy8tBKvkr/iuMFx8ktzmVb5jbGJI/hsSse44ejP3DbV7fxVJ+nGNlyJD8d/4m84jwUpXfT3vj6mPIThlEf/PPTbby/Zj8/TBlERLDbRwW8N/G3vqy17kzdidO662NaRj5fbT3meq9RAwalNOKLzUe4Z+aPfHTPFXS55Nxj+J5wqvgU07dOJykiid8k/QaH08GX6V8yOGEwPuLDiI9HcDDvIABNQpuQFJnEA10eoNhRzKL0RaTlpPFwt4dJikhif+5+UjNS6dKoC/ty9rFk/xLGJo+lQ8MOHm6lYRgX6scDJxk9bRXPXt+RsV3j3b157038lbkDl9OppB7KoWXDUMIC/Vi46TC/6dDEa2b2Hs47zO6Tu8m357P0wFI2HNtAVlEWAIG+gSRFJPHKoFeICY7h9dTXmb9rPh+N/IgiRxHXfHgNNoeNOzrcwXXJ12F32pmxdQaNQxtzbctriQuJq/ATRIG9gPTcdAJ9AwnzD/vV8JZhGNVPVenz729IjA3h/dt7uPvvr24n/rJW783kxjfW0DE+gvsHX0q+rYSth3Np07gBIy5rio9P7U9sxwuO88meT2gS1oR+8f1oENCg9L0ThScoLCkkPiweESHfns/UtVNZuHdh6TpBvkHYHDYU5W89/8a41uP4YPsHvLH5Dd4d+i7Nw5szedlkvjv0XeknKYDooGgev+Jx+jfvT3ZRNpFBkQCsPbKWUP/Q0iGt07eiPFl0EkWJDjr/iSmnOsm15ZZu0zAMl9e+3cvTi3bwjxEp3Nq7hTs3XX8SP8AnGw/x9Bc7OJpbBLhupehU6JYYxa29WzCsQ5PzbMH7pGWnsf7YerKKshidPJoSZwmzd8ymY8OODEwYyKaMTXye9jmPdn8UEWHtkbVsOLaB5KhkHE4H2TbXvYrTc9K5OvFqVhxcwcxhMyl2FnPdJ9fx2uDX6NW0Fx9s/4DnNzzPpdGXkpqRCkC/+H50a9yNJfuXkBCewANdHyA2OJa07DTy7Hlc1vAyih3F9JvTj5aRLRmdPJrdJ3dT5ChiTPKYs86RGEZ94nQqk97bwIpdGSz9Uz8uiXFbAbf6lfgBbCUOvtlxHF8fHwa0iWPu+p95adluDucU8fToDtzY/RIcTsXXCz4B1JTMwkz++M0fSc1I5erEq3m679P4+fjxZfqX9I/vT5BfEDuydvDetvfYcmILgxMGAzBz+0zy7Hk0b9CcI/lHuLXdrdzX5T7uWnoXR/OOsuDaBQDM3zWf6Vunsz93P4G+gfj5+GF32BnaYiitIlvRp1kfkqOSz4prf+5+fjr+E6pKw5CGtIxoycrDK2kW2oxeTXtV+PE4357P/tz9tIlug494x7CfUT8dyy2i/zPLGdAmjpdv6uKuzda/xF8eh1OZsmAzN/dMIDmuAWNeWcXglEbcN/DsZFOf2Rw2An0rX327xFnCyaKTRAdFc+DUAYL9gmkc2phj+cc4lHeILo1++UW2O+1sPL6RttFtsTvtTF07lfXH1nOi8AT+Pv4sGbsERVmwZwF3dLgDgAFzB5BRmFHuvi9vdDlJEUkMSRxCjyY9UFUKSwoJ8Q9hU8Ymbv7iZoa1GMaTfZ40cymMWu2Fpbt5fukuXpvQlavbNXbHJk3iP1NOoZ2Xlu2mS0IUwzo04WhOEQ2C/AgN9I4JzXVNZmEmGzM2MvCSgTy84mG+P/Q9S8YuIcQ/hM/TPqdtTFsCfQM5nHeYHVk7SIlJYdfJXby26TUCfANYMGoBwX7BPPjtg0QFRTGl5xRsDhvP/PAMc3bOoXNcZ8Ykj2Hd0XUE+wVz/aXX0zq6taebbRilikucjH7lew6dLOS7vwworVBQBSbxn8+f5m5k0eajXNu5Gbf3aUHLhqEXdYa9qKiIK6+8EpvNRklJCWPHjuXxxx9n3759jB8/nqysLLp06cJ7771HQEAANpuNW265hQ0bNhATE8OcOXNITEwE4Omnn+att97C19eXF198kauvvtrNra6dCksKOVF4guYNmp93XYfTgVOd+Pu6evN/XflX+sb3ZWji0NJ1Pt37Kc+uf5asoixC/UNxOB3YHDa6N+nO7zv8nh5NqrVComFU2rp9WYx7bTUvjO/EqE7Nqrq58hOYqtb6r65du2pNWJ+eqY98uEmT/+8LTfjLZ3r9K6s0t7D4grfjdDr11KlTqqpaXFys3bt319WrV+v111+vs2bNUlXVO++8U6dNm6aqqi+//LLeeeedqqo6a9YsHTdunKqqbt26VS+77DItKirStLQ0TUpK0pKSEnc0tV6yO+y6PXO75thyNMeWo8+se0bHfzpeVx5cqaqqmzM263/W/Ufzi/NVVfVEwQl1Op2eDNmohxwOp3Z/aolOevcHd2yu3Jzq8aRema+aSvynHc4u0Ne/3astH/1cr37+W/0i9fBFbys/P187d+6sa9as0ZiYGLXb7aqqumrVKh0yZIiqqg4ZMkRXrVqlqqp2u11jYmLU6XTq1KlTderUqaXbOr3evn37tHXr1nrLLbdohw4ddMyYMZqf70pWCQkJ+vDDD2u3bt20W7duunv3blVVnThxot51113av39/bdGihS5fvlxvvfVWbdOmjU6cOFFVVadNm6YPPfRQ6f7eeecdnTx58kW33Zs4nA6duGiiTl42WR1Oh3629zNtP729jl04Vu9ecrcOnjdYn1rzlJY4zD9eo/r945Mteulfv7iojucZys2p1XaZg4i8LSLHRWRLmWXRIrJERHZbj7Vvii3QJCKY31+ZxLSbulBkd3D3zB+Z+sV213/KSnI4HHTq1Im4uDgGDx5My5YtiYyMxM/PNWYXHx/PoUOHADh06BDNm7uGNPz8/IiIiCAzM/NXy8/8np07dzJp0iRSU1MJDw9n2rRppeuFh4ezbt06Jk+ezP3331+6/OTJk3z99dc8//zzjBgxggceeICtW7eyefNmNm7cyNixY/noo49K158zZw433HDDRfwEvY+P+DB96HReGvASPuJDt8bdGNlyJL7iS0ZhBgnhCczaMYsJiyaw4uAKT4dr1HFju8ZT7HDy3JJd1bL96ry+bTow9IxljwDLVDUZWGa9rrWGtGvMsj/356Yel/D6ijS+232i0t/r6+vLxo0bOXjwIOvWrWP79u1nrXP6/EF5/1BEpMLlAM2bN6d3794A3HzzzaxcubJ0nRtvvLH0cfXq1aXLR4wYgYjQoUMHGjVqRIcOHfDx8aFdu3akp6fTsGFDkpKSWLNmDZmZmezcubN0H/VNXEgcT/V5itnDZzNvxDzeGPIGj1/xODm2HP7w9R94bsNzZBdlA65LTbdlbvNwxEZd0r5ZBBN6JjB9VTo7jrr/vlfVlvhVdQWQdcbiUfxyo/YZwLXVtX938fUR/j4ihStaxuC8iBPhkZGR9O/fnzVr1pCdnU1JSQkABw8epGnTpoCrJ//zzz8DUFJSQk5ODtHR0b9afub3nHnSuezrip4HBrouz/Tx8Sl9fvr16bhuuOEG5s6dy4cffsh1111nyjeUMTp5NPNHzqdffD/e2fIOdqcdcN2/YcIXEziaf9TDERp1yZ8GX4q/jw+z1/18/pUvUE3PaGmkqkcArMe4ilYUkUkisl5E1mdklH/9dk0J9PPlg9/3pH/rOE7k2Vi159w9/4yMDLKzXb3BwsJCli5dStu2bbnqqquYP38+ADNmzGDUqFEAjBw5khkzXP8P58+fz4ABAxARRo4cyezZs7HZbOzbt4/du3fTvXt3AA4cOFDam581axZ9+vQp3f+cOXNKH3v1urC7lo0ePZoFCxYwa9asejPMcyGC/YJ5ccCLrP3tWmKDYwG4OeVm3h76No1D3XLdtWEAEBkSwKCUOBZuOkxxifP833ABau0F66r6OvA6uC7n9HA4paZ8vIUf0rP4/pEBBPmXX/jsyJEjTJw4EYfDgdPpZNy4cQwfPpyUlBTGjx/PlClT6Ny5M7fffjsAt99+OxMmTKBVq1ZER0cze/ZsANq1a8e4ceNISUnBz8+Pl19+GV9f1z7btm3LjBkzuPPOO0lOTubuu+8u3b/NZqNHjx44nU5mzZp1Qe2LiooiJSWFbdu2lf6TMc4W4v/LlPrY4Fhig2NRVebtmkeePY/b2t/mweiMumJMl3i+2HyU7/ec4Ko2FfaTL1i1XscvIonAZ6ra3nq9E+ivqkdEpAmwXFXPO4Ompq7jr4wDmQUUOxy0imtw/pWrSXp6OsOHD2fLli1nvZeYmMj69euJjY31QGTGo989yqJ9i5g5bCbtYtt5OhzDyxUWO2j/2Ffc078lfx5yUZMNyx2rremhnoXAROv5ROCTGt5/lV0SE0KruAZkFxTzwdoDF3Slj1H3PdrjUWKCY3h05aMUlRR5OhzDywUH+JIcF0bqwRy3brc6L+ecBawGWovIQRG5HfgXMFhEdgODrddeafG2Y/zfx5tZtTezxvedmJhYbm8fXJ8GTG/fc8IDwnmi9xPsy9nHm5vf9HQ4Rh3QMT6S1IPZbu1kVudVPTeqahNV9VfVeFV9S1UzVXWgqiZbj2de9eM1RnZsSligH5+lHvZ0KEYtc0XTKxiSMIR3t71LZmHNdwyMuqVDfAQnC+wcPFnotm2aOrUXKcjfl77JsXyzI8MM9xhnubfzvdgcNt7b9p6nQzG83GXxEQBuHe4xib8Krmodx9HcInYcPeXpUIxaJikiib7N+rJw70JKnCWeDsfwYpc2aoAI7DrmvjxjEn8V9GvdEIDlOz07z8Cona5tdS0ZhRmsPrz6/CsbRgWC/H2Jjwom7US+27ZpEn8VNAoPolVcGD+ke+2pCqMa9YvvR3hAON8f/t7ToRheLik2jLSMPLdtr9ZO4PIWXS+J4qttR3E61Stu4m7UHH9ffxaNWUR4QLinQzG8XFLDUH5Iz0JV3VJGxfT4q6hrQhTZBXa3fgwz6g6T9A13SGoYRkGxg6O57pkbYhJ/FXVNjCLI34f9mSbxG2c7nHeYh759iNSMVE+HYnixlrGhAKRluCfPmMRfRUmxoWx+7GoGtm3k6VCMWijYL5hNGZs4UVj5kt6GcaakhmEAbhvnN2P8VSQi+PuasX2jfFFBUSweu9jTYRherlF4IP6+wqFsM9RTa8xYlc6f5mz0dBiGYdRRIkJkSADZBcVu2Z5J/G6QZyshI8/m6TCMWmrm9pmM/2y8p8MwvFx0SABZ+e5J/Gaoxw3uvaoV917VytNhGLWUzWFja+ZW8orzCAsI83Q4hpeKCvXnpOnxG4Z3aBrmul3mobxDHo7E8GZRIQGcLLC7ZVsm8btB+ol8hv53Bd/sOO7pUIxaqFloM8B1aadhXKyo0ABOummoxyR+N2gQ5MeOo6dIN9fyG+Vo1sCV+E2P36iK6JAAThYU43RWvRqwSfxuEB0aQKCfD4ez3Vcv26g7ogKjCPYLNonfqJLIEH+cCqeKql7t1SR+NxARmkYGc9hN19gadYuI0CysmUn8RpVEhwYAkOWGE7wm8btJbFgAmfnmkk6jfI1CG3Gs4JinwzC8WNTpxO+GcX6T+N3ENbnCPWfcjbonKjCKHJt7b5ht1C9RIa7E745JXOY6fjeJDPZns0n8RgVSYlIodrjnigyjfooOcV+P3yR+N4kKDSC70PxhG+WbkDKBCSkTPB2G4cWiQv0B3DKJywz1uElEsD9FdidFdoenQzEMow4KC/TDz0fcMonLJH43adkwjL7JsdjsTk+HYtRC3x/6nkHzBpGWnebpUAwvJSJEhQaQlWeGemqNoe0bM7R9Y0+HYdRSMcEx9GzSE39ff0+HYnixRuGBHDtV9cvGTeI3jBrQJroNT/Z50tNhGF6ucXgwB08WVHk7ZqjHTdIy8uj7n69Zus1cq22UT1VxOM05IOPiNYkI4khO1Xv8JvG7SXiwP5cnRJeeeTeMsopKiujyfhemb53u6VAML9Y4IoicQjuFxVXrQJihHjeJDQvk+Rs6eToMo5YK9A3EBx8zicuokiYRQQAczS2ihXUD9othevxu5o7KeUbdIyJEBkZy0nbS06EYXqyxlfiP5FStIKRHEr+IDBWRnSKyR0Qe8UQM1aH/M9/w6EebPR2GUUtFBEWQbcv2dBiGF2sSEQzA0SqO89d44hcRX+Bl4BogBbhRRFJqOo7qEOTv67Zboxl1T2RgpBnqMaqkcfjpHn/VEr8nxvi7A3tUNQ1ARGYDo4BtHojFraJCAli6/Rgpf/8SOeO95tEhfHn/lR6Jy6gdogKjWLx/MTuydtAmuo2nwzG8UHCAL5Eh/vx36S6mfbPnvOtv/efQcpd7IvE3A34u8/og0OPMlURkEjDJemkTkS01EFu12QbIA2ctjgVO1Hgw1c+06xza0tYNobiVOV7epdLtkif4UlXPyv6eSPxndoYBzjojqqqvA68DiMh6Vb28ugOraaZd3sW0y7uYdlXMEyd3DwLNy7yOB8xdqA3DMGqIJxL/D0CyiLQQkQBgPLDQA3EYhmHUSzU+1KOqJSIyGfgK8AXeVtWt5/m216s/Mo8w7fIupl3exbSrAqJqJhwZhmHUJ2bmrmEYRj1jEr9hGEY9U6sTf10q7SAi6SKyWUQ2ish6a1m0iCwRkd3WY5Sn46wMEXlbRI6XnVtRUVvE5UXrGKaKSBfPRV6xCtr0mIgcso7ZRhEZVua9R6027RSRqz0T9fmJSHMR+UZEtovIVhH5o7Xc249XRe3y6mMmIkEisk5ENlntetxa3kJE1lrHa451YQwiEmi93mO9n1ipHalqrfzCdeJ3L5AEBACbgBRPx1WF9qQDsWcs+w/wiPX8EeDfno6zkm25EugCbDlfW4BhwCJc8zd6Ams9Hf8FtOkx4MFy1k2xfh8DgRbW76mvp9tQQbuaAF2s5w2AXVb83n68KmqXVx8z6+ceZj33B9Zax2EuMN5a/ipwt/X8HuBV6/l4YE5l9lObe/ylpR1UtRg4XdqhLhkFzLCezwCu9WAslaaqK4CsMxZX1JZRwLvqsgaIFJEmNRNp5VXQpoqMAmarqk1V9wF7cP2+1jqqekRVf7SenwK245o97+3Hq6J2VcQrjpn1c8+zXvpbXwoMAOZby888XqeP43xgoIiUN0n2V2pz4i+vtMO5Dmxtp8BiEdlglaMAaKSqR8D1iwzEeSy6qquoLd5+HCdbQx5vlxmK88o2WcMAnXH1IuvM8TqjXeDlx0xEfEVkI3AcWILr00m2qpZYq5SNvbRd1vs5QMz59lGbE3+lSjt4kd6q2gVXVdJ7RaS+VGzz5uP4CtAS6AQcAf6ftdzr2iQiYcCHwP2qmnuuVctZVmvbVk67vP6YqapDVTvhqmrQHcot7nQ69otqV21O/HWqtIOqHrYejwMf4zqgx05/jLYej3suwiqrqC1eexxV9Zj1R+gE3uCXoQGvapOI+ONKjjNV9SNrsdcfr/LaVVeOGYCqZgPLcY3xR4rI6Qm3ZWMvbZf1fgSVGLKszYm/zpR2EJFQEWlw+jkwBNiCqz0TrdUmAp94JkK3qKgtC4FbrKtFegI5p4cYarszxravw3XMwNWm8dYVFS2AZGBdTcdXGdZ471vAdlV9rsxbXn28KmqXtx8zEWkoIpHW82BgEK7zF98AY63Vzjxep4/jWOBrtc70npOnz2Kf5wz3MFxn6/cCf/V0PFVoRxKuKwo2AVtPtwXXWNwyYLf1GO3pWCvZnlm4PkbbcfU4bq+oLbg+ir5sHcPNwOWejv8C2vSeFXOq9QfWpMz6f7XatBO4xtPxn6NdfXB99E8FNlpfw+rA8aqoXV59zIDLgJ+s+LcAf7eWJ+H6R7UHmAcEWsuDrNd7rPeTKrMfU7LBMAyjnqnNQz2GYRhGNTCJ3zAMo54xid8wDKOeMYnfMAyjnjGJ3zAMo54xid/weiISU6Ya49EzqjOuqob9/U5EMkTkTXdvu5L7nykiWSIy9vxrG8bZavzWi4bhbqqaiWuKPiLyGJCnqs9W827nqOrk6tq4iPiqqqO891T1JhGZXl37Nuo+0+M36jQRybMe+4vItyIyV0R2ici/ROQmq/b5ZhFpaa3XUEQ+FJEfrK/eldjHdyLSqczr70XkMmvG9tvWdn4SkVHW+4nW9/xofV1RJsZvROQDYLP1/Z9btdm3iMgN1fJDMuod0+M36pOOuApeZQFpwJuq2l1cN/H4A3A/8ALwvKquFJFLgK8ov0hWWW8CvwPuF5FLcc2qTBWRqbim0N9mTcNfJyJLcdXFGayqRSKSjGvW8OXWtroD7VV1n4iMAQ6r6m8ARCTCXT8Io34zPX6jPvlBXXXcbbim7i+2lm8GEq3ng4D/WWVxFwLhp+ssncM8YLhVNOw2YLq1fAjwiLWt5bim11+Cq8b6GyKy2frelDLbWqeuevGn4xokIv8Wkb6qmnMRbTaMs5gev1Gf2Mo8d5Z57eSXvwUfoJeqFlZ2o6paICJLcN0UYxy/9N4FGKOqO8uub52HOIbrE4gPUFTm7fwy290lIl1x1aB5WkQWq+o/KxuXYVTE9PgN49cWA6UnbcuO3Z/Hm8CLuD5VnC6L+xXwB6uSJCLS2VoeARxRV+ngCbhuM3oWEWkKFKjq+8CzuG4NaRhVZhK/YfzafcDl1h2ctgF3VeabVHUDkAu8U2bxE7iGdVLFdRP3J6zl04CJIrIGuJQyvfwzdMB1XmAjrsqST15oYwyjPKY6p2FcIBH5Ha5yxWU/GTTFNY7fxurJV3cM04HPVHX++dY1jDOZHr9hXLhC4JrTE7hE5BZc93v9aw0l/ZlAP359bsAwKs30+A3DMOoZ0+M3DMOoZ0ziNwzDqGdM4jcMw6hnTOI3DMOoZ0ziNwzDqGf+P2TjyKJOQr1nAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# sea ice latitude\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ice_lat1 = np.arcsin(1-da1) * (180./np.pi) \n",
+ "ice_lat1_5m = np.arcsin(1-da1_5m) * (180./np.pi) \n",
+ "\n",
+ "ice_lat2 = np.arcsin(1-da2) * (180./np.pi) \n",
+ "ice_lat2_5m = np.arcsin(1-da2_5m) * (180./np.pi) \n",
+ "\n",
+ "ice_lat3 = np.arcsin(1-da3) * (180./np.pi) \n",
+ "ice_lat3_5m = np.arcsin(1-da3_5m) * (180./np.pi) \n",
+ "\n",
+ "(1-da1).plot(color='C0',ls='-.')\n",
+ "(1-da1_5m).plot(color='C2',ls='-.')\n",
+ "\n",
+ "(1-da2).plot(color='C0',ls='--')\n",
+ "(1-da2_5m).plot(color='C2',ls='--')\n",
+ "\n",
+ "(1-da3).plot(color='C0',ls='-')\n",
+ "(1-da3_5m).plot(color='C2',ls='-')\n",
+ "plt.xlim(0,310)\n",
+ "plt.xlabel(\"Time [years]\")\n",
+ "plt.ylabel(\"Ice-Edge Latitude [°]\")\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(40)),np.sin(np.radians(50)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_yticklabels([0,10,20,30,40,50,60,90])\n",
+ "plt.ylim(0,1)\n",
+ "\n",
+ "plt.title(\"\")\n",
+ "#plt.legend([\"Semtner (5000ppmv)\", \"Semtner-limited (5000ppmv)\", \"Semtner (3000ppmv)\", \"Semtner-limited (3000ppmv)\"])\n",
+ "legend_color(ax,['0L-Semtner','0L-Semtner-lim5'],1)\n",
+ "#ax.annotate('5000ppmv',(35,0.36))\n",
+ "#ax.annotate('3000ppmv',(40,0.17))\n",
+ "ax.annotate('5000ppmv',(42,0.4))\n",
+ "ax.annotate('3000ppmv',(40,0.17))\n",
+ "ax.annotate('1500ppmv',(20,0.85))\n",
+ "\n",
+ "plt.savefig(\"plots/icelat_comparison.pdf\",bbox_inches='tight')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /Winton_Semtner_lores_comparison_PAPERPLOTS.ipynb b/python_scripts /Winton_Semtner_lores_comparison_PAPERPLOTS.ipynb
new file mode 100644
index 0000000..11b6504
--- /dev/null
+++ b/python_scripts /Winton_Semtner_lores_comparison_PAPERPLOTS.ipynb
@@ -0,0 +1,1947 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Zonal distribution of albedo and shortwave radiation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<xarray.core.options.set_options at 0x2b5488d5cf10>"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "import sys\n",
+ "from scipy import stats\n",
+ "\n",
+ "import sys\n",
+ "import xarray as xr\n",
+ "xr.set_options(display_style=\"html\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'0.16.2'"
+ ]
+ },
+ "execution_count": 30,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "xr.__version__\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=True) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def load_experiment_zm(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.zm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=True) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime=True): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " #if offsettime:\n",
+ " #da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " #else:\n",
+ " #da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return np.squeeze(da)\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " \n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " elif stable==1: # stable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " elif stable==3: # towards Snowball\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "def get_albedo(DS, offsettime=True):\n",
+ " sw_out = get_var(DS,\"rsuscs\", offsettime) \n",
+ " sw_in = get_var(DS,\"rsdscs\", offsettime)\n",
+ " return np.squeeze(sw_out/sw_in.where(sw_in!=0))\n",
+ "\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend\n",
+ "\n",
+ "def equivalent_co2_factor(heatflux): # heatflux in W/m²\n",
+ " alpha = 5.35\n",
+ " return np.exp(heatflux/alpha)\n",
+ "\n",
+ "def selmonmean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "def seltimemean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).mean(dim='time')\n",
+ "\n",
+ "\n",
+ "def icebordermean(DA, l_iceborder, r_iceborder, inside):\n",
+ " if inside:\n",
+ " indeces = np.r_[l_iceborder:r_iceborder+1]\n",
+ " print(\"indeces equatorwards of iceborder: \" +str(indeces))\n",
+ " else:\n",
+ " indeces = np.r_[0:l_iceborder,r_iceborder+1:np.size(DA[\"lat\"])]\n",
+ " print(\"indeces polewards of iceborder: \" +str(indeces))\n",
+ " weights = np.cos(np.deg2rad(DA.lat))\n",
+ " DA_weighted = DA[indeces]*(weights[indeces]/weights[indeces].mean()) #\n",
+ " return DA_weighted.mean()\n",
+ "\n",
+ "def selmean(DA, nyears):\n",
+ " return DA.where(DA['time.year'] >= DA['time.year'][-nyears*12], drop=True).mean(dim='time')\n",
+ "\n",
+ "def integrate_zonal_data(data, lat):\n",
+ " #function to integrate ICON data as zonal mean over longitude for each latitude\n",
+ " #latitude dimension has to be equally spaced!\n",
+ " dlat_array = np.ediff1d(lat)\n",
+ " dlat = dlat_array.mean()\n",
+ " if not np.all(dlat_array == dlat):\n",
+ " print(\"Latitude array not equally spaced!\")\n",
+ " return\n",
+ " \n",
+ " # upper and lower limit of each longitudinal band\n",
+ " latlim_lower = lat-dlat/2\n",
+ " latlim_upper = lat+dlat/2\n",
+ " \n",
+ " # area from the north pole to lower and upper limit\n",
+ " lower = 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(latlim_lower+90)))\n",
+ " upper = 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(latlim_upper+90)))\n",
+ " return (upper-lower) * data\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "321.23447741995005\n"
+ ]
+ }
+ ],
+ "source": [
+ "albsnow_warm = 0.66\n",
+ "albsnow_cold = 0.79\n",
+ "albice_warm = 0.38\n",
+ "albice_cold = 0.45\n",
+ "\n",
+ "albocean = 0.07\n",
+ "\n",
+ "scale_ssi_preind = 0.9442 \n",
+ "ssi_preind = (11.95005, 20.14612, 23.40302, 22.09443, 55.41679, 102.512, 24.69536, 347.4719, 217.2217, 343.2816, 129.3001, 47.07624, 3.130199, 13.17521)\n",
+ "\n",
+ "tsi = scale_ssi_preind*np.sum(ssi_preind)\n",
+ "print(tsi/4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.zm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "winton_exparray=np.empty(10, dtype=\"U100\")\n",
+ "semtner_exparray=np.empty(10, dtype=\"U100\")\n",
+ "\n",
+ "winton_simarray=np.empty(10,dtype=object)\n",
+ "semtner_simarray=np.empty(10,dtype=object)\n",
+ "\n",
+ "winton_zmsimarray=np.empty(10,dtype=object)\n",
+ "semtner_zmsimarray=np.empty(10,dtype=object)\n",
+ "\n",
+ "winton_exparray_all=np.empty(10, dtype=\"U100\")\n",
+ "semtner_exparray_all=np.empty(10, dtype=\"U100\")\n",
+ "\n",
+ "winton_simarray_all=np.empty(10,dtype=object)\n",
+ "semtner_simarray_all=np.empty(10,dtype=object)\n",
+ "\n",
+ "\n",
+ "winton_exparray[0]=\"mlo_aqua_3000ppmv_winton\"\n",
+ "winton_exparray[1]=\"mlo_aqua_2437ppmv_winton\"\n",
+ "winton_exparray[2]=\"mlo_aqua_2625ppmv_winton\"\n",
+ "winton_exparray[3]=\"\"\n",
+ "\n",
+ "semtner_exparray[0]=\"mlo_aqua_2250ppmv_hice_unlim\"\n",
+ "semtner_exparray[1]=\"mlo_aqua_1688ppmv_hice_unlim\"\n",
+ "semtner_exparray[2]=\"mlo_aqua_3000ppmv\"\n",
+ "semtner_exparray[3]=\"mlo_aqua_1875ppmv_hice_unlim\"\n",
+ "\n",
+ "\n",
+ "#winton_exparray_all[0]=\"mlo_aqua_5000ppmv_winton\"\n",
+ "winton_exparray_all[1]=\"mlo_aqua_3000ppmv_winton\"\n",
+ "winton_exparray_all[2]=\"mlo_aqua_2437ppmv_winton\"\n",
+ "winton_exparray_all[3]=\"mlo_aqua_2625ppmv_winton\"\n",
+ "winton_exparray_all[4]=\"\"\n",
+ "\n",
+ "#semtner_exparray_all[0]=\"mlo_aqua_5000ppmv\"\n",
+ "semtner_exparray_all[0]=\"mlo_aqua_2250ppmv_hice_unlim\"\n",
+ "semtner_exparray_all[1]=\"mlo_aqua_1688ppmv_hice_unlim\"\n",
+ "semtner_exparray_all[2]=\"mlo_aqua_3000ppmv\"\n",
+ "semtner_exparray_all[3]=\"mlo_aqua_1875ppmv_hice_unlim\"\n",
+ "\n",
+ "\n",
+ "for i in range(0,10):\n",
+ " if winton_exparray[i]!=\"\":\n",
+ " winton_simarray[i] = load_experiment(winton_exparray[i])\n",
+ " winton_zmsimarray[i] = load_experiment_zm(winton_exparray[i])\n",
+ " semtner_simarray[i] = load_experiment(semtner_exparray[i])\n",
+ " \n",
+ " if semtner_exparray[i]!=\"\":\n",
+ " semtner_simarray[i] = load_experiment(semtner_exparray[i])\n",
+ " semtner_zmsimarray[i] = load_experiment_zm(semtner_exparray[i])\n",
+ " \n",
+ " if semtner_exparray_all[i]!=\"\":\n",
+ " semtner_simarray_all[i] = load_experiment(semtner_exparray_all[i])\n",
+ " \n",
+ " if winton_exparray_all[i]!=\"\":\n",
+ " winton_simarray_all[i] = load_experiment(winton_exparray_all[i])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# calculate iceborders\n",
+ "count=0\n",
+ "Nmin_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Smin_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Nmax_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Smax_iceborderW=np.zeros(2,dtype=\"intc\")\n",
+ "Nmin_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Smin_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Nmax_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "Smax_iceborderS=np.zeros(2,dtype=\"intc\")\n",
+ "for ind in [0,1]:\n",
+ " timemean_sicW = seltimemean(get_var(winton_zmsimarray[ind], 'sic', False),40)\n",
+ " timemean_sicS = seltimemean(get_var(semtner_zmsimarray[ind], 'sic', False),40) \n",
+ "\n",
+ " Nmin_iceborderW[ind] = np.min(np.where(timemean_sicW<1)) # minimum iceborder where there is open ocean\n",
+ " Smin_iceborderW[ind] = np.max(np.where(timemean_sicW<1))\n",
+ "\n",
+ " Nmax_iceborderW[ind] = np.min(np.where(timemean_sicW==0)) # minimum iceborder where there is no ice\n",
+ " Smax_iceborderW[ind] = np.max(np.where(timemean_sicW==0))\n",
+ "\n",
+ "\n",
+ "\n",
+ " Nmin_iceborderS[ind] = np.min(np.where(timemean_sicS<1))\n",
+ " Smin_iceborderS[ind] = np.max(np.where(timemean_sicS<1))\n",
+ "\n",
+ " Nmax_iceborderS[ind] = np.min(np.where(timemean_sicS==0)) # minimum iceborder where there is no ice\n",
+ " Smax_iceborderS[ind] = np.max(np.where(timemean_sicS==0))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "axis 0: mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n",
+ "axis 1: mlo_aqua_3000ppmv_winton and mlo_aqua_2250ppmv_hice_unlim\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(2,1,figsize=(6,4),sharex=True,sharey=True)\n",
+ "month_name=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
+ "axcount=0;\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ " albedo_W = get_albedo(winton_simarray[ind])\n",
+ " albedo_S = get_albedo(semtner_simarray[ind])\n",
+ "\n",
+ " SW_out_W = get_var(winton_simarray[ind],\"rsuscs\", True) \n",
+ " SW_out_S = get_var(semtner_simarray[ind],\"rsuscs\", True) \n",
+ "\n",
+ " monmean_Wzm=albedo_Wzm.where(albedo_Wzm['time.year'] >= albedo_Wzm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " monmean_Szm=albedo_Szm.where(albedo_Szm['time.year'] >= albedo_Szm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " monmean_W=albedo_W.where(albedo_W['time.year'] >= albedo_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " monmean_S=albedo_S.where(albedo_S['time.year'] >= albedo_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " SW_outmonmean_W=SW_out_W.where(SW_out_W['time.year'] >= SW_out_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ " SW_outmonmean_S=SW_out_S.where(SW_out_S['time.year'] >= SW_out_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ " ax[axcount].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[axcount], Smin_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ " ax[axcount].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[axcount], Smax_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "\n",
+ " month = 8\n",
+ " rect_snow=mpl.patches.Rectangle((-90,albsnow_warm),180,albsnow_cold-albsnow_warm, alpha=0.4, color='lightblue')\n",
+ " rect_ice=mpl.patches.Rectangle((-90,albice_warm),180,albice_cold-albice_warm, alpha=0.2, color='blue')\n",
+ " ax[axcount].hlines(albocean,-90,90,linewidth=1,color='grey',alpha=0.5)\n",
+ " ax[axcount].add_patch(rect_snow)\n",
+ " ax[axcount].add_patch(rect_ice)\n",
+ " lW=ax[axcount].plot(monmean_Wzm['lat'],monmean_Wzm.sel(month=month),c='C1',label='Winton')\n",
+ " lS=ax[axcount].plot(monmean_Szm['lat'],monmean_Szm.sel(month=month),c='C0',label='Semtner')\n",
+ " print(\"axis \" +str(axcount) +\": \" +winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ " #ax[axcount].annotate(month_name[month-1],(0,0.55),horizontalalignment='center')\n",
+ " axcount+=1;\n",
+ "#ax.annotate(equivalent_co2_factor((SW_outmonmean_W.sel(month=month)-SW_outmonmean_S.sel(month=month)).values).round(3),(40,0.37),horizontalalignment='center',verticalalignment='top')\n",
+ "ax[1].set_xlim(-90,90)\n",
+ "ax[1].set_ylim(0,0.82)\n",
+ "ax[1].set_yticks([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8])\n",
+ "legend_color(ax[0],['3L-Winton', '0L-Semtner'],9)\n",
+ "ax[1].set_xlabel('Latitude [°]')\n",
+ "ax[0].set_ylabel('Surface albedo []')\n",
+ "ax[1].set_ylabel('Surface albedo []')\n",
+ "#fig.suptitle('monthly mean zonal mean surface albedo over the last 40 years\\n' +winton_exparray[ind] +' & ' +semtner_exparray[ind])\n",
+ "#plt.subplots_adjust(left=0, bottom=0, right=1, top=0.9, wspace=0.05, hspace=0.1)\n",
+ "\n",
+ "ax[0].text(-0.12,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.12,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "plt.savefig(\"plots/surface_albedo_July_multi.pdf\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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NGfA8SzfW0tEVobUzzIPXnZSYFy+Z9LSlTZzXZ1VbZ5j3K/fz5dOmD3NQw8trQfC/wDIR6Zlh4xLgt3H28ZJ99LPAY6q6E0BVx9qAPV8UZKUxIRs2tE2G1r1Ack5mX9PUzsT8zN7nZfkZrNy139O+1546nbNue5WTpo/jjNklXDq/nIzUIHe+splTDh/HrZcdS2NbF5f86k1OnemkPdlU08xfbjiNjq4wZ976Kt9aModnbjyNHz21jkcrqrj21Gnc97ftfOcTRzC3vKD3XEVZqfzlhtO4/63t/M/rW/npp+cOeJ6KHft57qbTKMjqmwrbHIKqCsgogKK+X/bv7WygK6ycMIbbB8BjQaCqPxeRV4FTca4ErlHV9+Ls5iX76Cwg1T12LnCHqv7+4AOJyHXAdQBTpkzxEnLSm1OSwYYdkyEUOx1yMoiV6NPrVCI3nj2TS+ZN5PUP9vLEymqeXFnNH79yMm98sJeX1tdwz+vbAOjoClO9vw2Ak6ePIyc9hZz0FHIzUjjbrYaaMyGX9Xua+j3X+UeXAXD0pHyeW7sHYMDznDqz2AqBoVRd4VwNxJh/YNm2egICCw4bu+0DEH9imuhicLt7610XZxIZL9lHU4DjgcVAJvCWiLytqge0zKnqPcA9AAsWLOg/j6/pdXhpHm9vL0Nb9nr+8htrJuRnUN3Y1vt8d2M7pXkZtNT1zWZy8yOrWFvdxPi8dO695gQADhuXzefGZXPlwsnM//GLNIQ6UZRfX308M0oOHLH93s79pKV8WF8vIr3PRZz2iv70bBcMCN3uSKWBzpM1huuqh11XG9Ssg1Nvirn6nW31HDUxn9yM1OGNa5jFa2laASx37+uATcAH7uN4k796yT5aCTynqiFV3Qu8DljX1CFQWpRPO+m0NCXvhG/HluezfV+IXfWtdHZHeGpVNeccGbux+LbLjuXZG0/rLQRe2VCDupcU2/eFCAaEvMxUTp9Zwn1/2967bk1V46BiyklPoaWjO+52H/U8xqM9q0HDMXsMdXSHqdjZMOarhSB+rqFpACJyN/CkmzsIEVkCnB3n2F6yjz4B3CkiKUAaTtXR7YP9I0xfJflOA2ldQxNjY+zj4KUEA/zooqP5/O/eIRxRPrOgnFluo++/PL6aHz3lNFeVFWTw+Fc/dsC+j1VU8eOn15ORGiQlIPziinkEA8INi2fyw6fWcf4v3kBRyguz+N0XY89YFsunjy/nu4+v6W0s7s9HPY/xqPJd5758QZ9V71c20tEdsYIgykJV7c0YqqrPisiPB9pBVbtFpCf7aBD4XU/2UXf93aq6XkSeA94HIjhdTC1t5hAoyXG6J9Y1tzG2+zsMbNGcUhYdNJHIf34m/kXnnZ+N3ZUwIzXIf3zqmD7LL1swmcsWfHgB/OYtZ8Vct+SYMpYcUxZzu7nlBfzxKycP6jzmI9q1DAqmQG7faVVeWl9DSkA4aQyPKO7htSDYKyLfBR7Aqee/GtgXbyeP2Ud7J7A3Q6ck1+n6WNfS5XMkxoxQqrDrHZh6aoxVynNr9nDK4cXkZ43t9gHwnmLiSqAEeNy9lbjLzAjVWxC0JvfIYmP61VgJzbthct+p1NfvbmbHvlaWHB13ksYxwWv30XrgRhHJUdWhGWJpEqogM5UUiVDXbiNPjYlp1zLnvrxv28uza3YTEDi3n84FY43XXEOniMg63MFgbgK6uxIamflIAgGhOK2buq50iIyNnOnGDKld7zgZR8cf3WfVs2v2cOK0cYzLSY75pL3+XLwdOA+3XUBVVwGnJyooMzRKMqFO86Gtwe9QjBl5di2DScf3yTi6ubaZzbUtLDkmOaqFYBBpqFV110GL4v7MFJHzRWSjiGwWkVtirD9TRBpFZKV7+57XeEx8JVlBpyAI7fU7FGNGls6QM4Zg8gl9Vj272hndfd5RyVMQeO01tEtETgFURNKAG3AmpO+Xl6RzrjdU9YJBxm08KMlNZ011gZtmYo7f4RgzclS/5wwki9FQ/MyaPRx/WOGQZIgdLbxeEVwP/ANO/qAq4Dj3+UB6k86paifQk3TODJOS/Gz2kUe4xa4IjDlAPw3FO/aFWL+7KWl6C/Xw2mtoL3DVII/tJekcwMkisgon/cTNqrp2kOcx/SgpzCdMIw0NdRT7HYwxI8mud2DczD4p2p9d41QLnZ9kBYHXXkPTReQpEakTkVoReUJE4g1Y9ZJ0rgI4TFWPxZnk5s/9nP86EVkuIsvr6pI3m+ZglRY5GRPr9vef+dKYpNMzkOygaiFV5YmV1cwtz6e8MMun4PzhtWro/4CHgTJgIvAI8GCcfeImnVPVpp5xCe4o5FQR6fPjVVXvUdUFqrqgpKTEY8imJ99QbWPfbJvGJK19W6Ctvk9D8cvra1m/u4mrTzrMp8D847UgEFW9X1W73VtPqomB9CadcxuYrwCePOCgIhNEnCTgInKCG0/c1BXGmw/TTHT6HIkxI0hP+0BUQaCq/OLlTUwpyuKT8yb5FJh/vM5HsNTt/vkQTgFwOfCXgfb1knQO+DTw9yLSDbQBV6jGmk7EHIpidzBMXcgGlBnTa9cySM+H4tm9i15eX8uaqiZ+9um5pCbhPNDxGotX4Hzx99T3fyVqnQLxMpAOmHROVe8E7vQarBmc7PQUsgNdlmbCmGiVy5200wHnc5HsVwPgcT4CM3qVpHVR1+F1uIgxY1xnCOrWw5xP9C5K9qsBiF819KmB1qvqY0MbTnyhEDz33HCf9dCE3DZaP+PNQakLZ/L8s92opIyYuIzpTyLfnwVN73OSRlhRM5+655yrgf9YsYnijCyyayd5PudY+wzF+6l44QDrFBj2giAchtHScajTbaP1M97izAC7OgqYkF9Pd3rpiInLmP4k8v1Z2lQBQMqUeZRkwIrddexsaeKrC+YyYbz3q4Gx9hmKVzV0zXAFYhKjICONCi0gpaOutyAwJlllN1bQmTGR7gxnwNhTm7ZSlJnBGYclZ9tAD8+VxyLyCeAooDcBh6r+KM4+5wN34PQa+o2q/qSf7RYCbwOXq+qfvMZk4svPyKKJINpWB3l+R2OMv7L2VxAqcKYh3b6/idW1+7jqmNmkBJKzbaCH15HFd+N0Gf0aTg+iy4ABR11EJZ1bAhwJXCkiR/az3U9xupmaIZaf7Xz7N7XY8AyT3IKdDWSEttJaMA+Apz/YRnowyDnTp/gcmf+8FoOnqOrngQZV/SFwMgeOGo7Fa9K5rwGPArUeYzGDkJ/tpJloarU0Eya5ZTWuBCBUMJ+G9nbe2FnNoqnl5Kal+RvYCOC1IGhz71tFZCLQBcTrWhor6dwBFXEiMgn4JHDAhPZm6OTmjAOgsc1mGDXJLXu/01Dcmj+P57fspDsS4RMzp/ob1AjhtSB4WkQKgFtxEsVtJ36uIS9J534BfEtVBxz6Gp10rrHRks4NRkGmk29of3u7z5EY46+s/RW0Z0+nLZjH81t2cHxZKRNzc/wOa0Twmoa6ZwTxoyLyNJChqo1xdoubdA5YADzkphsqBj4uIt2q+ueDzn8PcA/ArFkLLAXFIOSnO5e9DR3dPkdijL+y979HS9FJvL6ziqaOTi6cZeNlewx6yKmqdgAdHjbtTTqHM5nNFcBnDzpW739CRO4Fnj64EDhYMAijJRN1V5dz72+8AQqkjb3t0hvHyIjLmNgS8f5M66whrb2K2tT5vLCpkknZuYxn3CGfY6x9hhKWe8Bj0rlBy86G888fwkATaOlS537RIn/juP3tTpoI9r5uIyUuY2JJyPtz43tQAbMWzWPP75q4bMFkliyJVXvtzVj7DCU0CU28pHMHLf9iImNJZiUZYeqak2f+VWP6qK4ACVCVOZtQ5zJmT8j1O6IRxes4AhGRq0Xke+7zKe78AWYUKMkKUBfJgXCX36EY44+qCiiZw6Z6p1/KrPFWEETz2mvoLpyxA1e6z5txBouZUaA0J4VaLUBDNom9SUKqzhXBxPlsrGkGYNZ46y0UzWtBcKKq/gPQDqCqDYCNwhglSvIy6SSNpnobs2eS0P6d0LoPJs1j055mJhVkkpuR6ndUI4rXgqDLTQWhACJSAkQSFpUZUiX5TpqJun12RWCSUM1a537CsWysabGrgRi8FgS/BB4HSkXk34C/Av8ebycROV9ENorIZneqy4PXXywi74vISnfA2KmDit54UlJUAEBd/X5f4zDGFw3bAOgunM6W2hZrH4jB64CyP4jICmAxzojhS1R1/UD7RCWdOwdncNm7IvKkqq6L2uxl4ElVVRGZCzwMzDmEv8MMoKSkFKiibn+8MYDGjEH12yA9n+2hNDrDESsIYvBUEIjIScBaVf2V+zxXRE5U1WUD7NabdM7dpyfpXG9BoKrRCXCy6ZuCwgyB0uJiAGoaLN+QSUIN26DwMDbVOu9/6zral9eqoV8D0d8iIXfZQOImnQMQkU+KyAbgL8CXPMZjBiEvM5VcaaeqybqPmiRUvw2KprFxTzMicHiptREczGtBIKra+2tdVSPEv5rwknQOVX1cVecAlwA/7rMHByadqxsrY7qHkYgwKb2VXaGg36EYM7wiYafXUOE0NtU0M3VcNhmp9jk4mNeCYKuI3CAiqe7tRmBrnH28JJ3rpaqvAzNEpDjGuntUdYGqLigZK5OEDrPyrDCVHVl+h2HM8GqqgkiXc0VQ02w9hvrhtSC4HjgFJ3lcJXAicF2cfXqTzolIGk7SuSejNxCRw8VNPSoi83HGJthUWgkwOT+FykgR2m4T1JgkUu/0GGrPPYzte0PMtobimLz2GqrF+SL3zGPSuUuBz4tIF87kN5dHV0GZoVNelENoWyoNe3b4HYoxw8ftOrpVy4joFmZZQ3FMXnsNZQDX0nfy+gEbd+MlnVPVn+LMV2wSrLy0GGiksroKSPc7HGOGR/02CKSyKZQNYFcE/fBaNXQ/MAE4D3gNp76/OVFBmaE3edJEACprrLHdJJGG7VAwhY21IVKDwtTibL8jGpG8FgSHq+q/AiFVvQ/4BHBM4sIyQ21SmdNzt3Kfld8miTRsg8KpbNrTzPTiHFKDXr/ykovnXEPu/X4RORrIB6YmJCKTEPnZ6eRJG7sabSyBSRKqUL/9wx5D1j7QL68FwT0iUgh8F6fnzzqsbn/UmZzWQmXIfhGZJNHWAB2NtOROp7KhjdnWdbRfAzYWi8iNqnoHsN5NPf06MH1YIjNDrjw7zNZGG0tgkoTbY+gDmQrYZDQDiffz8Br3/r8O5eAeso9e5WYffV9E/iYixx7KeYw35bkpVIYLINzpdyjGJJ47hmBNWxEAR5Tl+RnNiBav++h6EdmOk376/ajlAqiqzu1vR4/ZR7cBZ6hqg4gsAe7BGaxmEqC8KIu2HRl0ttSTlj/B73CMSSz3imDN/jQKslIpL8z0OaCRa8CCQFWvFJEJOIPCLhrksb1kH/1b1PZv43RLNQkyuXQc0EZj035KrCAwY139dsgZz+rdrRwzKR83iYGJwUvLYR2wWlV3HHyLs5+n7KNRrgWejbXCks4NjfKJZQA0tLT5HIkxw6BhG+35h7OpppmjJ+X7Hc2IFrcgUNUwUOzmCxoMT9lHAURkEU5B8K1+YrCkc0OgvPwwAPa1dvsciTHDoGE7G9OPoTuiHGMFwYA8pZgAdgBvisiTOHMRAKCqPx9gH0/ZR92ZyX4DLFFVSziXQDnZWRRKiLp2u0Q2Y1xXOzRVs7p4BoAVBHF4LQiq3VsA8NoHqzf7KE7W0iuAz0ZvICJTgMeAz6nqJo/HNR9BeVoLNZ2Wa8iMcft3AMrq9lJrKPbAa/bRHw72wB6zj34PGAfc5TbkdKvqgsGey3hXntXNhkYbWGPGOLfr6OqmTGso9sBr9tGlxJ5d7KyB9vOQffTLwJc9RWqGxOS8AK80FKIRaycwY1jDdto1lU31Yf7uaKsWisdr1dDNUY8zcOYRsG+SUai8MJuOHWm0t+z3OxRjEqdhGxuDs+jusIZiL7xWDa04aNGbIvJaAuIxCVZeUgR009jU6HcoxiRO/VZWZ8yHVmso9sJTBjIRKYq6FYvIeTjzE5hRZnLvWIJWnyMxJkHaGmDb66xJnUt+pjUUe+G1amgFThuB4FQJbcPp929GmUmTpwK7qG+1dNRmjHr/EehuZ3VkKnPLraHYC09XBKo6TVWnu/czVfVcVf1rvP08JJ2bIyJviUiHiNwc6xhmaGXl5FEkTTaWwIxNqrDiXtrHz2fjvm4bUezRgAWBiCx0cw31PP+8iDwhIr8UkaI4+/YknVsCHAlcKSJHHrRZPXADcNshRW8OycRgE3s6bCyBGYOqVkDtWjbOuMZGFA9CvCuC/wY6AUTkdOAnwO+BRpxMoQPpTTqnqp1AT9K5Xqpaq6rv8uEMaGYYTEhtZWd3PuFwxO9QjBlaK+6F1CxWZzpJjK0g8CZeQRBU1Xr38eXAPar6qDt/8eFx9h1s0jkzTBaM62J3pJDb/vdBv0MxZui0N8Gax+DoS1lT22ENxYMQtyAQkZ4G5cXAK1Hr4jU0e046F49lHx1as488nk9mr+HXmwt45oXn/Q7HmKGx5k/QFeLxnMt5tKKSk6YXWUOxR/EKggeB10TkCaANeANARA7HqR4aiKekc15Y9tEhJgE+ceIxzEur4uZXWti0YY3fERnzkeny+7gj/Xq+/mITCw4r4meX2oSHXsWbmObfRORloAx4QVV7ftEHgK/FOXbcpHPGP8HUTH79d4u54K53+Mr9K7jphI1kZaSTlZVJWmqq/ZIyvqmu3ArA8mUxvp5UD3jc2VxHa80WQnU7eGXvx3gi8jE+NX8SP/nUXNJSPHWKNHgYR6Cqb8dYFjdTqJekc26PpOVAHhARkZuAI1W1aXB/hjkUEybP4K6LqvjcE/u48a2e6Sba3ZsxfnE7Kq718jWQCRzt3uDrZ03jhnOOsB8ygySqh1Rt75u5c+fqL3/5S7/D8GTbNicD4rRp03yO5EAHx9XeFiIUaqa7q5Ourk7rTWR8VV/v9E8pKhqwhzoqQEo2ZJeSlhokJ03ISxueAmCkfrYHsmjRohX9ZXf2OrJ4xEhLS+PMM8/0OwxPegrZkRbvSI3LGIClS5cCsGjRIp8j6d9Y+wxZJZoxxiQ5KwiMMSbJWUFgjDFJzgoCY4xJclYQGGNMkrOCwBhjkpwVBMYYk+RG3YAyEakDdgzR4YqBvUN0rKFiMXkzEmOCkRmXxeTNWI/pMFWNmaxt1BUEQ0lElvc30s4vFpM3IzEmGJlxWUzeJHNMVjVkjDFJzgoCY4xJcsleEMSbbtMPFpM3IzEmGJlxWUzeJG1MSd1GYIwxxq4IjDEm6SVdQSAix4nI2yKy0p0H+YSodd8Wkc0islFEzvMhtq+5514rIj8bQXHdLCIqIsV+xyQit4rIBhF5X0QeF5ECv2Nyz32+e97NInLLcJ47KobJIrJURNa776Eb3eVFIvKiiHzg3hf6EFtQRN4TkadHUEwFIvIn9/20XkRO9jsuEfm6+79bIyIPikjGsMSkqkl1A14AlriPPw686j4+ElgFpAPTgC1AcBjjWgS8BKS7z0tHSFyTcWaZ2wEU+x0TcC6Q4j7+KfDTERBT0D3fdCDNjePI4fofRcVRBsx3H+cCm9zX5WfALe7yW3pes2GO7RvA/wFPu89HQkz3AV92H6cBBX7GBUwCtgGZ7vOHgS8OR0xJd0UAKM7UmAD5QLX7+GLgIVXtUNVtwGbghBj7J8rfAz9R1Q4AVa0dIXHdDnwT53Xr4VtMqvqCqna7T98Gyv2OyT3PZlXdqqqdwENuPMNKVXeraoX7uBlYj/PlcjHOlx7u/SXDGZeIlAOfAH4TtdjvmPKA04HfAqhqp6ru9zsunMnCMkUkBcjC+X5KeEzJWBDcBNwqIruA24Bvu8snAbuitqt0lw2XWcBpIrJMRF4TkYV+xyUiFwFVqrrqoFV+v1Y9vgQ86z72M6aR8nr0EpGpwDxgGTBeVXeDU1gApcMczi9wfkxEz4Hqd0zTgTrgf90qq9+ISLafcalqFc530k5gN9Coqi8MR0yjbqpKL0TkJXpnwD7Ad4DFwNdV9VER+QzOL4KzgViTnQ5pl6o4caUAhcBJwELgYRGZnui44sT0LzhVMX128ysmVX3C3eY7QDfwh+GIKQ4/z92HiOQAjwI3qWqTnxO5i8gFQK2qrhCRM30LpK8UYD7wNVVdJiJ34FS7+Mat+78Yp2pzP/CIiFw9HOcekwWBqp7d3zoR+T1wo/v0ET68XK3EqQ/vUc6H1UbDEdffA4+pUxH4johEcPKMJDSu/mISkWNw3pCr3C+ScqDCbVz3Jaao2L4AXAAsdl8vEh1THH6e+wAikopTCPxBVR9zF9eISJmq7haRMqC2/yMMuY8BF4nIx4EMIE9EHvA5JnD+Z5Wqusx9/iecgsDPuM4GtqlqHYCIPAacMhwxJWPVUDVwhvv4LOAD9/GTwBUiki4i04CZwDvDGNef3XgQkVk4jVd7/YpLVVeraqmqTlXVqTgfnPmqusevmMDpnQN8C7hIVVujVvn5/3sXmCki00QkDbjCjWdYiVNi/xZYr6o/j1r1JPAF9/EXgCeGKyZV/baqlrvvoSuAV1T1aj9jcuPaA+wSkdnuosXAOp/j2gmcJCJZ7v9yMU47T+JjGq4W8ZFyA04FVuD07FgGHB+17js4vT824vYsGsa40oAHgDVABXDWSIgrKobtuL2G/IwJpxF4F7DSvd3td0zuuT+O00tnC04Vlh//o1NxqqTej3p9Pg6MA17G+dHzMlDkU3xn8mGvId9jAo4Dlruv159xqmZ9jQv4IbDB/R64H6cXXMJjspHFxhiT5JKxasgYY0wUKwiMMSbJWUFgjDFJzgoCY4xJclYQGGNMkrOCwBhjkpwVBGZME5GWQWx7poicEvX8ehH5vPv4iyIy8RDOv12i0nd73H61iCxwnx8lIm+JyH0iEnCX3Soie0Tk5sHGY0wsYzLFhDGH6EygBfgbgKreHbXuiziDfIYjdcQiVd3rPv4GcBHOqNxzgedU9Z9FJDQMcZgkYQWBSToiciHwXZzR3PuAq4BM4Hog7Cb6+hrOEP8WnFHVC4A/iEgbcDLO0P8FqrrX/fV+m6qeKSLjgAeBEpwUFxJ13quBG9zzLgO+qqrhOOEGcUYLR4id3M6Yj8yqhkwy+itwkqrOw5k74Juquh24G7hdVY9T1Td6NlbVP+GkIrjKXdc2wLG/D/zVPfaTwBQAETkCuBz4mKoeB4RxCqB47gD+glP4vDCov9IYj+yKwCSjcuCPbibHNJxZoYbK6cCnAFT1LyLS4C5fDBwPvOtmc83EQxZJVX0POHEI4zOmDysITDL6L+DnqvqkmyP/B4dwjG4+vKLOOGhdrAReAtynqt+Osc4YX1nVkElG+UCV+/gLUcubceb6jeXgddtxfuEDXBq1/HXcKh8RWYKT0RKcrJGfFpFSd12RiBx2iPEbM6SsIDBjXZaIVEbdvoFzBfCIiLyBM+dDj6eAT4rIShE57aDj3Avc7a7LxEkXfId7jOgG3x8Cp4tIBU4vn50AqroOp4H6BRF5H3gRZ7J5Y3xnaaiNGUFEZDtub6Q42/0AaFHV24YjLjO22RWBMSNLHfByz4CyWETkVuBqwMYSmCFhVwTGGJPk7IrAGGOSnBUExhiT5KwgMMaYJGcFgTHGJDkrCIwxJsn9f0JnWt2Q7nd6AAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 432x144 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(1,1,figsize=(6,2),sharex=True,sharey=True)\n",
+ "month_name=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
+ "axcount=0;\n",
+ "ind=1\n",
+ "albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ "albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ "albedo_W = get_albedo(winton_simarray[ind])\n",
+ "albedo_S = get_albedo(semtner_simarray[ind])\n",
+ "\n",
+ "SW_out_W = get_var(winton_simarray[ind],\"rsuscs\", True) \n",
+ "SW_out_S = get_var(semtner_simarray[ind],\"rsuscs\", True) \n",
+ "\n",
+ "monmean_Wzm=albedo_Wzm.where(albedo_Wzm['time.year'] >= albedo_Wzm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "monmean_Szm=albedo_Szm.where(albedo_Szm['time.year'] >= albedo_Szm['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "monmean_W=albedo_W.where(albedo_W['time.year'] >= albedo_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "monmean_S=albedo_S.where(albedo_S['time.year'] >= albedo_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "SW_outmonmean_W=SW_out_W.where(SW_out_W['time.year'] >= SW_out_W['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "SW_outmonmean_S=SW_out_S.where(SW_out_S['time.year'] >= SW_out_S['time.year'][-40*12], drop=True).groupby('time.month').mean(dim='time')\n",
+ "\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[axcount], Smin_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "ax.vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[axcount], Smax_iceborderS[axcount]]],0,400,color='darkgray', alpha=1)\n",
+ "\n",
+ "month = 8\n",
+ "rect_snow=mpl.patches.Rectangle((-90,albsnow_warm),180,albsnow_cold-albsnow_warm, alpha=0.4, color='lightblue')\n",
+ "rect_ice=mpl.patches.Rectangle((-90,albice_warm),180,albice_cold-albice_warm, alpha=0.2, color='blue')\n",
+ "ax.hlines(albocean,-90,90,linewidth=1,color='grey',alpha=0.5)\n",
+ "ax.add_patch(rect_snow)\n",
+ "ax.add_patch(rect_ice)\n",
+ "lW=ax.plot(monmean_Wzm['lat'],monmean_Wzm.sel(month=month),c='C1',label='Winton')\n",
+ "lS=ax.plot(monmean_Szm['lat'],monmean_Szm.sel(month=month),c='C0',label='Semtner')\n",
+ "print(winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ "#ax[axcount].annotate(month_name[month-1],(0,0.55),horizontalalignment='center')\n",
+ "\n",
+ "#ax.annotate(equivalent_co2_factor((SW_outmonmean_W.sel(month=month)-SW_outmonmean_S.sel(month=month)).values).round(3),(40,0.37),horizontalalignment='center',verticalalignment='top')\n",
+ "ax.set_xlim(-90,90)\n",
+ "ax.set_ylim(0,0.82)\n",
+ "ax.set_yticks([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8])\n",
+ "legend_color(ax,['3L-Winton', '0L-Semtner'],9)\n",
+ "ax.set_xlabel('Latitude [°]')\n",
+ "ax.set_ylabel('Surface albedo []')\n",
+ "#fig.suptitle('monthly mean zonal mean surface albedo over the last 40 years\\n' +winton_exparray[ind] +' & ' +semtner_exparray[ind])\n",
+ "#plt.subplots_adjust(left=0, bottom=0, right=1, top=0.9, wspace=0.05, hspace=0.1)\n",
+ "\n",
+ "plt.savefig(\"plots/surface_albedo_July.pdf\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton: SWin=321.23425 SWout=98.25365; LWout=222.16487; total=0.81573486\n",
+ "mlo_aqua_1688ppmv_hice_unlim: SWin=321.23425 SWout=97.2439; LWout=223.32451; total=0.6658478\n",
+ "\n",
+ "mlo_aqua_3000ppmv_winton: SWin=321.23425 SWout=94.45228; LWout=225.86537; total=0.9166107\n",
+ "mlo_aqua_2250ppmv_hice_unlim: SWin=321.23425 SWout=93.05864; LWout=227.3154; total=0.86021423\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "import csv\n",
+ "## get components of TOA energy balance\n",
+ "\n",
+ "fieldnames=[\"simulation\", \"SW in\", \"SW out\", \"LW out\"]\n",
+ "f = open(\"plots/TOA_balance.csv\", 'w')\n",
+ "writer = csv.writer(f)\n",
+ "writer.writerow([\"simulation\", \"SW in\", \"SW out\", \"LW out\", \"SW cs out\", \"LW cs out\"])\n",
+ "for ind in [1,0]:\n",
+ " \n",
+ " SW_in_W = get_var(winton_simarray[ind],\"rsdt\", True) \n",
+ " SW_in_S = get_var(semtner_simarray[ind],\"rsdt\", True) \n",
+ " SW_inmean_W=seltimemean(SW_in_W, 40).values\n",
+ " SW_inmean_S=seltimemean(SW_in_S, 40).values\n",
+ " \n",
+ " SW_out_W = get_var(winton_simarray[ind],\"rsut\", True) \n",
+ " SW_out_S = get_var(semtner_simarray[ind],\"rsut\", True) \n",
+ " SW_outmean_W=seltimemean(SW_out_W, 40).values\n",
+ " SW_outmean_S=seltimemean(SW_out_S, 40).values\n",
+ " \n",
+ " LW_out_W = get_var(winton_simarray[ind],\"rlut\", True) \n",
+ " LW_out_S = get_var(semtner_simarray[ind],\"rlut\", True) \n",
+ " LW_outmean_W=seltimemean(LW_out_W, 40).values\n",
+ " LW_outmean_S=seltimemean(LW_out_S, 40).values\n",
+ " \n",
+ " SWcs_out_W = get_var(winton_simarray[ind],\"rsutcs\", True) \n",
+ " SWcs_out_S = get_var(semtner_simarray[ind],\"rsutcs\", True) \n",
+ " SWcs_outmean_W=seltimemean(SWcs_out_W, 40).values\n",
+ " SWcs_outmean_S=seltimemean(SWcs_out_S, 40).values\n",
+ " \n",
+ " LWcs_out_W = get_var(winton_simarray[ind],\"rlutcs\", True) \n",
+ " LWcs_out_S = get_var(semtner_simarray[ind],\"rlutcs\", True) \n",
+ " LWcs_outmean_W=seltimemean(LWcs_out_W, 40).values\n",
+ " LWcs_outmean_S=seltimemean(LWcs_out_S, 40).values\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " print(winton_exparray[ind] +\": \" +\" SWin=\"+str(SW_inmean_W) +\" SWout=\"+str(SW_outmean_W) +\"; LWout=\" +str(LW_outmean_W) +\"; total=\" +str(SW_inmean_W-SW_outmean_W-LW_outmean_W))\n",
+ " print(semtner_exparray[ind] +\": \" +\" SWin=\"+str(SW_inmean_S) +\" SWout=\"+str(SW_outmean_S) +\"; LWout=\" +str(LW_outmean_S)+\"; total=\" +str(SW_inmean_S-SW_outmean_S-LW_outmean_S))\n",
+ " print(\"\")\n",
+ " \n",
+ " \n",
+ " writer.writerow([winton_exparray[ind], str(SW_inmean_W), str(SW_outmean_W), str(LW_outmean_W), str(SWcs_outmean_W), str(LWcs_outmean_W)])\n",
+ " writer.writerow([semtner_exparray[ind], str(SW_inmean_S), str(SW_outmean_S), str(LW_outmean_S), str(SWcs_outmean_S), str(LWcs_outmean_S)])\n",
+ " \n",
+ "f.close()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "clear sky:\n",
+ "637.0255380792839 PW; 1.2489118006869346 W/m^2 = 1.2489128 W/m^2\n",
+ "0.23056602641189058\n",
+ "0.8042223095666693\n",
+ "-0.03478833597856455\n",
+ "all sky:\n",
+ "515.034057095216 PW; 1.0097430530043008 W/m^2 = 1.0097504 W/m^2\n",
+ "0.16410614491583508\n",
+ "0.709068870009622\n",
+ "0.12682498507453116\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton\n",
+ "mlo_aqua_1688ppmv_hice_unlim\n"
+ ]
+ }
+ ],
+ "source": [
+ "fig, ax = plt.subplots(2,1,figsize=(6,4),sharex=True, sharey = True)\n",
+ "dN1=np.zeros(3)\n",
+ "dN2=np.zeros(3)\n",
+ "dE=np.zeros(3)\n",
+ "dglob=np.zeros(3)\n",
+ "nyears = 40\n",
+ "\n",
+ "ind=1\n",
+ "for sky_ind in range(2):\n",
+ " SW_out_W_cs = get_var(winton_zmsimarray[ind],\"rsutcs\", True) \n",
+ " SW_out_S_cs = get_var(semtner_zmsimarray[ind],\"rsutcs\", True)\n",
+ "\n",
+ " LW_out_W_cs = get_var(winton_zmsimarray[ind],\"rlutcs\", True) \n",
+ " LW_out_S_cs = get_var(semtner_zmsimarray[ind],\"rlutcs\", True)\n",
+ "\n",
+ " SW_out_W = get_var(winton_zmsimarray[ind],\"rsut\", True) \n",
+ " SW_out_S = get_var(semtner_zmsimarray[ind],\"rsut\", True)\n",
+ "\n",
+ " SW_in_W = get_var(winton_zmsimarray[ind],\"rsdt\", True) \n",
+ " SW_in_S = get_var(semtner_zmsimarray[ind],\"rsdt\", True) \n",
+ "\n",
+ " LW_out_W = get_var(winton_zmsimarray[ind],\"rlut\", True) \n",
+ " LW_out_S = get_var(semtner_zmsimarray[ind],\"rlut\", True)\n",
+ "\n",
+ "\n",
+ " timemean_SWinW = seltimemean(SW_in_W, nyears)\n",
+ " timemean_SWinS = seltimemean(SW_in_S, nyears)\n",
+ " timemean_SWoutW_cs = seltimemean(SW_out_W_cs, nyears)\n",
+ " timemean_SWoutS_cs = seltimemean(SW_out_S_cs, nyears)\n",
+ " timemean_LWoutW_cs = seltimemean(LW_out_W_cs, nyears)\n",
+ " timemean_LWoutS_cs = seltimemean(LW_out_S_cs, nyears)\n",
+ " timemean_SWoutW = seltimemean(SW_out_W, nyears)\n",
+ " timemean_SWoutS = seltimemean(SW_out_S, nyears)\n",
+ " timemean_LWoutW = seltimemean(LW_out_W, nyears)\n",
+ " timemean_LWoutS = seltimemean(LW_out_S, nyears)\n",
+ "\n",
+ " SW_out_W_integrated = integrate_zonal_data(timemean_SWoutW,timemean_SWoutW.lat)\n",
+ " SW_out_S_integrated = integrate_zonal_data(timemean_SWoutS,timemean_SWoutS.lat)\n",
+ " SW_out_W_cs_integrated = integrate_zonal_data(timemean_SWoutW_cs,timemean_SWoutW_cs.lat)\n",
+ " SW_out_S_cs_integrated = integrate_zonal_data(timemean_SWoutS_cs,timemean_SWoutS_cs.lat)\n",
+ " \n",
+ " \n",
+ " if sky_ind==0:\n",
+ " N1_W = SW_out_W_cs_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_W = SW_out_W_cs_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_W = SW_out_W_cs_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_W = SW_out_W_cs_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_W = SW_out_W_cs_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ "\n",
+ " N1_S = SW_out_S_cs_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_S = SW_out_S_cs_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_S = SW_out_S_cs_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_S = SW_out_S_cs_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_S = SW_out_S_cs_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ " \n",
+ " dglob[sky_ind] = SW_out_W_cs_integrated.sum()-SW_out_S_cs_integrated.sum()\n",
+ " elif sky_ind==1:\n",
+ " N1_W = SW_out_W_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_W = SW_out_W_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_W = SW_out_W_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_W = SW_out_W_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_W = SW_out_W_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ "\n",
+ " N1_S = SW_out_S_integrated[0:Nmin_iceborderS[ind]].sum()\n",
+ " N2_S = SW_out_S_integrated[Nmin_iceborderS[ind]:Nmax_iceborderS[ind]].sum()\n",
+ " E_S = SW_out_S_integrated[Nmax_iceborderS[ind]:Smax_iceborderS[ind]+1].sum()\n",
+ " S2_S = SW_out_S_integrated[Smax_iceborderS[ind]+1:Smin_iceborderS[ind]+1].sum()\n",
+ " S1_S = SW_out_S_integrated[Smin_iceborderS[ind]+1:].sum()\n",
+ " \n",
+ " dglob[sky_ind] = SW_out_W_integrated.sum()-SW_out_S_integrated.sum()\n",
+ " \n",
+ " dN1[sky_ind] = (N1_W.values+S1_W.values) - (N1_S.values+S1_S.values)\n",
+ " dN2[sky_ind] = (N2_W.values+S2_W.values) - (N2_S.values+S2_S.values)\n",
+ " dE[sky_ind] = E_W.values - E_S.values\n",
+ " \n",
+ "\n",
+ " \n",
+ " \n",
+ " #areas\n",
+ " NA1 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[ind]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmin_iceborderS[ind]]+90)))\n",
+ " NA2 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmin_iceborderS[ind]]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmax_iceborderS[ind]]+90)))\n",
+ " E = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Nmax_iceborderS[ind]]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smax_iceborderS[ind]+1]+90)))\n",
+ " SA2 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smax_iceborderS[ind]+1]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90)))\n",
+ " SA1 = -2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90))) + 2*np.pi*6371000**2 * (1-np.cos(np.deg2rad(SW_out_W_integrated.lat[Smin_iceborderS[ind]+1]+90)))\n",
+ " \n",
+ " \n",
+ " if sky_ind!=2:\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[ind], Smin_iceborderS[ind]]],0,400,color='darkgray', alpha=1)\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[ind], Smax_iceborderS[ind]]],0,400,color='darkgray', alpha=1)\n",
+ " else:\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmin_iceborderS[ind], Smin_iceborderS[ind]]],-200,200,color='darkgray', alpha=1)\n",
+ " ax[sky_ind].vlines(timemean_sicS[\"lat\"][[Nmax_iceborderS[ind], Smax_iceborderS[ind]]],-200,200,color='darkgray', alpha=1)\n",
+ " \n",
+ " if sky_ind== 0:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW_cs['lat'],timemean_SWoutW_cs,c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS_cs['lat'],timemean_SWoutS_cs,c='C0',label='Semtner')\n",
+ " elif sky_ind==1:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW['lat'],timemean_SWoutW,c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS['lat'],timemean_SWoutS,c='C0',label='Semtner')\n",
+ " elif sky_ind==2:\n",
+ " lW_SW=ax[sky_ind].plot(timemean_SWoutW['lat'],-1 * (timemean_SWoutW_cs-timemean_SWoutW),c='C1',label='Winton')\n",
+ " lS_SW=ax[sky_ind].plot(timemean_SWoutS['lat'],-1 * (timemean_SWoutS_cs-timemean_SWoutS),c='C0',label='Semtner')\n",
+ " \n",
+ " if sky_ind==0:\n",
+ " print(\"clear sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsutcs\", True), nyears) - selmean(get_var(semtner_simarray[ind],\"rsutcs\", True), nyears)\n",
+ " else:\n",
+ " print(\"all sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsut\", True), nyears) - selmean(get_var(semtner_simarray[ind],\"rsut\", True), nyears)\n",
+ " \n",
+ " print(str(dglob[sky_ind]*1e-12) +\" PW; \" +str(dglob[sky_ind]/(4 * np.pi *6371000**2)) +\" W/m^2 = \" +str(total.values)+\" W/m^2\" )\n",
+ " print(dN1[sky_ind] / dglob[sky_ind])\n",
+ " print(dN2[sky_ind] / dglob[sky_ind])\n",
+ " print(dE[sky_ind] / dglob[sky_ind])\n",
+ " \n",
+ "ax[0].set_xlim(-90,90)\n",
+ "ax[1].set_xlim(-90,90)\n",
+ "ax[0].set_ylim(0,150)\n",
+ "legend_color(ax[0],['3L-Winton', '0L-Semtner'],9)\n",
+ "ax[1].set_xlabel('Latitude [°]')\n",
+ "ax[0].set_ylabel('TOA SW out cs\\n[W m$^{-2}$]')\n",
+ "ax[1].set_ylabel('TOA SW out as\\n[W m$^{-2}$]')\n",
+ "#ax[2].set_ylabel('CRE [W m$^{-2}$]')\n",
+ "ax[1].annotate(\"dF = \" +str(round(total.values.tolist(),2)) +\"Wm$^{-2}$\",(-20,40)) # 1.01 Wm$^{-2}$\")\n",
+ "ax[1].annotate(f'{100*round(dN1[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(70,20))\n",
+ "ax[1].annotate(f'{100*round(dN2[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(45,20))\n",
+ "ax[1].annotate(f'{100*round(dE[sky_ind] / dglob[sky_ind],2):.0f}' +\"%\",(20,20))\n",
+ "\n",
+ "#ax[1].annotate(\"dF = 1.01 Wm$^{-2}$\",(-20,40))\n",
+ "#ax[1].annotate(\"16%\",(70,20))\n",
+ "#ax[1].annotate(\"71%\",(45,20))\n",
+ "#ax[1].annotate(\"13%\",(20,20))\n",
+ "\n",
+ "#ax[0].annotate(\"dF = 1.25 Wm$^{-2}$\",(-20,50))\n",
+ "#ax[0].annotate(\"23%\",(70,20))\n",
+ "#ax[0].annotate(\"80%\",(45,20))\n",
+ "#ax[0].annotate(\"-3%\",(20,20))\n",
+ "\n",
+ "ax[0].text(-0.15,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.15,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "plt.savefig(\"plots/TOA_EB.pdf\")\n",
+ "plt.savefig(\"plots/TOA_EB.png\", dpi=500)\n",
+ "plt.show()\n",
+ "print(winton_exparray[ind])\n",
+ "print(semtner_exparray[ind])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'13'"
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "f'{100*round(dE[sky_ind] / dglob[sky_ind],2):.0f}'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_2437ppmv_winton and mlo_aqua_1688ppmv_hice_unlim\n",
+ "clear sky:\n",
+ "565.753899508404 PW; 1.109181153884533 W/m^2 = 1.2489128 W/m^2\n",
+ "0.26597838147609043\n",
+ "0.7762234553976921\n",
+ "-0.04220183687378603\n",
+ "all sky:\n",
+ "477.785142218552 PW; 0.9367151968644755 W/m^2 = 1.0097504 W/m^2\n",
+ "0.18244825306403012\n",
+ "0.6864882730880162\n",
+ "0.13106347384797457\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(winton_exparray[ind] +\" and \" +semtner_exparray[ind])\n",
+ "for sky_ind in range(2):\n",
+ " if sky_ind==0:\n",
+ " print(\"clear sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsutcs\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsutcs\", True), 40)\n",
+ " else:\n",
+ " print(\"all sky:\")\n",
+ " total = selmean(get_var(winton_simarray[ind],\"rsut\", True), 40) - selmean(get_var(semtner_simarray[ind],\"rsut\", True), 40)\n",
+ " \n",
+ " print(str(dglob[sky_ind]*1e-12) +\" PW; \" +str(dglob[sky_ind]/(4 * np.pi *6371000**2)) +\" W/m^2 = \" +str(total.values)+\" W/m^2\" )\n",
+ " print(dN1[sky_ind] / dglob[sky_ind])\n",
+ " print(dN2[sky_ind] / dglob[sky_ind])\n",
+ " print(dE[sky_ind] / dglob[sky_ind])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " \n",
+ " f1 = ax[axind,0].contourf(albedo_Wzmmean.lat,albedo_Wzmmean.month, albedo_Wzmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " f2 = ax[axind,1].contourf(albedo_Szmmean.lat,albedo_Szmmean.month, albedo_Szmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " c2 = ax[axind,1].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(winton_exparray[ind])\n",
+ " ax[axind,1].set_title(semtner_exparray[ind])\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " cbar.set_label(\"surface albedo\")\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x432 with 3 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(1,2,figsize=(8,6), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "ind=1\n",
+ "\n",
+ "albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ "albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ "sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ "sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ "\n",
+ "albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ "albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ "sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ "sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ "\n",
+ "f1 = ax[0].contourf(albedo_Wzmmean.lat,albedo_Wzmmean.month, albedo_Wzmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ "f2 = ax[1].contourf(albedo_Szmmean.lat,albedo_Szmmean.month, albedo_Szmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ "\n",
+ "c1 = ax[0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ "c2 = ax[1].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ "plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ "plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ "\n",
+ "ax[0].set_xlim(35,70)\n",
+ "ax[0].set_title(winton_exparray[ind])\n",
+ "ax[1].set_title(semtner_exparray[ind])\n",
+ "cbar = plt.colorbar(f2,ax=ax[1])\n",
+ "cbar.set_label(\"surface albedo\")\n",
+ "\n",
+ "ax[0].set_ylabel(\"month\")\n",
+ "ax[0].set_ylabel(\"month\")\n",
+ "ax[0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1].set_xlabel(\"latitude [°]\")\n",
+ "plt.savefig(\"plots/hovmoeller_albedo.png\",dpi=300)\n",
+ "plt.savefig(\"plots/hovmoeller_albedo.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 0, 'latitude [°]')"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of snow thickness\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=np.linspace(0,2,11)\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " hs_Wzm = get_var(winton_zmsimarray[ind], \"hs_icecl\")\n",
+ " hs_Szm = get_var(semtner_zmsimarray[ind], \"hs_icecl\")\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " hs_Wzmmean = selmonmean(hs_Wzm, 40)\n",
+ " hs_Szmmean = selmonmean(hs_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " \n",
+ " f1 = ax[axind,0].contourf(hs_Wzmmean.lat,hs_Wzmmean.month, hs_Wzmmean,levels = ticks)\n",
+ " f2 = ax[axind,1].contourf(hs_Szmmean.lat,hs_Szmmean.month, hs_Szmmean,levels = ticks)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " c2 = ax[axind,1].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(winton_exparray[ind])\n",
+ " ax[axind,1].set_title(semtner_exparray[ind])\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " cbar.set_label(\"snow thickness [m]\")\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,1,figsize=(8,12), sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_W = get_albedo(winton_simarray[ind])\n",
+ " albedo_S = get_albedo(semtner_simarray[ind])\n",
+ " \n",
+ " sic_W = get_var(winton_simarray[ind], \"sic\")\n",
+ " sic_S = get_var(semtner_simarray[ind], \"sic\")\n",
+ " \n",
+ " albedo_Wmean = selmonmean(albedo_W, 40)\n",
+ " albedo_Smean = selmonmean(albedo_S, 40)\n",
+ " sic_Wmean = selmonmean(sic_W, 40)\n",
+ " sic_Smean = selmonmean(sic_S, 40)\n",
+ " \n",
+ " ax[axind].plot(sic_Smean.month,sic_Smean)\n",
+ " ax[axind].plot(sic_Wmean.month,sic_Wmean)\n",
+ " \n",
+ " axind+=1\n",
+ " #c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 0, 'latitude [°]')"
+ ]
+ },
+ "execution_count": 36,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "colors1 = np.linspace(0.0, 1.0, 12)\n",
+ "colors = np.append(\"darkblue\",colors1.astype(\"str\"))\n",
+ "\n",
+ "#ticks=[0,0.01, 0.5,1,1.5,2,2.5,3,3.5,4,4.5,5,10,20]\n",
+ "ticks=[0, 0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8]\n",
+ "\n",
+ "cmap= mpl.colors.ListedColormap(colors)\n",
+ "norm = mpl.colors.BoundaryNorm(ticks, cmap.N)\n",
+ "\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " rsutcs_Wzm = get_var(winton_zmsimarray[ind], \"rsutcs\")\n",
+ " rsutcs_Szm = get_var(semtner_zmsimarray[ind], \"rsutcs\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ " rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ " \n",
+ " #f1 = ax[axind,0].contourf(albedo_Wzmmean.lat,albedo_Wzmmean.month, albedo_Wzmmean,levels = ticks,cmap= cmap,norm=norm)\n",
+ " f2 = ax[axind,1].contourf(albedo_Szmmean.lat,albedo_Szmmean.month, albedo_Szmmean-albedo_Wzmmean)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " c2 = ax[axind,0].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"red\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(winton_exparray[ind])\n",
+ " ax[axind,1].set_title(semtner_exparray[ind])\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " cbar.set_label(\"surface albedo\")\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-70. -65. -60. -55. -50. -45. -40. -35. -30. -25. -20. -15. -10. -5.\n",
+ " 0. 5. 10. 15. 20. 25. 30. 35. 40. 45. 50. 55. 60. 65.\n",
+ " 70.]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 360x864 with 4 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "from matplotlib.colors import LinearSegmentedColormap\n",
+ "fig, ax = plt.subplots(2,1,figsize=(5,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "cmap1 = plt.get_cmap(\"Reds\")\n",
+ "cmap2 = plt.get_cmap(\"Blues_r\")\n",
+ "\n",
+ "cmap = LinearSegmentedColormap.from_list(\"blub\", colors, N=12)\n",
+ "ticks=np.linspace(-70,70,29)\n",
+ "print(ticks)\n",
+ "\n",
+ "for ind in [1,0]:\n",
+ " albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ " albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " rsutcs_Wzm = get_var(winton_zmsimarray[ind], \"rsut\")\n",
+ " rsutcs_Szm = get_var(semtner_zmsimarray[ind], \"rsut\")\n",
+ " \n",
+ " albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ " albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ " rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ " rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ " \n",
+ " #f1 = ax[axind,0].contourf(rsutcs_Wzmmean.lat,rsutcs_Wzmmean.month, rsutcs_Wzmmean, levels=ticks)\n",
+ " f2 = ax[axind].contourf(rsutcs_Szmmean.lat,rsutcs_Szmmean.month, rsutcs_Szmmean-rsutcs_Wzmmean, levels=ticks,cmap=\"seismic\")\n",
+ " \n",
+ " c1 = ax[axind].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"C1\",linewidths=1.5)\n",
+ " c2 = ax[axind].contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999],colors=\"C0\",linewidths=1.5)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"C1\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"C0\")\n",
+ " \n",
+ " ax[axind].set_xlim(35,85)\n",
+ " ax[axind].set_title(str(winton_exparray[ind]) +\"-\" +str(semtner_exparray[ind]),fontdict={'size': 10})\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind])\n",
+ " cbar.set_label(\"$\\Delta$TOA SW cs out [Wm$^{-2}$]\")\n",
+ " axind+=1\n",
+ "ax[0].set_ylabel(\"month\")\n",
+ "ax[1].set_ylabel(\"month\")\n",
+ "ax[1].set_xlabel(\"latitude [°]\")\n",
+ "ax[1].set_xlabel(\"latitude [°]\")\n",
+ "plt.savefig(\"plots/hovmoeller_rsutcs_multi.png\",dpi=300)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-35. -32.5 -30. -27.5 -25. -22.5 -20. -17.5 -15. -12.5 -10. -7.5\n",
+ " -5. -2.5 0. 2.5 5. ]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 432x432 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(1,1,figsize=(6,6))\n",
+ "var=\"rsutcs\"\n",
+ "ind=1\n",
+ "\n",
+ "ticks=np.linspace(-35,5,17)\n",
+ "#ticks=np.linspace(-55,5,13)\n",
+ "print(ticks)\n",
+ "reds = mpl.cm.get_cmap('Reds', np.size(ticks)-3)\n",
+ "blues = mpl.cm.get_cmap('Blues_r', np.size(ticks)-3)\n",
+ "\n",
+ "\n",
+ "newcolors2 = reds(np.linspace(0, 1, np.size(ticks)-3))\n",
+ "newcolors = blues(np.linspace(0, 1, np.size(ticks)-3))\n",
+ "newcolors = np.vstack((newcolors, newcolors2[:2,:]))\n",
+ "\n",
+ "cmap = mpl.colors.ListedColormap(newcolors, name='newcmap')\n",
+ "\n",
+ "\n",
+ "albedo_Wzm = get_albedo(winton_zmsimarray[ind])\n",
+ "albedo_Szm = get_albedo(semtner_zmsimarray[ind])\n",
+ "\n",
+ "sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ "sic_Szm = get_var(semtner_zmsimarray[ind], \"sic\")\n",
+ "\n",
+ "rsutcs_Wzm = get_var(winton_zmsimarray[ind], var)\n",
+ "rsutcs_Szm = get_var(semtner_zmsimarray[ind], var)\n",
+ "\n",
+ "albedo_Wzmmean = selmonmean(albedo_Wzm, 40)\n",
+ "albedo_Szmmean = selmonmean(albedo_Szm, 40)\n",
+ "sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ "sic_Szmmean = selmonmean(sic_Szm, 40)\n",
+ "rsutcs_Wzmmean = selmonmean(rsutcs_Wzm, 40)\n",
+ "rsutcs_Szmmean = selmonmean(rsutcs_Szm, 40)\n",
+ "\n",
+ "#f1 = ax[axind,0].contourf(rsutcs_Wzmmean.lat,rsutcs_Wzmmean.month, rsutcs_Wzmmean, levels=ticks)\n",
+ "f2 = ax.contourf(rsutcs_Szmmean.lat,rsutcs_Szmmean.month, rsutcs_Szmmean-rsutcs_Wzmmean, levels=ticks,cmap=cmap)\n",
+ "\n",
+ "c1 = ax.contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999999],colors=\"C1\",linewidths=1.5)\n",
+ "c2 = ax.contour(sic_Szmmean.lat,sic_Szmmean.month, sic_Szmmean, levels=[0,0.5,0.999999999],colors=\"C0\",linewidths=1.5)\n",
+ "plt.clabel(c1,fmt='%1.1f',colors=\"C1\")\n",
+ "plt.clabel(c2,fmt='%1.1f',colors=\"C0\")\n",
+ "\n",
+ "ax.set_xlim(35,70)\n",
+ "cbar = plt.colorbar(f2)\n",
+ "cbar.set_label(\"$\\Delta$TOA SW as out [Wm$^{-2}$]\")\n",
+ "\n",
+ "ax.set_ylabel(\"Month\")\n",
+ "ax.set_xlabel(\"Latitude [°]\")\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.savefig(\"plots/hovmoeller_\" +var +\".png\",dpi=300)\n",
+ "plt.savefig(\"plots/hovmoeller_\" +var +\".pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
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+ ".xr-section-item input + label {\n",
+ " color: var(--xr-disabled-color);\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input:enabled + label {\n",
+ " cursor: pointer;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input:enabled + label:hover {\n",
+ " color: var(--xr-font-color0);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary {\n",
+ " grid-column: 1;\n",
+ " color: var(--xr-font-color2);\n",
+ " font-weight: 500;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary > span {\n",
+ " display: inline-block;\n",
+ " padding-left: 0.5em;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label {\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in + label:before {\n",
+ " display: inline-block;\n",
+ " content: '►';\n",
+ " font-size: 11px;\n",
+ " width: 15px;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label:before {\n",
+ " color: var(--xr-disabled-color);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label:before {\n",
+ " content: '▼';\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label > span {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary,\n",
+ ".xr-section-inline-details {\n",
+ " padding-top: 4px;\n",
+ " padding-bottom: 4px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-inline-details {\n",
+ " grid-column: 2 / -1;\n",
+ "}\n",
+ "\n",
+ ".xr-section-details {\n",
+ " display: none;\n",
+ " grid-column: 1 / -1;\n",
+ " margin-bottom: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap {\n",
+ " grid-column: 1 / -1;\n",
+ " display: grid;\n",
+ " grid-template-columns: 20px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap > label {\n",
+ " grid-column: 1;\n",
+ " vertical-align: top;\n",
+ "}\n",
+ "\n",
+ ".xr-preview {\n",
+ " color: var(--xr-font-color3);\n",
+ "}\n",
+ "\n",
+ ".xr-array-preview,\n",
+ ".xr-array-data {\n",
+ " padding: 0 5px !important;\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-array-data,\n",
+ ".xr-array-in:checked ~ .xr-array-preview {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-array-in:checked ~ .xr-array-data,\n",
+ ".xr-array-preview {\n",
+ " display: inline-block;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list {\n",
+ " display: inline-block !important;\n",
+ " list-style: none;\n",
+ " padding: 0 !important;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li {\n",
+ " display: inline-block;\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:before {\n",
+ " content: '(';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:after {\n",
+ " content: ')';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li:not(:last-child):after {\n",
+ " content: ',';\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-has-index {\n",
+ " font-weight: bold;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list,\n",
+ ".xr-var-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > div,\n",
+ ".xr-var-item label,\n",
+ ".xr-var-item > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-even);\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > .xr-var-name:hover span {\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list > li:nth-child(odd) > div,\n",
+ ".xr-var-list > li:nth-child(odd) > label,\n",
+ ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-odd);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name {\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dims {\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dtype {\n",
+ " grid-column: 3;\n",
+ " text-align: right;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-preview {\n",
+ " grid-column: 4;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name,\n",
+ ".xr-var-dims,\n",
+ ".xr-var-dtype,\n",
+ ".xr-preview,\n",
+ ".xr-attrs dt {\n",
+ " white-space: nowrap;\n",
+ " overflow: hidden;\n",
+ " text-overflow: ellipsis;\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name:hover,\n",
+ ".xr-var-dims:hover,\n",
+ ".xr-var-dtype:hover,\n",
+ ".xr-attrs dt:hover {\n",
+ " overflow: visible;\n",
+ " width: auto;\n",
+ " z-index: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data {\n",
+ " display: none;\n",
+ " background-color: var(--xr-background-color) !important;\n",
+ " padding-bottom: 5px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+ ".xr-var-data-in:checked ~ .xr-var-data {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ ".xr-var-data > table {\n",
+ " float: right;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name span,\n",
+ ".xr-var-data,\n",
+ ".xr-attrs {\n",
+ " padding-left: 25px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs,\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data {\n",
+ " grid-column: 1 / -1;\n",
+ "}\n",
+ "\n",
+ "dl.xr-attrs {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " display: grid;\n",
+ " grid-template-columns: 125px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt,\n",
+ ".xr-attrs dd {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " float: left;\n",
+ " padding-right: 10px;\n",
+ " width: auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
+ " word-break: break-all;\n",
+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2 {\n",
+ " display: inline-block;\n",
+ " vertical-align: middle;\n",
+ " width: 1em;\n",
+ " height: 1.5em !important;\n",
+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'rsutcs' ()>\n",
+ "array(-53.59790039)\n",
+ "Coordinates:\n",
+ " lon float64 0.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'rsutcs'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7609ff91-1a93-4b37-803a-a3cc1f3675d8' class='xr-array-in' type='checkbox' checked><label for='section-7609ff91-1a93-4b37-803a-a3cc1f3675d8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-53.6</span></div><div class='xr-array-data'><pre>array(-53.59790039)</pre></div></div></li><li class='xr-section-item'><input id='section-5bf40b2e-b3f3-4447-b5c8-a907083eaeda' class='xr-section-summary-in' type='checkbox' checked><label for='section-5bf40b2e-b3f3-4447-b5c8-a907083eaeda' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-d333ac2b-7e55-46be-a98e-4526ce3dbd81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d333ac2b-7e55-46be-a98e-4526ce3dbd81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5a56c7f-fa02-474e-9fd9-04ac57ef31f5' class='xr-var-data-in' type='checkbox'><label for='data-c5a56c7f-fa02-474e-9fd9-04ac57ef31f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e968cfe-3209-49fd-be27-d39979ca9521' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2e968cfe-3209-49fd-be27-d39979ca9521' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.DataArray 'rsutcs' ()>\n",
+ "array(-53.59790039)\n",
+ "Coordinates:\n",
+ " lon float64 0.0"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "(rsutcs_Szmmean-rsutcs_Wzmmean).min()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.colors.LinearSegmentedColormap at 0x2b35e7fee5d0>"
+ ]
+ },
+ "execution_count": 83,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cmap"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 112,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.colorbar.Colorbar at 0x2b35e9105090>"
+ ]
+ },
+ "execution_count": 112,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "\n",
+ "top = mpl.cm.get_cmap('Reds_r', 128)\n",
+ "bottom = mpl.cm.get_cmap('Blues', 128)\n",
+ "\n",
+ "\n",
+ "\n",
+ "newcolors = bottom(np.linspace(0, 1, 12))\n",
+ "white = np.array([1, 1, 1, 1])\n",
+ "newcolors = np.vstack((white, newcolors))\n",
+ "newcolors = np.vstack((white, newcolors))\n",
+ "newcmp = mpl.colors.ListedColormap(newcolors)\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.contourf([np.linspace(0,100,1001),np.linspace(0,100,1001)],np.linspace(0,100,1001),cmap=newcmp)\n",
+ "plt.colorbar()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([[1. , 1. , 1. , 1. ],\n",
+ " [1. , 1. , 1. , 1. ],\n",
+ " [0.90069477, 0.94083681, 0.97826154, 1. ],\n",
+ " [0.82834646, 0.89340744, 0.95454686, 1. ],\n",
+ " [0.75423807, 0.84937471, 0.92947352, 1. ],\n",
+ " [0.63566466, 0.79898101, 0.88797283, 1. ],\n",
+ " [0.48889918, 0.72039524, 0.85416088, 1. ],\n",
+ " [0.36390304, 0.64431064, 0.81747723, 1. ],\n",
+ " [0.24557666, 0.55930215, 0.76964644, 1. ],\n",
+ " [0.14775359, 0.46147908, 0.71925274, 1. ],\n",
+ " [0.0753744 , 0.37396943, 0.65576656, 1. ],\n",
+ " [0.03137255, 0.27790644, 0.55275591, 1. ],\n",
+ " [0.03137255, 0.18823529, 0.41960784, 1. ]])"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.vstack((white, newcolors))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 133,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-20. -19. -18. -17. -16. -15. -14. -13. -12. -11. -10. -9. -8. -7.\n",
+ " -6. -5. -4. -3. -2. -1. 0.]\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "Text(0.5, 0, 'latitude [°]')"
+ ]
+ },
+ "execution_count": 133,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 576x864 with 6 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# hovmoeller plots of reflected sw radiation\n",
+ "fig, ax = plt.subplots(2,2,figsize=(8,12), sharey = True, sharex = True, constrained_layout=True)\n",
+ "axind=0\n",
+ "\n",
+ "ticks=np.linspace(-20,0,21)\n",
+ "print(ticks)\n",
+ "\n",
+ "\n",
+ "\n",
+ "for ind in [2,0]:\n",
+ " T1zm = get_var(winton_zmsimarray[ind], \"t1_icecl\")\n",
+ " T2zm = get_var(winton_zmsimarray[ind], \"t2_icecl\")\n",
+ " \n",
+ " sic_Wzm = get_var(winton_zmsimarray[ind], \"sic\")\n",
+ " \n",
+ " sic_Wzmmean = selmonmean(sic_Wzm, 40)\n",
+ " T1_Wzmmean = selmonmean(T1zm, 40)\n",
+ " T2_Wzmmean = selmonmean(T2zm, 40)\n",
+ " \n",
+ " f1 = ax[axind,0].contourf(T1_Wzmmean.lat,T1_Wzmmean.month, T1_Wzmmean,levels=ticks)\n",
+ " f2 = ax[axind,1].contourf(T2_Wzmmean.lat,T2_Wzmmean.month, T2_Wzmmean,levels=ticks)\n",
+ " \n",
+ " c1 = ax[axind,0].contour(sic_Wzmmean.lat,sic_Wzmmean.month, sic_Wzmmean, levels=[0,0.5,0.999999],colors=\"orange\",linewidths=1)\n",
+ " plt.clabel(c1,fmt='%1.1f',colors=\"orange\")\n",
+ " plt.clabel(c2,fmt='%1.1f',colors=\"orange\")\n",
+ " \n",
+ " ax[axind,0].set_xlim(35,85)\n",
+ " ax[axind,0].set_title(\"T1\")\n",
+ " ax[axind,1].set_title(\"T2\")\n",
+ " cbar = plt.colorbar(f2,ax=ax[axind,1])\n",
+ " axind+=1\n",
+ "ax[0,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_ylabel(\"month\")\n",
+ "ax[1,0].set_xlabel(\"latitude [°]\")\n",
+ "ax[1,1].set_xlabel(\"latitude [°]\")\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 81,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "unsupported operand type(s) for /: 'tuple' and 'int'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-68-c3a95e9b0ab5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap1\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbytes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;36m256\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'tuple' and 'int'"
+ ]
+ }
+ ],
+ "source": [
+ "plt.plot(2,2,color=cmap1(0,bytes=True)/256)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([[1. , 0.96078431, 0.94117647, 1. ],\n",
+ " [0.99987697, 0.95820069, 0.93748558, 1. ]])"
+ ]
+ },
+ "execution_count": 70,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cmap1(range(2))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "new-kernel",
+ "language": "python",
+ "name": "new-kernel"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /Winton_artificial_forcing.ipynb b/python_scripts /Winton_artificial_forcing.ipynb
new file mode 100644
index 0000000..0907502
--- /dev/null
+++ b/python_scripts /Winton_artificial_forcing.ipynb
@@ -0,0 +1,1575 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Offline sea-ice models: Semnter 0-layer and reformulated Winton 3-layer\n",
+ "\n",
+ "Sea-ice models are written to resemble the models as implemented in ICON-AES 1.3.00. The Winton model is almost exactly structured as in Winton (2000), except for small fixes (which are also in the ICON code).\n",
+ "The Semnter 0-layer models is further simplified, especially as brine pockets are neglected (as in the ICON code). \n",
+ "Calculcation of surface fluxes is not a part of either model, it's implemented in the same way as in ICON.\n",
+ "\n",
+ "Semtner, A. J. (1976) ‘A Model for the Thermodynamic Growth of Sea Ice in Numerical Investigations of Climate’, Journal of Physical Oceanography, 6(3), pp. 379–389. doi: 10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2.\n",
+ "\n",
+ "Winton, M. (2000) ‘A Reformulated Three-Layer Sea Ice Model’, Journal of Atmospheric and Oceanic Technology, 17(4), pp. 525–531. doi: 10.1175/1520-0426(2000)017<0525:ARTLSI>2.0.CO;2.\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import xarray as xr\n",
+ "import matplotlib.pyplot as plt\n",
+ "import math\n",
+ "import pylab as pl"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.27\n"
+ ]
+ }
+ ],
+ "source": [
+ "# physical constants from ICON\n",
+ "dtime = 600 # model time step [s]\n",
+ "Ki = 2.1656 # heat conductivity ice [J/(msK)]\n",
+ "Ks = 0.31 # heat conductivity snow [J/(msK)]\n",
+ "rhoi = 917.0 # density of sea ice [kg/m^3]\n",
+ "rhos = 300 # density of snow [kg/m^3]\n",
+ "rhow = 1025.022 # density of ocean water [kg/m^3]\n",
+ "ci = 2106 # heat capacity of ice [J/(kgK)]\n",
+ "cs = 2090 # heat capacity of snow [J/(kgK)]\n",
+ "Tf = -1.9 # freezing temperature of ocean water [°C]\n",
+ "Tmelt = 273.15 # melting temperature of water [K]\n",
+ "zemissdef = 0.996 # longwave emissivity factor [] ICON\n",
+ "#zemissdef = 1-0.7 # longwave emissivity factor [] Abbot(2010)\n",
+ "sigma = 5.6704e-8 # Stefan-Boltzman constant [W/(m^2K^4)]\n",
+ "# albedo values defined in runscript!\n",
+ "albsnow_warm = 0.66\n",
+ "albsnow_cold = 0.79\n",
+ "albice_warm = 0.38\n",
+ "albice_cold = 0.45\n",
+ "I0 = 0.17 # ice surface penetrating radiation []\n",
+ "L = 2.8345e6 - 2.5008e6 # latent heat of fusion [J/kg]\n",
+ "muS = 0.054 * 5.0 # constant of linear salt - freezing point relationship * Sea ice bulk salinity [°C]\n",
+ "\n",
+ "hcilayer = 0.1 # thickness of stabilizing constant heat capacity layer [m]\n",
+ "\n",
+ "print(muS)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# functions\n",
+ "def E(T): \n",
+ " return ci*(T+muS)-L*(1+muS/T) # enthalpy of melting for upper layer [J/kg] #(1)\n",
+ "def E2(T):\n",
+ " return ci*(T+muS)-L # enthalpy of melting for lower layer [J/kg] #(25)\n",
+ "\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ "\n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# surface fluxes (not actually part of the Winton Model!)\n",
+ "def surface_fluxes(Tsurfold, hsold, rsds, rlds, lhflx, shflx, albedo):\n",
+ " #print(\"calculate surface fluxes\")\n",
+ " # check for snow on ice\n",
+ " if hsold>0: \n",
+ " I=0 # fraction of penetrating radiation []\n",
+ " #print(\"snow on ice\")\n",
+ " else: \n",
+ " I=I0\n",
+ " #print(\"bare ice\")\n",
+ " if hsold>1e-6: # ICON checks diferently for Tsurfmelt and I!\n",
+ " Tsurfmelt = 0 # melting temperature of surface [°C]\n",
+ " #print(\"snow on ice\")\n",
+ " else: \n",
+ " Tsurfmelt = - muS\n",
+ " #print(\"bare ice\")\n",
+ "\n",
+ " # surface energy flux balance \n",
+ " # longwave incoming + longwave outgoing + shortwave balance + latent heat flux + sensible heat flux\n",
+ " # in ICON: addition of zemissdef\n",
+ " SWnet = rsds * (1-albedo)\n",
+ " FS = 1* ( zemissdef *(rlds - sigma* (Tsurfold+Tmelt)**4 ) + SWnet*(1-I) + lhflx + shflx ) #UPWARD flux!\n",
+ " dFS = -4 * zemissdef * sigma * (Tsurfold+Tmelt)**3\n",
+ " \n",
+ " #print(\"FS = \" +str(FS) +\" W/m^2\")\n",
+ " #print(\"dFS = \" +str(dFS) +\" + \" +str(rhoi * hcilayer /dtime *ci) +\" W/(m^2K)\")\n",
+ " \n",
+ " return FS, dFS, SWnet, I, Tsurfmelt "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 2.a) temperature calculation\n",
+ "def set_ice_temp(Tsurfold, T1old, T2old, hiold, hsold, FS, dFS, SWnet, I, Tsurfmelt, c_stability=True):\n",
+ "# if hsold>1e-6: \n",
+ "# I=0 # fraction of penetrating radiation []\n",
+ "# Tsurfmelt = 0 # melting temperature of surface [°C]\n",
+ "# print(\"snow on ice\")\n",
+ "# else: \n",
+ "# Tsurfmelt = - muS\n",
+ "# I=I0 # fraction of penetrating radiation []\n",
+ "# print(\"bare ice\")\n",
+ " \n",
+ " # Factor B + stabilizing ice layer in ICON ?\n",
+ " # stabilizing ice layer dominates the sensitivity of temperature on surface flux balance -> surface temperature is far less sensitive\n",
+ " B = -dFS #(8)\n",
+ " if c_stability:\n",
+ " B = B+rhoi * hcilayer /dtime *ci \n",
+ " A = -FS - Tsurfold * B #(7)\n",
+ "\n",
+ " #conductivities\n",
+ " K12 = (4*Ki*Ks) / (Ks*hiold + 4*Ki*hsold) # coupled conductivity of snow-ice layer (upper layer) [W/(mK)] (5)\n",
+ " K32 = 2*Ki/hiold # coupled conductivity of both ice layers (lower layer) [W/(mK)] (10)\n",
+ "\n",
+ "\n",
+ " A1 = (rhoi*hiold)/(2*dtime) * ci + K32*(4*dtime*K32+rhoi*hiold*ci)/(6*dtime*K32+rhoi*hiold*ci) + (K12*B)/(K12+B) # (16)\n",
+ " B1 = -1*(rhoi*hiold)/(2*dtime) * (ci*T1old - (L*muS)/T1old) - SWnet * I - \\\n",
+ " K32 * (4*dtime*K32*Tf + rhoi*hiold*ci*T2old)/(6*dtime*K32 + rhoi*hiold*ci) + (A*K12)/(K12+B) # (17)\n",
+ " C1 = -1 * (rhoi*hiold)/(2*dtime) * L *muS\n",
+ "\n",
+ " # temperature T1\n",
+ " T1 = -1 * (B1+ (B1**2 - 4*A1*C1)**0.5)/(2*A1) # (21)\n",
+ "\n",
+ " # temperature T2 (not necessary to calculate here?)\n",
+ " T2 = (2 * dtime * K32 * (T1 + 2*Tf) + rhoi*hiold*ci*T2old) / (6 * dtime * K32 + rhoi * hiold * ci) #(15)\n",
+ "\n",
+ " # surface temperature\n",
+ " Tsurf = (K12 * T1 - A) / (K12 + B) # (6)\n",
+ " #print(K12,A,B)\n",
+ "\n",
+ " if Tsurf>Tsurfmelt: #check for melting of upper snow or ice surface\n",
+ " #print(\"surface melting\")\n",
+ " Tsurf = Tsurfmelt\n",
+ " \n",
+ " # recalculate A1 & B1 for surface melting\n",
+ " A1 = (rhoi*hiold)/(2*dtime) * ci + K32*(4*dtime*K32+rhoi*hiold*ci)/(6*dtime*K32+rhoi*hiold*ci) + K12 # (19)\n",
+ " B1 = -1*(rhoi*hiold)/(2*dtime) * (ci*T1old - (L*muS)/T1old) - SWnet * I- \\\n",
+ " K32 * (4*dtime*K32*Tf + rhoi*hiold*ci*T2old)/(6*dtime*K32 + rhoi*hiold*ci) + K12*Tsurf # (20)\n",
+ "\n",
+ " # recalculate T1 & T2\n",
+ " T1 = -1 * (B1+ (B1**2 - 4*A1*C1)**0.5)/(2*A1) # (21)\n",
+ " T2 = (2 * dtime * K32 * (T1 + 2*Tf) + rhoi*hiold*ci*T2old) / (6 * dtime * K32 + rhoi * hiold * ci) #(15)\n",
+ "\n",
+ " Qtop = K12 * (T1-Tsurf) - (A+B*Tsurf) # (22)\n",
+ " else:\n",
+ " Qtop = 0\n",
+ "\n",
+ " Qbot = -4 * Ki * (Tf-T2)/hiold # (23)\n",
+ "\n",
+ " # calculated values \n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf) +\" °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1) +\" °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2) +\" °C\")\n",
+ "\n",
+ " #print(\"Qbot= \" +str(Qbot) +\" W/m^2\")\n",
+ " #print(\"Qtop= \" +str(Qtop) +\" W/m^2\")\n",
+ "\n",
+ " # Temeperatures may change in the ice growth scheme!\n",
+ " # ICON output values\n",
+ " #print(\"ICON: \")\n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf_ICON) +\" °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1_ICON) +\" °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2_ICON) +\" °C\")\n",
+ " \n",
+ " return Tsurf, T1, T2, Qbot, Qtop"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# 2.b) ice thickness calculation\n",
+ "\n",
+ "def ice_growth(hiold, hsold, Tsurf, T1, T2, Qbot, Qtop, prls, prcs):\n",
+ " # snow thickness calculation\n",
+ " #print(\"calculate snow accumulation\")\n",
+ " hs=hsold +(prls+prcs)*dtime / rhos\n",
+ "\n",
+ " #print(\"hs: \" +str(hsold) +\" -> \" +str(hs) +\" m\")\n",
+ "\n",
+ " # initialize h1 & h2\n",
+ " h1=hiold/2\n",
+ " h2=hiold/2\n",
+ "\n",
+ "\n",
+ " #print(\"calculate ice thickness change\")\n",
+ " # bottom accretion\n",
+ " if Qbot<0:\n",
+ " #print(\"bottom accretion\")\n",
+ " dh2 = Qbot * dtime / (rhoi * E2(Tf)) #(24) \n",
+ " T2 = (dh2*Tf + h2*T2)/(dh2 + h2) #temperature change of lower ice layer due to added mass (26)\n",
+ " h2 += dh2 \n",
+ " \n",
+ " hi = h1+h2\n",
+ " \n",
+ " fluxres_w=0\n",
+ " # surface melting\n",
+ " if Qtop>0:\n",
+ " #print(\"surface melting\")\n",
+ " dhs = -min( (Qtop*dtime) /(L *rhos) ,hs) #(27)\n",
+ " dh1 = -min(max((Qtop*dtime - L*hs*rhos) /(-1*E(T1) *rhoi),0 ),h1) #(28)\n",
+ " dh2 = -min(max((Qtop*dtime - L*hs*rhos + E(T1)*h1*rhoi)/(-1*E2(T2)*rhoi),0 ),h2) #(29)\n",
+ "\n",
+ " fluxres_w = max(Qtop*dtime - L*hs + E(T1)*hiold + E2(T2)*h2 ,0) #(30)\n",
+ " h1 += dh1\n",
+ " h2 += dh2\n",
+ " hs += dhs\n",
+ "\n",
+ " # bottom melting\n",
+ " if Qbot>0:\n",
+ " #print(\"bottom melting\")\n",
+ " dh2 = -min( (Qbot*dtime) /(-E2(T2)*rhoi) ,h2) #(31)\n",
+ " dh1 = -min(max((Qbot*dtime + E2(T2)*h2*rhoi) /(-E(T1)*rhoi) ,0),h1) #(32)\n",
+ " dhs = -min(max((Qbot*dtime + E2(T2)*h2*rhoi + E(T1)*h1*rhoi)/(L*rhos) ,0),hs) #(33)\n",
+ "\n",
+ " fluxres_w += max(Qbot*dtime - L*hs + E(T1)*hiold + E2(T2)+h2, 0)\n",
+ " h1 += dh1\n",
+ " h2 += dh2\n",
+ " hs += dhs\n",
+ " \n",
+ " hi = h1+h2\n",
+ "\n",
+ " # snow ice conversion\n",
+ " dhs = -max((hs - ((rhow-rhoi)/rhos)*hi)*(rhoi/rhow),0)\n",
+ " dh1 = -dhs\n",
+ " if dhs<0:\n",
+ " print(\"convert snow to ice\")\n",
+ "\n",
+ " # adjust T1 due to incorporation of zero heat capacity snow\n",
+ " f1 = h1/(h1+dh1)\n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(-muS) # (39) with T2=-muS\n",
+ " T1 = (Tbar - (Tbar**2 + 4*muS*L / ci)**0.5)/2 # (38)\n",
+ "\n",
+ "\n",
+ " hs += dhs\n",
+ " h1 += dh1\n",
+ " hi = h1+h2\n",
+ "\n",
+ " # even up h1 & h2 and change temperature accordingly\n",
+ " if h1>h2:\n",
+ " #print(\"convert h1 to h2\")\n",
+ "\n",
+ " f1 = h1/(0.5*hi)-1\n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(T2) # (39) \n",
+ " T2 = Tbar # (40)\n",
+ " elif h2>h1:\n",
+ " #print(\"convert h2 to h1\") \n",
+ "\n",
+ " f1 = h1/(0.5*hi) \n",
+ " Tbar = f1 * (T1- (L/ci) * (muS/T1)) + (1-f1)*(T2) # (39) \n",
+ " T1 = (Tbar - (Tbar**2 + 4*muS*L / ci)**0.5)/2 # (38)\n",
+ "\n",
+ "\n",
+ " # check if T2>-muS through ice conversion\n",
+ " # not explicitly defined in Winton (2000), taken from the ICON code\n",
+ " # available energy h2*ci*(T2 + muS) is used t euqally melt upper and lower layer with enthalpies E(T1) and E2(-muS)\n",
+ " if T2>-muS:\n",
+ " print(\"T2 over bulk melting temperature: melting\")\n",
+ " #hi = hi - h2*ci*(T2 + muS) / (0.5*L- 0.5*(ci*(T1 +muS) - L * (1+muS/T1)))\n",
+ " hi = hi - h2*ci*(T2 + muS) / (-0.5* E(T1) - 0.5* E2(-muS))\n",
+ " T2=-muS\n",
+ " \n",
+ " #print(\"hi: \" +str(hiold) +\" -> \" +str(hi) +\" (\" +str(hi_ICON) +\") m\")\n",
+ " #print(\"hs: \" +str(hsold) +\" -> \" +str(hs) +\" (\" +str(hs_ICON) +\") m\")\n",
+ " #print(\"Tsurf: \" +str(Tsurfold) +\" -> \" +str(Tsurf) +\" (\" +str(Tsurf_ICON) +\") °C\")\n",
+ " #print(\"T1: \" +str(T1old) +\" -> \" +str(T1) +\" (\" +str(T1_ICON) +\") °C\")\n",
+ " #print(\"T2: \" +str(T2old) +\" -> \" +str(T2) +\" (\" +str(T2_ICON) +\") °C\")\n",
+ "\n",
+ " #print(\"\")\n",
+ " return hi, hs, T1, T2, fluxres_w"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# surface fluxes \n",
+ "def surface_fluxes_semtner(Tsurfold, rsds, rlds, lhflx, shflx, albedo):\n",
+ " #print(\"calculate surface fluxes\")\n",
+ "\n",
+ " # surface energy flux balance \n",
+ " # longwave incoming + longwave outgoing + shortwave balance + latent heat flux + sensible heat flux\n",
+ " # in ICON: addition of zemissdef\n",
+ " SWnet = rsds * (1-albedo) # = swflx_ice\n",
+ " nonsolar_ice = 1* ( zemissdef *(rlds - sigma* (Tsurfold+Tmelt)**4 ) + lhflx + shflx ) #UPWARD flux # =nonsolar_ice!\n",
+ " dnonsolarT = -4 * zemissdef * sigma * (Tsurfold+Tmelt)**3 # dnonsolarT\n",
+ " \n",
+ " #print(\"FS = \" +str(FS) +\" W/m^2\")\n",
+ " #print(\"dFS = \" +str(dFS) +\" + \" +str(rhoi * hcilayer /dtime *ci) +\" W/(m^2K)\")\n",
+ " \n",
+ " return nonsolar_ice, dnonsolarT, SWnet\n",
+ "\n",
+ "\n",
+ "# set ice temperature\n",
+ "def set_ice_temp_semtner(Tsurfold, hiold, hsold, nonsolar_ice, dnonsolarT, SWnet, c_stability=True):\n",
+ " \n",
+ " # effective heat conductivity of ice&snow\n",
+ " k_eff = (Ki * Ks) / (Ks*hiold + Ki*hsold) # in Semtner paper not a variable but used in the formula for Fs\n",
+ " \n",
+ " F_A = -1*nonsolar_ice - SWnet # Flux from atmosphere, not in Semtner paper\n",
+ " \n",
+ " F_S = k_eff * (Tf - Tsurfold) # Flux into ice\n",
+ " \n",
+ " deltaTdenominator = k_eff - dnonsolarT \n",
+ " if c_stability:\n",
+ " deltaTdenominator = deltaTdenominator +rhoi*hcilayer*ci/dtime # addition of constant heat capacity to stabilize surface temperture (not in Semtner paper)\n",
+ " \n",
+ " deltaT = (F_S - F_A) / deltaTdenominator\n",
+ " \n",
+ " if Tsurfold + deltaT > 0: # Tsurf > 0°C -> Surface melting\n",
+ " deltaT = -Tsurfold\n",
+ " Tsurf = 0\n",
+ " \n",
+ " Qtop = (F_S - F_A) - deltaT * deltaTdenominator # Qtop >0 -> melting \n",
+ " # (F_S - F_A) -> flux imbalance from old surface temperature Tsurfold\n",
+ " # Tsurfold * deltaTdenominator -> flux imbalance resulting from warming Tsurf to 0°C (Tsurfold in °C!)\n",
+ " \n",
+ " Qbot = - F_S + deltaT * k_eff # originally Qbot = -F_S\n",
+ " else:\n",
+ " Tsurf = Tsurfold + deltaT\n",
+ " \n",
+ " Qtop = 0\n",
+ " Qbot = k_eff * (Tsurf - Tf)\n",
+ " \n",
+ " return Tsurf, Qbot, Qtop, F_A, F_S\n",
+ "\n",
+ "\n",
+ "def ice_growth_semtner(hiold, hsold, Tsurf, Qbot, Qtop, prls, prcs):\n",
+ " \n",
+ " #print(\"calculate snow accumulation\")\n",
+ " hs=hsold +(prls+prcs)*dtime / rhos\n",
+ " \n",
+ " \n",
+ " if hs>0:\n",
+ " hs = max(hs - dtime * Qtop / (L*rhos),0) # alf*rhos = qs\n",
+ " hi = hiold\n",
+ " else:\n",
+ " hi = max(hiold - dtime* Qtop / (L*rhoi),0) # alf*rhoi = qi\n",
+ " \n",
+ " hi = hi - dtime * Qbot / (L*rhoi) # Qbot=-F_S; alf*rhoi = qi\n",
+ " \n",
+ " return hi, hs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def set_albedo(hi, hs, Tsurf): # after set_ice_albedo in mo_sea_ice.f90 in ICON\n",
+ "\n",
+ " if hs>1e-2*rhow/rhos: # snow has to be thicker than 0.034m\n",
+ " if Tsurf==0:\n",
+ " albedo=albsnow_warm\n",
+ " elif Tsurf <=-1:\n",
+ " albedo=albsnow_cold\n",
+ " else:\n",
+ " albedo = (1 + Tsurf)*albsnow_warm - Tsurf*albsnow_cold\n",
+ "\n",
+ " else: # bare ice\n",
+ " if Tsurf==0:\n",
+ " albedo=albice_warm\n",
+ " elif Tsurf <=-1:\n",
+ " albedo=albice_cold\n",
+ " else:\n",
+ " albedo = (1 + Tsurf)*albice_warm - Tsurf*albice_cold\n",
+ " \n",
+ " \n",
+ " return albedo\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ -86400. -85800. -85200. ... 2677200. 2677800. 2678400.]\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2ba8c5d73cf8>]"
+ ]
+ },
+ "execution_count": 62,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# initial conditions\n",
+ "init_Tsurf = -10\n",
+ "init_T1 = -10\n",
+ "init_T2 = -6\n",
+ "init_Qbot = 0\n",
+ "init_Qtop = 0\n",
+ "init_hi = 1\n",
+ "init_hs = 0\n",
+ "\n",
+ "prls = 0\n",
+ "prcs = 0\n",
+ "albedo_init = albice_cold\n",
+ "\n",
+ "# boundary conditions\n",
+ "lhflx = 0\n",
+ "shflx = 0\n",
+ "\n",
+ "initial_conditions=\"melting_cold\"\n",
+ "if initial_conditions==\"melting\":\n",
+ " # melting -> melt ratched effect with abbot (2010) zemissfac\n",
+ " rlds = 0 \n",
+ " shflx = 60 \n",
+ " rsds = 500\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 4\n",
+ "elif initial_conditions==\"melting_icon\":\n",
+ " # melting -> melt ratched effect with ICON zemissfac\n",
+ " rlds = 0\n",
+ " shflx = 150\n",
+ " rsds = 750\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 4\n",
+ " \"\"\"\n",
+ " rlds = 0\n",
+ " shflx = 150 \n",
+ " rsds = 800\n",
+ " init_T1 = -4.5\n",
+ " init_T2 = -2.5\n",
+ " init_Tsurf = -3\n",
+ " init_hi = 1\"\"\"\n",
+ "elif initial_conditions==\"melting_snow\":\n",
+ " rlds = 0\n",
+ " shflx = 150\n",
+ " rsds = 700\n",
+ " init_T1 = -14\n",
+ " init_T2 = -8\n",
+ " init_Tsurf = -5\n",
+ " init_hi = 20\n",
+ " init_hs = 1\n",
+ "elif initial_conditions==\"freezing\":\n",
+ " # freezing\n",
+ " rlds = 0 \n",
+ " shflx = 20\n",
+ " init_hi = 2\n",
+ " init_hs = 0.5\n",
+ " rsds = 500\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -9\n",
+ " init_T2 = -5\n",
+ " init_Tsurf = -5\n",
+ "elif initial_conditions==\"freezing_2\":\n",
+ " # freezing\n",
+ " init_hi = 0.05\n",
+ " init_hs = 0.0\n",
+ " prls = 0\n",
+ " rlds = 0 \n",
+ " shflx = 20\n",
+ " rsds = 500\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -1.9\n",
+ " init_T2 = -1.9\n",
+ " init_Tsurf = -1.9\n",
+ "elif initial_conditions==\"freezing_cold\":\n",
+ " # freezing\n",
+ " init_hi = 10\n",
+ " init_hs = 0.0\n",
+ " prls = 0\n",
+ " rlds = 0 \n",
+ " shflx = 20\n",
+ " rsds = 500\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -40\n",
+ " init_T2 = -50\n",
+ " init_Tsurf = -20\n",
+ "elif initial_conditions==\"melting_cold\":\n",
+ " # freezing\n",
+ " init_hi = 10\n",
+ " init_hs = 1.0\n",
+ " prls = 0\n",
+ " rlds = 0 \n",
+ " shflx = 150\n",
+ " rsds = 750\n",
+ " #rlds = 100 \n",
+ " #rsds = 200\n",
+ " init_T1 = -100\n",
+ " init_T2 = -100\n",
+ " init_Tsurf = -60\n",
+ "elif initial_conditions==\"melting_2\":\n",
+ " rlds = 120 \n",
+ " rsds = 300\n",
+ " init_hi = 1\n",
+ " init_T1 = -5\n",
+ " init_T2 = -3\n",
+ " init_Tsurf = -8\n",
+ "elif initial_conditions==\"snowball\":\n",
+ " shflx = -50\n",
+ " rlds = 0\n",
+ " rsds = 800\n",
+ " init_T1 = -7\n",
+ " init_T2 = -5\n",
+ " init_Tsurf = -10\n",
+ " init_hi = 20\n",
+ "elif initial_conditions==\"abbot\":\n",
+ " shflx = 80 \n",
+ " rlds = 0\n",
+ " rsds = 40/ albedo_init\n",
+ " init_T1 = -3.5\n",
+ " init_T2 = -2.8\n",
+ " init_Tsurf = -8\n",
+ "else:\n",
+ " rlds=0\n",
+ " rsds=0\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "#artificial radiative forcing\n",
+ "days = 31\n",
+ "spinupdays = 1\n",
+ "time_artificial=np.linspace(-int(spinupdays),int(days),(days+spinupdays)* int((60 * 60 * 24)/dtime)+1) # timestep has to be 600s = 10m = 1/6h = 1/144d \n",
+ " # = dtime / (60 * 60 * 24)\n",
+ "print(time_artificial*24*60*60)\n",
+ "rsds_array_artificial = rsds*np.sin(time_artificial*2*np.pi-np.pi/2)\n",
+ "rsds_array_artificial[rsds_array_artificial<0]=0\n",
+ "plt.plot(time_artificial,rsds_array_artificial)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Winton model\n",
+ "\n",
+ "Initial conditions are defined here. Albedo calculation is activatred or deactivated by commenting out the set_albedo function. The model breaks if the ice thickness is below 0m, there is no handling of minimal ice thickness implemented as in the ICON sea-ice scheme!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "-92.55910893914947\n",
+ "-72.05158580079488\n"
+ ]
+ }
+ ],
+ "source": [
+ "# run Winton model\n",
+ "\n",
+ "# initial conditions\n",
+ "Tsurf = init_Tsurf\n",
+ "T1 = init_T1\n",
+ "T2 = init_T2\n",
+ "Qbot = init_Qbot\n",
+ "Qtop = init_Qtop\n",
+ "hi = init_hi\n",
+ "hs = init_hs\n",
+ "albedo = albedo_init\n",
+ "\n",
+ "# result array\n",
+ "hi_result=[]\n",
+ "hi_result.append(hi)\n",
+ "\n",
+ "hs_result=[]\n",
+ "hs_result.append(hs)\n",
+ "\n",
+ "Tsurf_result=[]\n",
+ "Tsurf_result.append(Tsurf)\n",
+ "\n",
+ "T1_result=[]\n",
+ "T1_result.append(T1)\n",
+ "\n",
+ "T2_result=[]\n",
+ "T2_result.append(T2)\n",
+ "\n",
+ "Qbot_result=[]\n",
+ "Qbot_result.append(Qbot)\n",
+ "\n",
+ "Qtop_result=[]\n",
+ "Qtop_result.append(Qtop)\n",
+ "\n",
+ "albedo_result=[]\n",
+ "albedo_result.append(albedo)\n",
+ "\n",
+ "FS_result=[]\n",
+ "\n",
+ "SWnet_result=[]\n",
+ "\n",
+ "for i in range(1,rsds_array_artificial.size):\n",
+ " FS, dFS, SWnet, I, Tsurfmelt = surface_fluxes(Tsurf, hs, rsds_array_artificial[i], rlds, lhflx, shflx, albedo)\n",
+ " Tsurf, T1, T2, Qbot, Qtop = set_ice_temp(Tsurf, T1, T2, hi, hs, FS, dFS, SWnet, I, Tsurfmelt, True)\n",
+ " #Qtop=0\n",
+ " hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, Tsurf, T1, T2, Qbot, Qtop, prls, prcs)\n",
+ " #albedo = set_albedo(hi, hs, Tsurf)\n",
+ " #print(\"time=\", str(time_artificial[i]), \" Tsurf=\", str(Tsurf))\n",
+ " \n",
+ " \n",
+ " #hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], t1_array.values[tind+i,lind], t2_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ " \n",
+ " # assign results to final array\n",
+ " hi_result.append(hi)\n",
+ " hs_result.append(hs)\n",
+ " Tsurf_result.append(Tsurf)\n",
+ " T1_result.append(T1)\n",
+ " T2_result.append(T2)\n",
+ " Qbot_result.append(Qbot)\n",
+ " Qtop_result.append(Qtop)\n",
+ " albedo_result.append(albedo)\n",
+ " SWnet_result.append(SWnet)\n",
+ " FS_result.append(FS)\n",
+ " \n",
+ " if hi<=0: \n",
+ " break\n",
+ "print(T1)\n",
+ "print(T2)\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Semtner model\n",
+ "\n",
+ "Initial conditions are defined here. Albedo calculation is activatred or deactivated by commenting out the set_albedo function. The model breaks if the ice thickness is below 0m, there is no handling of minimal ice thickness implemented as in the ICON sea-ice scheme!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# run semtner model \n",
+ "\n",
+ "# initial conditions\n",
+ "Tsurf = init_Tsurf\n",
+ "T1 = init_T1\n",
+ "T2 = init_T2\n",
+ "Qbot = init_Qbot\n",
+ "Qtop = init_Qtop\n",
+ "hi = init_hi\n",
+ "hs = init_hs\n",
+ "albedo = albedo_init\n",
+ "\n",
+ "# result array\n",
+ "hi_result_Semtner=[]\n",
+ "hi_result_Semtner.append(hi)\n",
+ "\n",
+ "hs_result_Semtner=[]\n",
+ "hs_result_Semtner.append(hs)\n",
+ "\n",
+ "Tsurf_result_Semtner=[]\n",
+ "Tsurf_result_Semtner.append(Tsurf)\n",
+ "\n",
+ "T1_result_Semtner=[]\n",
+ "T1_result_Semtner.append(T1)\n",
+ "\n",
+ "T2_result_Semtner=[]\n",
+ "T2_result_Semtner.append(T2)\n",
+ "\n",
+ "Qbot_result_Semtner=[]\n",
+ "Qbot_result_Semtner.append(Qbot)\n",
+ "\n",
+ "Qtop_result_Semtner=[]\n",
+ "Qtop_result_Semtner.append(Qtop)\n",
+ "\n",
+ "albedo_result_Semtner=[]\n",
+ "albedo_result_Semtner.append(albedo)\n",
+ "\n",
+ "FS_result_Semtner=[]\n",
+ "FA_result_Semtner=[]\n",
+ "\n",
+ "SWnet_result_Semtner=[]\n",
+ "\n",
+ "for i in range(1,rsds_array_artificial.size):\n",
+ " nonsolar_ice, dnonsolarT, SWnet = surface_fluxes_semtner(Tsurf, rsds_array_artificial[i], rlds, lhflx, shflx, albedo)\n",
+ " Tsurf, Qbot, Qtop, FA, FS = set_ice_temp_semtner(Tsurf, hi, hs, nonsolar_ice, dnonsolarT, SWnet, True)\n",
+ " #Qtop=0\n",
+ " hi, hs = ice_growth_semtner(hi, hs, Tsurf, Qbot, Qtop, prls, prcs)\n",
+ " #albedo = set_albedo(hi, hs, Tsurf)\n",
+ " #hi, hs = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ "\n",
+ " \n",
+ " \n",
+ " #hi, hs, T1, T2, fluxres_w = ice_growth(hi, hs, tsurf_array.values[tind+i,lind], t1_array.values[tind+i,lind], t2_array.values[tind+i,lind], qbot_array.values[tind+i,lind], qtop_array.values[tind+i,lind], prls_array.values[tind+i,lind], prcs_array.values[tind+i,lind])\n",
+ " \n",
+ " # assign results to final array\n",
+ " hi_result_Semtner.append(hi)\n",
+ " hs_result_Semtner.append(hs)\n",
+ " Tsurf_result_Semtner.append(Tsurf)\n",
+ " Qbot_result_Semtner.append(Qbot)\n",
+ " Qtop_result_Semtner.append(Qtop)\n",
+ " albedo_result_Semtner.append(albedo)\n",
+ " SWnet_result_Semtner.append(SWnet)\n",
+ " FS_result_Semtner.append(FS)\n",
+ " FA_result_Semtner.append(FA)\n",
+ " if hi<=0: \n",
+ " break"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "(0, 1)"
+ ]
+ },
+ "execution_count": 69,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "l0, = plt.plot(time_artificial[1:],-np.array(FS_result_Semtner)-np.array(FA_result_Semtner))\n",
+ "l1, = plt.plot(time_artificial,Qtop_result_Semtner)\n",
+ "#l2, = plt.plot(time_artificial,Qbot_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "plt.legend([l0, l1],[\"F$_S$ +F$_A$\", \"Qtop\"])\n",
+ "plt.xlabel(\"time [days]\")\n",
+ "plt.ylabel(\"F [Wm$^2$]\")\n",
+ "plt.title(\"Semtner surface fluxes\")\n",
+ "plt.show()\n",
+ "\n",
+ "#plt.plot(time_artificial,rsds_array_artificial)\n",
+ "plt.plot(time_artificial,Tsurf_result)\n",
+ "plt.plot(time_artificial,Tsurf_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(time_artificial,Qtop_result)\n",
+ "plt.plot(time_artificial,Qtop_result_Semtner)\n",
+ "plt.xlim(0,1)\n",
+ "\n",
+ "plt.show()\n",
+ "#plt.plot(time_artificial[1:],FA_result_Semtner)\n",
+ "#plt.plot(time_artificial[1:],SWnet_result)\n",
+ "#plt.plot(time_artificial[1:],SWnet_result_Semtner)\n",
+ "plt.plot(time_artificial[1:],-np.array(FS_result_Semtner)-np.array(FA_result_Semtner))\n",
+ "plt.xlim(0,1)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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hhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCqhquI2J6RKyIiFURcXs7/WZEREZEXat1NRExLyKWRMRLEdG3mrVKkiRJb1Wvau04InoC9wIXAY3A8xHxVGYuPaBff+Bm4LlW63oB/xv4WGa+EBGDgN3VqlWSJEkqoZpXrs8HVmXm6szcBTwGXNFGvy8DdwE7W627GHgxM18AyMxNmbm3irVKkiRJb1k1w/UZwLpWy42VdS0iYjwwLDN/dMC2fwxkRPwkIhZExOeqWKckSZJURNWmhQDRxrpsaYzoAdwNfLyNfr2AKcB5wHbgXyJifmb+y34HiLgOuA7gzDPPLFO1JEmS9CZV88p1IzCs1fJQ4NVWy/2BMcDsiFgDTASeqnyosRH4RWZuzMztwD8B7zrwAJl5f2bWZWbdkCFDqvQyJEmSpI6pZrh+Hjg7IkZGxAnAh4Cn9jVm5pbMHJyZIzJzBPAscHlmNgA/AWoiol/lw41TgaUHH0KSJEk6dlQtXGfmHuAmmoPyMuA7mbkkIu6MiMsPs+2/AX9Dc0BfBCzIzP9brVolSZKkEiIzD9+rC6irq8uGhobOLkOSJEndXOWzgHVttfkNjZIkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiG92muMiN8eZvsA1mfmH5crSZIkSeqa2g3XwMuZOb69DhGxsGA9kiRJUpd1uGkhH+jAPjrSR5IkSer22g3Xmbn6cDvoSB9JkiTpeNBuuI6IHx1uBx3pI0mSJB0PDjfnekpEPNVOewDvLFiPJEmS1GUdLlxf0YF97CpRiCRJktTVtRuuM/MXR6sQSZIkqavzS2QkSZKkQgzXkiRJUiGHm3PdIiJOAPZ9E+OKzNxdnZIkSZKkrqlD4ToipgEPA2tovkPIsIi4NjOfrl5pkiRJUtfS0SvXfw1cnJkrACLij4FHgQnVKkySJEnqajo657r3vmANkJkrgd7VKUmSJEnqmjp65bohIr4F/GNl+SPA/OqUJEmSJHVNHQ3X1wM3AjfTPOf6aeC+ahUlSZIkdUUdmhaSmb/PzL/JzPdn5lWZeXdm/v5w20XE9IhYERGrIuL2dvrNiIiMiLrK8oiI2BERiyqPb3b8JUmSJEmdo90r1xHxEpCHas/Mmna27QncC1wENALPR8RTmbn0gH79ab4i/twBu3g5M8e1X74kSZJ07DjctJDLKj9vrPxsPed6+2G2PR9YlZmrASLiMeAKYOkB/b4M3AXc0pGCjzXbt8OuXQev790bevaEvXthdxt3BD9c+wknQI8esGdP8+NI2/v0gYjDt+/e3VzDkbb37dv8c9cueOONI2uPaN5/R9p//3vIPLL2Hj2axwdg586Daztce8+ezb+fw7VnNh//SNt79Wp+vPFG2+fO4dr3nTuHa/fc89w7kOee596h2j33PPeg6517vXpBv37NxziWtBuuM/PXABExOTMnt2q6PSKeAe5sZ/MzgHWtlhuBC1p3iIjxwLDM/FFEHBiuR0bEQuC3wH/LzF+2/1I6x8knH3yiSZIkqfqefhre/e7OrmJ/Hf1A40kRMSUz5wBExCTgpMNsE22sa4mhEdEDuBv4eBv91gNnZuamiJgAPBkRozPzt/sdIOI64DqAM888s4MvpazbboOFCw9eP3o0DBkCmzbBSy8d3F5bCwMHwoYNsPTAa/nAu94Ff/AHsH49rFhxcPt558FJJ8G6dfDyywe3T5zY/E52zZrmx4EmT25+J/jyy837ONCFFza/E1y5El59df+2Hj2a2wGWLYPXXtu/vXfv5v0DLF4MGzfu337iiXBB5W3WokWwefP+7SefDHV1zc/nz4etW/dvHzAAxo9vfv6v/9r814PW3vY2qKlMWJo37+B3ukOGNP9+AObMOfgqw2mnwTnnND//xS8OfvM0dCj80R81X134ZRtv+YYPh5Ejm68QzJ17cPtZZ8GZZ8KOHfDcgZOhgLPPhjPOaH7d89u4J8855zTXuHlz8/gdyHOv+bnn3sHtnnuee+C557m3f3tXPvdGjGh+HGsiO3DZtRJwHwAG0ByQtwCfyMwF7WxTD9yRmZdUlv8MIDP/orI8AHgZ2FbZ5DTgdeDyzGw4YF+zgVsOXN9aXV1dNjQcslmSJEkqIiLmZ2ZdW20dunKdmfOB2oj4A5oD+ZYObPY8cHZEjAR+A3wI+HCrfW4BBrcqcjaVAB0RQ4DXM3NvRJwFnA2s7kitkiRJUmfp0BTwiDi18iUyj2fmloh4Z0T85/a2ycw9wE3AT4BlwHcyc0lE3BkRlx/mkBcCL0bEC8ATwCcz8/WO1CpJkiR1lo5OC/kx8CDwhcysjYhewMLMHFvtAjvKaSGSJEk6GtqbFtLRm5cMzszvAG9Ay1XpNm4WI0mSJB2/OhqufxcRg6jc7SMiJtL8oUZJkiRJFR29Fd9ngaeAd1Tubz0EmFG1qiRJkqQuqKN3C1kQEVOBUTTfv3pFZrbxHUeSJEnS8atD4Toi+gI3AFNonhryy4j4Zma28UWVkiRJ0vGpo9NC/gHYCny9snwN8I/AB6tRlCRJktQVdTRcj8rM2lbLsyr3oJYkSZJU0dG7hSys3CEEgIi4AHimOiVJkiRJXVO7V64j4iWa51j3Bv5TRKytLA8Hlla/PEmSJKnrONy0kMuOShWSJElSN3C4cL31qFQhSZIkdQOHC9fzaZ4GEm20JXBW8YokSZKkLqrdcJ2ZI49WIZIkSVJX19Fb8RERA4Gzgb771mXm09UoSpIkSeqKOvoNjf8F+DQwFFgETATmAe+pXmmSJElS19LR+1x/GjgP+HVm/jtgPNBUtaokSZKkLqij4XpnZu4EiIg+mbkcGFW9siRJkqSup6Nzrhsj4hTgSeCfI+LfgFerV5YkSZLU9XQoXGfmVZWnd0TELGAA8P+qVpUkSZLUBXX4biH7ZOYvqlGIJEmS1NV1dM61JEmSpMMwXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpkKqG64iYHhErImJVRNzeTr8ZEZERUXfA+jMjYltE3FLNOiVJkqQSqhauI6IncC9wKfBO4JqIeGcb/foDNwPPtbGbu4EfV6tGSZIkqaRqXrk+H1iVmaszcxfwGHBFG/2+DNwF7Gy9MiKuBFYDS6pYoyRJklRMNcP1GcC6VsuNlXUtImI8MCwzf3TA+pOA24AvVbE+SZIkqahqhutoY122NEb0oHnax5+20e9LwN2Zua3dA0RcFxENEdHQ1NT0loqVJEmS3qpeVdx3IzCs1fJQ4NVWy/2BMcDsiAA4DXgqIi4HLgBmRMRdwCnAGxGxMzO/0foAmXk/cD9AXV1dIkmSJHWiaobr54GzI2Ik8BvgQ8CH9zVm5hZg8L7liJgN3JKZDcC7W62/A9h2YLCWJEmSjjVVmxaSmXuAm4CfAMuA72Tmkoi4s3J1WpIkSepWIrN7zKaoq6vLhoaGzi5DkiRJ3VxEzM/Murba/IZGSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKmQqobriJgeESsiYlVE3N5OvxkRkRFRV1k+PyIWVR4vRMRV1axTkiRJKqFXtXYcET2Be4GLgEbg+Yh4KjOXHtCvP3Az8Fyr1YuBuszcExGnAy9ExP/JzD3VqleSJEl6q6p55fp8YFVmrs7MXcBjwBVt9PsycBewc9+KzNzeKkj3BbKKdUqSJElFVDNcnwGsa7XcWFnXIiLGA8My80cHbhwRF0TEEuAl4JNetZYkSdKxrprhOtpY13IFOiJ6AHcDf9rWxpn5XGaOBs4D/iwi+h50gIjrIqIhIhqampoKlS1JkiS9OdUM143AsFbLQ4FXWy33B8YAsyNiDTAReGrfhxr3ycxlwO8qfTmg7f7MrMvMuiFDhhQuX5IkSToy1QzXzwNnR8TIiDgB+BDw1L7GzNySmYMzc0RmjgCeBS7PzIbKNr0AImI4MApYU8VaJUmSpLesancLqdzp4ybgJ0BP4IHMXBIRdwINmflUO5tPAW6PiN3AG8ANmbmxWrVKkiRJJURm97gRR11dXTY0NHR2GZIkSermImJ+Zta11eY3NEqSJEmFGK4lSZKkQgzXkiRJUiGGa0mSJKkQw7UkSZJUiOFakiRJKsRwLUmSJBViuJYkSZIKMVxLkiRJhRiuJUmSpEIM15IkSVIhhmtJkiSpEMO1JEmSVIjhWpIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklSI4VqSJEkqxHAtSZIkFWK4liRJkgoxXEuSJEmFGK4lSZKkQiIzO7uGIiKiCfh1Z9dRwGBgY2cXcZxy7DuPY995HPvO49h3Hse+83SXsR+emUPaaug24bq7iIiGzKzr7DqOR45953HsO49j33kc+87j2Hee42HsnRYiSZIkFWK4liRJkgoxXB977u/sAo5jjn3ncew7j2PfeRz7zuPYd55uP/bOuZYkSZIK8cq1JEmSVIjh+hgREdMjYkVErIqI2zu7nuNNRKyJiJciYlFENHR2Pd1ZRDwQERsiYnGrdW+LiH+OiF9Vfg7szBq7q0OM/R0R8ZvKub8oIv5DZ9bYXUXEsIiYFRHLImJJRHy6st5zv8raGXvP/SqLiL4R8a8R8UJl7L9UWT8yIp6rnPePR8QJnV1rSU4LOQZERE9gJXAR0Ag8D1yTmUs7tbDjSESsAeoyszvce/OYFhEXAtuAf8jMMZV1dwGvZ+ZXK28uB2bmbZ1ZZ3d0iLG/A9iWmV/rzIAkQwwAAALPSURBVNq6u4g4HTg9MxdERH9gPnAl8HE896uqnbH/j3juV1VEBHBSZm6LiN7AHODTwGeB72fmYxHxTeCFzPy7zqy1JK9cHxvOB1Zl5urM3AU8BlzRyTVJVZGZTwOvH7D6CuDhyvOHaf6HT4UdYux1FGTm+sxcUHm+FVgGnIHnftW1M/aqsmy2rbLYu/JI4D3AE5X13e68N1wfG84A1rVabsT/8I+2BH4aEfMj4rrOLuY4dGpmrofmfwiBt3dyPcebmyLixcq0EaclVFlEjADGA8/huX9UHTD24LlfdRHRMyIWARuAfwZeBjZn5p5Kl26XeQzXx4ZoY53zdY6uyZn5LuBS4MbKn8+l48HfAe8AxgHrgb/u3HK6t4g4Gfge8JnM/G1n13M8aWPsPfePgszcm5njgKE0/6X+3La6Hd2qqstwfWxoBIa1Wh4KvNpJtRyXMvPVys8NwA9o/h+Ajp7XKvMi982P3NDJ9Rw3MvO1yj9+bwD/C8/9qqnMOf0e8Ehmfr+y2nP/KGhr7D33j67M3AzMBiYCp0REr0pTt8s8hutjw/PA2ZVPz54AfAh4qpNrOm5ExEmVD7kQEScBFwOL299KhT0FXFt5fi3ww06s5biyL9hVXIXnflVUPtj1LWBZZv5NqybP/So71Nh77ldfRAyJiFMqz08E/j3Nc95nATMq3brdee/dQo4RlVsA/S3QE3ggM/+8k0s6bkTEWTRfrQboBXzb8a+eiHgUmAYMBl4D/gfwJPAd4ExgLfDBzPSDd4UdYuyn0fxn8QTWAP913xxglRMRU4BfAi8Bb1RWf57mub+e+1XUzthfg+d+VUVEDc0fWOxJ8wXd72TmnZV/dx8D3gYsBD6amb/vvErLMlxLkiRJhTgtRJIkSSrEcC1JkiQVYriWJEmSCjFcS5IkSYUYriVJkqRCDNeSJElSIYZrSZIkqRDDtSRJklTI/wfvxHhf6Fo3AgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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Acxiech0bG51/1EkrVxZVAkzdMsI1MU/CsiQx09Sq/YblfqwoLNMDTpWY79rFM+3jyuKe9gkrnMpU+8ZGx7gWOQGmYJl1FFY4dXQ4X64aGujSUQoDzDW1LUOSb0lipqlVr80j7res2qZ8IHnKzY3l3riTsiqVHmNuWJxSSMoTnvLAktrnm2VMCqcE2KwfRUKXBxZVvaT24VjNzc57nioBNmkytwTYfFZQGWBOLEsSM00typ5pYUUTZfpeqTitMRxTSGEJy4vV2OiYAS5Jq7CEVVZWv350R1EAx+hzSoC5sixJzDS10kqAOZnWsrGSzmO9K7wkaYvhbugoWZRJK9d1LIsBpkwhua4jV5bUPv8spWjmkeOJpGKmRX1k+okpTuCpx4p7iKesLMrac5jHSsUx1BQsM7a0WEk+ENNkUayjMcAULCD54ds0WRS1T4PFtV5Se2GVZR4bGmhOJK3dRyZhWZKYaWqZN4X55gckN4duVlJDVzYWZe2LNo+VivOPgmXGRlEvN6u5mY5FkQAbFkCzY8sDi6L2abC41ktqLyyZx+gsgOZEUksSM00t86Yw/U1AcuMkLGFxZ2nttLJQsMzYmpt7LqFFwQJoPvSFJSxhCUtY9CyKHnNLEjNNLbdBSdrvKSxhZcWiNOamJy+JMe/q6vmgTton6P7QF5awhCUsYfFnaR2fZ0FipqnV1eX8pDh0Lixh+bHMhw8FK6kBdrOAZOlCdzcdy4xNWMISlrCElS4rrgGuZZnHciQx09TiehheWDxYSQ0wZQLsZgHJPly5srq7nQ94zoc2hSUsYQnLFiuuAa5lAfENcD1Wzlo9xExTq55xSnrimrCKwzJnP1OwzE9hZcMyJ2xSsMzYhCUsYQkrCmvXLhoDbH6az0gKVpLPaSqWJYmZppb5ZuY2YXG/rVGy6plDDuPKA0spxwBT1N78pBiXsLJlUc5jPWOe5LCmu8e8qKzaHS6XcQkrmso6j0laIGqNJkUCTLGP5MiyJDHT1DI73Kamnh6gpDtvCpa7p5XTuNJiNTQ4JpiCZX5S1D4pi3JcwoomynmkZJkTNilYgFMzjqwyrGMZWGWcR8D58kzFSvK5Q8WiHBcly5LETFOLMgGux0pySCbNcVGwGhvpWOansIRVy6LYhtIYF4f0XWva5FBYxWTF3YbSHhclyxw9omABPNLkMrAsScw0tdw7SfMNi2LnTZXapjUuCpZSDo/K7AhLWPVYVAaY8zrGZZkrqVCwzNiEVTwWlWlNY1wU/cQU+9taFkVvsrDYSsw0tdyHbyn6iKhY7sPdlONK2k9ce7ibIqHjxqptNeAyLmFFk8xjNFUqjrGhYAG9DwVT9LQKyw4rzXkEer4QUrAo2ik4sWprz2VclCxLEjNNLa4JsPtQsOkn5pCElYFVexiey7iEFU0yj/ZYtSdsck5theWvrq7eLHP3VIpxmceEVV+1tecyLkmmRX3k3oFQpcnNzdJPLCxhCau8LOq+8O5uGhbQ2wiUhSX9xMLiyrIkMdPUcn/oGwNMkYRx6iemTOjKwJLaF4Ml82iPxbX25koqaaW2lCxzAyMKlnksjrgmrWVglaH2liRmmlruvkqq6xOn0e9JcSKWsISVN5ZsQ8KiZJn2BAqWGVstK8kJdW4WwKPXNq1xCUtYFiVmmlppHialTGO4HL4tA0tqz4cl21A+WWWovUmOaw93c2unoEwhObUHlIFVhtpbkphpapkPGNPiQXlok4upEJaw8sqSbUhYabPi9hPXY7kfj6J6J2zGZZnXcTTmwhIWE4mZplZXV0+LB0CTxrgPfyT90Kc43F07LmH5S2rPhyXbUD5Zadc+bj9xPZb78SKwzAmbtYfhk2xHVC0jZn8rrHAqQ+0tScw0tdzfsIDkO+/Gxh5jTtEnmIdkR1jCSpMl21BxWHEMsFcCHOd9QZkmc2XVttgkqVe9Ezbjjsu8TljCYiAx09SqNdNJ05haVtw3WFdXb2POpU+wDKwy9HvmiZVkG0pzXMLyVr3aAzTtFEmSsDKz4mxHtXfYTJqYp9V+UlSW9EynJjHT1HK/WYHkJzzVsqiMedJxNTQ4/yhYAE16xZVFmdBxXcc8sTgk03mqFyUr7g06skhahRWNZTvJN1+kqBJNysScK4syAea6jpaUqplWSg1TSt2nlHpZKbVYKXWUUmovpdTjSqml1Z97VpdVSqnrlVLLlFIvKaXGpTm21OTuSQKS77zdrKQpUVrjojAobmNO1VcpLGHVsiiSVu7rSM1KekJdba9tEhMmLPssipSb2zqa9zgFy4xNWHZYlpR2Mv2/AB7VWh8M4HAAiwFcBuBJrfUYAE9W/waAEwGMqf47H8DNKY8tHaXZ5kGZclO3nyRlUbafUBonafMoFosyaeW6joZF0U9sflKkyUlMmFebB9cWiCKzKFNuruuYtP2k9g6bcVlmbNLmwV6pmWml1FAAHwFwGwBorTu11psBTAQwrbrYNACnVH+fCOB27eg5AMOUUm9La3ypidIAczXmnFlNTb1P2EzamuH+tsyhzUNYyVhcjHnaLMB+O4WwisniYszLwJITNnOjNJPpAwG0AZiilJqrlJqslBoE4C1a69cAoPpzn+ry+wFY43p9a/WxfKmri641o5ZFYTTTGFdRWe6+cC6JuXmdsOKxKL9gUa+j1vHaKeqx3I8XgUXZasB1HfPCojCa3NeRC6v2DptJE3O3D6BIuTmyLClNM90EYByAm7XW7wOwHT0tHfWk6jzW5zilUup8pdRspdTstrY2mpFSSpJpYdVjUZ2wmad0lCOLOpmOe31irkmYsIQVxJJkOp+s2iupcEqTJZn2VSuAVq31P6t/3wfHXL9h2jeqP9e5lt/f9fqRANbWQrXWt2qtx2utx48YMSK1wccWVwPMvWe6yCzq2ivVc4dNSnNYBlZTU/x+4jL0e3JlSe35sKRnOp8sytqbEIGCBfTe30oy3Vta69cBrFFKHVR96GMAFgGYAeCs6mNnAXig+vsMAF+sXtXjSABbTDtIrlRrnLgaYMpxCctfnGsP9BhzypPz0mBRGmDb/cT11lFY3pLa82FxNebC8hfX2psrqeQ8mW4KXiSRvg7gTqVUPwArAJwNx8Dfq5Q6F8BqAKdVl30EwCcBLAPQXl02f3L3JAG0fc7UrCTGXFjFYVHeYdPdV0nJApwPXGP8k7Jq65iERdEDLCxh5Y2VxNDlZR2FlT7Lqyc/Z8l0qmZaaz0PwPg6T32szrIawIVpjicT1WsP2LGDhpXUoHBsgRBWcVi1d9g0iUNDxANgfoc245rp2tTD9iFXYQkrryzZhoTFlWVRcgdEanFt8+DaAiEsXqwk/cS1LPN4HFbtCZuA/UPUXA/fCktYWbJkGxIWV5ZFiZmmVu3h46RpX1ptHpTjElZxWED8fuJ6rLhJBSULoDHmtYc2KcYlLGHljSXbkLDSZJkT7CWZLrnqtWYkMcBpHdKnHJew7LLMHbcoWObxorHc7SdAsg999wmbScblHo+whJUXVhotI9zWUVjRWA0NzmcsBcuMTZLpkisvBphyXMKKzjL9xBQsIP6OrWwsbsacMtnh1r8orGKyuBpzYUVjmVCAgmV+t82yKDHT1OrqomvNqGUleYOlOa6ysOLeoKMeyzxOxYqznmVkJdkZUY/LfcImRc8hxWF4YQkriJV0G0prXGVgGQNMwVIq/j6ylmV+t82yKDHT1PI6qYuKlcQcpjkuziwOJ9QJixcr7oc+13Wsd8JmErNTm0IKS1gUyXTe1pEbK0k/cS3LjK1ILIsSM00tkzgZJU2ThZWMBcRrp/Bixf2wEJaw8sICeow5Bct9t05hCatsLPNFl4JlxiYsdhIzTa3ubrrDFdQs95uV07hqWXH7ieuxgHhjo2bV1p4Li2u9uLLKUHuq9hNzUizF4W7Dojj5Mw0W5TqWgcW99ubLJAXL/M6FReED0mBJm4eolzintrW9o5TjStJPzDWho2Sl1bfLaR3LwJLaR2MBtCl3Gn27XBPNIrPSqD1FO4VhKcUjaU2DReED0mBJMi3qpbwl03EMsFcSFufNzzmh45poliEd5cqS2ttjAZJMF4WVRu1NP7HtdJQ7S5LpVCRmmlppJtNJmvK9UjXpJ86GJck0D1bS9Epqb49lrmVLwQIkmY7LokiA3e0U0k+cLUuS6VQkZppa1L3JtW8wreP3E3NNR4UlrKxYSUxFXtZRWMEsgOaumNwT8zRYpqc+7jbkZpmxcUlHhZVvlkWJmaZWbXrV1BT/hLp6LID2kCtFQicsf2XRFmN7HfPGkm0oXyzqbajeSZYUCR1XljEqVCkk9SF9ynEJq74oa891Hi1KzDS10kzCDCvJTSIoWJTjKgOLsvYyj/ZYUnt7LM7bEND3JEuKhI6SleQGHfWSw+bmZNeZpmBRjqsMLMrac51HixIzTa3aNMa8QcwbxharNtnhMq4ysChrL/NojyW1t8cqyzbkZijl/EvCqh2bbVa9RJPDuMrAoqw913m0KDHT1KpNY5J+6FOxatMYLuMqA4uy9jKP9lhSe3ussmxDSvWk3IaXxOzUjs02q16iyWFcZWBR1p7rPFqUmGlKmZMDi95zyLWvkitLeqaLwZLa22PlZRsyZpiCZcaWpA/VbVA49LRy7bUtA0t6plOVmGlKeX3Dcj8XlVeGNKborLKkakVnSe3tsdLchkwSTLGOZmwcWO5LCSZlmdcnZXFNNMvAkmQ6VYmZppTXNywg+hujUnGSbgqWeQ0VyytxElZ9UdZe5tEeS2pvj5XmNmRu9kGxjmZsRWMBvdtP4rK8Es0k4xJWOFHWnus8WpSYaUr5JdNRD1lQsrT2ToniHuIRVnh5pWq2WVzrxZUltbfH8kqTKVhmbBTrWGRWbcpN1X6SZFzCCi/K2nOdR4sSM00pymS6HivuoU1zjWuOiVMZWJJM82ElbVvIwzpyZVHW3ozNNotzmpwmi7L9hEOiWQaWJNOpSsw0pdJOps2bLSrL61tkHJZpP+GYXnFlSTLNhxV3GzKvycM6cmUlPTmPKmmVZDo5K8nJZpTjAvpe/cR2OsqVJcl0qhIzTSnKNJmSVe9bJAcWQJtecWXVJmFcWFzrxZVVxtonOTmPOtHkyKJcxzKwqGtfr/2EKh0tGstr322bRbmOFiVmmlKUabIfK64xT3tccVJuKpYZG0dWbRrDhcW1Xlmwkuy80xwXN5Y5OY9josmBRbmOeWNRbENpjIsq5U7Kqt0mbbO8fIBtFuU6WpSYaUpllUzHNcDcEnNKljnJkmPaJ8k0P1bcD/08rCOXNJlroinJNA2LYhtKY1wcWOb1VCxuabIk030kZppSlGlyVsm0zXFRsvxS7rgfFmknmrZZlOtYBlaatU/6BYsqOeTK8ko0bbO41osrqyy1r72TZdIT/Wo/d6hMPgcW5TpalJhpSvklwJRpsrDSZdW7k2UaiaawhGVkrnBAmfYJS1jCyj/LvJ6KVfsZViSWRYmZphRlAux1qIiKxSHl5sqiTMzN2ITFg5W0nSItFsAj7ROWsMKwkhzSz8s6cmFRX0qQWzJNybIoMdOUSjtpTWoOuSXAZWDVu8Y313S0DKykrRluVpJLvXFOwoQlrCBWkkP6eVnHIrJq2084pMmSTIv6KO00Oa6pyGpcwkqX5XcnS25JK1dWGnfO45j2CUtYabNkGyo3y7yeE8uixExTKu00WVjlZlHfyTLN1JaSlcRMp52qCUtYwhJWGVlU7Sde+0gx0z1SSq1USs1XSs1TSs2uPraXUupxpdTS6s89q48rpdT1SqllSqmXlFLj0hxbKsoqTRaWsJKyzEmWFCzzmrRYSU7OyyJVE5awhCUsYcVnATTtJxaVRTJ9rNZ6rNZ6fPXvywA8qbUeA+DJ6t8AcCKAMdV/5wO4OYOx0SqrPue4LPebn0PSWiYWZe25zaN5TV7S5LiHEGtbbKjHJSx/FmXtZR6TsWQbyieL6zbU2EiTcluUjTaPiQCmVX+fBuAU1+O3a0fPARimlHqbhfHFV9opZFyzY1j1zE5RklbuLMrac5vHSsVJut2sJCfnpZ2gxP2g7uqiOxmIc0rElUVZe5nHZCzZhvLJKvo2ZFFpm2kN4C9KqTlKqfOrj71Fa/0aAFR/7lN9fMfMLawAACAASURBVD8Aa1yvba0+1ktKqfOVUrOVUrPb2tpSHHoMZZVMR32TcU00y8TKQzId98559Vjm76iseneyjMsyY6P60JdUzS6La6rGtV6yDQmrlpWnbci0IuZETcGLJNLRWuu1Sql9ADyulHrZZ1lV5zHd5wGtbwVwKwCMHz++z/NWxTWZpjTm3BNgbqw0vhSlNY9KxdtJ1mOZv+Ok3FQsM7Y0P/Q5pDFlYFEburTnsbOTjhV3XM3NdCzZhvLPyts2ZP6fhnxcJyPVUWqt11Z/rgNwP4APAHjDtG9Uf66rLt4KYH/Xy0cCWJvm+MjlZ3a4GmDKcQmrryhrX49FnSY3NhaHVe9OloZF+aHPoQ+16CzK2ss80rBkG8oXK4ttCIieJnuto3kuJ0rNTCulBimlhpjfARwPYAGAGQDOqi52FoAHqr/PAPDF6lU9jgSwxbSD5EZp9DmnZYApxyUsb6Vt8s3fFOtYNFa9thjzt+1DrtR9qEVncT10zrVeabNkG8ofy6/2OuJBfi+WeS6KvNYxDsui0mzzeAuA+5VzhmYTgN9rrR9VSv0LwL1KqXMBrAZwWnX5RwB8EsAyAO0Azk5xbOko7UP6aRjzorQtcGV5pclxLvVG2U7hlwAXnRVnZ1TvJMu44zJj43jIlSvLy9Dt2kXHsr2OeWJRG3OO61g0VlCaXPtcXFa9FiM/+SXTOToJMTUzrbVeAeDwOo9vAPCxOo9rABemNZ5MlFUyzc2Yl4HF4eQ8SaZpWLaNeb07WcZlAXyTsCxStZ076Vi21zFPrCTmsH//9MZVFpZpYYvSTxyUJkcx05JM91E+OrvzIkmmi8vicHKeJNM0LNvGvN6dLOOyAL5JWBapmm0W13pJMl1slnkuioLSZFusgiTTYqYpJck0L5Zpp+DQtyvJNB8WV2MeN+Wud4iWc6pmu9dWkunkLK7GnDMLiH5yHmVqS5kmSzLdR2KmKZVV0srNmHNlGZ5NliTTPFkcjbltluFxZEkyzY/F0ZinsY4UJ+dxSG0lmU5VYqYp5Wdabaa2WRlzCpZStGkytXGiSpNts7jWKwsW5VEBrusYh+V3kiWlcaJKkzmwKNcxTyzKowJc19H8TZEmp9GaQZEmc2BRrqNFiZmmFGU7BWVqy9WYc22B4HpIvwztJ1mwKI8KcF1H2yzqO1lyPaTPtf0kbRblUQHqdTRfCilY5rkisCjbKbi2n1iUmGlKUbZTZGWAKcallNOfXJQWiDIc0udaryxYXI15kVjUd7Lk2gLBtf0kbRZXY55GOirtFOmyKNfRosRMUypPyXTRLvXGlSXJND8WV2MurPrifJJlntJkrga4qalnjpOOi0M6ypUlyXSqEjNNqbSTacp2iqJd6o0rS5JpniyOxlxY9UVZe8OTZDo5q7ub9uQ8SZPTZUkynarETFMq7X7iNO6cR2kqhNVXlLWXeaRhNTXJNpQnFmXtqU+y9DIVRWeZv22enEdpzMvAyqotxuY6WpSYaUqlnUybvzmaCmHVF2XtZR5pWLIN5YvFdRvyu5MlZQsEJSvOyXlpGyfzN0WiKSxvUdae6zxalJhpSnm1UzQ08OzbtZ04lYElyTQ/lmxD+WJx3Yb87mTJMU1OwwAXJdEsA0uS6VQlZppSlCcpZdFzSDkuYdUXZe1lHmlYsg3li1WGbcjvJMs4J+f5pX2Uxoky0aQYl7C8RVl7rvNoUU3Bi4hCyy+NoTzphqOpEFZ9leGkLj9WZyfPcck2lB9W2bch83xDhOzLL+3r6gL696dhcTPmwvIWQe137dqF1tZW7Lz6aqC5GVi8uOfJt70N+POf+z4epKuucsbhfs3eezusgQOjsQjV0tKCkSNHorm5OdTyYqYpZd6QtR961KmHpGr5YeUxVaPsj+U6j7IN5YeVx20IcNLksAY4iNXd7ZiUMPI6yTKN5FCS6fywCGrf2tqKIUOGYPRb3wrV0gK88509T775pvPee8c7gCFDwo9La+e9PWZMz2Nbtzpjesc7gKFDw7OIpLXGhg0b0NraigMOOCDUa6TNg1L13qxAsqQi7T5BrmlMUVhlT9W4smQbyg8rq22ouzvayXlBaXKUsXFled3JUpLp/LEIar9z504MHz4cCnDOB6OQ1n1Z5u+oJ8sSSSmF4cOHY+fOnaFfI2aaUvXerED8nbc5edGtJGlM2sZcWH1FWXuZRxqWbEP5YmW1DQHRepP91tH9f+WZ5XUnyyTpKMW4AH9zKKy+Iqq9UorWANdjMZCKOCYx05TySqbj7rypUu4yHHLlyjK158biWq8sWEm2obysY5FYfrWPeqk3PxYQbWx+61h0VtyUu1Kha/OgbBkpA6uri45VT5RpsuVkOo7ETFPKL5mmOCQDxN+xmRu+UIzLvFZYwfJLwmyyuNYrCxZ1Ms1xHYvECkqT45hDilaDoAS4yKwkxpyqzYOyZaQMLL9kOiqLMk1Ouc1j5cqVOPTQQxNzgiRmmlKck2nKcVG3n3BLwiSZLjZLkmm7LCBeOwVFqibJtL1kmrL2Xtf45pAAc2VRJtNM2jy01qhEvWxkSqrjsESxlUUyHbdPMItxFSUJ82NFOCEBgCTTXFmSTEdjdXdH2+mFSUf79QvHCpNohr3UmyTTtKwiHBXwupMlhzSZazIN0KbJEVgrV67EiSeeiGOPPRb/+Mc/MGzYMLS1tUEphXPOOQcXX3wx5syZg3POOQcDBw7Ehz70od2vXbhwIc4++2x0dnaiUqlg+vTpGOO+ikgCiZmmVBbJdNFY9dpPqJMwqmsdc077hCWsNFlA/ZuKxGVxS1qFVV6WpNzxkukf/hBYsaLnsUoF2L4dGDCgvkfw0rZtzvItLcDYscB11wUa8yVLlmDKlCk499xzcdlll2HBggUAgM2bNwMAzj77bNxwww045phj8J3vfGf362655RZcdNFFmDRpEjo7O9Eddb19JG0elMoqmRZWfRbQt/2Ec9onLGGlyYp7ch635FBYwsoLy+tOlhySaUpWVlfg8Pj8GjVqFI488kgceOCBWLFiBb7+9a/j0UcfxdChQ7FlyxZs3rwZxxxzDADgzDPP3P26o446Cj/5yU/ws5/9DKtWrcKAAQPIhirJNKX8+pxtJ8Bpj4ua1dERndXYWP8kS8peW2Hln0Xdf82VZZ4PmxKFYVGOS1j5ZaXRfy2s+jyOLK2BH/wA2H//nsd27gQWLAAOOAAYPjw8a948YK+9gLe/veexAKM+aNAgAMCee+6JF198EY899hhuvPFG3Hvvvbj22ms9L2v3hS98AR/84Afx8MMP44QTTsDkyZPx0Y9+NPxYfSTJNKW8ktY4O+8sEmDKcRWNBaR/J0th2WFRJsDU62iSLQoWEG1swhJWWBZlAsx1HW2zsryTJUW7Q5ITEGOy1q9fj0qlgs9+9rP40Y9+hBdeeAHDhg3DHnvsgVmzZgEA7rzzzt3Lr1ixAgceeCC+8Y1v4OSTT8ZLL70Ubaw+8o0slFJh/qc2rfXHiMaTb/klrXFOFsgiAaYcV5ze5CzGZZtlXkvFqpcuCCsaizIBphyXeT7sbaiDWHFOzvNjhZWwysGiTG25rmMRWEF3srTZ5uHHCjDTr776Ks4+++zdV/T46U9/CgCYMmXK7hMQTzjhhN3L33PPPbjjjjvQ3NyMt771rfje975Hsw4IbvNoBPBJn+cVgBlko8m7OCetXixJudNnUV1KMG8JcFlYgJMihTXAYdKr5mY6VlgJS1jCKiaL+k6WaV8az8eojx49evcJh4cffjheeOGFPsscccQRePHFF3f//YMf/AAAcPnll+Pyyy+PNr6QCjLTX9Far/JbQCl1AeF48i3O6agXK86l3vK2jkVimddSsfKUJlMn01HSlTApUdRLvXFLr4QlLGEJK0jGLFu6NB5XBUUpf1dK9QcApdQ+9RbQWs8iH1VexTkdFVYxWFSXEsxjApxGmkzFKkJ6JSxhCUtYWStBzzQnBZnp+wHcp5R6H4AfZzCefItzoiksYdWy6rWfcE6To56cxzXZEZawhCWsvLIok2kvVg4VZKZfBzARwLkARqU/nJzLK4U0h5WFJayissxr02QBNGmMsIQlLGEJKx4rCzNdwGR6gda6AuDbALbG+Q+UUo1KqblKqYeqfx+glPqnUmqpUuoepVS/6uP9q38vqz4/Os7/Z1VeyWGcQ9TCElaeWF7tJwBNmhzncKSwhCUsYQmLlpWFimamtdY3VH/u1FqfGvP/uAjAYtffPwPwS631GACb4KTeqP7cpLV+J4BfVpfLl/zSvqiHu4UlLFus7u7od87zYpnno7CA+u0ncVleaYywhCUsYQlL2jwIFOpaTkqpT1XT5Y1KqTeVUluVUm+GeN1IACcBmFz9WwH4KID7qotMA3BK9feJ1b9Rff5jyus2NlzV3U1ndoQlLFss8zwVK2pvX72UOy7L/VphCUtYwhJWMhazNo/Ro0dj/fr1fR7/wQ9+gGuuuSb8WBIq7B0QrwNwFoDhWuuhWushWuuhIV/3XQDmOO9wAJu11mbmWgHsV/19PwBrAKD6/Jbq8vmRn6mIcqhbWMKKytI62odYkAGO2prBlQV4p9xxWF47I2EJS1jCKgMrKykVuE/TWu++YYtthTXTa+D0T4feWyulPgVgndZ6jvvhOovqEM+5uecrpWYrpWa3tbWFHU428jMCcfpQhSWssCyA1rRSJtM2WX4pd5yeQ6+dkbCEJSxhlYFluc1j5cqVePe7340LLrgA48aNw5o1a3Y/d9VVV+Gggw7CcccdhyVLlux+/Prrr8chhxyCww47DKeffnr48UVQnTOQ6uq7AB5RSv0NQId5UGt9rc9rjgZwslLqkwBaAAyFk1QPU0o1VdPnkQDWVpdvBbA/gFalVBOAPQBsrIVqrW8FcCsAjB8/nld3eh5NmLDssSqV6DcOCTKa9Z6PywqrsrAA75S7CDtJYQlLWMIKksssz507ofdzO7YCa/oB6/qHZ7VvA1a2AK82433vm9nznE8yvWTJEkyZMgU33XQTRo8eDQCYM2cO7r77bsydOxddXV0YN24cjjjiCADA1VdfjVdeeQX9+/fH5s2bQ65oNIVNpq8C0A7HFA9x/fOU1vpyrfVIrfVoAKcDeEprPQnAXwGYkxnPAvBA9fcZ1b9Rff6pKEk4C+XR0EVlVSrFZ5UhTfarl00WZzNNlXJ73dq3SCyuRoCSJbWX2qfJyqL2Sjn/ou7XzGstadSoUTjyyCN7PfbMM8/g05/+NAYOHIihQ4fi5JNP3v3cYYcdhkmTJuGOO+5AU72rWBEoLHUvrfXxRP/npQDuVkr9GMBcALdVH78NwO+UUsvgJNLpZPFpqlLpm1wB8c0hR5YxFUVm+dXL9CaH/SDxYwHR0uQwrLDyq5dNFuU6cmWZZSnbTygTcwqWMRVFZkntpfZpsrzqZf6mYJmxxUymeyXJAPDCC8CIEcD++4djdXQA8+cDo0Y5r3PLJ5keNGhQ3ce9rlnx8MMP4+mnn8aMGTPwox/9CAsXLiQ31WGT6SeUUrHNtNZ6ptb6U9XfV2itP6C1fqfW+jStdUf18Z3Vv99ZfX5F3P/PmvySMK4nrgkrGgsozsl5wrLH8ku5i3CSkrCEJax0WObOtRQs81ick/gok+l6rIj8j3zkI7j//vuxY8cObN26FQ8++CAAoFKpYM2aNTj22GPx85//HJs3b8a2bdsoRt1LYa35hQC+q5TqALALzsmCOuQVPcojrx1uQwNde4CworOoepPdiUDYNDkMK6yEJax6LPdrKVi1YxOWsITFh2V4tlh+Jw2GuAJHaJb7+RAaN24cPv/5z2Ps2LEYNWoUPvzhDwMAuru7ccYZZ2DLli3QWuPiiy/GsGHDwo8xpHzNtDlRUGvt2x8tqsovvaIyh0Vj9a9zogL1uADvvt44LArjJCxhUbHkiiXCEhZvVpze5KA02RbLT9RpdR0zPXr0aCxYsGD33ytXrtz9+xVXXIErrriiz2tmzZpFNy4PBSXTzymlWgE8CuBRrfXK1EeUZ3E9oY6alUVvctQ0OcxJcGHNNNeT86hZHPuJOderDLUHaPs9KQwKdxa3fmLu9Spj7c1jRWARpslFugOir5nWWo9XSo0CcCKA65RS+wGYBeDPAP5m+p1FVZmUqFZxk1aurCxSbiB6mtzc7M2Kk/YVncU5aS06i2vtTYJGwQL4ndSVBotrOsq1XnmpfZI0mWJ/y5Xlp6htHlmxMlDgCYha61Va61u01qcA+D8AHgRwHIBnlFIPpz3AXMlvx0Z5EhxXAywn+kVncTVhXOsltc8Py/3aNFncTBj3ekntw7HMY2VgUSbTURTUf50jBfVMnwLg71rrdQCgtd4F4KnqP1STapGR186I8oQ6atNKxTLfeL0OO8dheaXNcVlh5fX/Up5sxsHsUNYrTyypfTaseik35YlYXI0m1xPXylB7836jWEfA7ol+WbGi+gCmJyDaVpDrOQPAXKXUUqXU1OqtvN9jntRav5ru8HKmLPqc4xhzahbXfk+q5DALVtxrhVKyyjqPUntvFtdtyP1aoyTX26Vk5aVvtwy1N3zbLAofkBUrjg/IQkVq89Ban6q13g/AxwH8BcBhAG5XSrUppR7JYoC5Unc33z5nvx1uUQ6dc+2P5cqSebTHktpHYwF8e7m5tkBw7XNO8zKO5jHbLG59zpSsLJPpHCnU8fjqVTxegHPHwnkA1gEYkN6wciq/HVscA5wFyzwvLGEJS1hlYLlfKyz7LPOYsPLB8pOFExBHjx6N9evX93m8o6MDxx13HMaOHYt77rkHEyZMwOzZs2nGVkdBPdP/DeAoACMALAHwHIBfAThfa83wuIBlZWmAKXqT3R+ISXuTOewkhSUsYQkriAWUI5lOk1XENFlY4ZTVCYgJNXfuXOzatQvz5s0DANx8883k/4dbQW7siwDeBuc603cC+L3Weq4YaQ/59QlGPdGPc/9ikMkXVniWzKM9ltS+GCyb8+h+bS0r6jrmiWUeo6hXGizKdSwDKyfJ9Pbt23HSSSfh8MMPx6GHHop77rkHAHDDDTdg3LhxeO9734uXX34Z69atwxlnnIF58+Zh7NixWL58+W7GqlWrMGbMGKxfvx6VSgUf/vCH8Ze//CXxcIOuM32wUmovOJfEmwDgMqXUYAAvwrnKx5TEIyiSurvrp8Vxr3RB2eecNituUlFWFod5rPfByrVeRat9nurFlcVhHgHaK5ZQ9hPXspJc6cKrZnHqlTYr7pUuysqKWntXmjxh6oTez23f7vwfs0J2AXd3A+3twIsDgcZGzPzSTN/FH330Uey77754+GHnqsxbtmzBpZdeir333hsvvPACbrrpJlxzzTWYPHkyJk+ejGuuuQYPPfRQL8aoUaNw6aWX4qtf/So++MEP4pBDDsHxxx8fbrw+CnOd6Y1a64cAfA/A5QD+AOBYAJMT/+9FUxaHNjlc8orr4ds8sWQe7bGk9sVgFW0e3a9Ng2Ueo2JxvtSbsMKzKK/mkfLtxN/73vfiiSeewKWXXopnnnkGe+yxBwDgM5/5DADgiCOO6HV7cS+dd9552Lp1K2655RZcc801JMMN6pk+GU4qfTSA9wBYCODvAC6p/hS5FebDVXqThSUsYQlLWLUsoBxXuhBWvlmuZLpPkrxokeNxxowJx9qyBVi6FDj4YGDw4N7P1THT73rXuzBnzhw88sgjuPzyy3cnyv3796+uSiO6uroC/9v29na0trYCALZt24YhQ4aEG6+PfM00gC/BMc3fBTBHa92Z+H8ssjj39glLWGmy+vXjOS5hCSvPLMOLynKPQ1jCSqNnmuLSeH6sOlq7di322msvnHHGGRg8eDCmTp0a/f8CcOmll2LSpEkYNWoUvvzlL/dpBYmjoJ7pzyT+H8oirZ1/XK/TKixhCUtYwkqfRdkXbsYWJ4WsZ1Disrhd61hY9lh+ZjnudaZDsubPn4/vfOc7aGhoQHNzM26++Waceuqp4f8/AH/729/wr3/9C88++ywaGxsxffp0TJkyBWeffXYkTq2C2jwe0lp/KukypZDfYRT3CYhReFwPR6a9jmVgyTx6s6qH7FIbl9S+GCyu8wg460mxjnFZDQ31zXQcFsCv1SBof0u1jmVgxTXTFi6Nd8IJJ+CEE07o9Zi7R3r8+PGYOXMmAGDChAmYMGHC7ufM4wDw3HPP7f79j3/8Y6QheymozeNDSqkZPs8rAIeQjCTvCnqzupcJkkm5ZcdWXJbMoz2W1L4YLMram505lQGOYw65sgDvBL4I5rDsrKi19xP1pfGoxpWBgsz0xBAM6aMGaM00JcssS8XKW8+h7XpxZZWl9vVSbtvj4lp7zvOYNkup6Fc1oO5z5mqmvVJum+aQaz8xJYurMc/JTVuyVlDP9N+yGkjuZTYiin48Spb0ckdneV0PvEgsqb3UPk1WFrWP05vsd63/uEaTG4tyHalZAL8eYK4synpRsvxEmSZTptwZKPA606KQ4ppMB31TjsIyywpLWMISlm1WnDSZOrUVVjSWUvxSbmHxTKbFTJdUYQxw2G9sXI25Xy931HU0/2/ZWdwMCvd6Se3zzaLsczZj42o0KdeRK8tm7QHauyl6vffLwIpjpuuJ8moeOZOvmVZKvT2rgeRefm/WqIcjuZppv5Q77iFXjqwgI8DVhEntw7Gk9umz/IxTUdJkvz5nyv5rynoVqfZ+VyyJyjJj4MQK8hS2kmmjtK8zXbBk+k/mF6XU9JTHkm9RtlOEMa1hv5VSsoLSAPcyQdKavg81bbOThnGKki5Qsrq7+fbaSu3tsdI25mZslEaTYh7jsLxqD8QzmpS9yVL7aCwzBioWhWnN6sTIqLVPo80jggZX75Q4c+ZMfOpT9a/K/Mwzz+A973kPxo4di8WLF+PQQw9NNMwwCjLT7modmOZAci9Ko8mdlfYXBg6mogwsjqkt53qVtfZxe5M5Gk1qFsfUlnO9uNaeupeb28mMlCw/MUmm77zzTnz729/GvHnzMGDAgFiMqAoy09rjd1GtKI2msKKxTMrN1aAIS1hZs6hbM2ybHWEJKy8s87qishhdGm/btm049dRTcfDBB2PSpEnQWmPy5Mm49957ceWVV2LSpEm9lr/22mtxzjnnAHDupnjooYeivb090SoYBV1n+nCl1JtwEuoB1d9R/VtrrYeSjKII4mo0uabJlCyzQebJ7NhmyfWJi137uNdNbvLYJdg2KBxZZbnONEdWlrXv6IjGKvoVS1xy3WDQ0c59HdagkIBdw4CdA4DBjYACXDcpDJVMz507FwsXLsS+++6Lo48+Gs8++yzOO+88zJo1C5/61Kdw6qmn9rpD4je/+U1MmDAB999/P6666ir8+te/xsCBA0MO1l++ybTWulFrPVRrPURr3VT93fwtRtqtrPqcbZpWv0NFlP3XcVkUtTfLps2ybcK8DrlS9gBL7esri9obHtWVG2z2x3I2rZS1p2JJ7YuzDQHen4dULKvJtPnFo80jQB/4wAcwcuRINDQ0YOzYsb2Mcz01NDRg6tSpOPPMM3HMMcfg6KOPjjxkLwUl06Kw8jOHlKbVsChPGsz7Jfsoax90cfsoLLMsRe3TYHFMbYPWsci1N4mWzeSQa0+r37goT1wrymXjsupz5lr7XbvoWDZrD2TTyx3zRiu9kmQAeOV1YOtW4LDDwgHe2ASsWQOMHVv/qFhAMt3fdYfbxsZGdHV1Bf6XS5cuxeDBg7F27dpwYwwpuc40lbIympSX2SvKJfu4ssyyFLXPisXBTJe19oB9E5Y3llw2zh5Lap8vlnldraLWPuhGK1GU8U1btmzZgosuughPP/00NmzYgPvuu4+MLWaaSlwNHSWLa/tJGq0s3MZlluXYtlDmnuk4aTLXQ+fStyu1zwuLa+05zyNAczWPIIPL+NrQF198MS644AK8613vwm233YbLLrsM69atI2Gn1uahlGoB8DSA/tX/5z6t9feVUgcAuBvAXgBeAHCm1rpTKdUfwO0AjgCwAcDntdYr0xofubiaw6x6pjmwuNWL2kxn0bdrm8XV5GfV72mbxdFUVCpAv378xsV1HrmawyDWzp3hWVxrz3kbomIZUaTJMZLpbdu2AQAmTJiACa4zIH/1q1/t/n3q1Km7fx89ejQWLFgAAPjtb3+7+/H9998fy5YtCz/WAKWZTHcA+KjW+nAAYwF8Qil1JICfAfil1noMgE0Azq0ufy6ATVrrdwL4ZXW5/CiMObRxc5SsTStl/7XNvnBu82hu5Z7VtY4p+69t9iZ7XTc5Tm9yVjtcyt5Rmz2tWbFkHvuypPb2WEXfhiiT56Bbk+dIqZlp7Whb9c/m6j8N4KMATKPKNACnVH+fWP0b1ec/plSOqulnDsvQm8y1l5sry+Y8mmUp1jGPLMD+IVcvFtc+VK4smUd7LKl9MVg2k2k/FsC6ZaRWqfZMK6UalVLzAKwD8DiA5QA2a63NKZetAPar/r4fgDUAUH1+C4DhdZjnK6VmK6Vmt7W1pTn8aMraONlIgLm2QHDtmeY6j9TX5c6iZzqNK13YSq+4Hr7l3O8p8xieJbWXbSgqK0LttbmWdj0xPwExinTE/ztVM6217tZajwUwEsAHALy73mLVn/Vmoc/aaK1v1VqP11qPHzFiBN1gkyorcxg1oaNkmeXy2H7CzeQXZR7Nsmn3TBseFSvODU0oU6I8HjqXeewtrvMotZdtKAorQu1bWlqwob3d/3bYOUqTvaS1xoYNG9DS0hL6NZlcZ1prvVkpNRPAkQCGKaWaqunzSADmYn+tAPYH0KqUagKwB4CNWYyPRNyNJjfTmgaLa724sihqb3q5KdNkrjtJjjtcahbXenFlZTWPUa+bzLVeeax9UepFwBo5ciRa//IXtDU0AIsX911g0ybnOtP1nqunTZuAN9+sv/zmzcCWLeFZxGppacHIkSNDL5/m1TxGANhVNdIDABwH56TCvwI4pyiRAAAAIABJREFUFc4VPc4C8ED1JTOqf/+j+vxTOmrOblPcjaawhJU1yzxelJ2ksISVJst1A4o+rKhXuuC6jsLKNau5uRkHPPEEcNttjgmu1eWXA//zP0BnZ7hxffe7wA03ADt29H3u+98HrrzSSdVzcPpcmsn02wBMU0o1wmknuVdr/ZBSahGAu5VSPwYwF8Bt1eVvA/A7pdQyOIn06SmOjV5+psJ8I8z7nQbDtBpQ9F/bZJV9Hs2HFkXtAadmUXq5vVLuqCyA5c4IQHa3e7bJ8qtXWebR1ntCai/bUBQW53kEnH1Cmc201volAO+r8/gKOP3TtY/vBHBaWuNJXVyNUxqsIrctlIlFcQgxDRbHD/2yHArmWi+uLL/ah03nwrAoU+4y1F62IXusSiW8AQ6qfdAyjMR/hHmR+ZZIYQ7DsKImh5TXTc6TOUyj9tzm0fQmU8yjedyGAfZbx6gsv+tyG1bUxInymq9cd5KUJ8FlxZJ57C2pvWxDUVmU8wiEPwkxqPZmmRxIzDSVsjKact3kYrAoa294NgwwV1aY9hOqHW4Zrt3LlSXzaI8ltS8Gi3oezTJJWWKmS6o8Grq4SWuRWXk105RG0xaLqzHXmu+1aLmy8mgqpPb5YXGtfV7nEYh2ZJPKAAfVKwrLssRMUymMCStDO0XUdcyq/YQbyzxu02hSHPZLg+W3jjZqT/mFwYyN8nB3VofOubJsGpSyz6PUvi8rj9uQWcYGK6hlJMp6WpSYaSpldYMOrqkt1/YTytqbEyqKngBTtoxEYVG2ZnCtfVDKzfXQuc0bdOQxOZTap8viWvss59Esk5RlM00OqlcUlmWJmaZSmKSVMgG2ycpjYk6Z2haFlcfEPO+sNFLurNI+YfVlyTzaY5W99maZvLOojLlliZmmUtZGk1vbAgcznXbKbR6nZOW9BSLPrLzXnrqXm7NBoah91iyu9ZLa22MBdnqTsx6XjXW0LDHTVMqjOYzbAsH1EnR5M3S22ykok9a8JeZFqL25/BTl5bPyZlBsH4bneBk0qb1dVpYGmIJFeQWOOJ6CKuW2LDHTVOLa5yxXuohnDovM4pomc61XGWpveFQsrr22efzCUJR65bX2QP6vdMGVJcm0qI/MhNf7lhX1ZAE/VlzTmnbPdNx19PuGS3VFCa6sOMYpiwQ4zjrmbR6l9r0VlJhHYZmxZcGKY5yySIDjrCMlS2pPxwKibZN+tefIiuMDsuiZjrqOliVmmkpZpbZcWdx7k4UlLGFlwzI8YQnLFsvcAZWCZZYRFm+WZYmZplIeDXCcwztA/W+lStnv2+VmKriypGdaau/FolzHPJqwKCyufbtc65Vl7c3/Z4PF0WhyZUnPtKiPsupzjnN9SS+WuW6yXAWiR1maijiH4SlYUnupfZosajMddL3dKIeBKVmcjWYeaw9ImuxWVn3OlNesjtN+Ism0qJfMhHPtc6ZIk7nuvP3WUVjeLJlHeyypfTiWOVyft75d2yyu9eJ4fWJqFtfeZK4sMdOiXvLbsZnHKNIr7r3JXK/dy5Ul82iPJbUvBourAeZ6DWZKFufeZK7XTebK4vpFRk5ALJmyMsA20+Qwh7vzzgqqVxGSfKm91D5NFtd5NMaPykwHHe62xfIzKJQsmyYsTKtB3llB80jFKso8WpaYaSqF6XOm2rFR7rzjmApuh4KzNDtFYHGdR671KkPtZRuKl0xzbKcI6rWNkiZzvj5x0dsWuNae6zxalphpKvnt2OKmyUXe4abB4lovriyZR3ssqX2+WdQpd5AJozTmZpm8szgmrZzrxZVFVXvLEjNNpSx3krZu7MDdCOSNJfNojyW1LwarCPNoeFRpclZGk/LKDTavAlF2VlHm0bLETFMprzujIhxyletMS+3zwuJae5lHe/UKk3ID/EyYTRbXtgW5znQ0FmW9LEvMNJXCfFAXJb3yO8QTdR0pWVnVXuYxXZbU3h5LtqFoLL/ah02Tw9x8x71cmLEFGZQiJMCU9cpr7WUe2UjMNJWCPhBt3x0wi35P22f8Z1F7mcf0WFJ72YaisjjPo/v/pGCFGVvQdbnjnAxP1R9LyfIzdLavmpFF7WUe2UnMNJW6u50TDc1dBWtlO0ERlrCEJSxh+bPCpslhWO7lsmKFaT8JyzLLCUtYeWBZlphpKvm9KQD6D30bh1y59mjmud9T5rFHUnvZhuKwKOcRCMejNK2ULEpjrnW4nlYbbQtc+5zz3DOd93m0LDHTVKI2034pN9dDwXF2kmW43Bhl7WUeaVhS+/qsPG5DlQpNmhzlsHKY2ttkZWHyubZTxDGaHC/1lhWrKPNoWWKmqeT3DQuInl5RGfOsEyeuJylRJod5TyGl9lL7NFlZz6N7OQoWpWml6JlOYx2zrpfhFT1pzTq1zXuST1kvyxIzTSW/b1hA9PTKjxVn551FLzfXtI8ri2sKWYZ5lNrXZ2W1DUVNk/OWAMdJubNIzG2l72GvWFLkpJUri2uSLycgllR+bwog+g6XI4tr2pfnfk8bLKm91D5Nlo3UljJNjmIOubG41ouSBfBNWvPcM22DJT3Toj7iaoCpWQBtyl3mfk/brLyltkVi5bH2VL3JRTB0eU3Mi8BKI+Uuc8+0bZb0TIt6ibrPOYhF2X9N0Q9mWHk3O1mnfTb6UKX2Uvs4LIDvlS6y7ifmbjSl9vk3mlkn5jZ6uSnrZVmpmWml1P5Kqb8qpRYrpRYqpS6qPr6XUupxpdTS6s89q48rpdT1SqllSqmXlFLj0hpbKvL7hgVE37Fl1X8dlUVtprkmdFmwbPe0cjV0Uns6VlF6k7PoAabsc7adAEvts//yYZbjmphz7eUWMx2oLgCXaK3fDeBIABcqpQ4BcBmAJ7XWYwA8Wf0bAE4EMKb673wAN6c4NnqFMZq2EuCiJ+ZZJ4d5TyHznNpK7aOxgGi3tM4yOSxDAsw1tZXa07PMclmmtjYS4KzT97JfzUNr/ZrW+oXq71sBLAawH4CJAKZVF5sG4JTq7xMB3K4dPQdgmFLqbWmNj1xBptVmAkzJ4pqYm9dQsbxqxjmFLHpqK7WPznIvF4blV3uOLK4JMNfUVmqfHsvcPZOi9ma5LFg2zTRlym1ZmfRMK6VGA3gfgH8CeIvW+jXAMdwA9qkuth+ANa6XtVYfy4ey7pm2weJs8inrZV5TVBZXo8m1XnKli3SSwzyzpPZS+zRZAN+rjHC9YollpW6mlVKDAUwH8E2t9Zt+i9Z5rM/xSaXU+Uqp2Uqp2W1tbVTDTK6gpJUyAbbJ4miAqdcR4HvFkjJcNYNrvfxYRbnSRd56pm2zZB6l9rUsinU0KXfe+q/FTKcjpVQzHCN9p9b6j9WH3zDtG9Wf66qPtwLY3/XykQDW1jK11rdqrcdrrcePGDEivcFHVdZGk7L/mrLPuQjpe0NDNje5iTqPVKw8p7Zcaw/Q9iZLchiNlXU/sdReap8mizrlDmNabfRyy3Wmg6WUUgBuA7BYa32t66kZAM6q/n4WgAdcj3+xelWPIwFsMe0guVCWBpiy/5qyzznqOlKyOH75CEoqbPcTByWttlhZGGDq2ruXC8MKSnaiGBRKFjfjlEbtZR6l9mmyuG1D3Hu5KWrPQE0pso8GcCaA+UqpedXH/hvA1QDuVUqdC2A1gNOqzz0C4JMAlgFoB3B2imOjV1A6GmXnzTm15Wrys6p9VBZVyp1lAmzL5AetIyXL/UHt96UuCqu7G2hu9mdxNygUrDDzSMXimhxK7dNjca19GebR8LJIzHN2AmJqZlprPQv1+6AB4GN1ltcALkxrPKkrTNJKmQB3dtoZV1bGnLpeRWAB0jNNyTLLBZnpKKyw4+J2KDiNdSwDS+ZRal/L4lovql5uvwCC0kxLm0dJxdlocky5ubK41r6720m4uaXccqULewkdVxbX2pdhHrnWqwy1L8M8ck65LUvMNJU4m7AyJMBc68WVBfC9aga3HUiZ0iuu9eLKknmU2teyuNaLG4s65bYsMdNUyto4cT05rwhGswzzSJVy5z1N5npiUZ53kjKP/OsltRdWLSvPV2VhIDHTVAo6kSmK2QlixTkJjoLF2RxmVXuZx74s8xovFhDtw5Xi7O4gVpwTeLK4Q51tg5JF7WUe02NJ7WUbisoqwjwykJhpKgUZFGqzY4OV5RVLbLFkHp11NJdTCsPyS7m5nllvKyXK8ix9WyyZR6l9miyutZd5pJ1Hs0+RZLpk4mqcqFnSM10MVlDtzXJZs9yvKTJL+j2LwZJ5lNrXsrjWiyvLq/ZKRQuvLEvMNJU4GydhlYMFhD8cGYYV9gORkhXUyx2F5X6NsIQlLGEJK10WZWJunhMzXTJxvdRbWS4bx7FeWbMAOwaYikW5jnLJK3ssrrUvwzxyrVcZai/z2POcmGlRbHV3Z9cC0dBAd3JeVBZHA5xl7annEQjXmxyWlfdkmrplJKiXm+LEojgsbjvvoHXkypJ5rM+S2he79pQs8xlJMY/mOYp5NM+JmS6ZgkxFEUxrmCtKUF7pIgorq9pTz6NZLktWmNqb5bJkhak9Fct24kRhKtJgBR2+pdhJFsE4cZ1Hqb1sQ1FZUXqTKQ1wUO3Nc3I1j5KJqwEWFj0r7JUuuJppYdlPibgZFGEJS1j5YdnqTebKYiAx01TKc68tV9NqK32nTIA5sriaVq71oq69+zVFZOW131Nqnw8W19pnOY9R0mTKPmfpmfaUmGkqdXfns2+3CAY4zDpGSZO5XjaOksXRTHOuF3UvN9eUO2/9nrZZ3EwY93qVufZx0mSKfTd3lphpUS9xNpqUqS2VMadmcTWHHFlham+DxbVenGsP0BgUSQ7t174MRrPItadMkymNJldWmJ7pHJnpJtsDyKsmTJ3Q6+/bN63EstXrcWXN40YXL/s3Pty+AZ/xeN6t365fhtbGV/E9j2W/vmQZjt/5Jv4jBOvX6xZjY2c/XO6x7NcWLcfJne04MQTrxtdfQntLE77jsex5C1fg812d+HgI1nVr5wEAvumx7Jfmr8SXtMaEKcd4X5GhqmvWvIj+nRV83YM16cVV+DKA46Z+FF1N/t8fr141H8O27sJXPViff2ENvgbgxNtPwI4Wnw8UAD9+ZQHe+uZOnOfB+uy/WvF1AP9xx0nYOrjZl/X95Ytw4LbtOMuDdfI/1+JbAD5z1ynYuEc/X9YV/16MQ9rfxCQP1iefew3fBXDa3Z9F2/AWX9Z3X16C8Ts34XMerI///Q1cAeALfzgda/cZ4Mv61qJ/40OdWzy3kWP/uQ7fB/DF6Wdg9b6DfFnfWLAUx3W342QP1odnt+FHAM69/2wsnzPYl/W1l5bjZN3puY0cNW8DfgrgKw98GUvmD/VlfXnuCnxOac9tZPyCjbgGwIUPfg0LX97Dl/WlOSvxJQATbv9o3W1k7MubcR2Abz7yDcxbMcyXdca/VuE8AB+743h019lG3rN0C24E8O1Hv4XZrXv5sk7/52p8FcAn7joJO/v33UYOemUrfg3g8r9cin+s+7kv69R/tOK/AHzqnonYNqjvNvKO1dtwG4D/98QVeGbzdb6sic++iosBfPoPp2JTnW3k7Wu343YAV/71B3iq/SZf1klPv4bvADht+ul1t5F91+3A7wFc9bcf4/Fdv/FlHf/s6/hvAF/405l1t5ERG3biDwB+/szVeERN82V99Ll1+B6AL844G6v/NbDP83tu6cT9AK599n8wo/9dvqyPzG7DlQDOeejLWPFi321kyLZdeBDADf/4X0wfMt2XddS89c428sgFWLJ4SJ/nB+zsxp8B3Pz8Tbhn6oO+rPfP34hfALjw0W9g4fK+20hTVwVPAPjN7F/jzqmP+rLGLt7kbCOPX4J5a+psI1pjJoCpL/wWU6c+5cs6dOkW/ArAJU9+F3Nev7ruMo8rjXvm3Y7JU2f5sg5e8SZuAXDZX6/AcxuvrbvMn3UnZrx0F26e+rwv652rt2EygP/7tx9g1rZf1V3mwa52/GXhfbhh6jxf1qhXt2MagB8+82P8tfPWusv8sXMLZi3+E66dusiXtd8bO3AngKv+/jM8jql1l7l350b8a8lD+EXN5+XML830ZduQJNNEaqgA3Q3epq+iFBorIdoMACitUfGZmUoD0BCS1aCBbh8z2t0QflwNFfiOSysVelyNFR1Qr+r/GQLnjMubpavrH2ZsDSFqH5altDPv3iw743JY/u9VAGgMVXv/cWnVs1yYcfm+J6rPNYY4uZu69n7j6q6uf6h6BdR+93s1REtSY0WjW8Hzy2YlSu2ry3iNTUeqF3xZUcaltP+4ds9jyM+JUCyCepl1DPPZGjSuaLV3lun2eItFGZcKmseG8O9Vs47dHp8Vu7chivfq7s/7QNTuzxKvcUEpVFTE94TP545W4cYVtA2Z/ydM7dXuenkvE9ZThBpXQzgf0FMv/3GF9SfWpbXO7b8jjjhCs9EBB2h9xhnez3/961oPGxaOddBBWn/uc97PX3KJ1gMHhmO9971an3KK9/OXX651U1M41rhxWp90kvfz3/ue05lcqQSzjjxS649/3Pv5H//YYXV0BLM+8hGtjznG+/mf/9xhbd0azDruOK2POsr7+euuc1gbNgSzPvlJrf3eozfd5LBeey2Ydcopzlx6afJkh7VqVTDrtNO0Pvhg7+enTXNYy5YFsyZN0vrAA72fv+suh7VoUTDr7LO1HjnS+/np0x3WvHnBrK98Ret99vF+/sEHHdbzzwezgrbdxx5zWLNmBbO+9S2tBw3yfv6ppxzWX/8azLrsMq2bm72fnzXLYT32WDAraNt9/nnn+QcfDGYFbbvz5jnPT58ezAradhctcp6/665gVtC2u2yZ8/y0acGsG290ln399frPr1rlPD95cjDrN79xll29uv7zr73mPH/TTcGsoG13wwbn+euuC2YFbbtbtzrP//znwaygbbejw3n+xz8OZs2Y4Sz7r3/Vf75ScZ7//veDWY8+6iz77LPeyzQ1OfvJIIXZdgcOdPbfQQqz7Q4b5nw2BSnMtrvPPs5nZpDCbLsjRzqf5UFauNBh3X239zJBvsqCAMzWdfyoJNNU4trnnHXPtFmOihW294pjfyxXlvRMS+29WHIr93z37XKtV5a1V8r5l3XfLtcrXXBlFaxnWsw0lbga4DAsuW6ysIQlLEoWIOZQWOFZct1kYSVhMZCYaSplfW1oqrsDRkmTOe+8KZPDrFlhk/yiz6PUvjjbEFXKHfYqIxR3qIs6j2FYtlLbLFkUtTdXusj6NtRcWTauDU0xj1FYYqZFddXdTXdbzLAsiusmR00E/N74Nm8dTXlL66xZYWsv80jPktr3sLhuQ+7XeLEoEnPKdNT2raMpb02e1XWTKS8bR2nMo7IofIANVp7nkYHETFMpTLIT9htW2JQo6ySM613lpGdaap8XFtfac55H0wNLwXK/JglL7g4YrTc576lt1iyuiTnXeWQgMdNUCrMDiZImc92xcb2rHNd6cWXJPNpjSe3tsdyvoWCV+e6A5jlbrCLf0a9MLDkBUdRLYT/0Kc00ZTJdhn5PrvXiypLa22PJNpQOK0zKzbVnmmJcZv0pe1q5srgaTa714soSM10yBV2mKkp/GVdW0I6Ne79nnmuf93nMc73yXnvZhuhZQUYgjZ7psOvofo0XL8+sMCaMc890nmvPdR4ZSMw0lfKeOIXdkIrO4lr7Mswj13qVofYyj9HrRdXLHdQ7KpeN6y2ufc7SMx2NJT3TorrifGiTkhWmR9MGi2u9uLJkHu2xpPbFYFHWHgjmcT0Mb4tFWS+pfb7nkYHETFOJ8nC3sIQlLGEJK78sk1hHSfuyPHQuLGEVicVAYqapxPWQqxy+LUbtyzCPXOtVhtrLPNLWy9yEhIJlxhZ2Hc3yRWWFTUfzzOJae67zyEBipikUpim/CIeCw+6MbLA41osri+s8cq1XGWov21C0kwaDam/GljXLGA+vXu44LG7tFGENnS0Wt3pxZVHWnoHETFMo7OEK97JBPK4syrPhs75CgrB6lpF5tMeS2vNkGR5F7W2yKNcR4HdIP4yhs8niWi+uLIraM1BqZlop9Vul1Dql1ALXY3sppR5XSi2t/tyz+rhSSl2vlFqmlHpJKTUurXGlorCHK4Dgb1lhv62FYZmxZc3ieoiaa724sqT29liyDYVjRb0EHWUCTNWaYWNcZTg5j2ubB9d6cWWV3UwDmArgEzWPXQbgSa31GABPVv8GgBMBjKn+Ox/AzSmOi15hDHDYBIWSZXhZJTvcd7hZ14srS2pfjtqXYR6j3NI6TDsFdZ8zlQEOOy7KdaRmAdmlo1zNoY16cWVR1p6BUjPTWuunAWyseXgigGnV36cBOMX1+O3a0XMAhiml3pbW2MgV9hu8e9ksWFo7/yhYAF+DErbfk+KQaxFYWc5jEeqV19qXYRsyvKxZWZtWG+tIzQKCe7nzbA7D9kxTtUDknUVZewbKumf6LVrr1wCg+nOf6uP7AVjjWq61+lgfKaXOV0rNVkrNbmtrS3WwoUXZ5sGVZXhcd7h5TPtssrKex7zXK8+157YNRb2lNdcWiKxNaxHqleWJkbaMZh4Tc5ssitozEJcTEOttYbreglrrW7XW47XW40eMGJHysEIq7OEd97J5Y5mUm6tByeowfBlYUnt7rDJsQ4ZXdJaNNo+ysMzyXuJqNIty0qC0efRR1mb6DdO+Uf25rvp4K4D9XcuNBLA247HFV5STBoPeZFxZlMbcLJO1QaE45FoEltS+HLW3xaJsW+DKsmHM81yvNFpZ/FJuzuYwbL2KzqKsPQNlbaZnADir+vtZAB5wPf7F6lU9jgSwxbSD5EJhvykD4VszuLEorzJCnXKH7fekPAyfZ1ZYc5g1i2u9ylD7oG3I8ChbIPLMCmsOs2ZxrRfn2gM0KTclK430nRsrrKfISTLdlBZYKXUXgAkA9lZKtQL4PoCrAdyrlDoXwGoAp1UXfwTAJwEsA9AO4Oy0xpWKuLZmpMEKuiZkGFaYD50iJHScWZS1l3mMxqKsV3Oz9/NRb2nN9ZA+V1aQObTF4lovrrU3PfwULCCf7RQ2WUGfhzlJplMz01rr//R46mN1ltUALkxrLKkr7OEdIL8nIEZhUZj8sCyt6dNRYfUsx3FcZWCFrX1Li/fzadzSOu8nwWXNktrbY1HWvqMjHAvIZy83Z1ZOzDSXExDzrbCXeAHCp7bcWFxNPuU6Gl7RWVmawyLUK8vaGxZHgxLWmIc5DJ93ltTeHouzyafq5Q67X8szi9KYM5CYaQqF/UbqXjZvLK4mP2yfWhiWSbkpWGYZjqwsjWYR6pVl7W3dhCRszzTVYfi8s7I2mnmvV55rb2sbMv93UVmUxpyBxExTiGtqmwaLm8nPOuXm3h5AeUIdpdHMe70o02SOBoVz2seVlfU85r1eea69jW0oqJebc2sG5cmMYqZLpDBvsKKcgMjV5HOrV5hebq4n1Nlq88grK0qazNmgZHkYvgwsqb09lmxDvVlAdq0Z0uYhiq0o5pDStHJjcTf5WbKipNyUBpib0eS6jpQsw+NoKqgNirDCs6T29liyDfVmhUm5KQ1w1sacgcRMUyhK327YVgOuLG5Gk3u9qFogwvZyh2VRGU3KK6lQr6MfK8otrcP2QlLU3rAoah+VRbmOZWBlPY95r1eeay/bUA8LoLliSVgfIGa6RMpzahuVRWF20mBxrRcFi/KETbMMZZ+zH4tra4bh2WBR9sdm2WvLNe0rwzwWoV55rb1sQ71ZZvksWNLmUTJFaQ/g1k9cBtPKtV42WIaXdZuHjRP9qNK+rFlcd7hc68WVJbW3x5JtKB8ss7yXpM2jZMqz0cx7b3Ke68U15Y7S5lGWNDnrHS5HFtd6cWVJ7e2xZBvKB8ss7yVp8yiZovTHhjU73Fhck9awG6R7WS9xrT3XeTQ8KjMdtrcvzyzOKRHHenFl2ZjHPNcr77WXbYieRVl7BhIzTSHuRpOCFcbQRU1HKVnc6sWVRVl7rYNZ5pbWeT8cScUKszMKm+xQszjWiysr63nMe73yXHvZhtJhUdaegcRMU4jrIX1bbR7cjCbXenFnUdTe8PJ+ODLrQ9Qcd5Jc68WVJbW3x5JtqBisxkYntDHBDWOJmaZQno1mGUwr13pxZYW9CUlYMx1mZxTmCENYlhlbXlmcd2wc68WVJbW3x5JtqBisKCedW5aYaQpRXrqMKyuKoePGynvts55H8zwVK8zOKKyZpjzkaoMVdmfEkZX32ud5HvNerzzXXuYxOqtSCU6Tw9beLMtcYqYpZCaa8gQxbqwoJ8FR9O2mwcpr7cOwwqbJYeplxkZRe8OiWMewLHNYkPJEmaxP4KHqOaRmZV0vriypvT2WbEP8WUC4/QcVi4HETFMoz4f0pc2jGCzzfJZ9zjbGlTXL8OQQNd96cWVJ7e2xZBuyywLCfU6HbfOQZLokyrPRlDYPeyyl6FhmbJQGmOO4smaZlFsOUfM1KFxZUnt7LNmGorOAbA1wFGMuZrokCtPvGbWdghsrz6kt19qb57Nk2UqA81ovShaQ/8QpzDqGvURYnllSe3ss2YbSYQHhPg+pWJQpNwOJmaaQedNQ9ABzZYXpj416Ql1WLMp6Rb1sHEU/HiUrbJ9zlJMGua0jV1bYXu4oJwNlyYpiKorOktrbY2Vde87zCIQ70Y+qN5mSFbb25v9lLjHTFMpzq4G0eURjGV7RWdLmQc+ylXJzPaxcdJbU3h6rLNuQWbaoLGnzKJmK0AJRZFbUNDnrFghhCSsqS+vwh1y5Hu4WlrDKyApzExLKFogysBhIzDSF8pwml4FFfROSPKejwioGK2zKzTU5FJawysoC+J3ol3cWA4mZplCUvt2wO8mysyh7ps3YhCUsYXnzhCUsYdVnhUmTw7KAcNu3sKTNo3TKcwsE13YKkybn9TB83lkNDTzHVQYWZe3DsKL0cnM9dM6RFab2NsZVBhZl7SnT5Ly3U2TNCluCLy97AAAPzElEQVR7BhIzTaE8t0BwPQHRPJ/Xw/B5Z0nt7bEoa5/1PIbt5eZ8GJ6KFTYdzfM6cmUZY57lLa25tkDkmSXJdMmUtdHkyuKeJnM0KJxZUvti1D7Lecz7FUuoWZSpLdd15MoC+J7ol6XRLAJLkumSKEo/cdhDrnlkmefD7nCzZIXZsQmrR1J7eyzZhnrz8soKm7TmeR25sqKcc5MlK8r+VlhyAmLplOfWDOpbWnNN+7ge0ufKktrbY8k25Chsys251YDjuDizgGInwFzbKbiypM2jZIrSTsHtpEHzvLCEJSxhFZVleMLizQL4nQQnLP4sBhIzTaG8p8lcEzphCUtYwpKUmzeL6iYkXNNRYfFnMZCYaQpF6U0O+6Hvx1KKvheSamdki0W5jmVgyTxK7WtZXOvFjWV4FLVPg0W5jmH7Y8PUn5IVNtHMmsW1XlxZVLVnIFZmWin1CaXUEqXUMqXUZbbHE1pRkum8HiY1LIqTSNJgca0XV5bMo9S+lsW1XtxYJomlOqGuu5uWFWYd835La6qT4KhZXOvFlUVVewZiY6aVUo0AbgRwIoBDAPynUuoQu6MKqbCtGXJLa2EJS1jCElYtL2sWQGOc8t4eIKxisBioyfYAXPoAgGVa6xUAoJS6G8BEAIusjqpW8+YBX/saXpq/ffdD+3Suw1sBfPDo+ehWzZ4vfU43YuPPfo3Xf/mA5zIjdrXhbQA+dMxC7Gwc4LncM7sUtv3yt3jtxj97LrP3rvXYF8Cxxy3C1qahnss91Q50/up3WPubJz2XGb5rA/YDcPyJi7GxeZ3nco9t0cCtd+PVac94LrPXrk0YCeCkk1/GG/02ey730PoK+k2djta7/um5zJ5dm7E/gImfWYJX+2/3XO5Pr3dj0J0PYM19h3kuM6xrM94O4LOf/zdWtezyXO6+NV0Y9sojWD3Dm7VH1xaMAnD6pKVYNlB5LnfXK7uwz5LHsWqwN2to11aMBnDml5Zh8aD+nsvd/u8OjJw/Eyt9WEO6t+EAAOd8eTleGjzEc7nbXt6Jd+x4Fit8WIO7t+FAAF+54BXMGTLPc7lfL9mBg9rn+bIGdbfjHQAu/MZK/HOoN+vGf7fj0O3zsdyHNbB7B94J4KJLVuHZK71Z1y3djiO2vYSlPqwBlZ0YA+Dbl67GzKu9Wb9Yvg1HbXkZ//Zh9a904CAAl//fNXj8Wm/WT1ZsxUc2Lw9gdeIgAN/7YSse+ZU368pX3sRxm1bhZR9Wv8ouHAzgyqtexYxfe7O+t3ILTtz4Khb7sJp1F94N4Kc/X4vpU7xZl6/ahInr27DIh9Wou/EeAL/45Wu4505v1rdXb8SpGzYHsCp4D4DrbngDd/zBm3VR6wZM2roNC3xYDVrjUAA33rIOUx7wZl3w6nqc09GBl3xYAHCY1rj1tjbc+mdv1vlr23B+pRLM6uzEb6etx01PeLPOeW0dLgCwYOhYVJT3Z9Oh27fjjt9vwPVPe7POfP0NXARg4d7vR7fyzuYO2b4Ff/jDRvzPc96s0994Hd8GsHDf/4Nu5W2yDtm+Hn+6fxOufsGb9dm2tbgcwOLRx2CX8rY5725fi0ce2owfjfdmTVz/Kv4fgJfHHIfOBu/9+0Htq/HExoPwfR/WSRta8UMASw75BDoa+nku9672FXj69f3x3z6s4zeuwU8ALBn7H+ho8N4vvKt9Kf6+aji+68M6dtNq/ALA0g98BjsaWjyXG7NjKWYPeT8u9mF9aPMqXAdg2dGfR7uPh3nHjuWYP+gw/JcP64NvrsSNAJYfewa2Nw7c/fhhhw8Bnn3W83U2xMlM7wdgjevvVgAfrF1IKXU+gPMB4O1vf3s2I3OrsREYOhTbG3s+hF4ZMBh/GzYB3QHl/P1bvoAxO5b6LrO9cTCeHfoh7PR5QwPAXft8Ae9uXxzIem7oUdja6G2aAOCefU7HodsXBLLmDHk/NjXt6bvcH0Z8DodvfzGQNW/wWKxv3tt3uekjTsO4bXMCWfMHHYbX+73Fd7k/jjgV79/6fCBr0cD3YG2//QJYn8VRb/49kLVk4MFY0+L/Hv3T3p/Gh7Z4f/EwrKUDx2BlywG+yz2w9ymYsHlmIGt5yzuwfMA7fZebsfdEHLfpiUDWKy0HYumAMb7LPTT8ZHQ2PBbIWtUyCi8PPCiA9R+o+Oy0DWt1y9uxeKD/ga1Hhp+ERvgnHtsbB6O1/0gsHHSo73KP7nUiWio7A1kz+00INESP7fUJDOneGsAC/tbvGMwb/D7f5f6y5/H4/+3de4ycVRnH8e+PXgC7u7NbioZLkUuIGC69rZVLuxQEBDQiBpSLCopiolwM0UgwkYISUSv4lygqihFBBMRyEajQ0qXS0m1paUsRQSpCG4oWpCtYrH38Y07JUrozm5edObszv0/S7LxnznvmmSdnd56eOe9Mx+YNVceaP7qLpS2TK/ab03Es4/77IqLy9oD5pS56Wt9Xsc/9Hcew2+vrqo7VXZrO4ta3vAy8ydyOo9lr07NVx3qobRqL2iqP9WBpBvu+9jQ7DGCsP5UOr9inu9TFe159oupYC9qOYEFpWuU+pekc+O9V7EDl1eQFbYfTXZpeZawjOKR3edW5/3DbYcwvHVmxz8K2Q5mycVrVsR5pez/z2o+q2qe7NJ2RsblKv6k80PGBin16Wqcyv9TFqOh/UQRgcetU/thxbMU+S1qmDGispa1TmNNxXMU+j7ZM5sHSkYyO1yv3a53MvWOPr9hnecsE5pVmsGNsqjLWpKpjrRxzMHPbj6r6N2xZyyT+MPbEin0eH3MgD7Qfzc5bXqvY77GWCdw99kMV+zzxjgO2P1Zb/4uDuSiq7ZuqE0mnAh+MiM+l408BUyPi/P7O6ezsjJ6ennqFaGZmZmZNStKSiOjctn3I7JmmvBI9vs/xnsDaTLGYmZmZmVU1lIrpxcD+kvaRNBo4DZidOSYzMzMzs34NmT3TEbFZ0nnAvcAI4LqIWJU5LDMzMzOzfg2ZYhogIu4G7s4dh5mZmZnZQAylbR5mZmZmZsOKi2kzMzMzs4JcTJuZmZmZFeRi2szMzMysIBfTZmZmZmYFuZg2MzMzMyvIxbSZmZmZWUEups3MzMzMCnIxbWZmZmZWkCIidwyFSXoR+FvuOAbBOOAfuYNoUs59Ps59Ps59Ps59Ps59Po2S+3dHxK7bNg7rYrpRSOqJiM7ccTQj5z4f5z4f5z4f5z4f5z6fRs+9t3mYmZmZmRXkYtrMzMzMrCAX00PDtbkDaGLOfT7OfT7OfT7OfT7OfT4NnXvvmTYzMzMzK8gr02ZmZmZmBbmYzkjS8ZL+LOkpSRfnjqeZSFojaYWkZZJ6csfT6CRdJ2m9pJV92sZKmiPpL+lnR84YG1U/uZ8p6fk0/5dJOjFnjI1I0nhJcyWtlrRK0oWp3fO+xirk3vO+DiTtJOkRSctT/i9L7ftIWpTm/m8kjc4d62DxNo9MJI0AngSOBZ4DFgOnR8TjWQNrEpLWAJ0R0QifeznkSeoCeoFfRsRBqe27wIaIuDL9Z7IjIr6WM85G1E/uZwK9ETErZ2yNTNJuwG4RsVRSK7AE+ChwNp73NVUh9x/H877mJAkYExG9kkYBDwEXAhcBt0XETZJ+BCyPiGtyxjpYvDKdz1TgqYj4a0S8DtwEnJQ5JrOaiIj5wIZtmk8Crk+3r6f8YmeDrJ/cW41FxLqIWJpubwRWA3vgeV9zFXJvdRBlvelwVPoXwNHALam9oea+i+l89gD+3uf4OfzLXk8B3CdpiaRzcwfTpN4VEeug/OIHvDNzPM3mPEmPpW0g3mpQQ5L2BiYBi/C8r6ttcg+e93UhaYSkZcB6YA7wNPByRGxOXRqq5nExnY+20+Y9N/VzRERMBk4AvpTeCjdrFtcA+wETgXXA9/OG07gktQC3Al+OiFdyx9NMtpN7z/s6iYj/RcREYE/K78S/d3vd6htV7biYzuc5YHyf4z2BtZliaToRsTb9XA/8jvIvu9XXC2lv49Y9juszx9M0IuKF9GK3BfgJnv81kfaL3grcEBG3pWbP+zrYXu497+svIl4G5gGHAu2SRqa7GqrmcTGdz2Jg/3R162jgNGB25piagqQx6aIUJI0BjgNWVj7LamA2cFa6fRbw+4yxNJWtxVxyMp7/gy5dhPUzYHVEXNXnLs/7Gusv95739SFpV0nt6fbOwDGU963PBU5J3Rpq7vvTPDJKH8vzA2AEcF1EXJE5pKYgaV/Kq9EAI4FfO/e1JelGYAYwDngBuBS4HbgZ2At4Fjg1Inyh3CDrJ/czKL/VHcAa4Atb9/Ha4JA0DegGVgBbUvMllPfuet7XUIXcn47nfc1JOoTyBYYjKC/a3hwRl6fX3puAscCjwCcjYlO+SAePi2kzMzMzs4K8zcPMzMzMrCAX02ZmZmZmBbmYNjMzMzMryMW0mZmZmVlBLqbNzMzMzApyMW1mlpGkdklf7HO8u6RbavA4MyU9L+nyfu5fI2ncID7eDZI2SDqlem8zs+HLxbSZWV7twBvFdESsjYhaFaBXR8Q3ajT2m0TEmfiLqMysCbiYNjPL60pgP0nLJH1P0t6SVgJIOlvS7ZLukPSMpPMkXSTpUUkLJY1N/faTdI+kJZK6JR1Q7UEl7SLpvjTWjwH1ue/2NNYqSeemtnMkXd2nz+clXZW+UfQuScslrZT0icFOkJnZUOZi2swsr4uBpyNiYkR8dTv3HwScAUwFrgBejYhJwMPAp1Ofa4HzI2IK8BXghwN43EuBh9JYsyl/I99Wn01jdQIXSNqF8jeXfUTSqNTnM8DPgeOBtRExISIOAu4Z6BM3M2sEI3MHYGZmFc2NiI3ARkn/Au5I7SuAQyS1AIcDv5XeWFzecQDjdgEfA4iIuyS91Oe+CySdnG6PB/aPiIWSHgA+LGk1MCoiVkjaBMyS9B3gzojofhvP1cxs2HExbWY2tG3qc3tLn+MtlP+G7wC8HBETC4wd2zZImgEcAxwWEa9KmgfslO7+KXAJ8ATlVWki4klJU4ATgW9Lui8itnuRo5lZI/I2DzOzvDYCrUVPjohXgGcknQqgsgkDOHU+cGY65wSgI7WXgJdSIX0AcGifx1pEeaX6DODGdO7ulLee/AqYBUwu+lzMzIYjF9NmZhlFxD+BBenive8VHOZM4BxJy4FVwEkDOOcyoEvSUuA44NnUfg8wUtJjwDeBhducdzOwICK2bgs5GHhE0jLg68C3Cj4HM7NhSRFveZfPzMwajKSZQG9EzHqb49xJ+SP27h9A319Q3kc96J+bbWY2VHhl2sysOfQC5/b3pS3VpC+XeRJ4bYCF9A3AkcB/ijyemdlw4ZVpMzMzM7OCvDJtZmZmZlaQi2kzMzMzs4JcTJuZmZmZFeRi2szMzMysIBfTZmZmZmYFuZg2MzMzMyvo/5bz2KV59X9CAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plt.plot(hi_result)\n",
+ "#plt.plot(hi_array[0:10,lind])\n",
+ "\n",
+ "\n",
+ "titlestr = \"\"\n",
+ "\n",
+ "# temperatures\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "plt.grid()\n",
+ "ax1.hlines(-1,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.annotate(\"wet surface\",[25,-0.7])\n",
+ "ax1.plot(time_artificial,Tsurf_result,'b-')\n",
+ "ax1.plot(time_artificial,Tsurf_result_Semtner,'b--')\n",
+ "ax1.plot(time_artificial,T1_result,'g-')\n",
+ "ax1.plot(time_artificial,T2_result,'r-')\n",
+ "ax1.legend([\"Tsurf Winton\",\"Tsurf Semtner\", \"T1\", \"T2\"])\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24],\"\")\n",
+ "ax1.set_ylabel(\"T [°C]\")\n",
+ "ax1.set_title(titlestr)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hi\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,hi_result,'b-')\n",
+ "ax1.plot(time_artificial,hi_result_Semtner,'b--')\n",
+ "ax1.legend([\"hi Winton\", \"hi Semtner\"])\n",
+ "ax1.set_ylabel(\"hi [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# hs\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,hs_result,'b-')\n",
+ "ax1.plot(time_artificial,hs_result_Semtner,'b--')\n",
+ "ax1.legend([\"hs Winton\", \"hs Semtner\"])\n",
+ "ax1.set_ylabel(\"hs [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# Fluxes\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black') \n",
+ "ax1.annotate(\"melting\",[-1,30])\n",
+ "ax1.annotate(\"freezing\",[-1,-30])\n",
+ "\n",
+ "ax1.plot(time_artificial,Qbot_result,'b-')\n",
+ "ax1.plot(time_artificial,Qtop_result,'g-')\n",
+ "ax1.plot(time_artificial,Qbot_result_Semtner,'b--')\n",
+ "ax1.plot(time_artificial,Qtop_result_Semtner,'g--')\n",
+ "ax1.legend([\"Qbot Winton\", \"Qtop Winton\", \"Qbot Semtner\", \"Qtop Semtner\"])\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_ylabel('F [W/m$^2$]')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# albedo\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,albedo_result,'b-')\n",
+ "ax1.plot(time_artificial,albedo_result_Semtner,'b--')\n",
+ "ax1.legend([\"albedo Winton\", \"albedo Semtner\"])\n",
+ "ax1.set_ylabel(\"albedo []\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "# rsds\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rsds_array_artificial,'r-')\n",
+ "plt.hlines(rlds,time_artificial[0],time_artificial[-1],'y') #\n",
+ "plt.hlines(shflx,time_artificial[0],time_artificial[-1],'g') # shflx\n",
+ "plt.hlines(lhflx,time_artificial[0],time_artificial[-1],'b') #lhflx\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"F [W/m²]\")\n",
+ "plt.legend([\"rsds\", \"rlds\", \"shflx\", \"lhflx\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 864x432 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.0\n"
+ ]
+ }
+ ],
+ "source": [
+ "# quantify radiative forcing due to change in albedo\n",
+ "rad_absorbed_winton = rsds_array_artificial * albedo_result\n",
+ "rad_absorbed_semtner = rsds_array_artificial * albedo_result_Semtner\n",
+ "\n",
+ "\n",
+ "\n",
+ "# plot absorbed radiation\n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rad_absorbed_winton,'r-')\n",
+ "ax1.plot(time_artificial,rad_absorbed_semtner,'r--')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"absorbed radiation [W/m²]\")\n",
+ "plt.legend([\"winton\", \"Semtner\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "rad_forcing_dif = rad_absorbed_winton -rad_absorbed_semtner\n",
+ "\n",
+ "# plot difference \n",
+ "fig, (ax1) = plt.subplots(nrows=1,sharex=True,figsize=(12,6))\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "ax1.plot(time_artificial,rad_forcing_dif,'-')\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_ylabel(\"difference in absorbed radiation [W/m²]\")\n",
+ "plt.legend([\"Winton - Semtner\"])\n",
+ "ax1.set_title(titlestr)\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.mean(rad_forcing_dif))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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uwOLFi9Ha2hoQxtDQELa8sFkhQtqflBKNEyagu7srtvyFC4/Cwbb9ePKJx4NyXn5xszlgpV42CqOsCEMIcb4Q4kUhxMtCiBttj+Pm+smpGzJbo/1mMjrWOHetZpaGWBMJP2ZzrB4m6r8Y9YqoLBRerwxTL1PGanVvhrgGw1UvLmMut3r5Ctf/31SvnN/4evkDT9w9n6iCN9xzytipEZuBbthNAr293bjqqquwZMkSnHvaCXjlpRfwla98Bb/97W/x6U9/GsuXL8eKFSvw9NonrN1OmjwFJ5x4EpYtW4ZPffKTLK6mpgbf/vf/xBc//1ksX74cJ52wCs+ue5LFUzam7mEIIZIAvgfgHAA7ADwlhPidlFJfL6uYeg8jLmt3uYehqhHzVET0/wwxz6TOicepoXKpl2TqRSehdL1IInS4N6MpQmGev7fKriv1GuZ6qdtoXNiMAkMlNxNWsTjs0mOOxerVqwEAOw70omsghZaWZrS0tODhhx8OcC9lp6Qeeuih4O83nPJGvOPiCwLMQw89BCklNuzswA9+8p+Y0VwX/H3ReWcHuNtuuw0A0DuQwqKlR+MPDzyI5rpq9A6k8HJ2SsovJ85szkHZEAaAEwC8LKXcCgBCiF8BuBgATxgHXwV+/R6cdqAPt1V3oul3vwKqkzitrQ+3Vrdjwu9/A1RnT4EQAASufP0gzhwaBO76DQDgyh3tOH1oALj7twHGbzn/0LMXjalq4HctAASu692LxnQS+P30UBrl/f+Vqu1Y8cokYGAyElLii1XbseLlycDgpKxPz/esrn58rmo3Fqz/K7CtHod2D+LGql2Yt/5BYHsjQmkclu/sxD9V7UfDo2uB2mocs6MD1yX3o27Ns0BtjedTJACRwGmtezA71QuseREQCZzcthvTUj3AU68GGIgEAIGz+7dgSncd8OwrgBB409BLmNRVC2x6PcBAJCAlcGZiPeYe2Ads2QYhBU5NbMChBw8CW3dF/Nbv7cZx4iU0768GJkxFw/4eLBWvovFAA7BnXyTWCd27MVfsRvLgVmCwDo19uzEL+4GOHUCmPhJr3VA7mmUX0NcOiARq032ozfQDQ32RWCESgLS75xSMKVrGrGODTBxRrDFrRwDObqex0RkpXmEAdmpkzNeLd8NjDSyQj19biypCs8+RqpeNwhA2NzpKwYQQlwM4X0r5wezf7wFwopTyGgX3YQAfBoAl0xIrf3N5PZL1TUg2Tkbq4A4ImUGidgKSjZOQbt8NyDQEch0i2TARiapqpLv2QwBINjRBVNUi07XfG9OCcoBkwyRApiH7uyAAJOqbIWQGcqA7wPjiP9nQBAwNQKYGIIRAsq4RMjUIpIey5ft+E0hU10CmBiFkBkIIiKqaLC6T9ebzSwIJISBkWlsSWDHe0tmn8jOJKmQkINMppDPeYJaW2Qe2GiYiNTCA1ECfN8g1z8BQfw9SvV0BJiOBTFUdklNmY6BtF4b6eyCr6lE1Yz769m1HqrcT6eyrMjwfM5GcNg89Lz+J1FAKYuIhqJ51FLpeWI3U4EBQfkYC1XOWQzS1oPO5B5DOADVzj0Ni0iy0r70vi5FZ38CElW/DYG8nOp570Hs49IQrMNTfh/a19yGVLT+VAVJIYupbb0T7xofQtfkxpDISLVfehI7nHkT7sw8gLYFUxvObmDYPky/6JPbe/2/oef15JFvmYsplX8G++/4VXVvXB7hUBmg49s1oPusjeP2WdyLT34UJy8/H1POvwY7vvRfp7gORcz/1wutRd9gy7PzhBwAAU867BvXzj8fO71+lXadD3v89DB3Ygf33fAMAMPOq7yLdfQCtd34lCkxW4c8PP4GWyROR7jkIAKiZuQDp7gNa+aK6DtVTZ2PowC7IwV6I6lpUT52D1MHdyAz0RLCJhomoap6Gwb1bAZlBor4ZVROnY3DfNiATfVK7auIMiJp6DLVu8/5ung5R2xD8HbbqlsMgU4NIte/x/p46BzKTQurgbgUpUDNzPtJdbcNar7bOHvz9n7vV67VOSqm9VqCcCOMKAOcphHGClPJa7phVq1bJtWvX4vZHX8VX7nsez37hXExsqMYvn9yOz9y1AY9/5izMnBhdRXHDr5/BU68dwCOfOhMA8Nm7N+DPm/Zi7efP1vyfffPfsHDGBHz/XSsBAG+59VG0TKjBT98XfYCtfyiNRf/vj/j0+Yvw0TO8h+vm3ng/rjvrSNxwzsII9qltB3DFD9fgFx84Eace2YKNOztw0a2P4sfvXYVzlkSftNbq9cRr+Ozdz2HNp9+EmU012eVSEpAZfOa3z2L9623443WnATKDr92/CX97YR/+8o+nBhj/37v+43HMa6nHV9+yBJASH/nFWkxpSOKmty0L4SQGhlK4/AeP4eqTDsNlxx0KyAwu+/6jePvKQ3HlqtkRny/u6cDX738enz53IZbOasJr+7vw1fuexzVvmocVhzZHYn3ohb24++nX8Y1LlqGhOoHHt7biznWv4/MXHIWJ9VWRGO5a9zq2H+jGP565AJAZ/O+Gndiytwv/cOb8EA6AzOBnq7eiZUI1Llw2E5AZ/M9T29FYI3DhshnetEomDcg0Uuk0fv3ENhw7pxlLZjYCmQzueno7Fs9oxOIZjYBMe34zGbT39OHp1w7g2NlNmFxfhe7+AWzccRBHTW/E5Ppk1mcGkGm0dfVhX2cfFk5rQBIZdPYN4mB3H2ZPqkUS0vObxfcMDCKTTqOpJgHINIZSKUBmUC2ydSpBkyIBIZJIIYn+NNBQV4tEIgkkqrL/ktjfm0ZfSmLO1GYgUYVdnYM42J/B0kMnBxhkj3nitQ7U19bgmDlTgUQSf3v5IGqqq3HSghneTaOs35RM4Ompb8GyBXPRkH0Nxt6uATTWVmNCbVVuZgDAQFqitXsQLRNqUVedxGBaYk/HAFqaarNP2/tZnkBHfwr7uwcxt6URyUQCHX0p7OsawNyWRlQnkwEOENjZ0Y/ewTSOnNEU/N3Rl8IS5Y0HAPDini7UVSdw+FRv5dKWvV2oSiZwREtjBJfJSG2113M72jG9uQ4zm6Pjlrraq28whS2h1WBh2981gF0dfVhySDOqkgmsfWYDLv/V9sh4KIQgCaOcpqR2AAi/HWs2gF02BwZSS5m35Ob6RUisZYU46VddUcU9hKTenPZ/k/I+IzWsKdZQkN6KEySQEUmgKrocry9Rj14xAaj33nPVVzUJB0U/0KS/7mOP2IpJNc3AVI/cdlftQX91DTB9cbT8wTQ2yN1onbgImO1hn0YrTm5eAMyNvseoXbTh4Uw1/n72icCCFnQ1duCBTD2umLUSWDIzgn354Fbcm9mMryw7F6ivxrbB7fifJzfg+mVnYqLyuo2Ht67H013t+MeT3gQAeGzvBvypdQ/+4dRztHr957qHsKilGReeeRwA4BebH8XkxhpceG6U4IcG0/jcY3/EjYsWYUn26flPPHk/rlm4AIuV9zO9uLUN7//R4/ivs07EKQtasG1nB95x66P49zetxHlLo/W6+5Gt+Nr9m/HsB8/FxPpq/O+T23HjXRuw+v1nYpZSr8/9aj2e3t4evBXgS3dvwJ827cHaz2frlckExHXhdx/CopmNuPmyZUAmjat+8hgm11fhu1d4f/tE2D8wiMu+9zDef/JhuGzFTECm8Y4fPorLVszAFcfNCnDIpLBlTzv+7S8v4NozjsDC6Q3Y2daF2x58Ee854VAs8UkzkwIyaax9tRWPvLgXH33jXNQlM9iyqx2PvbQH71h8KCZUI8Ahk8arr7aio6cfc6ZPBTIpdPQfxMGBPqCuORdrahCQfZiY6UBDSgAHOoFMCgvS3ajOZIBtWzyf2RiSmRQaTz8HdUMHgCEAkJghAAxm/4WsFsBsASCbdNcAOCyR/TuaiGMigIkJAAfov8N2qP9jT+7vQ4HsCCUipDVfAhgQwF5vyvTwtAQyAFqT8AkIwhuFjhBp1PQmgSFv32FiCLX9VUAmGfFbnZaYKVKo6esBhpKoSku0iEFU9/dr2JqhFCZiCGIAQCKBZGYAb0g8j6qdE4CuRo+IGSsnwngKwJFCiCMA7ATwDgDvtDkwt+rF/988x6qvfOL9Rh9wo7HqzcacX8N8sBIr99Rs2G+p1IsSrXy96PLDfo2rv4jyR7Je6n0Bu2cbFCwVK1F+JNZEAv4ix37UYjDRECQD7cmpkMlqYNJhEZ/pgRQ2ye1om7gImOMR4VM4gFUT5wMLokTYVtuG32em4O/mn4iF81vQsasTv/zLIzh9/kosWRYlwmewFbc8vxkfPP1c1NVVY8NTr+Nrzz+HC844ExMUIvzFr9bj2dfbcfbbPSL873s24v4Nu/H0e3SC/9i3H8KSWc247Z0ewX/se49hYn219gqa3oEUdq17DtObFmFaNhPfsKMd05pqMbOpNns2JSCBnsEUtrf14LAp9WisSaJ/KI3X2nowa1IdmmqT2YshASnR3jeIA92DOHxqA5LCe4lpW/cAZk+uQ1VwbTzsgZ5BDKXTmNFUC0iJzr5B9KfSmD6hJijbx3b3DqIqAUyoqQKkxGDGm5auSSQCjOdaIokMElICqRQAiXpkkEwPAv0IYSWqpcQ0SIjsa8GqAcwSAPqy/0LWDKA5AaDd+7tuoA2/qvka8BvtEmhWNoQhpUwJIa4B8CcASQC3Syk3WR3LPRHNDAAuqzi0J1ENSsBqTbkSq79c0wZbzHpFbkw61otc0cXWKx7ru6dXlY1uvbTnZgz1Yp9gL0K9bFbAUfUSsKtXrm1Z+I2pl74Cr7B65bZErm72IOU14EJiCEnIRA1QVQWZSWMAg8gkaoHqqCofGuxHNxJAbROQEBhKD6ITSWRqmwDlVeTd/b3oy6QxY0ITAKAr3YeO1CCmN+tTUnv7u1BfncSE7Juq9+zrRkIA86ZGX+qYyUi8vKsDhzTWY1qT97DeSzs6MK2hBjMnRom4p38IW/f3YN7URkyoTaJvMI2trV2YM7kezXVVAbFAShzoHcT+rn7Mn9aIpAD692Twd4Ofwy1XLMP0xiSQHgK+/BYtbgDl9RyGlPJ/pZQLpZTzpZRftz2OfxKVwkpl6kiQDd/3G26i8aohPruVSqymp8LVegnHenFZsO17p6jDvWcACGx09syqXupqHq5esKwXlbWP93pxikytV069UrH6MUaxNu3QqAhhq16Jjcz0cHh/OObCTeIbX7gR3/3udwP3H3rnpfjgB3OvJf/EJz6Bm266Cdd98N2xS59uuukmkDWIrZcARAIikUAaCUiRBJLV3hR1VS1QXYd0ogb9qAGqG4CaRmSSNViTWYqBw88AFp4HLL6IdV9WhJGvuT9hq2RAjF/bJ1GhdD7/tylby3U+PlYXrMsT7LZr5f17r9r7tIgzFmShwQvqcmXpsUb9mrCQevkFP+ntUK8g1hKqF6cayrFeVm9SyOT2h7GUSWa/odtqD3pz2GOPPzF4DiOTyaD9QBs2bcpNgqxevRpnnXUWbvmPn8fGetNNNzk9kFhIvXyzWVY7LghDvelc3CeiVdVgkuyKX0Os6ttqTdiSq5dROeV8ej6I8jUiNGNd6hXJ2pknot3uzUSxLvXKJS40NqHEalsvXulGy/d/m+olQjhTrGGLw0YHSz4jkzIaK6+ciIysGKaWZWIMAMcd/4aAMF7c/DwWHLUYTU1NOHjwIAYGBrB582ZMnjwZbznjDQCAO+64A5deeine945LcOaJK/CpT30KAHDjjTeir68PK1ceh89c+yEIAdx8881YtmwZLj3rJPz4+97Detu2bcPixYvxoQ99CCcctxx//85L0denf9vEuroWBFU29zAKsULfVstm4lqnNneo8NfiEoKb4/U7tZKtMaphuOol8qyXiKmX3+tMc+K5dwPZ1Utd1WZaKq5l14apG02RFble5kUK0XqZnswP+/JjMNUr2g7oF/qp58D04J4aQ9xCDft2aKdGtMvyhxtxxPb1qEoI7V5DfSaDeUMZ1NUkASFQIyXmDaZRV53Q7ndMSmfQkMpA1CaBmcdAnK48/6HYjEMOQVVVFbZv3461Tz6O5StPgOw5gDVr1mDixIk45phjUFMTvU/yzDPP4K6/PIKamlpccOpKXHvttfjmN7+J2267DevWPY3nd3fi2fVP49XzRokAACAASURBVKc//SmeeOIJbNrZjvdcfA7ecv7ZmDx5MrZs2YJf/vKXuPnW7+PyK96Oe+++Cx9431XGODmJUVEYWePn+unGZ5Nd57C5v7nOpz0JG/jVfWpz4sZBhcaaYgiX7zInbvvEqK1yclklZZrr17LQhN03SYJYLVRDgCV85gbhHM4Uaxg7XPWKUw02q8r014jwsfpEqj47yioMJVbjN0kQxVrfw3A0Fw+m9n3KKadg9erVWPfkE1i+8nicdNJJWL16NVavXo2TT9Y/Q3vWWWehqXkiauvqsGTJErz22msa5vE1q3HJJZegsbERDY0TcMFFb8UjjzwCADjiiCOwYsUKSACLj14eHB83fWZbL9XGhcJQ5bXp+wbqtwW4RgoQc/3eM1YkzvOlZIHUfLC6mijIWKlY4YTNe64/geDj8iqOqpfVKimjauDqRWPznutnM1aiXkysmspTfFD10r+dYZG4MD79sqJqRCBFPNyXe27Hvl5qrDb1intZo/6xJzuFkRACaeJjpmqShQu+iW07OzC5sUZ7vqW3bwjb2nqwYPoENNRUYWgoja17uzBnSgMmN0Sz/4Od/djb2Y+jD53onTPmU7JhO/nkk7F69Wpsfn4jFhy1BHMmAN/5znfQ3NyM97///QHOj7W2tjarinOvKg/qpVYwXMfQ8T44mUginaY/YUuZUH5VXm+eNXaunxtYQ2fFOCdONH6680XLNfnNKDcm4+bvAbu5fill3vWyfaurh+Wy0CjWvJooWi/z90PU6TO3LySaskWruX7mi3s2Gb7pnhNAvAacxDFtlnYZKd+P20YNGfsMCquXUTklwli+DWimjqycmVJxRxPwFMZ9992HSZOnIJFMYsqUKWhvb8eaNWtw0kknsfGpxVdXV2NoyBv8TzrlVNxzzz3o7e1Fb18P/njf73HaaafFB0M5NkC56xC2caEw/EHF5g2wBd3DsJT3HtZu5ZO6XS3fLxeIywL1uX7rexj0jBQZayLBTcspJGBQDf4W/U2pNFZbqWbIWK3UEEXwTL38LTb3kbh6cVm7zTMIPtamXqpy82Mxvrbdol6acorB6kTM1wuKcrK6h5E1Gw6wmbpR+5fJjj76aOzfvx9vveyKyLbu7m60tLSgu7vbwgvw4Q9/GMcduwLzFy3Dz37+C1x99dU44YQTMJDK4N1XvQ/HHnsstm3bxh6fDw/azOyNC8JQn5dAkLEyDTqCtL+H4WXXpg6V2xb/zEYWl+DlooTa+fh6qViufK8s/b4E/crybLkKNm0YLANcwhCrRljeH2nmprNaLwoX+FViNS48CG3zCFb3ya0QorN2nYiBnEpR/drO9evTqOZ7M9FzYE4G1Fhp5aJeg2AzGavVUvRsaZrKMigctS/SHs37SbDilI7B259MJtHZ2Yk9HX1o7fKmsO64444AN3fuXNz74OMQAK6++mpcffXV2Nrqkch9990X4L71rW/hq1//Bl7Y0wkI4IYbbsANN9yATbs6MCk7dTZ37lxs3LgxKP+qj1yLI6dHH/4jq6UQvG+Vm95Zk9CfQQBMFz6K5acClKydwaqrY7zfXEeJYoNMgRkA1Dl5HkvdQ6GN8msaVGympLi5/tGuF2WqavCw9Fy7On2VWwZNY6nExQbrTbVxkzx2iUsuYw5hY6ZRtXpZJFmjlZBFzchEWqxcq6HqZY+1y++9c8tj1fNVjHpRViGMrOmdz4TVP1LPnUe6o9LlqwXz5JLbH/6fw1bqpdfLZCpJmAg+chwKJ/ixmriUSr3sdIMr1kqLkD754Vf3y6cCul/epz1WRDptdqsFt4wPwgA9dcOdoMigwqWhIAY2JgsN9it/sR0qVGzuM5o0tlIvggQMRBiNtLyIcKwSfDHqJSE1ojfwoO1ma3P5TIRHmvkHUMx6uX7eYnwQhtSzKsB2KsDfTmH1VxeYOqqehRmmAvzMLuioXKxjr15hXDhWKxurRFipl7Fer7UPoavjoP0AKCL/kSOrOrALHsr6LzLU2lmsT+H187a2NqQcbmWPi5veEtGWZ5bMvLyOm84QgvcJ6AO2zQ28uKmAcqmXWq6xXmy25EaE6k290SbCYhF8pV66z1ufOIilhzSjr9P7Mt2ejn60VyfQpTxb0TeYRlvPINBei+pkAumMxN6Ofgzur8a+2uhw2NE3hO6BFKo6vWc5+ofS2N89CHmwFjVV0Vx7f9cAJIChNu+5iM6+IXT2p7C5K/ocCADsae9DZ00VOhu8Dxu1dQ8gnZFIHYh+FCmVyWBvxwAG91djbza2Yterrq4Oncnm4DzG2bggDKiN1EleCxYLbbAtfF1/rqMi8oMtP1x6seoFu3pxx5nIJeSSLb+ciHCsEny51atzIIPdmWacvHg2AOCqrz+AMxdNxzcvi370677nduGa363Hn69/IxbOaMK+zn5c9PO/4mtvW4Z3rzg8gv3mH17A7Y/txEtfuwAA8NfNe/Gh363FvR8/BYvnTIpg3/0fT6BvKI07P7oCAPDdB17Cdx/Ygle/caFGhFd+6U+49LjZ+NJbvdg+cMdT2NPZj/uvOzaC297Wi7f8/P/w7SuW4/Jsvd779Qdw9uLp+Mal0Xrd/9xufPx3T+NP//hGHDWzCXuz9fr6JcvwLqpej+7ES1/36vXK83uD8xhn42NKCspgHchrJgMiGz+BDfnysdarU8CsulGwgX+u/GGolza2c/WiiJCrl0KEpnpVCL5Sr8BvkeuV8xT9wSYu4WMEAWKwamxRrBJLCRO8auODMCSzKoDCgvpEK9f49Zf0ceV7+1Vy4bG+N3Pns6+XVr7vg/LLYClcOEb/t82cuMkqBF+pl+rLx9reo4hLXCj/Ophu+6VIhMNF8KqNE8JQG3RuO4W1l9f6ibcdLAXMF8h2rt+6Xi7TBioRxpCbtkxThw4bEY5Vgh+r9dLK931QfrXjaOMSF1ust6NC8JV3SWVNH9j5Zsph2Rt4NheTuA7sU6tKphD3WmnreqmZlaleql/LRur7NU4FFJsIxyrBl1G9KJ98rNGNLokLZxQRmnyGo6wQPIz1Um18EIYMD6YxjV+TizyWuoFHd6jshVccm95Wq73RlPWaM3NHZeS1zcDGZWt2swMRrA0RjlWCL6d65Xwp5RvuZamxsomLoLC6jTYRjlWCd6mXauODMKC/stzbzmGFhiX9SuLCMzhAx5quvAjjYLrweqwcZ9mQgAelljgyTjEMRDhWCX7U60Wb3Vx/EBYVqqJITWUxiUuF4NlYwzbS9VJtfBCGyv7BnB2Npef3CCx0v6a5yLDFkYtWPoVVidAYqyqZY86BQ6w2RKg36Oh2PVbFJ+121Am+FOqlGlcvigjZeqlE6JC4hLdTIVQIfnTrpfqsKAzCyI5qc0Mo6NT02VTnAm3kon+c1VJVU6ysDLbIagz1ciVC1a9xEA4ks4EIS4TgR7NeWvkuBB/XtpQybEjTKXGpEHxR6hXsV2MwgK3qpSalhnqpNi4Ig3piFOAaH3PzitPiIROM01wjVbIKg0v1CVvOBPGb82tzo80H2xAhWa+4QdjHGshNja9oBF9O9WI7dTzBs/VSfPlxuyQulFUI3q1eqsVdgwg2pl5a+RSWmZmwsfFBGFAGXmNWwQ1AFFb/bgOHC/vyQ6AbXhRrIiztdQrGrEKSDYOXzIpbBheO1f/NEXEYa87Ahofgh6Ne4f3qMXGWD8Gz0yHEOdBgBSQuOR8VgmexlvUaSYK3mZlQfZhsfBAGIdkB5mJyTM1N80Sw5mwx2vg4clHKN908A5PV2GBNRKhJ5pgHi8JY0A1Pq5fiwxRr0Qjesl6UxRG8EmrRCd4lceGATh8aGqME71Ivb79lvdTjgvJosHYOGNXi7XcneKeZiRgiDNv4IAzQ769hkhoSa5UFWspggCcXKFjzAERfeFPjy5VvIELLWMl6cYOwWi8TEQ4XwauxcrhSJHjDtEEhBB/erpYftlImeJfERbU4gqfAxSZ4bmlxIQRvMheCV218EAahBADmBElJXhSrRsLhQvwfBnONCcg1oviGZ58BWRMh0fhNsUI7B9QAqNQrKIv2OxwEr1o5EXxue4XgbaycCJ6Ky8d5vujtpuOLRfCqjQ/CgN5JAP4EkexvlS3ZfcYTsJGh/v98rFQGxmGdiJCIlSsf0BufTeN3yizBY8cCwVNWIXjdSobgDTHo28ub4FUbH4QhAYBqpMzFDP2da/s2J97M0rq8pssPxxgbq4UEpbBGIiSIyNSYtPNlyIByHdVAhEysY43gw3FR4DFJ8GDOQRkQfGgHuWksErxq44IwAPrdLaZOFWDj5Jri2NxRLRp/0FEFuV3fZkmEbKeOH4XjB6BwDHGvN1c7avywEkea1FHlQPAmIiwngg/jwrFySjd6XPkQvHFcLSOCD+PCv21U3rggDE5a2mQV3MnMvRgs5JeZZCDfa8+RS5ApRGOlzYEImaxCxVL1YomQqpeh/HC5ufIIrCQ6vwkbLr9C8EUh+JyveIJXW4ETacKArRC8t1/9bToHFgSvJ8XmZCBs44IwAHWg8k+QRSMVNJaeX+R9ali4fWjILtbsdg1pny1xsVLGnwMSHik3jggjx1QIvqgEr0Dts9sYbNinCVuKBE/ZaBM8fZiZCK1iBbQ+a4w1ZOOCMLyLSV14BkueTAXn71fnFymfii//t+GeXNDiTB1KjTWWCMlsSSHCwFP0fFm/IyuGCIN6ORBhheCLQ/CqL/84G3JxIsIyIvhcebTnYhM8acNIhFZK14BVrSwIQwjxJSHETiHEM9l/F7ocrzX+3A4CG0GwJ5Na98w20qDxKxeTDDaK5TqUt81l7XfYmxkb3u8fRQ9qDueA8W81JVUheJYIKRttIhwugucsL1UclG/2a0vwYZ/h36NFhPkQvI1V2UNH3f5VSvntfA5kOx/ZUZSnZhmskjBnf8fIRSUG0wCUu/B+hyKwar20AsNYu2yJbNBMI835GmYiNDge7wRfikSYD8GzsTooXU01WPRFExHqPgsn+FJUusF2YptqZaEwCjUJhv2ZM0Rh1bPpMn+vXszcb5sL7xdPN34yW2MufbTtm4kwetwoE2EZEbzJXAhe9VlWRGhwrKcjNJSsF1c+US/bJCeWCG0JXtlYTgRvIkLVyokwrhFCPCeEuF0IMdnlQO8EERe+gGxJXffsY+lTzmBNnVpYNmhqPrgANVKSRKj4UK0QgqesoHqZiFD1GUeEiIBJ7EgRYT4ET5m10tVDtR4ste1qsAjVy4CtTGXrVjKEIYR4QAixkfh3MYAfAJgPYAWA3QC+Y/DzYSHEWiHE2tbWVgDUhee6P5Ut0R2FHrzsvoblxRmTVQQ4c6yR0k3kYtlISpIIh4ngOZ8F1UspTzVbgteOi4YWKj8XX3ysiq/gd3EJPredOQeRPxgipOrFECFZRgwRhnHh8tQYylXpmknbLnmkrGTuYUgpz7bBCSF+DOA+g58fAfgRAKxatco7BdygYjUXmd3ODgDqb/7Ca43fct4yskNxrPqkI6AaSRkR4TARPBsrUy+T5erFl8dOWxSZCEed4BGHhYa1GaxGmwjLSemq242xxkxlh61kFIbJhBCHhP68BMBGl+Ml6IvCDWx2c8f+/mhHMTfo+E6dG1jtsLZECA5bDkQ4TATPEiF5ZMz1UjK70STCUSf4itLlSaBApRtnNkpXKj5dlG7JKIwY+2chxAp4dd0G4O9dDmZfPcw0KLcGjQiWzlgJrKH8AGCBJT+KRMUAndxA+C1FIlR92GBtYzVmaw5EaLVjhIhw1AneQIRU+ZTbkiRCB4JXy1NjjfiNUboa1kSEIRznw0XpqlYWhCGlfE9Bx4NupGynIht0FEvLxbivfIXB5o/3qHOnTk9smohIxWo+S48InQgeNNblKefc/tIhwlImeH+f+tuGYMuKCA2Jie2UL+2LJsLc3uhxpuuVwxWHCFUriympQk1K/aT723WwOrDTWLKRxmUK2mBpaNBQsYRjDTdGidClXhwRUqqhnIiwlAkeUWIJbyexZUKELMEzfcFFEYatVIhwrC2rzdu8ixnf+Ugs5zOQgBYNGgSWcewyd+syx1pORFgIwcc+iKVgy4YIHQmeskLrxRmrXsudCB2mfD0/+rhRVkRIYFUbH4QhJdmh+EYSwgoaSw+s9ADkg+0adG5/OF4+swuXH41Nw5YLERI4zlTsWCVCl3ohJlbVrSmzVPvCaBNhSU/5kgpD9Vl6ROhyD2N8EAbAXEybxk9juZNrZv9wDHavX/YP5NZ+IwIbI0SoxKrGppo6WFNWykRYdIJnyqecsfViyYXGjgQRlvyUL4EtCyJkW5du44Iw9GmL7OZCGn8wWCoDgGGwDJupkXr7lcGCG6/HIhEqTmOJUOkkFLYUibCYBB82JyIkjo9gS4kIUTjB5/Zb1EvZOFaIUB3j9Oh4GxeEwb56uAAs/fEg7sPzTOczDUAWDapUiDDf1y9zRKjVK44Iw1jQ2JIkQgeCj7N8iRAobSJ0qVfY4slFj5dyWy5E6PbcClOveL4YJ4ShMSotFymsy9ssPRIwsL+SNdMDhb6Nl6ylQoQhLEeEHJbw6+3TO59pYAv7JLGlSISKD9XveCBC13qZzGo6hjtfJUyEo3nvU7XxQxhEg+awdOMncNA7tW1HRYzCiEAN2GITIatwrGWwfUc1EmEYN0aI0IXgvf0WWWC5E2FMvYii2G1aXzSIkVIjwkIJXo3RP7DQe5+qjQ/CgN3DXbn9OqNYzR2zAzsxqDA+wr7isMNChKEyY8unymXOARVj3LRcNIIxQIQMwVNmS5rlRoQclrN8iZCzUiFCl3MQtjgiVLGUuRChauODMLSBNTuoMOxLYdVLor6Txv9tPuk2jd8fABS/TKcuOhGS9TITYbSMGCJU524JzFglQs2nX56BtHLFlx8RFvLxnrFChFy9CAf6JoZcbBWhIVhrIlTN6tUgQogpFrCMlLLdxt9Im3oejJkC7E4mNai4yGCv8Wd0LDUAgCO34hNhbn8Ua3z9skKEUq8WrbJKnghtyI0geBarJgIEKBx/mRChC8GrwY5VIoxbqpo3ETJ+h3NqNGy275Lalf1nOgtJAIdZ+htR8xo0cYIcGr/WUYlGCuYCgWrQbAbE+LWQoUUlQgVLDiokucUQoep3hIiQJO0YItQ6H0mEjF+OCJVEIOxDtbIhQobgKeNIc6wRYc5HcYkQ4PuMHk7hRKiaLWFsllIeawIIIdZb+hoFY1Y7kEjL10oTo6VgGMP1dR8alsD52OEiQnVkM2ZAoW1xRBixkSRCjrBMI1AESxOhWm7g16JTjxUiVHGqDxsrJyLk72GMUSIMme09jJOKhBkVYwdLjn3JgZVOxbXB0jBQaDKUKp8chJlld8NJhKpfYyMtAyKk5VDRiFB9PUkpE6HWDk3kovotIyIkk7cCiNDluxRqebm/y4sIVbMiDCllfzEwo2USTAZkgWU7qr9fwRpvSKnsT5XviK0QoR0RcoOleVCxJ8KwlToRRmKNzVgrRKj7GL9EGEsYQohzhBA/zn7ACEKID1t7LxHjXrbFn/j4Tp1r0BaDCnQs5TOCVTJxtvNViNCKCKlyOCIM9kd+j08ipAZ3ClsKRGiTtef2V4hQ9xEvMWzuYXwMwPsAfD67WmqFxTElZdpgaZDMgPIxd9BYbgUDPagRWMG8RIw4nn9qtUKE1kRIjz9jhgj18otDhJHjSpwIo7FWiLAYRKiazZRUq5SyXUr5TwDOBXC8xTElZd4NqZwZMwUVGzuwRrGmgTVsggmAGixtB9YKERquV6AExiYRhq1ChBUiVH+r2OF8l9T9nlPRIqW8EcDPLI4pKfPGFOIEMViqo5I+CWwxOqpapi22QoRBBOzAUiHCChG6YMc7EaoWSxhSynuzP2/P/n2rhd+SMveXiIU7H42lViWQvcZDa1i+80UfqvHRbKeuEGGFCFW/Y4AIg/0VIhxVIlTN5dUg3BhTFmbD/iQWNFZKBRDGShqrd1QmUyHj4TpquPwKEVaIcGwQ4VidGg32lwkRquZCGDb+StKcOirsOqrqy4R1Gqxg31E1n+OQCMP7/fIpbLkRoRqeKxGS2CIQIefXtn+p8bkSIVk+V4YDEXJ+R4oIyfKLQIScX1siVG1cKAytU5syVqmwNIPNdb7woCLMWDWrYDPL6Kk2Y0M4pbwIFnYdVfVlwpYCEWrr30FjTUSo+6RisCdCzpwUIdT24kCEjM/CidCQCdsqQpk/EZp8qlgXIgz7MGGHiwi97TS5kWVYEqG3PR5rJsKouRDGZxywJWX6hedHS/5d8UymEMYGbuOzCsDwwjFtYOU/tjSSREj5VPe7EiHndySIMFeeer30+JyIkFFOms9hIkLuxBZOhEX44h7U9mJPhHyCURgRGqeERoAIXe9LkH4pRQjmHDgSYdisCUNKudEWW2rG3uShsFAuSuzAqkENCiMaA/eVLe3CWyuM4SHCUGg0Nk8iZEJ1JsJI6S5EGJsF5kmEhM/wPvW3aU46Llaz39IkQi7uKI4AOBIhh7UlQq34GCKMHGeYDgr78suwJUKqLG+bPREGO5WfFnxh/fLBrGOxCsDnAByePdarq5THuPgZaXN6d4o6ADFYLlOwxrKxEh1VDysox4UINafEdlNW4zV2oWMRxVoTIaOcNJ8xREhOC9ooQh+rhVqgIjSRi4siVHySscYQYbg4jggpG04itJ064f1GrznVvzifLkSov+7D4Fe5L5DbzvydLxESPn2sLRFGe7F+nU3mRBgA/gvAJwFsAAyv7iwxU8a5kAxmGhQhmdUGxX3oyEPSWCgdlZf3aqZgyoDsiZBUQw7kpg+sPJYonuyo/MAaxVHlk9tKmAi9xCWKixQYiZcmQsqnFqsTEfIqz4UIo0DfB40liZBTefkSIRUXdFwcVsVxprbvXJ8pnAgjxzFTiIB+XU1ESJnNOXAljFYp5e8cjxl10xk1t13DcnPHFgNrzgcdR9SvYe7YMgNTO/XwEWEuNgqbNxFqpefKKRciVHH+3zYDqxMRBj7U66XHEEeEShRsWU5ESJGbDRFyBJ8HEUZiNV0Dl8RF32w3PVxMIrRRGHBUhJbKSTVXwviiEOI/APwVwIC/UUp5l6OfETebqSOAIJeYjJUrg8LqGWt8+YFfm0Ya8qFj8yfCuFUU+RKh6UNDKs6vg47liFAtPx8ihIaNK98rw0CEFtfAd2x1L42IL5YIw25NyinPgZU7V1RM7BSiAxHS5Zq/YqfGUPiikvw/0Rr3pLXtvTTtONvrZfChmithvA/AIgDVyE1JSQClTRhSYXTDBdI7tQi2a07B+NUGYQIrTOUrAxCHhV1WY8QS5XPGzseqsXJZDeWTIRfo/dSKCMOeqb9ciFCNmFVODkRIrxCyIEImBhciVPeH/VLla8cx23lVTDt2IUK1fBLLJmQMEap+rQdWg3LSYo0hQqX8HDakCMkpxJFdXamaK2Esl1Ie7XjMqBt7gsgLz2QKLhdem+bRYzK9E0Zr0AwWEhCJKC67WYdaE2F2P3EOqFg9X4hgWXIjiJBUToRPLlYNCxqbDxHaKifSZ5GJMO77CmEb6XtpLotKnImQVBi6Tw2rF50rXxtYLfuMaWC1JELVVzjWUiRC1VyewwCAx4UQSxyPGXXjLjyLDf0dK++pC88NQOGNzMCqA02DsNKpi0CEgXKKhMMop2Bgjaos9uVsyjauXmrncyJCtqPqW0ztwCtXidWCsAK/lljOXIlwVO+lqURoUk6WRBiOT/NbzkQYig/K75IkQsVcFcapAK4SQrwK7x6GAFAGy2rtLqaPpXoqP80SPwSwF96C/X0smykUmwip7DpGOdkQITt3zKqsiHTKlmdBhI7kRmKHaQpRU4Qm5VRApx7xe2mqz9B2a6zFYBnsK0Ei1MrnFCE5hVi6RKiaK2Gc74gvCdMeFjLNXUuVXLiL6fsK+w1ckOWrjYSXq8SFJ3BqVlEMIqTKiWtQtkRorZwKIUKGXPSu50aExZhCVInQqJwsiTBQhGVChOH9ESxRvuk4CjuqRCjVJdPR2MI+gzI1H4RjBetKhKw5EGHYrKakhBD/KIQ4HsBOKeVr6j+HMOPKuUIIsUkIkck+JBje9xkhxMtCiBeFEOe5+HUbWOmHddRrZFz2xw1WSgw2kj0Wa5Gp+EE4EaGS1YTrEXJJYF2WaRo6dZ5E6KScGL/kNI9hYM2XCI3KyZYImcESGGkipNqWbioRlTQRgiE3rh0Sx40mEXrbLdpWyEec2SqM2QBuAbBICPEcgNUAHgOwRkp5wNKHjW0EcCmAfw9vzN43eQeApQBmAXhACLFQSpm2caqeYJO8L87UjQrWy+HvSxAX3oQtlAgJnLqfX/FBYU1EaKmcCiBClylEJyKkgNEiI39bEaFJOSmO2XZI+CppIlSIqJSJEBy56UhdFTsQIWcuREj5tFZOMX0mbFaEIb3Ps0IIUQNgFYCTAbwfwI+FEO1SyqLcCJdSbs6Wo+66GMCvpJQDAF4VQrwM4AQAa6z8grnwVp2ayWqCv/ULz2dAIb9c+TY0z2BdiDAUHOmT7qjGQyNYqhhr5WTwo2PV50sY5VQoEZrILV8iDLYT4FB8YTBLAqNIhOEy1d+qaW1WiQ3K3yNFhGSsGKHVlZxyohJNjgiJ/m09hWggQtVcV0nVA2gGMDH7bxeAJxx95GOHAng99PeO7DbNhBAfFkKsFUKsbW1t9Taq84tMpuJB6XfFcwOQUra/U/Gp7Ic/qMQ3PIDv1AURYWg7HSvhg+nVKtaasEydOgqjyyf8slOIhRIh7MnNFhurnMqFCENleuX7PmgsJeFtiJAz7nrZEiEH5RIyMga1HXI4wpdpPNJ8GchNP85uCtHiFAdmpTCEED+CNx3UBY8gVgO4WUp50L6owNcDAGYSuz4nc5+D1Q4jttHkKeWPAPwIAFatWiV9oO1NJnZgtchqcmNV/IU3KQw9U2DeH1MQETJZTSgPVbHaIExJVTo3UQAAIABJREFUZsKnj82bCE3KCdw1UHAFEqFxOkbdWAwiVDyUNBFKdbozhggj5OJAhFy9fCJU2iyXMVPtsNj30iLbI7ES8TD7uDbropzYNkv2g3iNYXsP4zAAtQC2ANgJL8NvtzxWDersPA7bAWBO6O/Z8NSNZZlMFuqAZRsfhdUGVqJcYddI/TJssVT5FDZ2PtiCCOnByuWLe5ZEaFBO4f2+TwpbCkSo+TQRIZOxjhQRhssMb+BImzrO6V6aDREyyknzBTO56ceN3L203GKZ+HaQa7GKerNUTtZE6KAwrKakpJTnAzgewLezmz4B4CkhxJ+FEF+2Ly5v+x2AdwghaoUQRwA4EsCTtgfzSxTZXh3+g8SS00xBeaCxRGalxUqkKoIjl0KIUIlNtXyJ0IXcXBs0q5zKhAjVJLAo99LyIMJIrFz5ks7EGX6P4opIhDZ+SeVkILe8pxAJfzms3b20cHwatkTvpYXN+jkM6UW/UQjRDqAj++8ieDefv2jrx2RCiEsA3ApgGoD7hRDPSCnPk1JuEkL8BsDzAFIAPm67QsqL3XIADKQtgVV9gsIyF56R1zRhUctq3d4SakOEvLyP1sXzG4NVMituAMqXCNXyItsUr6VMhLAkNw9qeS/NQIRE8VlslFzYtqVs41b2SNWnAxFyRr9HCbRfg8qijrVWTkwbGlf30hSzvYdxHbyVUacAGEJ2SS2A2+F9G6MoJqW8G8DdzL6vA/h6fn65zFLHAUzn4y48OQAw2NA2QeCCWJVtrgrDhghZ5VQoEfLDVf5EGKOcIj5LmQj1TZHyVKzt/Lkege+DyW6V33y9LH0Ow700KtpSvpcW3h+O2maMUfdFAlD9GsjNlggJGF0+YbYKYy6A3wK4Xkq52/KYkjF1COTlfXa/xbwll4Wa/EK98BwJUI1J31QYEcYOrA5YRLFOy/5slEAxphDzIMJoPDxrWRMhl4USZnsvzTh1Y6GcWCIk4nNRWVxsenbrb7dXTqV4L00C9LjBkNuoEqF0I8Kw2T6HcYMNrlRNm+f2t2sNj8qY/X26T2+/3vq1xkdgjdm1lrHyn1q0IcJwmbnfESdQ/8ybCHWXwbF5E6GDcioqEWoET0ZrrwgLmEKMJcI8lVPlXpo9NlY5jSIRqjgTVt0St6gkbLavBnm6GJjRNKeG54BVB8voTsVvngrDpyEda0mEZPmMciqUCE2DpS0RKoOVk3ICDc6HCNWBrShEGPZZTCKMYOPIJep3uO6lsWaR3ZbCFKKOjJYX2cYcVwwiVI9zGTfoS2s/haia7ZTU4uwrQTgT8B7kK0nTM1Z6CKYHoBhsaJvz1A0VK/RGaj114zIAgcESjt0GYYcv7lFOQWV2dAaUG9gJlVUEIrSdQlTNRIR5TyGCAYfiU39btUPGpcsUIjl/Dl45CeKvkryXJhXCclFOeRAh5VMrl03IdE9cvJTKCpdnMlvCWGSBsV61NNJGZbfeDq7hERkQc0fK6uVoUscCpkGFyIB0qD0RKnUJ/9Zj9aMjsET5FJaf440aPwBFN7LKyWUKUS8mfhDOdwqRcap26nyIkPbpeA6IdqD5dVVOVm2LVjiU37ymEBHFFnovTXt4sohTiJRxe+ynEO22u0whqmZ7D+M1e5elZ2R2SwzCJoZ1UxhqI+Gw9ACkmvUj/mpwaqwUuRFeWSwzAERiNZKbHRF6ZUZxZPkuWALMDkDK/iBWC9VgxuZ/Lw1x2DynEEObtXJspxCze7VfNv3LTb3SfrhkgG1bLkRIHDfuphBD5vouqbI0SoIJ8ARhlS1RWDBYKlviyrckN9+vFRFSJMQqp1x8GpYjQgvlRJdheJGajXIiz6ttfm8iQuhY7hooOBOW8kmWT2FhxlamEAEVymfXdkQ4HFOIXDJi9BuOlcAFsSrbijWFGLbxQRiSyZa0RprdR0pAC2xcxqpg2QHIktxssXkpJxciDJdvUE7WRDgMU4ikymISq4KnEAskQiq+Up9CJMmtGFOILoOw5RSiarYpRjGmEHP71fItzwHbZh2Vk0XbosyJMIQQ37LZVmomAa31kwMrIwFBYcnGz0hLKgNiBxVisBSmjxLZy0kn5eRChPkqJwY7LFOIoTJ1LKOclPI5IlSN7dQlMoWokiY/qKhJFk9uKo4sP4jPAksUxLVDdX8Qq0vb4oiQVBjxRIg4bBlMIVLmqjDOIbZd4Ohj5I2TayrMJVuDjgXT+FVfXPm+X3pgpclF55YiKScHIrRWTpZE6KKytFhdroFfHpe150mE2c36NlsidJhCNLdZmggVz2U3hUiVr2GN7TBqJjFgQ24kVoktXL4KjlVOaqI5QlOIlNm+GuSjAD4GYJ6yvLYJ3mtCStq8E6SwL9FRuAsEGDIg6sKr5VMNmvDpY20bNNn4qVjzUE6aUybe8H7vJ6+cqMNsVdZYnkLUcPkoJxciDJdvUE6lNoXIuC14CtGLjcOGPHJEGOwPY7lY/egILFE+hR2pKUTKbJfV/jeAPwD4BoAbQ9u7ZHE/0Tospp4gAICwk4t8tkZhGXIhOwq38okiN1N2qw6sxVdOhgQs4osr3/dLDUCUSaLQYhFhKU4hFqKc8iLCPJWTMcmxUU4ORBguM+zTw9LKyZYI9TIcVyGqOILcRnoVouozDqviqPIps11W67+d9u+EEMsBnJbd9QiA0icMMJmdlcLI7mN6n90cZ3S/Wl4US78l1OZ12V4Zw6CcOCIsVDkx2MoUou/HRjm5E6GtctJsBKcQ81JO+RKhcRCmfNDJI3VcMaYQbZWTFkOBU4iUud70vg7AfwGYnv33CyHEtS4+RsO4aR4n9lV9+vsprE3jF4RTf5N1Zke2kuIrJ8Rg81VOJiKsTCE6DayaUybe8H7vp71yMhHhmJxCHAbllBcRKuVbKyf2HNhNIVJm/T2MrH0QwIlSyh4vIPEteK85v9XRz4ga/SZHvaPQ86ZctqZj4+YitfLpYO3nIkE3/qIrJ26wKlQ5UeUzWIoIc7vyJMJRmELUYi9UOTHkZrLRmkLkyid9FmEKkfPrtPiCJE06Zpc+Qx1no3KclBODtSVCylxXSQlEXwGSRnz7HHVjFQY3WCo40ieVBXINmhysmGyNIzcqq7BUTi6N1KicOGy+yqlQIiQHFX8fHazLFCIVF2X6NRhB5UQ02pKdQgz6AV2e4lLHxigntc2wD6WSAyutnPRjizSFSGD1cYPw60DwxZpCDJurwvgpgCeEEP5Hjt4G4CeOPkbcpJcqRIwa12gSCPkgzCkLVDMFJl4yuyYHVjvllBss81ROcVil8Vsrp0KJkCqHMSMRWgxWLBFS9yUInz7WRjm5TCGCvAY0dtSnEKl+ENNnoPQZyriEiFcNOpb0SxRKXVuXKUSyzBiVpSonlylEzq/NFCJlToQhpbxZCPEQgFOz8bxPSrnexcdomc1DLfRUQHaw5LIK4qrYMDWbXXPSkvBhq5zoN3/ScRkbvyXWVjkVSoT5TAu6YaPlU8YNQCM2hUhhOSIk2jdRfBZb/ClEqpw45eQ0hWgVK0VuBSonctwIXKguNazqR7V8pxA9nxaZLhMPZa4KA1LKpwGU9LcvVFOf2AT8QZiRgJHs2vcBEguiQbMyNHLhTdm1Sm6AzGhQe+XEKJzwPg2rF2c3H0uU72PJAcgWSw3CZF9g1FCBU4hsceQAVBpTiESo2v5iTCFSZZJEmI9yotosm7zZKSc99sriCypWypwIQwhRB+8BvlOz5T4K4AdSyn4XPyNt5AmiMnFyYPf3WWDBYf39USLis2s1VAEJgjEUn148hgat4PzySKzQscyQSSgMHcPeaKOrZUeELsrJJQukBiuDctKsQOVU6BSi4kbHFjCFyECtBisX5UQP7DRW9WXyUVl8ATrJYZSLaq4K42cAupBbFfV3AH4O4ApHPyNq3DSPhiO2cQ/gmDI7Fqv0fy671mJgB2FL5SSJhseUl2uM9li18dt/N4ImQlplWc6Jc7Fqpeh+TDaSyqngKUQXlWUgQpqEGOXkQFhhiyVtG6yyP/hdoHKS0M+7UTlZqIa8lBPnSzG9bdl9otU71u4VMa6EcZSUcnno7/8TQjzr6GPEjX8xV/wFymU18VlgnAyN8gXNGFxmxSQKdsop5AfKbyesWj7T+J0UBpct2hBhaF/uOEY5MdOCUU98DMVQTrZTiGT5YR+qTzBtlipfLYMpnyI3k3LSoQUqJyq7jlNZBSin4Vp8Yaf2zVjNJ1mOHmyxlFPYXJfVrhdCvCEoQ4gTUQ7vkuI6tYqj6D/Yx2AVn9Q+7h06ttma7RObHlY3lrBAND4T1qLxs8qJ2MYSIdeg2czOQg1piOFWTgwJuSgnBeeXFy3f36+XZaWcnEmbLqfYyonazyuMApWTgQhdFl9QcfNJlnDAKn45NUTEUIhyosz25YMbsu6qAbxXCLE9u+swAM/b+BhN404QdxOVbNBWqiG6Lw5Ld1Tq1SDcIGypnAgi5JST8QVxnGRWs0A2E7ckQjANmsCF44vEyl3bUVROw7L4gppCZBptZfEFQ24MliqfvLZ5Kacwksaq+/3fnHKijitEOVFmOyV1Ufb/RnikAQADAPosjy8BIwZWi2zNZVmt6zQP26Ats0Vb5UQRoRqbWo4VETIqi86uHYiQzNgspxAZ5UQvvRxh5aT69P2yyinq0xir0yAcJSI+u1ZDHV+LLzgi1HAOyslJjYyycqLMljB2AfgXAO8BsA3eVNZ0ALdKKb8phDi2lJ/H4KZubDsUKCx0bJBVsA1ayRRss2sxfC99Y5WTzWDlpJwciJBUTnyHslJOlBoaaeXEtEMNR2xj35pKXQN2AIru9w+0J+0ClZPLFCKhnDgrxhQidRYolQUC6aSclP2UH+5v/7hClZPtFCJltoTxHQANAOZKKbu8AkQzgG8LIX4A4HwAR1j6GgWzy26dHlpzyAKpK2Gev1cbNO3D2+SgnIhpC7u5dpcs0F45sURoObC6KCfKT5xyUgfhQpWT55PKxOOVU640OlaqDJa4DfFw5XixFqacwn7U38VQTkrxbomL1YRM4cqJiqFUl61TZksYFwI4UoZatpSyU3gfVtqPEv/qHj3NY3mzMWbaIuqRKR/2SoBWGNzFZDI7G9Wg7AuXr2FjiNBaOdkSIZhO7RBrUZSTcr5sOyrl0wvJ7qNEI6mcskAy/uFSTmT/YsDjQTnFYUdr2TpltqukMpJoKVLKNIBWKeXjln5GxcjBSvh7orjcvuhvu3sYDLkQEpCb5GSlJdepCbesciKK55STjTlloVTnM3ZqC+UUDCrxyolSWfHKKToIs9l1gcpJJ+JwdOSuiE8VO9LKyXXZuhURBmo/moxE/Ch+NSJiEzJ9LChEObkkWeYxRsEWmLiYppmsFDxhtoTxvBDivXqh4t0ANlv6GDVjMwUbRg/2aV55rDYAUTeZomVGvGoN2vTqAnWr7QNuZuVEqRGtfNsBEHTn47DWyomaQgzFFo2VwMYop2j5ji99Y5STFREq8UV+FzJYDZdy4gYrFWeY9LAiQi55o8iFIUJ6+qo0lq0z0OheA7mpxuSkbFJYzJcPfhzAXUKI9wNYl43veAD1AC6x9DFqRg5WVKZAXSEX9jd0VKr8YJ8IY11fXeCgnCAUHK+coj45cqGel+CVE+W3GO9cslJOREwsEVJYJ4VhUk56DHzGHK+ccn5GTzn5fqLx2CknflAjyjDs0/yyuOIrp4gj5aeNcgr2ceNRuAiOMTifBM5WOVFm+4nWnQBOFEKcCWBptrw/SCn/anP8aBs7H8t2vigucBL26e+3kZagOhSTgVBY5mLSfvnsWsWBwDopJ/K85soM7yOVkxZVDmujnII9NsqJJHgea6uc/H12WLd7GONBOWk7DVgn5WQgouFSThbVGlblpLfDwpQTZa6vN38QwIMux5SC0R9CMTU8KhNnsJGB1R+AiIGVVAI+VihYLVp+TlxFjqByUl2q2DjlxPkcDuXkRISuysl2CpG7tqzC0IsvVDlZqyEXrCXBOt1zIqaHXZRTeLu6zfqeE4UF0WZNhGVDbso+DRtXfrYg+2vrqJxC5vpqkLI0rlPZZArsxSSyQHYQhj5SMO0J5P0OQZOet6+inODS+SwzVpd7TrYKg1ZONE6LtVjKyTZWBywsp3mclFPID5TfI6WcohH6MfDKScVRZuoXVgraQNpkeQUoJ8pKijCEEFcIITYJITJCiFWh7XOFEH1CiGey/37o5Jg8QbZfBONVA2BHLgRfuN3vAG2lr5xUrBZtUZRTBBuTiVsTIVF+uMxcDExmV4hyIrLrYiknzUwM5qCciIMLUk60R9pKUTnlyiuucjK+Yr7Yyokw5w8oDbNtBHApgH8n9r0ipVyRj1NvALC4mNn/yQyI8KlhGR3KXUwyBo79XTJxDVdeykm9/+H5NSgnqkMxBK/6pIweKHjlRHkuSkcdYeWk3nMqRDkZpxAryilv5eRtLkw5eZvskgHVSoowpJSbAV7OFeCXbtBEtggwmR2DDZ94vlPrFxMclppf5AZLMsMfA8qJ2Ga8N0OVr/mkMjvfD6HUjMopNLCyaojuqKWsnLR7ToUoJx02rMpJf48Sn4m7KCfdTfkrp3B84RhsFEZJTUnF2BFCiPVCiL8JIU7jQEKIDwsh1goh1ra2tgLgO4pV54vJLK06KqMaKJNEsC4Kw9te3sqJnEIkY3VQTgRpDptyAm3DqZyspxAdlJNeD3vlRISa+3sYlJMeqb+PSgb0v7n+pR07jpQTZSOuMIQQDwCYSez6nJTyXuaw3QAOk1K2CSFWArhHCLFUStmpAqWUPwLwIwBYtWqV9LbRHcXmvfa5fmqTiTMXHtTFdMByWYWkL3zZKyclVi/eApVT4DdcBh1rocqJM1flZJOxmqYQ9fK5eyi0cqJjzV85keFVlFPJKifKRpwwpJRn53HMALzXqUNKuU4I8QqAhQDWWh3PzZ8TSG+ffuEpnxyWzuyYjqqN7oBQdJ/bm20ryomOVR9YS105qTi/PLV8zshdFeU0ZpRT3PUpVDlRVhZTUkKIaUKIZPb3PABHAthqe7ytXHOZvzdi1fJdBgAiCwSrMPRtFeUUrYduo6ecpBKrF29FOVE+iquc9Bj0WMtPOUVjLb5yoqykCEMIcYkQYgeAkwDcL4T4U3bXGwE8J7zvh/8WwEeklAds/XpyTSvLaf7e5uWDTLLENrxwmREslQWSmUKZKSciCxwp5WTM7AjscCgnzs94U05kvSrKiSh/dJUTZaW2SupuAHcT2+8EcGf+jonMDqbs2iILBYWlO1/EkYolMkaqU3MKY7SVE1U+6RcSQs1PDMqJ7KgFKCc1Pt8nHWtFOQ3nPScV58cWLd/3Gy6D8VPuyinwo5dY6D0nylyVU9hKSmEMl1HfIaAGKzIDYi68uj/ym+yo9HH0mBdPbsGxo6yctNiLpJwovxXlVJrKic1Yx5lyUnF+eWr5HJj0W4By8soj2qGjcgrb+CAMJhPXB/bQvgDHZJZkNpDdp5YPfQBSywz7tRlUfMcV5VQKyknv1RXlhHGnnErtnhOnpGyVE2XjgzDADVbx2TWXWRqzdupiMhkQkbBqRg2WfkwV5VRRThy2nJWTGl80VsVvRTm5KSfKLxErZeODMIgMhMxYSf73fagbskiqo2oX3pCxkheeyGqoYaWinLL79CyUcElgC1dOwMgqJ8onhx1J5aSaq3LifJa7cuJtFJUT1b8I5UTZ+CAM2LGvSWHoPv1GEsIqfsJ+2czOqvHbZ0C2yomzcldO4diif/MqqxDl5F2v4VdOudjov4utnKjyTcop39V6udj0JEvF5qOcqBBclJNqtsopHBtl5aCcKBsfhEFmdm6vAWezW5sLD6p8GgsiEwd34QtQTqapCG9/mSonwzVQrayUEzcVAQKbh3LSQmWSgaIrJyeFkd2nYg0DHX1D2l452ZALp7DIWAtUTiZzUU7asYRyomxcEAYA7cqb5/eorCaKoToqggtPDZZ0GXbfV2A6NSi/dllNOLaoz/JRTmqZnk+68+WIMOqTjNWknGi3USxVPuyVU67MqE861sKUk+onF+vIKCdT21KxJuXEJi5E+x4R5cSpIUflpJqRXByUky25qDbmCSM3v0js07DQsGxW4yTv9UtkkqGUX+snUQnllFdmVw7KSYb3qrE6dFQL5RTaqcVQdOVEkfYwKSe+HRZfOeX2jYByMvSvYisnKoRiKSenRQpFVk6UjQPC8P4nGwnXUW2yUAqb26nFQGY1jF/qSVT2UuarnDg1RB9JYx2Vk+61MOXkdg+DKp/Hck8DcwObii32PafhUk5qmYrbaKxU+bBXTnS9mPILvedkaN9FV05O9dKxpaKcbGzsE0b2f/rdKfEdNefHJmtnsiXiwsMBSw6WhSonQyP1sFQmTpVkr5zoeo2Qcgr8xMeq4iJYomL6tR155UTGSu3TsPRJoJVuaSonP7bo34xfZv7eRTkRsOw+e+UU9Vkc5aQd6qCcuNhUG/uEQWQq/t829yU44iX6tDv7RxzljiXloiW5WSsnungn5USVz9moKyfyfBmyUE4RKmXT2JFXTtFzwGCZaxAuMxprPLnlsNFt9Eoof1/Yp1k5UT5t5u/VMo2xUuWDUU6wa1uxyolIBiz4wqycyHpZKiciVsrGPmFk/yezWxVLpKymzNKDElkgeeEtMyAiWltyyx1p0aAN0xZqBC7Kie8ow6ecVJ9k+TBcL9Kveg14Ihou5aT6pMxFOXGxkmUWqJy88u3rxd9zssCS9SpcOQFEO6TGDaPKU7HR/WQZQaymexgElho3GN/kcxgMNmxjnzC4TBzE8rhgXwgXDJagsVS2RMTAZaHUgGlzszEf5RQt39/HSGarbIkYyEzkMlzKKeJTqYfBL6+cmE/6Un6LoJxYaOR36SonvXw6Y3V5MLYklBPZZsGSEH29VKd6OdyuYignriBbNaLa2CeMIFOJZ1+qkWo7Vazi09tHNFLFncs8M0ANljTWSC42asgBSz9dqgQY+XMUlZMaXxg7AspJ9aP6oP62W95dAspJ88qpx2h86m/Vpx4tgx0u5QQuE7dph74PRrnYtNkClRO3nVwFaFAjYRv7hMF1XCJj5U5ZQgAZQgn4fuK8eJkKkwFZZO2CSGvyUU6gGikTe97KySSZLZST6ieC5UiAUkMWaeDIKidaEYbrkfu7vJSTJNLbQh+MVeMzxzo8yolssyhQOREJrGlariDlxEy10VPmsGKMMU8YvlEXPmOhGgAgQWUV0LEJNrslVISpoyoRkISVj3LSotCDLVg5cVKcLJ968yelRQpXTpRyGVHlFJxXolNbZeL8eVUjMD2lPlLKyawwLK4Beb54NaTF46CcOKOqWrByovqXsk/FquWz+4i/WeWkJQ6V15sD4DtqwpDpUVmYrjB0LDewknOGpgZtoRo4oxsJTS7Dopy4bMlWOSl+AmyBykmNz/dJYYdDOfH10r26KCfqHOT2xQ+sxVJOlBWknII2q4VK5cxQTwCPZZIsaqqNJNgCXymkxGeKlU7IaCyIdshOtUm75d2UjX3CIBoe4KkBXmFYZIHQsb7C0NWAQTJbYBMm1UBmCgwWFLa4ysknYkoRuTyDwGXJJNa004A1KSfViqWcNCSZsdorJ/KeE2isy/JuZW8kBqJ4uh0WoJxMmTg122jfv+j3n7FjJUkuHNSlzdopJy7R1PxCb4fFeqVQ2MY+YbCDJZDJqFiOXKiLqTv2B0sqC9MVDtdRqOVxAhl1BPb3EcrJJqvJYdXydayTcnJo/AmK3JiuS6khTjkZp69slZOyrWjKifDLqREb5WTMWKmB1TITpwYV0mcQqp4MFFs5Fe3BWIvBctgejC1QOanxqTGErVjKKWxjnzCy/9vM2bGdGvwaZerCWymMAEvEQDVopVxTZmetnCDIWFVsImawUmMNlxnG0lN98Q3fw9orp4RREdrEarjZSCoMF+WkH8u/rZYwG+XETbUx5RNuwb3inSdiAstdS0I5aTZMykkSHWxEH4wl2w8DJstn/DJt1kU52djYJwyi4Xl/8/cl1J6SENAyfDqrMGTXSly56Ssia1ewgpriIOaD/VjZbIkkonjlxJIbOX9vr5yogV0tMxKrpXISZKw6NiGYbk3ExJOm7T0MWuEMh3Jip9oclFN4X2iLFRHHxUoxIeeXjNWGtA3KifJbkHIi2tZYWN5N2ZgnDN/I6RBtAGLIRVCZONFR/X1kdu0yFaAPKnYPbPmqwU452Q7YCaajSujnKncPI145kThGDZGqwYRVyqEGABdF6B9GJQ5WbYvrjESsSpGRv12UE3kfyVI5cVMcNoOl57fAB2OpQZhTTsQ1cFoqW6ByIkko2Mc2Wh1LkQDD8COxvJuyMU8Y3ElIJIhOwcpQ+gIB0cafYC8mJe85NUJPBdhMHQWxWionbo5Th9JqiBssw/HxPrNYloj1YymFQ2IFjw0HYbyPxNRLNYo0KfUaji3q1z4ZIJd3G7Pt+CHAOMVBJANFWd5tcXOEuofAKifobYtxq/n0t9hm4nToeqJpmpq1x47u8m7Kxj5hMI200Ew8wEZkqPe/djOdiMuYtRMDBTsAWsVKK6cEpZyI80UtQQ5iVbZx01eQ9KDi9CyMRXYdxGAxYPs/qXbAdVTyOmiEZbovofu1ng4xJQ5hIkxEywyD+SlEy4zVUjlR9eIuCk1E0fhMXiTTtjysRb0o5aT4MZYfOAr75BMn1W+pLu+mbMwTRqAalM0uGRA5f04MAKb7EtqgEmTtegyUGrG+8MQgzConIlb6FdScwqBejsZk7dDrRS4XDtVDDVarV2hf1C9/45+MVY2BUk7ZnsINbFG/dLbo71NjLeiGK5Xdcm2L8qmUacJS1ysXGxGrguGSAePrNogyuHOrxgoUf3n3sCxSMCRkqo3k8m7KxjxhmJ/DKC7WLO9Vn1E/EawDYalmnr+PmlGyhjNWkxpSfQZ+KHJRy+eVE71cmIkjhrn1AAAZVElEQVTVKmuniJCJFXq9ctNXhHIisPaDpWF5t+aX7/Cgrhc5NaqrzHB8JuxILu8GgTUtUuDuYdg920D3WcqGdXk3FauC4ZRTeJ/JjGNB/OHjgDBMCsMyUxCgpa1qZnlPS2Z9sOAGCmWjQQ3xK4SUTp0w3ZiMz1ipkdW0BJccLJmM3SoTdyF44hxwg6WKCxudteuExU53kpk4jdViguXX3tjsmp/iKIfl3aZ6qcapESrWQhcpFDqNytfLbZECvVKMGwuix9u+TWLsE0b2f33lkd19Cf9Ym5uYbCZOZgr+IByvLen7LXQWartO3D/WbQAi1JBWPoMlSJO86W04zyRhgZDiFGlCx/q/yak2xSWX3ZLYhOkmKkUuUYykggWzvNswheiyvJtKmvXEaXSXd7ssUjBPjcZfg3BsYTOpPLp/xQ/Y7CIFA9lRioiKtZBFCpSNfcLgGikMK2ks5HXOT3wmTl9MOoOlMgWXV4MYV91AxfJEFMEl6FZKk0C0TJNf6hpwyoleBs1jVaOn2vhBhcquAfv7ArYruowrxYgpof/f3plH2VGVCfz3vaXT2TsJSZsN0CzsIYA448iEHUEZcR1FHNcZBgcHOZyZEcWjqMNBR1zG8eiIC+oRRdwBZ5gAokBkEwxrIEQSICQkhCwkpDvpfu+bP6re61dV91bf191J5z2/3zl9ul/V927d23Xrfsv97i2/4dvYD2vXdNXV4+m6wnKOexs+6R2eVJIXP08OrDl1dTwz0TnHfXB5ecHekKe/OOvg95wScr4kBdzGayQ7+H0YfpKCo66Di7Q2/k6a4wa7LKAAa8nfSd0dD9weRma8C3Rta59DraW8OYyQuros1tqRENm8rUFc6jRkA8io3LzJ/IaB1TNY+uYlGq/ZWAenl5c65h/om0hScLXLYQzkpXdnr59jtTvr6qxqc33LoTRDjJxmkhRyFTxZ2VCvvJkkBfLGjSBD022MNF4zT3a4SQou2l9heHq002toxhJ3yTZhhfqsCnc4ZOBcoxx4LHFvTDxrsYaF2jwPqscNjuqXknU8qbkDoPNBzV7fXffQje9q5WTL9cWOnWE5l3vvbZfLCg20xHEPFI1tafzbld7tKjOq3+CGi3uw9HlDOYNwSFjOEToRx3MQyeYpeIcx4HxmUmKesUCkPZMUXH3WRfsrDG+sP8+qaMINbZD1dVKfuwi+UIBP1nX9lGxeh3ZZIL7QSYgljqvjuTu0TzbYc8obhFOyLg/DRTOx/rxdVd0DRepgzgDkHazSA5srSaFerqMfpsp1jazNJCnQhIfhUi7kyfq8EVddXX3LE+INmiBnhJIUHM+t/942lumvq99zctTB5eUFXB/yd31IyA0u0uJ4/gm5rmVK1hm+csj6O3QzL3PPDqyu7Tby6xpqsTZpibsGS4+HEbTvVMO5NE1Z4o6RLft/zSrNXG8oU5/ot9MjcgwUIXNDUbnh6d2C2xtyyTrriiUp7NEkhUwdwpIUap9GM0nBpTRd7FMKQ0Q+LyKPiciDIvILEelqOPdREVklIo+LyGtDy8y1xAMGS4jCRyEpnf4OnWexOh7qzPWziqheH0eoLYPPYg1+UH11zeIP8+SFDRrkcr2hVJmeoPjeTFJIl1m/fkrGb9mRaZjfcwpbkDhSSQpBg4q3b1mSQmiSQt46p+z3ot8hSQp5XnmaVvUwbgIOV9VFwErgowAicijwDuAw4HTgayJSDCnQ5bLHZeYMlmn9n2eJO0IBAZ00NwXXMzYl6uvzMHKsW5fS8g9sjg7tkPWt9A7Zd8rV+X3eEAw3SSEr6/eG3JalS9Z1feKHTwPa5bRYPeW62uWiGcMF/PcrzZ5KUhCn4ZIdhL2hUY913XjNxjoEPQe4cdXVY7vlz9Glrh8V4/CGPM+XO+SbZMR2Umgsc1CJvYiqLlXV/vjjXcCc+O+zgGtUdZeqrgZWAa8KKtPjsrvda79161MuCbwDkCsc47NuGwpqrCsuOY83NCIPaqNcXFdHjCHEa6iV6099zNbV5TkNK0kBh2yeN+T4vybqV69vXpJCUg48lrh/eEp+coZGs3221ZIUcncibijX771mB1b/rsnDT1LwDsKp4w7n0fnc7jM7KTA4pQCZ0eL9wI/jv2cTKZAaa+NjGUTkXOBcgK5Zr+Dy/3ksOp6WA/qryvbePvorSl+1ypadu50VcbprDm2cv0lfYId2WQ4uS9znObk8DI9sXkza2aHJyobOS7g9jKx1OxJJCvkDkMsjDLgHPksc1/8gO2DneQ3NJCmk74Lr3notcRz9Jddizcr6Y/2pz3mDcEp2zyQpJK+ZJ5uXpJCtwzB3UnDdL4/x6NIYze6kEKKwanVQTXVEB3tdYYjIzcDLHKcuUdVfxTKXAP3A1bWvOeSdt1RVrwSuBBg3e6He9eQLHDhtHIfOmpSQKxcLPL15J0dcujRTRmc55XgJPLxuG5+6/hEqVaWvojzwzFbvANjbV2FbTx/9lSr9VaW3r+KVzT4nYVagd2I0p5OkcXsYyfpBvjfki/WHWO3OhzrXYg0bgNx1zSqivZGkUEyFRrIPdTMWq3h3QnZa4q7B0te3nOGQ9PUbzyXv83B2UoCwN1o2l6TgVvDx5VIf9+JOCg7Zgfvl8IYy149+hyQp5IXS0xQKoBX3uUb2usJQ1VPyzovIe4AzgZN14D+4FpjbIDYHWDfYtQ6dOYl7LnFf7oMnzGNB9wRKBYl+igVKBWHq+A7mTZ+QkD1s1mRuevQ5fvqHtZSKA7InHTQjIVeKe/QVS1dyxdKViXPHHjgl1c7o9w/ufoqljz5Hf0Xpr1Z5sbffG4/dubtCRZX+ivLCjt3xuSTunHKfxep4UF1WaT0c43ZvXe1yv6Ew26HTl9TUucZyh5Wk4ApxxL9HOknBNWD7khTEUaZ/IjkwJo6vrlkGBqBsFVx9q3bN9CDnGiyHs5NCcwvccl7RmsKn4F2GAHiUgGfUdf2/mokg5Cm+9DV8Sit5fcdxT99yKU0X+1RISkROBz4CHK+qOxtOXQf8UES+CMwCFgD3DOda82dMYP6MCYMLAv919lFBcp3lIl85+yjWbe2hVBDKxQKlolAuFDj6gK6E7OyusXSNK3PLig2UC4W6Ipo+YQzHHjg1IVsqRjf32MtuzlxzTMobEoEXduzi8v9dESmhSpXVL+zMfA+izlepKrv7q/RVqvRXlB6HN5Q7me8Y2Gvn0tI+69YVasvUNXdeIsCyaihn4Po57Qrw8mqfQ0Jtzc235Fi3qWOusNxQkhRCd3WFqF2FVNjNVdc9laQQspNC/pqN7AFvf0mJNqVcHO1y4V+Z7zdcwoycnF0fHLIBVd23FAbwVWAMcFP8j7lLVc9T1UdE5FrgUaJQ1fmqIQ7U3ucNR84Kkps7dRzLP3FakOzfHDmL3r4oFlEuDnhE4zqKnH7YzITswu6J3PDgeq5atoZyLFcuCgu7JzBnytiEbKko3PDgem54cH3i+JhSSgnFv2974nle7O1jd6xcntiwg2kTOlKyAx1aNQrf9VerVD0dGpIddU8lKeSllQw/SSEl6zBvfYNlXpKCq9xmsm5CkhQGvKy05PCSFFxzGCOVpDCsBW6av5NCWoG6FKw/AcYlm6qro896vbwcpe3sM64Igs8YcRg5PuXSyD6lMFR1fs65y4DL9mJ19hn2mzCGD54wL0j2/BPnc/6J3n9jgo+//lDuf3pL5Ak1KJd0SG5MqcDsrrHc/sQmlq3aFMnF8qcd1p2QrXlD7/rW3ZkOWC4mFVHNsvrW7U9SFKGvUmVrTx/gUC4EZqrhizNnGUqSgnsS023dDjtJwTVYBFjteR5GGv8CtzDPKe+9Ef5YfzbM4vcwsh5hWjivXVmV6QozDRgDxdT/zmWMZOvqGYQdNXD1g+YyC33BNlffygnjpr7rWg/kYp9SGMbeZcnC6SxZOH1QuVKxwO3/diLQsCjMw6I5k7no1IX09lUoxwooUkQFTj88meswuyvyeL588xP1Y+WiMKmzxLxUuLBYEJ7avJPDP/l/9FWiEFrtYagpqRoisHrTS3zv92tiWeWe1ZvDQkcNZSQPEMumJcNTVV3lukIBvlCbyxIfKGdAtqnN7LztCrRuPQNQtC2Gp66Z6/hXu7u+574HztG6yTmEATPdN7BC2A60EN+vkCQF/HX1zc2EeMXUFVE2SSGNS7m4MIVhBDGYoqgxplTkgpMXBMmeccRMHv30axGEclEoFiT74Mf83asPYFJniWKhQLkk9XmfaeM7WDhjYkK2e2Indz75Ag89uy1xfGF3UgnVmvTV36zi23espq+i9FWqvLSrn0VzulKykfCyVZt4dmsP/bHS6tld8SYphKUL57x21TFYZMdKx8Cak6TQzPxUJsSSl6TgCLU1s3AvJAPOu6FgpqZDWw/kHDAdiQehoTZXu1z19e7C6/he7lboadkGBZ9NUsgaI/71QAOYwjBGlXEdYV3w6P2ncPT+UwYXBL77/mPZurOvnnTQEYfciimlN66jxAUnzWft1p5IpiixV1RgyYKk5zVlXDRX89VbV2WuN2fKuMTn2rP45q/9vp7V1tsXTbmlQwoFgZd29XPr4xvp64/SsO9/aouzXb73K/is0KAkhfh3MyvzGwcWb6jNFT/3yIam4DYV66+fCw+1JdrlVfDhobbQ9UDpwTwtm7i+wxiJ6uAPtTkcQue9TXtDLkxhGG3HmFKR7klBO8dw0WkHBckd9LKJ3PGRE9nVX617N+VigY5igcnjygnZJQunc+rqzQhQLkXzPeU4SeGEg5KKaGJniY3bd/G+q+5NHC8ITBmfTChA4M4/beLt37gzymqrKuu29nit63Xbelj+zNZ6CG/LS7v9g6UrzJMpN/qd3DU5xxsKUAK1z1mrPTsI51niXs8pQDY31OYoN+hVBzEh64F8Ct4VanMlitS+mz/vlh9qC30fhikMwwgk7Un4WNg9kW+++5VBshefcQhnLZ5dT8OuzftMHltm2oQxCdk3HDmL21Y+jxJ5R6Wi0D2pk0NmJhelluJMuquWreGqZWsS546bv1/ic20A+sotT/D9OwfmfLb19Hkt1g0v9rKlWKCvUuW5bb3xuSR564HS5G234aqrM9TmSe/eE+uBXIN14zVrhK4HciVJ1GRdA3t0Lu1h+NcDuRR8JqvNUaYLUxiGMYpMGFPKrLvxceEpC7nwlIWDyo0pFfnJea9m4/ZddMRKqOYRzU9lwL18v/Ec/LKJPPdiL5t27IoUVqnA4rldnHxwMgOuI063PvkLv8tcc2xH0qMTgU07dvGZGx6tezhP5awHqmo0uO+OZV27I+TPt6TK9FjieUkKe3M9kLOuAeHGoax2Tygtj4cRulutKQzDaEOOCpzv6Z7UyY0XLgmSfePi2ZSKUk9S6ChFymhsR5HXzEt6LofMnMSNDz/Hj+99hnLD3NCiOZOZm/LUigXh+gfWcf0Dyc0bfOuB7l69GSVa47O7v8qTz79EVyos6Iv1N5ZT/+xQLnmhNl/sxp2CGx5qC8nWG0oGXGi2Xsut9DYMY99l8rgy5/zFAUGy5x0/j/OOD1s79LHXHcJ9T21JJCmUi5JJre4oFZg6voObV2zg5hUb6sdLBeE186clZGuW+AU/Wk6xQLybgbJjV38m+aHmudyyYgPFQrQeaNN2/9Y7/i1PkuStdk/KOb+eG2prZj1QSKjNuU2QA1MYhmGMKicePIMTD54xqFy5WOD3F5/UsMYnyn5zpXwfPnsyZ79qf3b1V+phuXKxQEepwFuOTm50Pakz8k4+fM3yTDndkzoTn0Vg/bbeeuJBX0XZ/NLu+rm07LaePh5Zt62esr12S09TobbwdTP+/bScC0gzbpZ5GIZhtBmd5SKd5cEz4MaPKXH5m48IKvMtx8zhsNmTEISO0kD4bGy5mMlUO/XQbp7ZvLN+jXKxwKyuTo4/aHpmb7rOUpHfrXye3618PnF8Umdy2K2N3b9+aD0rN2ynr1Jld6XKw89uqy9uHZCNpGvrhWr7wFWqOe+maTjmSxd2bb3jwhSGYRh/1hQLwmGzJgfJnrloFmcuCtsv7j/fsZjHntseezZCR7FIuSjMmZqcw+ksFzlyzmTWbulh44u99bmhGRM7eW1qd4RyvKvBu7+T3Xt1TCmbeADw3WWrERF291fZ6nnnT5R4YB6GYRjGqLCgeyILuicOKlcsCL/60HFBZS6a08XHX38IvX2VumLpKEXrgY5PrfGZOTnyThpftVBL2U7PDxUE1m7p4bjP/Ya+in8FnykMwzCMFqGjVODv//oVQbKvXzSTv154GgWJs9qKBe/WO289Zi79VaUjVkC+d0eYwjAMw2hTahP6g3Hcgv04bsFAavTnPHIFz3HDMAzDSGAKwzAMwwjCFIZhGIYRhCkMwzAMIwhTGIZhGEYQpjAMwzCMIExhGIZhGEGYwjAMwzCCkJC3LLUqIrIdeHy067EH2A/YNNqV2ANYu1oLa1dr0Uy7DlDV6emD7b7S+3FVDXtXZgshIn+wdrUO1q7Wwtrlx0JShmEYRhCmMAzDMIwg2l1hXDnaFdhDWLtaC2tXa2Ht8tDWk96GYRjGyNHuHoZhGIYxQpjCMAzDMIJoS4UhIqeLyOMiskpELh7t+owkIrJGRB4SkeUi8ofRrs9QEZHviMhGEXm44dhUEblJRJ6If08ZzToOBU+7LhWRZ+N7tlxEXjeadWwWEZkrIreKyAoReUREPhwfb+n7ldOuVr9fnSJyj4g8ELfrU/Hxl4vI3fH9+rGIdDRddrvNYYhIEVgJnAqsBe4FzlbVR0e1YiOEiKwBXqmqLb2wSESWADuA76vq4fGx/wA2q+pnY0U/RVU/Mpr1bBZPuy4FdqjqFaNZt6EiIjOBmap6v4hMBO4D3gi8lxa+Xznt+lta+34JMF5Vd4hIGbgD+DBwEfBzVb1GRP4beEBVv95M2e3oYbwKWKWqT6rqbuAa4KxRrpORQlVvAzanDp8FfC/++3tED29L4WlXS6Oq61X1/vjv7cAKYDYtfr9y2tXSaMSO+GM5/lHgJOCn8fEh3a92VBizgWcaPq+lDTpBAwosFZH7ROTc0a7MCNOtqushepiBGaNcn5HkQyLyYByyaqnQTSMiciBwFHA3bXS/Uu2CFr9fIlIUkeXARuAm4E/AVlXtj0WGNC62o8IQx7F2iru9RlWPBs4Azo9DIMa+zdeBecBiYD3whdGtztAQkQnAz4ALVfXF0a7PSOFoV8vfL1WtqOpiYA5R1OUQl1iz5bajwlgLzG34PAdYN0p1GXFUdV38eyPwC6LO0C5siOPKtfjyxlGuz4igqhviB7gKfJMWvGdxLPxnwNWq+vP4cMvfL1e72uF+1VDVrcBvgb8EukSktn/gkMbFdlQY9wIL4oyADuAdwHWjXKcRQUTGx5NziMh44DTg4fxvtRTXAe+J/34P8KtRrMuIURtUY95Ei92zeBL128AKVf1iw6mWvl++drXB/ZouIl3x32OBU4jmZ24F3hqLDel+tV2WFECcBvdloAh8R1UvG+UqjQgi8goirwKinYZ/2KptE5EfAScQbbm8Afgk8EvgWmB/4GngbaraUhPInnadQBTeUGAN8I+12H8rICLHAbcDDwHV+PDHiOL9LXu/ctp1Nq19vxYRTWoXiZyCa1X10/H4cQ0wFfgj8C5V3dVU2e2oMAzDMIyRpx1DUoZhGMYewBSGYRiGEYQpDMMwDCMIUxiGYRhGEKYwDMMwjCBMYRgGICJdIvJPDZ9nichP874zxOvUdkL9tOf8GhHZbwSvd7WIbBaRtw4ubRj5mMIwjIguoK4wVHWdqu6pQfZLqvqJPVR2AlU9hzZZuGqMPqYwDCPis8C8+P0HnxeRA2vvtBCR94rIL0XkehFZLSIfEpGLROSPInKXiEyN5eaJyI3xxpC3i8jBg11URKaJyNK4rG/QsBdafM374ncanBsf+4CIfKlB5h9E5IvxLgC/jt+B8LCIvH2k/0GGYQrDMCIuBv6kqotV9V8d5w8H3km0r9BlwE5VPQq4E3h3LHMl8M+qegzwL8DXAq77SeCOuKzriFZN13h/XNYrgQtEZBrRSt03xHsgAbwPuAo4HVinqkfG7+G4MbThhhFKaXARwzCAW+N3JmwXkW3A9fHxh4BF8Y6nfwX8JNqiCIAxAeUuAd4MoKq/FpEtDecuEJE3xX/PBRao6l0i8hvgTBFZAZRV9SER2QVcISKfA25Q1duH0VbDcGIKwzDCaNxzp9rwuUr0HBWI3jeweAhlZ/bnEZETiDaNe7Wq7hSR3wKd8elvEe159BiRd4GqrhSRY4DXAZeLyFJVdU6sG8ZQsZCUYURsByYO9cvxexRWi8jbINoJVUSODPjqbcA58XfOAGov65kMbImVxcFE21PXrnU3kcfxTuBH8XdnEYXJfgBcARw91LYYhg9TGIYBqOoLwLJ4wvjzQyzmHOADIvIA8Ahhrwb+FLBERO4n2q7+6fj4jUBJRB4EPgPclfretcAyVa2FsI4A7onfsnYJ8O9DbINheLHdag1jLyIilwI7VPWKYZZzA1F67i0Bst8lmtcY8XUlxp8X5mEYxt5lB3Cub+HeYMQLDFcCPYHK4mrgeKB3KNczjEbMwzAMwzCCMA/DMAzDCMIUhmEYhhGEKQzDMAwjCFMYhmEYRhCmMAzDMIwg/h/vqs4pi7zuuwAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "59.27211415115418\n",
+ "38.46705417626044\n",
+ "-11.294842918690131\n",
+ "-0.14219326233654664\n",
+ "3.782292105536017\n",
+ "3.8030541356377157\n"
+ ]
+ }
+ ],
+ "source": [
+ "# plots for presentation\n",
+ "# qtop\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,Qtop_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,Qtop_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\",\"Winton\"],loc=1)\n",
+ "ax1.set_ylabel(\"Qtop [Wm$^{-2}$]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "#ax1.set_ylim(0,400)\n",
+ "ax1.set_xlim(0,days)\n",
+ "\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_qtop_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "# plots for presentation\n",
+ "# qbot\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,Qbot_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,Qbot_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\",\"Winton\"],loc=1)\n",
+ "ax1.set_ylabel(\"Qbot [Wm$^{-2}$]\")\n",
+ "ax1.hlines(0,time_artificial[0],time_artificial[-1],'black',lw=1) \n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "\"\"\"if initial_conditions==\"melting\":\n",
+ " ax1.set_ylim(-3.2,3.2)\n",
+ "elif initial_conditions==\"freezing\":\n",
+ " ax1.set_ylim(-20,4)\"\"\"\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_qbot_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hi\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,hi_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,hi_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\", \"Winton\"])\n",
+ "ax1.set_ylabel(\"hi [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "#ax1.set_ylim(3.3,4)\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_hi_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "# hs\n",
+ "fig, (ax1) = plt.subplots()\n",
+ "plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "ax1.plot(time_artificial,hs_result_Semtner,color='C0',linestyle='-')\n",
+ "ax1.plot(time_artificial,hs_result,color='C1',linestyle='-')\n",
+ "ax1.legend([\"Semtner\", \"Winton\"])\n",
+ "ax1.set_ylabel(\"hs [m]\")\n",
+ "#ax1.set_xticks([3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24])\n",
+ "ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "#ax1.set_ylim(3.3,4)\n",
+ "\n",
+ "ax1.set_xlabel(\"time [days]\")\n",
+ "ax1.set_xlim(0,days)\n",
+ "plt.savefig(\"plots/model_hs_{}.svg\".format(initial_conditions),dpi=500)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.nanmean(Qtop_result_Semtner))\n",
+ "print(np.nanmean(Qtop_result))\n",
+ "print(np.nanmean(Qbot_result_Semtner))\n",
+ "print(np.nanmean(Qbot_result))\n",
+ "print(np.nanmean(hi_result_Semtner))\n",
+ "print(np.nanmean(hi_result))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 3 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plots for thesis\n",
+ "\n",
+ "if initial_conditions==\"melting_icon\" or initial_conditions==\"melting\":\n",
+ " hilim=[3.95,4]\n",
+ " qtoplim=[0,300]\n",
+ " qbotlim=[-50,4]\n",
+ "elif initial_conditions==\"melting_snow\":\n",
+ " hslim=[0.8,1]\n",
+ " qtoplim=[0,150]\n",
+ " qbotlim=[-10,10]\n",
+ "elif initial_conditions==\"freezing\" or initial_conditions==\"freezing_2\":\n",
+ " qbotlim=[-240,0]\n",
+ " qtoplim=[0,300]\n",
+ " hilim=[0,0.4]\n",
+ " \n",
+ "\n",
+ "#hi\n",
+ "fig, (ax1, ax2, ax3) = plt.subplots(3,1,figsize=(6,4))\n",
+ "#plt.subplots_adjust(hspace=0)\n",
+ "\n",
+ "\n",
+ "if init_hs==0:\n",
+ " ax1.plot(time_artificial,hi_result_Semtner,color='C0',linestyle='-')\n",
+ " ax1.plot(time_artificial,hi_result,color='C1',linestyle='-')\n",
+ "\n",
+ " legend = legend_color(ax1,['3L-Winton','0L-Semtner'],1)\n",
+ " ax1.set_ylabel(\"hi [m]\")\n",
+ " #ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ " ax1.set_xlim(0,7)\n",
+ " ax1.set_ylim(hilim[0],hilim[1])\n",
+ " ax1.xaxis.set_ticks_position('none')\n",
+ " ax1.set_xticklabels('')\n",
+ "else:\n",
+ " ax1.plot(time_artificial,hs_result_Semtner,color='C0',linestyle='-')\n",
+ " ax1.plot(time_artificial,hs_result,color='C1',linestyle='-')\n",
+ "\n",
+ " legend = legend_color(ax1,['3L-Winton','0L-Semtner'],1)\n",
+ " ax1.set_ylabel(\"hs [m]\")\n",
+ " #ax1.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ " ax1.set_xlim(0,7)\n",
+ " ax1.set_ylim(hslim[0],hslim[1])\n",
+ " ax1.xaxis.set_ticks_position('none')\n",
+ " ax1.set_xticklabels('')\n",
+ " \n",
+ "\n",
+ "\n",
+ "\n",
+ "# qtop\n",
+ "ax2.plot(time_artificial,Qtop_result_Semtner,color='C0',linestyle='-')\n",
+ "ax2.plot(time_artificial,Qtop_result,color='C1',linestyle='-')\n",
+ "#ax2.legend([\"Qtop Semtner\",\"Qtop Winton\"],loc=1)\n",
+ "ax2.set_ylabel(\"Qtop [Wm$^{-2}$]\")\n",
+ "#ax2.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "ax2.set_ylim(qtoplim[0],qtoplim[1])\n",
+ "ax2.xaxis.set_ticks_position('none')\n",
+ "ax2.set_xticklabels('')\n",
+ "ax2.set_xlim(0,7)\n",
+ "#ax2.hlines(0,0,7,lw=1,color='black')\n",
+ "\n",
+ "\n",
+ "# qbot\n",
+ "ax3.hlines(0,0,7,lw=1,color='black')\n",
+ "ax3.plot(time_artificial,Qbot_result_Semtner,color='C0',linestyle='-')\n",
+ "ax3.plot(time_artificial,Qbot_result,color='C1',linestyle='-')\n",
+ "#ax3.legend([\"Qbot Semtner\",\"Qbot Winton\"],loc=1)\n",
+ "ax3.set_ylabel(\"Qbot [Wm$^{-2}$]\")\n",
+ "#ax3.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "ax3.set_ylim(qbotlim[0],qbotlim[1])\n",
+ "ax3.ticklabel_format(axis='both', style='plain',useOffset=False)\n",
+ "\n",
+ "ax3.set_xlabel(\"Time [days]\")\n",
+ "ax3.set_xlim(0,7)\n",
+ "\n",
+ "ax1.spines['right'].set_color('none')\n",
+ "ax2.spines['right'].set_color('none')\n",
+ "ax3.spines['right'].set_color('none')\n",
+ "ax1.spines['top'].set_color('none')\n",
+ "ax2.spines['top'].set_color('none')\n",
+ "ax3.spines['top'].set_color('none')\n",
+ "ax1.spines['bottom'].set_color('none')\n",
+ "#ax2.spines['bottom'].set_color('none')\n",
+ "ax3.spines['bottom'].set_color('none')\n",
+ "\n",
+ "\n",
+ "plt.subplots_adjust(hspace=0.05)\n",
+ "ax1.text(-0.16,1,\"a)\", transform=ax1.transAxes, fontsize=10)\n",
+ "ax2.text(-0.16,1,\"b)\", transform=ax2.transAxes, fontsize=10)\n",
+ "ax3.text(-0.16,1,\"c)\", transform=ax3.transAxes, fontsize=10)\n",
+ "\n",
+ "plt.savefig(\"plots/model_hi_qtop_qbot_{}.pdf\".format(initial_conditions))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## compare enthalpy"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/sw/rhel6-x64/conda/anaconda3-bleeding_edge/lib/python3.6/site-packages/ipykernel_launcher.py:3: RuntimeWarning: divide by zero encountered in true_divide\n",
+ " This is separate from the ipykernel package so we can avoid doing imports until\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# example of E & E2\n",
+ "plt.subplot()\n",
+ "T_vector=np.linspace(-100,0,401)\n",
+ "plt.plot(T_vector,E(T_vector),'C3')\n",
+ "plt.plot(T_vector,E2(T_vector),'C1')\n",
+ "plt.hlines(-L,T_vector[0],T_vector[-1],'C0')\n",
+ "plt.legend(['Winton upper layer','Winton lower layer','Semtner'])\n",
+ "plt.xlabel('Ice Temperature [°C]')\n",
+ "plt.ylabel('Enthalpy [Jkg$^{-1}$]')\n",
+ "plt.xlim(-8,0)\n",
+ "plt.ylim(-360000,-200000)\n",
+ "plt.tight_layout()\n",
+ "plt.savefig(\"plots/enthalpy.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "E1_array=np.zeros(np.size(T1_result))\n",
+ "E2_array=np.zeros(np.size(T2_result))\n",
+ "for i in range(np.size(T1_result)):\n",
+ " E1_array[i]=E(T1_result[i])\n",
+ " E2_array[i]=E2(T2_result[i])\n",
+ "\n",
+ "plt.plot(E1_array)\n",
+ "plt.plot(E2_array)\n",
+ "\n",
+ "dhi_bot = Qbot_result/(rhoi*E2_array)\n",
+ "dhi_bot_Semtner = -1*np.array(Qbot_result_Semtner)/(rhoi*L)\n",
+ "\n",
+ "dhi_surf = Qtop_result/(rhoi*E1_array)\n",
+ "dhi_surf_Semtner = -1*np.array(Qtop_result_Semtner)/(rhoi*L)\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 90,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "NameError",
+ "evalue": "name 'dhi_surf_Semtner' is not defined",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-90-b669873ae3d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdhi_surf_Semtner\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Semtner'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdhi_surf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Winton'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"surface ice thickness change [ms$^{-1}$]\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mNameError\u001b[0m: name 'dhi_surf_Semtner' is not defined"
+ ]
+ }
+ ],
+ "source": [
+ "plt.plot(dhi_surf_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_surf,label='Winton')\n",
+ "plt.ylabel(\"surface ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(dhi_bot_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_bot,label='Winton')\n",
+ "plt.ylabel(\"botom ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(dhi_surf_Semtner+dhi_bot_Semtner,label='Semtner')\n",
+ "plt.plot(dhi_surf+dhi_bot,label='Winton')\n",
+ "plt.ylabel(\"net ice thickness change [ms$^{-1}$]\")\n",
+ "plt.legend()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /bifurcation_Semtner_unlim-lim5.ipynb b/python_scripts /bifurcation_Semtner_unlim-lim5.ipynb
new file mode 100644
index 0000000..1bf799b
--- /dev/null
+++ b/python_scripts /bifurcation_Semtner_unlim-lim5.ipynb
@@ -0,0 +1,370 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create CO2 - ice-edge latitude diagrams and calculate stability\n",
+ "Stability is assessed by reading simulation data and applying the stability criterion. CO2 - ice-edge latitude diagrams are created by manual input of stability and equilibrium ice-edge latitude. The actual bifurcation diagram is added afterwards as a best guess."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " if stable==2:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " else:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "def plot_simulation_merged(axes,co2, startlat, endlat, col, stable, offset=0): #plot a simulation into the bifurcation diagram\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " handle = []\n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\",clip_on=False)\n",
+ " elif stable==1: # stable from warm\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='o',clip_on=False)\n",
+ " elif stable==3: # towards Snowball\n",
+ " if endlat==0:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='v',clip_on=False)\n",
+ " else:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='v',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='^',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "def plot_co2_equivalent(co2, startlat, endlat, col, stable, heatflux):\n",
+ " CO2_fac=np.exp(heatflux/5.35)\n",
+ "\n",
+ " handle, =plt.plot([co2*CO2_fac,co2*CO2_fac],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ " \n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-limited':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend\n",
+ "\n",
+ "def stability_index(DS):\n",
+ " LW = get_var(DS,\"rlut\",True)\n",
+ " SW = get_var(DS,\"rsdt\",True)-get_var(DS,\"rsut\",True)\n",
+ " T = get_var(DS,'ts',True)\n",
+ " \n",
+ " N = np.squeeze(SW[-50*12:]-LW[-50*12:])\n",
+ " Nparm = stats.linregress(LW.time[-50*12:]-LW.time[-50*12],N)\n",
+ " \n",
+ " f=(Nparm.slope) #*np.sign(np.squeeze(SW-LW).values[-1])\n",
+ " return f\n",
+ "\n",
+ "def is_stable(f):\n",
+ " if f>0: return False\n",
+ " else: return True"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv_hice_unlim/mlo_aqua_1594ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_61sic_hice_unlim/mlo_aqua_3000ppmv_61sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_69sic_hice_unlim/mlo_aqua_3750ppmv_69sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_77sic_hice_unlim/mlo_aqua_3750ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3907ppmv_77sic_hice_unlim/mlo_aqua_3907ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4063ppmv_77sic_hice_unlim/mlo_aqua_4063ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4375ppmv_77sic_hice_unlim/mlo_aqua_4375ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_83sic_hice_unlim/mlo_aqua_5000ppmv_83sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_77sic_hice_unlim/mlo_aqua_10000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv/mlo_aqua_5000ppmv_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_1594ppmv_hice_unlim\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_1688ppmv_hice_unlim\")\n",
+ "experiment4, DS4 = load_experiment(\"mlo_aqua_1875ppmv_hice_unlim\")\n",
+ "experiment5, DS5 = load_experiment(\"mlo_aqua_2250ppmv_hice_unlim\")\n",
+ "\n",
+ "experiment1_Jor, DS1_Jor = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "experiment2_Jor, DS2_Jor = load_experiment(\"mlo_aqua_3000ppmv_61sic_hice_unlim\")\n",
+ "experiment3_Jor, DS3_Jor = load_experiment(\"mlo_aqua_3750ppmv_69sic_hice_unlim\")\n",
+ "experiment4_Jor, DS4_Jor = load_experiment(\"mlo_aqua_3750ppmv_77sic_hice_unlim\")\n",
+ "experiment5_Jor, DS5_Jor = load_experiment(\"mlo_aqua_3907ppmv_77sic_hice_unlim\")\n",
+ "experiment6_Jor, DS6_Jor = load_experiment(\"mlo_aqua_4063ppmv_77sic_hice_unlim\")\n",
+ "experiment7_Jor, DS7_Jor = load_experiment(\"mlo_aqua_4219ppmv_77sic_hice_unlim\")\n",
+ "experiment8_Jor, DS8_Jor = load_experiment(\"mlo_aqua_4375ppmv_77sic_hice_unlim\")\n",
+ "experiment9_Jor, DS9_Jor = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "experiment10_Jor, DS10_Jor = load_experiment(\"mlo_aqua_5000ppmv_83sic_hice_unlim\")\n",
+ "experiment11_Jor, DS11_Jor = load_experiment(\"mlo_aqua_10000ppmv_77sic_hice_unlim\")\n",
+ "\n",
+ "experiment1_5m, DS1_5m = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "experiment2_5m, DS2_5m = load_experiment(\"mlo_aqua_3000ppmv\")\n",
+ "experiment3_5m, DS3_5m = load_experiment(\"mlo_aqua_5000ppmv\")\n",
+ "\n",
+ "DS_array=[DS1, DS2, DS3, DS4, DS5] #, DS1_Jor, DS2_Jor, DS3_Jor, DS4_Jor, DS5_Jor, DS6_Jor\n",
+ " # , DS7_Jor, DS8_Jor, DS9_Jor, DS10_Jor, DS11_Jor"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 147,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "### %matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "save_plot = True\n",
+ "plot_unlim = True\n",
+ "plot_5m = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ax.spines['left'].set_position(('outward',5))\n",
+ "ax.spines['bottom'].set_position(('outward',5))\n",
+ " \n",
+ "# 5m simulations\n",
+ "\n",
+ "if plot_5m:\n",
+ " color_5m='C2'\n",
+ " #b=plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)\n",
+ " #plot_simulation_merged(ax,1375, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1438, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1500, 90, 46.6, color_5m, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 50.3, color_5m, 1)\n",
+ " #plot_simulation_merged(ax,1250, 90, 0, color_5m, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_5m, 1)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_5m, 1)\n",
+ " \n",
+ " # Jormungand\n",
+ " #mlo_aqua_2000ppmv_Jor2\n",
+ " #plot_simulation_merged(ax,2000, 32.68, 29.34, color_5m, 3)\n",
+ " #mlo_aqua_2000ppmv_Jor5\n",
+ " plot_simulation_merged(ax,2000, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_2500ppmv_Jor2\n",
+ " plot_simulation_merged(ax,2500, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_2500ppmv_Jor5\n",
+ " #plot_simulation_merged(ax,2500, 32.68, 36.16, color_5m, 4)\n",
+ " #mlo_aqua_3000ppmv_Jor\n",
+ " plot_simulation_merged(ax,3000, 28.03, 36.87, color_5m, 4)\n",
+ " #mlo_aqua_3000ppmv_Jor2\n",
+ " plot_simulation_merged(ax,3000, 13.48, 0, color_5m, 3)\n",
+ " #mlo_aqua_3000ppmv_Jor3\n",
+ " #plot_simulation_merged(ax,3000, 16.26, 22.95, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor\n",
+ " #plot_simulation_merged(ax,5000, 28.03, 34.75, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor2\n",
+ " plot_simulation_merged(ax,5000, 13.29, 30.00, color_5m, 4)\n",
+ " #mlo_aqua_5000ppmv_Jor4\n",
+ " plot_simulation_merged(ax,5000, 7.47, 15.07, color_5m, 4, -offset)\n",
+ " #mlo_aqua_10000ppmv_Jor\n",
+ " #plot_simulation_merged(ax,10000, 28.03, 41.30, color_5m, 4)\n",
+ " \n",
+ " \n",
+ "#hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " offset=0.01\n",
+ " a=plot_simulation_merged(ax,1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 49.54, color_unlim, 1, offset)\n",
+ " plot_simulation_merged(ax,1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_unlim, 1, offset) #5m limited, but always under 5m\n",
+ " plot_simulation_merged(ax,3000, 14.46, 0, color_unlim, 3, offset)\n",
+ " #plot_simulation_merged(ax,3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation_merged(ax,3750, 14.46, 0, color_unlim, 3) \n",
+ " #plot_simulation_merged(ax,3750, 19.2, 18.7, color_unlim, 4)\n",
+ " #plot_simulation_merged(ax,3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4063, 14.46, 11.5, color_unlim, 3)\n",
+ " #plot_simulation_merged(ax,4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation_merged(ax,5000, 14.46, 24, color_unlim, 4, offset)\n",
+ " #plot_simulation_merged(ax,5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_unlim, 1, offset) # limited, but no ice at all\n",
+ " #plot_simulation_merged(ax,10000, 14.46, 18, color_unlim, 4) \n",
+ "\n",
+ "\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_ylim(-0.1,1.1)\n",
+ "ax.set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax.set_ylabel(\"Ice-Edge Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.yaxis.tick_left()\n",
+ "ax.xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "ax.set_xscale('log')\n",
+ "\n",
+ "ax.set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax.set_xticklabels([1000, 2000,3000,4000,5000,'','','','',10000] )\n",
+ "ax.set_xlim(1000,5000)\n",
+ "ax.set_ylim(0,1)\n",
+ "# extra ticks at bifurcation points\n",
+ "#semtner_bif=1641\n",
+ "#semtner_5m_bif=1547\n",
+ "semtner_bif=1547\n",
+ "semtner_5m_bif=1469\n",
+ "ax.vlines([semtner_5m_bif],-0.04,-0.01,color=color_5m,lw=1,clip_on=False)\n",
+ "ax.vlines([semtner_bif],-0.04,-0.01,color=color_unlim,lw=1,clip_on=False)\n",
+ "#ax.axvline(semtner_bif,-20,0.1)\n",
+ "ax.annotate(semtner_bif,(semtner_bif,0.02),color=color_unlim,ha='center',clip_on=False)\n",
+ "ax.annotate(semtner_5m_bif,(semtner_5m_bif,0.1),xytext=(semtner_5m_bif,-0.05),color=color_5m,ha='center',va='top',clip_on=False)\n",
+ "ax.set_yticklabels([0,10,20,30,45,60,90])\n",
+ "legend_color(ax,[\"0L-Semtner\",\"0L-Semtner-limited\"],2)\n",
+ "\n",
+ "\n",
+ "if save_plot:\n",
+ " plt.savefig(\"plots/bifurcation_5mlim_merged.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /bifurcation_Winton_Semtner_unlim.ipynb b/python_scripts /bifurcation_Winton_Semtner_unlim.ipynb
new file mode 100644
index 0000000..aa4d858
--- /dev/null
+++ b/python_scripts /bifurcation_Winton_Semtner_unlim.ipynb
@@ -0,0 +1,779 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create CO2 - ice-edge latitude diagrams and calculate stability\n",
+ "Stability is assessed by reading simulation data and applying the stability criterion. CO2 - ice-edge latitude diagrams are created by manual input of stability and equilibrium ice-edge latitude. The actual bifurcation diagram is added afterwards as a best guess."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "from scipy import stats\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "\n",
+ "def plot_simulation(axes,co2, startlat, endlat, col, stable): #plot a simulation into the bifurcation diagram\n",
+ " handle, =axes.plot([co2,co2],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " \n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\")\n",
+ " elif stable==1: # stable\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " elif stable==3: # towards Snowball\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ "\n",
+ "\n",
+ "\n",
+ "def plot_simulation_merged(axes,co2, startlat, endlat, col, stable, offset=0): #plot a simulation into the bifurcation diagram\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " handle = []\n",
+ " if stable==2: # metastable\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),markeredgecolor=col,marker='o',markerfacecolor=\"none\",clip_on=False)\n",
+ " elif stable==1: # stable from warm\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='o',clip_on=False)\n",
+ " elif stable==3: # towards Snowball\n",
+ " if endlat==0:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,marker='v',clip_on=False)\n",
+ " else:\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='v',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " elif stable==4: # towards icefree\n",
+ " axes.plot(co2 *(1+offset),np.sin(np.radians(endlat)),color=col,markerfacecolor='none',marker='^',clip_on=False)\n",
+ " handle, =axes.plot([co2 *(1+offset),co2 *(1+offset)],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='-',alpha=0.2,clip_on=False) #plot the line\n",
+ " return handle\n",
+ "\n",
+ "def plot_co2_equivalent(co2, startlat, endlat, col, stable, heatflux):\n",
+ " CO2_fac=np.exp(heatflux/5.35)\n",
+ "\n",
+ " handle, =plt.plot([co2*CO2_fac,co2*CO2_fac],[np.sin(np.radians(startlat)),np.sin(np.radians(endlat))],color=col,linestyle='--') #plot the line\n",
+ " #plt.plot(co2,np.sin(np.radians(startlat)),'bo',fillstyle='none')#\n",
+ " if stable:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='o')\n",
+ " else:\n",
+ " if endlat<startlat:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='v')\n",
+ " else:\n",
+ " plt.plot(co2*CO2_fac,np.sin(np.radians(endlat)),color=col,marker='^')\n",
+ " return handle\n",
+ " \n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def stability_index(DS):\n",
+ " LW = get_var(DS,\"rlut\",True)\n",
+ " SW = get_var(DS,\"rsdt\",True)-get_var(DS,\"rsut\",True)\n",
+ " T = get_var(DS,'ts',True)\n",
+ " \n",
+ " N = np.squeeze(SW[-50*12:]-LW[-50*12:])\n",
+ " Nparm = stats.linregress(LW.time[-50*12:]-LW.time[-50*12],N)\n",
+ " \n",
+ " f=(Nparm.slope) #*np.sign(np.squeeze(SW-LW).values[-1])\n",
+ " return f"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_winton/mlo_aqua_1875ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_winton/mlo_aqua_2250ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_winton/mlo_aqua_5000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton_50sic/mlo_aqua_3000ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_74sic_winton/mlo_aqua_3000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_winton_50sic/mlo_aqua_4219ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_37sic_winton/mlo_aqua_5000ppmv_37sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_74sic_winton/mlo_aqua_5000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_winton_semtnerrestart/mlo_aqua_5000ppmv_77sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_74sic_winton/mlo_aqua_10000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_1875ppmv_winton\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_2250ppmv_winton\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_2437ppmv_winton\")\n",
+ "experiment4, DS4 = load_experiment(\"mlo_aqua_2625ppmv_winton\")\n",
+ "experiment5, DS5 = load_experiment(\"mlo_aqua_3000ppmv_winton\")\n",
+ "experiment6, DS6 = load_experiment(\"mlo_aqua_5000ppmv_winton\")\n",
+ "\n",
+ "experiment1_Jor, DS1_Jor = load_experiment(\"mlo_aqua_3000ppmv_winton_50sic\")\n",
+ "experiment2_Jor, DS2_Jor = load_experiment(\"mlo_aqua_3000ppmv_74sic_winton\")\n",
+ "experiment3_Jor, DS3_Jor = load_experiment(\"mlo_aqua_4219ppmv_winton_50sic\")\n",
+ "experiment4_Jor, DS4_Jor = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")\n",
+ "experiment5_Jor, DS5_Jor = load_experiment(\"mlo_aqua_5000ppmv_37sic_winton\")\n",
+ "experiment6_Jor, DS6_Jor = load_experiment(\"mlo_aqua_5000ppmv_74sic_winton\")\n",
+ "experiment7_Jor, DS7_Jor = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "experiment8_Jor, DS8_Jor = load_experiment(\"mlo_aqua_10000ppmv_74sic_winton\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_1875ppmv_winton f=-0.21304795919592326\n",
+ "mlo_aqua_2250ppmv_winton f=-0.10866840147621822\n",
+ "mlo_aqua_2437ppmv_winton f=0.0006746875735950412\n",
+ "mlo_aqua_2625ppmv_winton f=0.002651551595564326\n",
+ "mlo_aqua_3000ppmv_winton f=0.0004580904092328009\n"
+ ]
+ }
+ ],
+ "source": [
+ "#plot stability index\n",
+ "f1=stability_index(DS1)\n",
+ "f2=stability_index(DS2)\n",
+ "f3=stability_index(DS3)\n",
+ "f4=stability_index(DS4)\n",
+ "f5=stability_index(DS5)\n",
+ "#f6=stability_index(DS6)\n",
+ "\n",
+ "\n",
+ "\n",
+ "print(experiment1 +\" f=\" +str(f1))\n",
+ "print(experiment2 +\" f=\" +str(f2))\n",
+ "print(experiment3 +\" f=\" +str(f3))\n",
+ "print(experiment4 +\" f=\" +str(f4))\n",
+ "print(experiment5 +\" f=\" +str(f5))\n",
+ "#print(experiment6 +\" f=\" +str(f6))\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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JZmwCual60jTQVuxcwfCk4Vwy7BKrS1GqQ1gHhHG7cbmzcSS3ULR3F9veX0t2XRNJI0ae8z5LSkoAGD48/K9VL6hqYmhKHDH28A5CqxXVF3Gk7gg3T7xZr2BSQSWsA8JzZC8Qg2NIMse25WMTYVppDbF96P9w4oT/WvUh4X+tekFVMyPTdNrLQNt1chcAs7NnW1yJUqcK64BwHTgAgCNvLMW7tjOopY2UOXOwxZ37tJkVFRUMHjyYmJjw7jhmjKHgZBMj0vQbbaAV1BcgCCMGjbC6FKVOEd4BcawE8CKjRlNecJTBTS1kfu+7fdpnRUVFWI/c2u5AeQN1LS6m54TvMObBorChkCEJQ4iJCu8vHSr0hG1AeA+spaUsEUdCIw31J/EaQ3r2MGJGndtlhB6PhxUrVnDy5ElGjhzZv8UGGWMM/++VXcRHRzF/fHj3FA8Glc2VZCVkWV2GUmcI24Coe/M4LjOehMumUH3Cd2J58LBz76V66NAhTpw4wfjx45k9O7zbineX1PNRYS33XTORrEE6i1ygVTRXkB6nHRFV8AnLgDDG0Fw5jPjk3SRePIKKA/sAyBg3/pz3efjwYaKjo1m6dCkOh6O/Sg1KWwqqAfjUJP1WG2jGGCpbKsmMD/9mSxV6wjIgPNXNGBNLdJbQ2tTIrrVvk9DaRmLeuU/jWFxcTE5OTtj3fQA4VNHI4HiHzgExACqaK2hyNekc1CoohWVAuA4fBcCRm07+66/Q1FDPxBNVRJ/DuYPq6mqefvppysrKyMmJjIHUDpU3kJeZpMNrDIANJzYAMDltssWVKHWm8AyIAt85B0feWA5seI/sxEFkewXHOXzAr1+/nmPHfFOUnn/++f1aZzAyxnCoopG8LB3eO9Dq2+p5ePPDTEidwJT0KVaXo9QZ7FYXEAiu0kaipJl6ey615aXk1DQTN2sWYut9HlZX+9rj7777bpKSkvq71KBT2eCkrsVFns7/EHDvFr1Li7uF+y+8H7stLN+KKsSF3avSGIOr1o4jpoLj+/YCkFpRRcavftOr/dTV1bFz504KCwu56KKLSE+PjKtMDlU0ApCXFf5haLW3Ct4iOyGb6RnTrS5FqS6FXRNT47pjuFvTiEmvY++6d4hzuRl67XXETe5dG++mTZtYs2YNABP6ODVpKFl3sBKbwPhsDYhAamhrYMOJDSwcsVDP9aigFVYB4Sprom51MXG2DygZmsiJQ/vJqaonce7cXu+roqICgJtvvjnsO8a1q2tx8ZcPj7N4+lDSdQ7qgHrj6Bu4vC6uGnGV1aUo9YnCKiCcx+vBCMlpqzh4rIb42HjGltcQP3Nmr/dVXl7OtGnTyMvLC0ClwendAxW0uDx8Yc5Iq0sJawV1Bfxq6684P/t8bV5SQS2gASEii0TkgIgcFpHvdXH/cBFZKyLbRGSniPRpBh5PRR3gImrKJZQc2EumzYEjKwt7L0debWpqoqGhgaysyOoo9q99FaQnRjMzV8dfCqSXD72M2+vm4Ysf1uYlFdQCFhAiEgU8DlwNTAKWi8ik0zb7PvCCMWYmsAz4XV+e01VUgl3KaM6ZT3NdLfHHC4m/8IJevQmNMaxevRogYpqW2u0sruXCUWnYbPqhFUi7Tu5iYtpEHX9JBb1AHkFcABw2xhw1xrQBzwPXn7aNAQb5bycDJ871yYwxuCrAIUeobPGNH5TU0kbmvff2aj+7du1i586dzJ8/n2HDhp1rOSHH4zWU1LTo8N4B5va62Vu1l6npU60uRaluBTIghgFFnZaL/es6+yFwi4gUAyuBr3W1IxG5S0TyRSS/srKyyydr3VOFpzWa2NiDVJb6TjBnjsnDkZ3dq6Lz8/NJT09n/vz5vXpcqDtR24Lba3R60QA7UnuEFneLdoxTISGQAdFVO4U5bXk58GdjTA5wDfAXETmjJmPMCmPMbGPM7IyMM4efNm4vta8fxRFdTvzQk5w8foxYt4dB43o39lJraytFRUVMmjQJ2zl0qgtlhyoaABirHeQCqn32OD2CUKEgkJ+CxUDnEchyOLMJ6Q7gBQBjzIdALNDrHmmt+6vx1DlJjvojDJ1K+dHDJDW3Ys/u3cnpjRs3YoxhxIjIm9lre1EdAOO0g1zAeI2XFw68wJCEIQxPCv85zVXoC2RAbAHyRGSUiETjOwn92mnbFAJXAIjIRHwB0XUb0lm0nWgEMcR4t7C7fhhVJUWkN7QQO7HnHdwqKyt59913yc3NZdQ5TioUqupaXDy76TjzxqaRHBfeQ5lb6c2jb7Kveh/3zLpHr15SISFgAWGMcQN3A6uBffiuVtojIg+JyGL/Zt8EviQiO4DngNuMMac3Q3XLfbKFKEc9ZbZc/vXaOwwZnM7Ik3XETe35YXx+fj4AN9xwQ8Q1Lz27qZCTjW18d1Hk9Bi3wrridQxJGMI1o/p0NbdSAyagYzEZY1biO/nced2DnW7vBeb19XncZfU43IfY5J6GI8bJBcQio0YRldKz6/mbmprYtGkTdrud5OTkvpYTcv62pZA5o9OYpvNPB9SB6gNMSJ2gRw8qZIT8V2Wv04Or0okxxzh0vJ4Jcy/Fu207cTNm9OjxFRUVvPnmmwDcdNNNETEhUGetLg8FVc3MGZNmdSlhrbq1moL6Ar16SYWUkB/NtWlLGRhhf5Pv0tYJiYNpqKtj0LXX9ujxf/vb36iqqmLw4MERd+4B4NjJJgBGpSdYXEl421K2BYALh1xocSVK9VxIH0G4KptpeKcQR8xRPjrZyKRLr8D16j+IHjGChLlzun18dXU1VVVVpKam8oUvfCEiD/23F9UCMHHIoG62VOfKGMObR98k0ZGoM8epkBLSAdH0YSneZjc4f4vbC1mxCbTu2EnqbV/s0eRAR44cAWD58uWkpqYGutyg09Dq4ukNBQxJjmVMhh5BBMqHpR+ytmgtd0y9QycGUiElpAPCVdZEdCbUtPlmfYsrLQebjeTFi7t5JDQ0NLB+/Xqys7MjZjKg0z31fgH7yxr48WemROTR00BZc3wN8fZ4bp10q9WlKNUrIRsQxmNoK2nE4Sikui0BRHAcPUbMmNHYEs7+bdgYw6uvvkpLSwuf+cxnIvbDcf2hSmYNT+GKiTpoXKB4jZd1xeuYO3Qu0VHRVpejVK+EbEA4C+owTg8x1X+nOjaP5IxMXLv3EDul+74PRUVFHDlyhCuvvJLsXo7VFC7cHi97TtQxI3ew1aWEtU2lmyhvLufKEVdaXYpSvRayAdH4wQlsDjex3vVUe1NJTkjCU11N/IUXfOJjjDHs27ePzZs3Y7PZmNHDS2HD0cHyRlpdXqbnRl6/j4H04sEXSYlJYeGIhVaXolSvheQZs5b91bTurSIpeT2SNoWa96pIcVdji49n0FWfPIXjnj17eOmllwAYM2YMsbGxA1Vy0NlZ7Lt6STvHBc7BmoOsLVzLLZNu0eYlFZJCMiAa3i1CYqNIal1BVfqXcLflE1tUQeJll2GLP3O46tLSUlavXk1BQQEAWVlZLFiwYGCLDjI7imsZFGtnpM7/EDB/3v1nHFEO7phyh9WlKHVOQi8gDLQVNpA4rg5bQSMHquIAyKhvJvO73zll0+bmZg4cOMDmzZspLS0FYOnSpUyadPrEdpFnS0ENM4cPjtgT9IF2rO4Yrx99nVsm3kJKrB6lqdAUcgFhXB7wGqLr1nIydjyb1nxAutNN5qKrcWRmnrLtu+++y+bNmwGYNGkSM2fOJC8vz4qyg8pHhTUcrmhk2fm53W+szsmqY6sQhNun3G51KUqds5ALCFdlCwiYytd5+lAe4CWnrIq4pTM7tjl69CgfffQRu3fvxuFwMGPGDK644oqIPufQzhjDT97cR3piDMsv0DkJAsEYwz8L/sns7Nlkxmd2/wClglTIBQRATPoxVu72zSx33tTzyNzxArapU9m2bRtNTU1s27aNqqoqAD7/+c8zrpczy4WzXSV1bD1ew0PXTyYhJiT//EFve+V2jtUd45aJt1hdilJ9ctZPCBHZ2YN9VBpjruinerrlSI9j09H/o7A5hXlLbyHzmRcomTqVF15++ZTtcnNzmTx5sjYpneZf+yqwCSyePtTqUsJSm6eNb637Fnaxa98HFfK6+woZhW+u6E8inDlLXGDZ3ByuimbihKGMaXJRuXcfh790JzQ0kJycTGJiIklJSSxZsgSHQ2dHO92mo1VMHppMSrxedhkIz+x7hormCh6a+xCpsZE3vpcKL90FxL8bY46fbQMR+Y9+rKdbzoZqPGYEU664luf+uZHqZTdCQwNXXHEFl1xyyUCWEnJaXR62FdVy60WRN+f2QNlYupG8wXnckHeD1aUo1Wdn7UltjHm/ux30ZJv+1NpQT4zdywmTQnVMDABDhgxh3rw+T0wX9tbsq6DN7eWScRlWlxKWml3NbKvYxsyMmd1vrFQIOGtAiMiK7nbQk236U4stjsbxF7Bq7VrSKyuZN24cy5Yti7h5pM/F42sPMyo9gXk6e1xA/OPIP2hxt3Dt6J5NVqVUsOuuiekzItJ6lvsFuKwf6+mWibLT6oWcmhrmVFYyafly7ezVA6V1Lewtree+qydgj9Iw7W8vH3yZn276KTMyZjAzU48gVHjoLiC+3YN9vNcfhfRUVFQUF4wZw6if/JShj/xCw6GHVu0uA9ChvQOgurWaX2z5BeMGj+MnF/9EX5MqbJw1IIwxTw9UIT2VlZXFRV4v5UDCnO6nFVU+/9xVxoTsJMZmJlpdSth55dArNLubeeTSRxg+SDsfqvARkm0NrXv3Yc/IwB6hM8H1VkOri62FNVypRw/9zhjDq4df5bys8xidMtrqcpTqV6EZEPv3EzNxgtVlhIT6VhcL/2c9Hq9h/ni9eqm/7ajcwfH643xm7GesLkWpfhdyAWFcbpyHDhE3bbrVpYSEtfsrKKtv5apJWcweobPH9bdXD79KnD2Oq0Z88jwkSoWqHgWEiLwtIimdlgeLyOrAlfXJPHW14PWSfJ1eStgTB8oasNuE3940S0+e9rMWdwurClaxcMRC4h06r4YKPz09gkg3xtS2LxhjagBLhqn01NcTO2UK0SNHWvH0IWdbYS3jspKItofcwWLQW1O4hiZXkzYvqbDV008Nr4h0XJ4hIiMAE5iSzs60tJB42QIrnjrkNDrdfFRYw0WjtWNcILx6+FWGJQ7jvKzzrC5FqYDo6XjP9wPvi8g6//KlwF2BKakbBhIjfLrQnig42cQL+UU43V4WTcm2upywU9RQxKbSTfzHjP/AJnp0psJTjwLCGLNKRGYBF+HrPf0NY8zJgFb2CWwJCcTqlKHdWvTYelpdXrIHxerJ6X7mNV6+te5b2MTG4jGLrS5HqYDpbiymCf7/ZwHDgRNACTDcv27ARY8Yridbu1Fc00yrywvA/9w4HZtNf1/96Z/H/sneqr185/zvMCxxmNXlKBUw3R1B3IuvKem/u7jPAJef7cEisgh4DN+8En80xvzstPt/xcdjOcUDmcaYs8/wroPydevlrSUArPv2AkakJVhcTXhp87Txm22/YULqBJZPWG51OUoFVHdDbdzl/7/XA/KJSBTwOLAQKAa2iMhrxpi9nfb/jU7bfw3QUc76wT92lHDx2HQNhwD424G/UdJYwpMLn9RzDyrs9bQfxOdFJMl/+/si8oqIdPdhfgFw2Bhz1BjTBjwPXH+W7ZcDz/WkHvXJKupbOVrZxLyxOgxJf2toa2DFzhXMGTKHuUPnWl2OUgHX069ADxhjGkTkYuBTwNPA77t5zDCgqNNysX/dGfyXzY4C3vmE++8SkXwRya+srOxhyZFp9Z72UVst6aYS1tYUrqHWWctXZ37V6lKUGhA9DQiP//9rgSeMMf8AupvUuKszo5/Ud2IZ8JIxxtPVncaYFcaY2caY2RkZOp7Q2byxs5SxmYmMy0qyupSws754PRlxGUxLn2Z1KUoNiJ4GRImIPAksBVaKSEwPHlsM5HZazsF3FVRXlqHNS31W0dDK5oJqrpk6xOpSws6Wsi28ffxtLs25VK+iUxGjpwGxFFgNLPIPuZFK95MJbQHyRGSUiETjC4HXTt9IRMYDg4EPe1y16tLq3WUYA9dqQPS7/87/b4YlDuNrM79mdSlKDZiedpRrBl7ptFwKlHbzGIHzw6MAABvUSURBVLeI3I0vWKKAp4wxe0TkISDfGNMeFsuB540xlgzdEQ6MMXzzxR288lEJYzISGJelkwL1p90nd7Onag/3X3g/aXE6bImKHD0dauOcGGNWAitPW/fgacs/DGQNkeDDI1W88pGv78O/XzpGm0D62XP7nyPeHs91o6+zuhSlBlRAA0INjH/tq8Am8K975zM6Q48e+lNlcyWrjq3ihrwbSIzW362KLNrTJwy8s7+cS8dlaDj0M7fXzT1r78Ft3Nw4/kary1FqwGlAhLhD5Q0UVDVz+QTt99Dffr755+w6uYsfzvkheYPzrC5HqQGnTUwhzBjD/a/uJjHGzqLJOqR3f3nl0Cv8dttvqWyp5OaJN3ND3g1Wl6SUJTQgQtjukno2H6vmwesmkTko1upyQp7T46S8qZz/+vC/cBs3AF+a+iWLq1LKOhoQIeynK/eREu/g+hlDrS4l5Lk8Lj732ucoqC8A4N+n/TszMmfoZa0qomlAhKii6mY+PFrFdxaNJy0xxupyQt6qglUd4XD9mOu5e+bd1hakVBDQgAhBxhhWrD8KwFWT9NxDX7W4W/jd9t8xJnkMz133HLFR2lynFGhAhKR1Byv5y8bjfHHOCMZm6qWtffXkjicpbizmqU89RZw9zupylAoaGhAh6Ff/OsTw1Hjuv1bn5u6LOmcdIsJLh17iqhFXcX72+VaXpFRQ0YAIIW6Pl83HqtlRVMv3r51ItF27sZwrYwzL3lhGcWMxANePPdtcVkpFJg2IEPL//r6LF/J9H2iL9cqlc+bxethavrUjHADmDJ1jYUVKBScNiBBw7wvbGZuZ2BEOv1k+k8wkPZF6rp7Y8QRP7nySaFs098y6h9S4VBw2h9VlKRV0NCCCXHl9a8dIrQCv330xU3OSLawotBlj+PuhvwPw/Yu+r72klToLDYgg9/6hkwAsnJTF4ulDNRz6oLGtkR9s+AEVLRU8NPchDQeluqEBEcRezC/i2y/tZHR6Ak/ech42m87z0Bc/+vBHvHX8LSakTuBTIz9ldTlKBT29DCZIOd0eHnp9LwD/eUWehkMfFdYXsrpgNZfnXs7Ti54m3hFvdUlKBT09gghSO4rqaHC6WfGF87hKR2o9Z06Pk/veu4+3j7+Nw+bggTkPaDgo1UMaEEFo6/Fqlj75IQAXjEq1uJrQU91ajcvj4s637iQlJoXtldsBWDxmMelx6RZXp1To0IAIQve+sAOA7ywaT0p8tMXVhJZn9z3Lw5sf5rLcyzoG3xsxaAT3nnev9pRWqpc0IIJMaV0Lx6ua+cqCMfzHgrFWlxNS2jxtPLz5YQDWFq3tWH/b5Nu4fPjlVpWlVMjSgAgiW4/XsOSJDQDcdMFwi6sJLRtLN/Klt3yT+2TEZdDsbub3V/6eoYlDyYjLsLg6pUKTBkSQqG91ceufNgHw+fNyyE3VE6k90exqZkfljo7Ob2NTxvLstc9iFzuOKO0drVRfaEAEiZfyi2lq8/CPr85j6jDtDNdTv9r6K54/8DwAS/KW8P2Lvo/dpi9rpfqDvpOCwONrD/PkuiPMGp7C9NwUq8sJKfnl+YDvRPStk27VcFCqH+m7yWLFNc08svoAAN+/Tud36E55Uzl1bXW8efRNTrac5HDtYe49715un3K71aUpFXY0ICz29t5yANZ8cz5jMnR2uK4YY3j96OvkJObwjXe/QXVrdcd9CY4Erh19rYXVKRW+NCAstLukjr9tKWJCdpKGw1lsLd/K/e/f37E8PGk4eYPzuGPKHaTFpZEZn2lhdUqFLw0IC+wqrmNbUQ0P/mMPAA9o09IZypvKSYpOosZZwz1r7wF8VyiNTRnLI/Mfsbg6pSKDBsQAO9no5NO/fb9j+Y6LR3H73JHWFRSEXF4XV750JRNTJ3K07ihOj5MleUv44dwfWl2aUhEloKO5isgiETkgIodF5HufsM1SEdkrIntE5NlA1hMMVu0u67j90pfn8MB1k3Sk1tNsK98GwL7qfTg9ThaPWczXZ33d4qqUijwBO4IQkSjgcWAhUAxsEZHXjDF7O22TB9wHzDPG1IhIWDcm1zW7eOLdI4zPSmLlPZcQpcEA+I4Y1hauZd6weTy771lWHlsJQG5SLnOGzOGBOQ9YXKFSkSmQTUwXAIeNMUcBROR54Hpgb6dtvgQ8boypATDGVASwHkt5vIbvvLyDktoWnrnzQg2HTp7c8SRP7nySmKgYnB4n4Bt59ScX/8TiypSKbIEMiGFAUaflYuDC07YZByAiHwBRwA+NMatO35GI3AXcBTB8eGiOUfTajhJW7ynn0nEZzBurQ04DHKk9woMfPMjOkzsB39wNdpudC7Iv0CYlpYJAIAOiq6/IpovnzwMWADnAeyIyxRhTe8qDjFkBrACYPXv26fsIauX1rWw6Vs0LW4pJirHzh1vPs7qkoNE5HB646AE2lm7kC5O+wMzMmRZXppSCwAZEMZDbaTkHONHFNhuNMS7gmIgcwBcYWwJY14D64lOb2V/WAMA3rhxHjD3K4oqsY4yhsqUSp8fJe8XvsfPkTm6bfBuLRi1ictpklo5fanWJSqlOAhkQW4A8ERkFlADLgJtO2+ZVYDnwZxFJx9fkdDSANQ0Yl8fLidqWjnBIiXew9Pwci6uy1jP7nuHnW35OSkwKtU7fQeKnx3yacYPHWVyZUqorAQsIY4xbRO4GVuM7v/CUMWaPiDwE5BtjXvPfd5WI7AU8wLeNMVWBqmkgfFRYw/qDlbx7oJLtRb4PwVe/Oo9xWYnER0dmt5M6Zx17q/by2pHXAKh11jJ+8HgemveQhoNSQSygn1jGmJXAytPWPdjptgHu9f8LC8tWbKTN7e1YHhzvYNqw5Ijs67C5dDM7T+5kU+kmNpZu7Fg/OGYwTy58krS4NAurU0p1JzK/0gZAaV0Lb+8tPyUcHvncNC7OS4/IcDDGcMdbd5yx/s+L/sy0jGk4bDqZj1LBTgOin3zlrx91NCn97LNTyUqO5bLxYd3vr0vGGD448QHvl7x/yvrbp9xOdnw2szJnIRJ5galUKNKA6KMNR05S2eDsCIfPzhzGsgidT/rra79OrbOWreVbARCEO6feSW5SLjfk3WBxdUqp3tKA6KOb/rCp4/ZTt82OuE5wHq+Hp3Y/RZu3jTWFa0657+aJN/Ofs/7TosqUUn2lAXGOthXW4PF+3Gdvek4yl0/IsrCiwDLGsPLYShbkLiDBkUBDWwPP7nuWtLg0fr3t16dsu3DEQh646AGSopMsqlYp1R80IM5BS5uHG363oWP5vqsncMtFIyysKPA2lW3ie+99j8VjFlPeVE5VaxWHaw+fss2o5FE8f+3zxNnj9DyDUmFAA+IcbC74eMpLEbh1zkjiosO7h/Sfdv0JoKMvQ2dXDL+Ce8+7l+ioaOId8QNdmlIqQAI6H0Q42lJQzQtbirAJfPtT4/njrbPDMhyO1h7ltlW3Ud1azYaSDaf0YwDf0cKP5/2YUcmjuHPqnQwfNJzshGyLqlVKBYIeQfSA12v45os7WDA+g3ue3w7AlRMz+eplYy2uLHB+seUXbC3fyvy/ze9Y99hlj7Hy2EpGDBrB12Z+DYDrx15vVYlKqQDTgOiBjwpr+Pu2Ev6+raRj3X3XTLSwov7zxI4nePv429x73r28V/we146+ljePvsnBmoMd28RExXBpzqVclnsZlw+/3MJqlVIDSQOiB947dLLj9vkjB/Pil+daWE3f7KjcQbQtmtEpo2l2NfO77b8D4Cv/+goAz+1/DuMflf2mCTdR31bPt8//NqmxqZbVrJSyhgbEWXi9hv/7sIA3dp4gLzORrywYwxUheilrSWMJ9c56bll5CwDTMqaxs3LnGdu1h4Nd7Nw88WaGD4rMTn9KKQ2ILlU2OPnCnzZx1aQsfv2O71LO2+aO5LOzQnO4bq/xcuvKW6lo+XhG187h8Mw1z5ASk8Ltq26noqWCdTeuw4aNlNgUK8pVSgUJDYgurD9Yyf6yho65HACumBga4yrtObmH8anjefHgi8zPmU9GXAb7qvd1hMOSvCWsKVxDSkwKU9KncO3oa5mWMQ2AP1/9ZwTR5iSlFADiG3E7dMyePdvk5+cHZN/l9a3c/MdNHK5oxCbgNb4jh6nDkvnsrGFB3/krvyyf21ffzgXZF7C5bDMANrGR6EikydXEuhvXkRyTTJOrCY/xMCh6kMUVK6UGiohsNcbM7s1j9Aiik3f2V3C4ohGAhZOyWDIrh0vyMoK+n8PJlpP8YssvaHG1AHSEA/ial+rb6lmQs4DkmGQAEhwJltSplAotGhCd7CyuAyA1IZo7LxnN+SODq6nFGIPB0OZpY1/1Pv51/F+sL16PTWwcrfPN1JrgSGBa+jRunHAjxQ3FpMam8vDmh7lz2p0WV6+UCjUaEEBRdTO/XnOIf2w/wZUTs/jjF3t1FBZwJ1tOUtVSxTuF7/CXfX9hesb0M+ZbaPfSp18iJ+nUk+lXj7oau03/1Eqp3tFPDeDJ9Ud4cWsxAJ+fbf2VSk2uJmxi49Gtj+L0ONlwYgOlTaUd93cOh59e/FNqWmtYMm4J5c3lZ4QDoOGglDonEf3Jsbukjue3FLJqdxmZSTE8cN0krppkfT+Hpa8vpbCh8Kzb/PySn5Mck8y8YfM61o1OHh3o0pRSESSiA+ILf9pETbMLgN8sn8mnpw8dsOc2xlDrrGVw7OCOdWVNZQBdhsPXZ32dpOgk5ufMJ8oWRXpcZE1MpJQaeBEZEDuLa3l7b3lHOMwZnTZg/Ry2lG3hvzb+F+MGj2N1wWqWT1jOmuNruO/C+/jGu984Zdt7Zt1DVnwWbq9bp+xUSg24iOoHUdfsoqnNzZInNlBa1wrAG1+7mCnDkvuzxFP86MMfsatyF7++/Ne8VfAWK4+tZF/1vm4f9/6y9zsuS1VKqb7SfhDdWP6HjewtrWdQrO/H/sqCMUwe2r+dxQ5UH2BL2RbGDh7Ll976Usf6G/5xA83uZgBmZc4izhGHx+s5Y56FcYPHcfnwyzUclFKWi4iA+O07h2hu87C3tB6A+lY3D10/mVvnjOz357rr7buobq0mLTYNgIy4DCpbKjvCITshmxVXrSAmKoaypjKe2fcMGXEZPJL/CJflXsavL//12XavlFIDJuwDwu3x8su3Dp6yLjnOwfXTh/Xr8zyz7xleOfQK1a2+6UirWqv48vQv89UZX+XfVv8bW8q28Nhlj3HJsEtwRDkAX1h8c/Y3McaQnZDN5PTJ/VqTUkr1RVgHRJPTzY6i2o7lKJvwr3vnkxhjJzne0ad917fVYxc72yu34/a6eXz74zS0NZyyzeLRiwF45NJH+LD0QxbkLsAmZ87yKiJcNfKqPtWjlFL9LSwDYuvxaoamxLHo0feoa3ERbbfx+1tmkRIfzaj0vo1D9Mstv2RMyhge+vAhRqWM4lDNoTO2eeOGNyisLyR3UC4AaXFpXDf6uj49r1JKDbSwC4jSuhaWPPHhKetuuXAEl3cx0Y8xhjZvGw6bg4K6AkannL2jWZ2zjqf3Pt2xfHo43DHlDm4cfyNDEocwYtCIPvwUSillvbAJCGMML+YXs+dE3SnrH/ncNK6ZOqTLxzy7/1l+tvlnLBu/jOcPPM/fF/+dsYPHdrnvZ/Y9Q4Or4Yz7cpNyKWooAuCuaXcR74jvh59GKaWsFxYBUdfsYltRDd952TdL2uiMBLKSYrl8Qiafn53bsd2Gkg3srd7LpLRJfHjiQ/66768APH/geQB+v/P3uL1uluQtIb88n1sn3UpVaxWF9YX8fMvPAd+4Rt85/ztcPPRiYu2xiAhVLVU0tDVoOCilwkpAO8qJyCLgMSAK+KMx5men3X8b8AhQ4l/1W2PMH8+2z/aOcm6Pl79uPM6cMel86tH1HfenJkTz1G3nMyM3hZVHV5IZn0luUi5e4+XGN26kxlnT4/rnDp3LhhMbOpYX5C7gqhFX8ekxn+7xPpRSKhgEVUc5EYkCHgcWAsXAFhF5zRiz97RN/2aMubu3+1+1p4wfvn7qrm6fN5IffHoybq+bo3VH+e573yXOHocxhlZP6xn7GJ08mqXjl/LYR48xOW0y+eX5LByxkLePvw1wSjgsHLGQ/1nwP70tUymlQlYgm5guAA4bY44CiMjzwPXA6QFxTvaeqO+4nTfUw8JxYymP+V/eODqfxz56rGPguxZ3yymPu3H8jRypPcKjlz1KUnQSNrGxdPxS7GKnrKmMrIQsPij5gNTYVJa9uQwAh83BZ/M+2x9lK6VUyAhkQAwDijotFwMXdrHdEhG5FDgIfMMYU3T6BiJyF3AXQEbuMOb89XISm5YQnX4Yb1s6ZcnPU5e4mLeOrOKtwlVdFpMWm8bUjKl8/6Lvn3Gfw+brEzEk0Xcy+5KcSwBYvWQ1mfG+Qfx0TgWlVKQJ5KeedLHu9BMerwPPGWOcIvJl4Gng8jMeZMwKYAVA3MhE0+ippDH298TEfrzNa0de67gdExXDD+b8gAuHXMi9795Lelw6j172aK9/gKGJAzf8t1JKBZtABkQxkNtpOQc40XkDY0xVp8U/AD/vdq/iOWNVWmwaVa1VREkUeYPzuGHsDR0nkv9y9V8wZ+SSUkqp7gQyILYAeSIyCt9VSsuAmzpvICJDjDHtc2kuBrodB9uGjQcvepDdJ/fzuXGf4UjdEa4ZdQ0vHHiBucPmnjGrmoggXR7MKKWUOptAX+Z6DfAovstcnzLG/EREHgLyjTGvicjD+ILBDVQDXzHG7D/bPvsyH4RSSkWqc7nMNaImDFJKqUh1LgFx5tCiSimlFBoQSimlPoEGhFJKqS5pQCillOqSBoRSSqkuaUAopZTqkgaEUkqpLmlAKKWU6pIGhFJKqS5pQCillOqSBoRSSqkuaUAopZTqkgaEUkqpLmlAKKWU6lLIDfctIg3AAavr6IF04KTVRfSA1tl/QqFG0Dr7W6jUOd4Yk9SbBwRyRrlAOdDbMc2tICL5Wmf/CYU6Q6FG0Dr7WyjV2dvHaBOTUkqpLmlAKKWU6lIoBsQKqwvoIa2zf4VCnaFQI2id/S1s6wy5k9RKKaUGRigeQSillBoAGhBKKaW6FFIBISKLROSAiBwWke9ZXU87EXlKRCpEZHendaki8raIHPL/P9jiGnNFZK2I7BORPSJyT5DWGSsim0Vkh7/OH/nXjxKRTf46/yYi0VbW2U5EokRkm4i84V8OujpFpEBEdonI9vZLHYPt7+6vKUVEXhKR/f7X6Zxgq1NExvt/j+3/6kXk60FY5zf875/dIvKc/33V69dmyASEiEQBjwNXA5OA5SIyydqqOvwZWHTauu8Ba4wxecAa/7KV3MA3jTETgYuAr/p/f8FWpxO43BgzHZgBLBKRi4CfA7/y11kD3GFhjZ3dA+zrtBysdV5mjJnR6Xr9YPu7AzwGrDLGTACm4/u9BlWdxpgD/t/jDOA8oBn4O0FUp4gMA/4TmG2MmQJEAcs4l9emMSYk/gFzgNWdlu8D7rO6rk71jAR2d1o+AAzx3x6Cr4Of5XV2qu8fwMJgrhOIBz4CLsTXU9Xe1WvBwvpy8H0YXA68AUiQ1lkApJ+2Lqj+7sAg4Bj+C2eCtc7TarsK+CDY6gSGAUVAKr7O0G8AnzqX12bIHEHw8Q/drti/LlhlGWNKAfz/Z1pcTwcRGQnMBDYRhHX6m222AxXA28ARoNYY4/ZvEix/+0eB7wBe/3IawVmnAd4Ska0icpd/XbD93UcDlcD/+pvs/igiCQRfnZ0tA57z3w6aOo0xJcAvgUKgFKgDtnIOr81QCgjpYp1eo9tLIpIIvAx83RhTb3U9XTHGeIzvED4HuACY2NVmA1vVqUTkOqDCGLO18+ouNg2G1+g8Y8wsfM2zXxWRS60uqAt2YBbwhDFmJtBEcDR7dcnffr8YeNHqWk7nP/9xPTAKGAok4Pvbn67b12YoBUQxkNtpOQc4YVEtPVEuIkMA/P9XWFwPIuLAFw7PGGNe8a8OujrbGWNqgXfxnTNJEZH2scOC4W8/D1gsIgXA8/iamR4l+OrEGHPC/38FvvbyCwi+v3sxUGyM2eRffglfYARbne2uBj4yxpT7l4OpziuBY8aYSmOMC3gFmMs5vDZDKSC2AHn+M/HR+A7vXrO4prN5Dfii//YX8bX5W0ZEBPgTsM8Y8z+d7gq2OjNEJMV/Ow7fi30fsBb4nH8zy+s0xtxnjMkxxozE91p8xxhzM0FWp4gkiEhS+2187ea7CbK/uzGmDCgSkfH+VVcAewmyOjtZzsfNSxBcdRYCF4lIvP993/677P1r0+oTPb08+XINcBBfm/T9VtfTqa7n8LX1ufB9E7oDX3v0GuCQ//9Ui2u8GN8h5U5gu//fNUFY5zRgm7/O3cCD/vWjgc3AYXyH9TFW/9071bwAeCMY6/TXs8P/b0/7+ybY/u7+mmYA+f6//avA4CCtMx6oApI7rQuqOoEfAfv976G/ADHn8trUoTaUUkp1KZSamJRSSg0gDQillFJd0oBQSinVJQ0IpZRSXdKAUEop1SUNCBV2/KOC/ken5aEi8lIAnueHIlIiIg/19757+PxrRaRRRGZ3v7VSvacBocJRCtAREMaYE8aYz51l+774lTHmwQDtm049X89gjLkMX78BpQJCA0KFo58BY/zj9T8iIiPFP1eHiNwmIq+KyOsickxE7haRe/0DxG0UkVT/dmNEZJV/gLv3RGTC2Z5QRGz+cfYzOi0fFpF0f+/wl0Vki//fPP82F4jIBv9zb2jvReyv8UUReR3fIHtDRGS9/+fZLSKXBPKXp1S7T/x2olQI+x4wxfgG/GsfvbazKfhGs43F16v0u8aYmSLyK+BWfGMqrQC+bIw5JCIXAr/DN95Sl4wxXhH5K3Cz//FXAjuMMSdF5Fl8Rxrvi8hwYDW+AQj3A5caY9wiciXwU2CJf5dzgGnGmGoR+Sa+oZl/4p8XJb5Pvx2lekgDQkWitcaYBqBBROqA1/3rdwHT/CPezgVe9A1lA/iGKujOU/jGt3kU+Dfgf/3rrwQmddrXIP/4SMnA0yKSh28YFEenfb1tjKn2394CPOUfbPFVY8z2Xv20Sp0jDQgViZydbns7LXvxvSds+MbOn9GbnRpjikSkXEQuxzfJ0c3+u2zAHGNMS+ftReQ3+MLqBv9Rzrud7m7qtN/1/iG6rwX+IiKPGGP+rze1KXUu9ByECkcNQNK5Ptj45sk4JiKfB99IuCIyvYcP/yPwV+AFY4zHv+4t4O72DUSkPXiSgRL/7ds+aYciMgLf3BN/wDci76we1qJUn2hAqLBjjKkCPvCf0H3kHHdzM3CHiLSPgnp9Dx/3GpDIx81L4J8fWER2ishe4Mv+9b8AHhaRD/DNG/xJFgDbRWQbvnMUj/X4p1CqD3Q0V6XOkYj8EGg0xvyy07rZ+E5ID8iVRiLyLvAtY4xe7qr6nR5BKHXuGoG72jvKicj38M3Yd99APLmIrMU3xr9rIJ5PRR49glBKKdUlPYJQSinVJQ0IpZRSXdKAUEop1SUNCKWUUl3SgFBKKdWl/w+6c9i/N8LhugAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot mean sea ice cover\n",
+ "da1=get_var(DS1,\"sic\",False)\n",
+ "da2=get_var(DS2,\"sic\",False)\n",
+ "da3=get_var(DS3,\"sic\",False)\n",
+ "da4=get_var(DS4,\"sic\",False)\n",
+ "da5=get_var(DS5,\"sic\",False)\n",
+ "da6=get_var(DS6,\"sic\",False)\n",
+ "\n",
+ "da1_Jor=get_var(DS1_Jor,\"sic\",True)\n",
+ "da2_Jor=get_var(DS2_Jor,\"sic\",True)\n",
+ "da3_Jor=get_var(DS3_Jor,\"sic\",True)\n",
+ "da4_Jor=get_var(DS4_Jor,\"sic\",True)\n",
+ "da5_Jor=get_var(DS5_Jor,\"sic\",True)\n",
+ "da6_Jor=get_var(DS6_Jor,\"sic\",True)\n",
+ "da7_Jor=get_var(DS7_Jor,\"sic\",True)\n",
+ "da8_Jor=get_var(DS8_Jor,\"sic\",True)\n",
+ "\n",
+ "\n",
+ "#mean_lat = np.arcsin(1-np.mean(da1[95:150,:])) * (180./np.pi) \n",
+ "#med_lat = np.arcsin(1-np.median(da1[95:150,:])) * (180./np.pi) \n",
+ "\n",
+ "\n",
+ "da1.plot()\n",
+ "da2.plot()\n",
+ "da3.plot()\n",
+ "da4.plot()\n",
+ "da5.plot()\n",
+ "da6.plot()\n",
+ "\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"sic []\")\n",
+ "plt.title(\"winton global sea ice cover\")\n",
+ "plt.ylim(0,1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1_Jor.time,np.squeeze(da1_Jor.values),'-')\n",
+ "plt.plot(da2_Jor.time,np.squeeze(da2_Jor.values),'-')\n",
+ "plt.plot(da3_Jor.time,np.squeeze(da3_Jor.values),'-')\n",
+ "plt.plot(da4_Jor.time,np.squeeze(da4_Jor.values),'-')\n",
+ "plt.plot(da5_Jor.time,np.squeeze(da5_Jor.values),'-')\n",
+ "plt.plot(da6_Jor.time,np.squeeze(da6_Jor.values),'-')\n",
+ "plt.plot(da7_Jor.time,np.squeeze(da7_Jor.values),'-')\n",
+ "plt.plot(da8_Jor.time,np.squeeze(da8_Jor.values),'-')\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"sic []\")\n",
+ "#plt.title(\"hice_unlim global sea ice cover\")\n",
+ "plt.ylim(0.45,1)\n",
+ "plt.xlim(0,80)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "#plt.legend([experiment1, experiment2, experiment3, experiment4],loc=4)\n",
+ "\n",
+ "# sea ice latitude\n",
+ "ice_lat1 = np.arcsin(1-da1) * (180./np.pi) \n",
+ "ice_lat2 = np.arcsin(1-da2) * (180./np.pi) \n",
+ "ice_lat3 = np.arcsin(1-da3) * (180./np.pi) \n",
+ "ice_lat4 = np.arcsin(1-da4) * (180./np.pi) \n",
+ "ice_lat5 = np.arcsin(1-da5) * (180./np.pi) \n",
+ "ice_lat6 = np.arcsin(1-da6) * (180./np.pi) \n",
+ "\n",
+ "\n",
+ "\n",
+ "ice_lat1_Jor = np.arcsin(1-da1_Jor) * (180./np.pi) \n",
+ "ice_lat2_Jor = np.arcsin(1-da2_Jor) * (180./np.pi) \n",
+ "ice_lat3_Jor = np.arcsin(1-da3_Jor) * (180./np.pi) \n",
+ "ice_lat4_Jor = np.arcsin(1-da4_Jor) * (180./np.pi) \n",
+ "ice_lat5_Jor = np.arcsin(1-da5_Jor) * (180./np.pi) \n",
+ "ice_lat6_Jor = np.arcsin(1-da6_Jor) * (180./np.pi) \n",
+ "ice_lat7_Jor = np.arcsin(1-da7_Jor) * (180./np.pi) \n",
+ "ice_lat8_Jor = np.arcsin(1-da8_Jor) * (180./np.pi) \n",
+ "\n",
+ "#print(da1[0,:])\n",
+ "#print(ice_lat1[0,:])\n",
+ "\n",
+ "\n",
+ "l1,=ice_lat1.plot(color='C0')\n",
+ "l2,=ice_lat2.plot(color='C1')\n",
+ "l3,=ice_lat3.plot(color='C2')\n",
+ "l4,=ice_lat4.plot(color='C3')\n",
+ "l5,=ice_lat5.plot(color='C4')\n",
+ "l6,=ice_lat6.plot(color='C5')\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,220)\n",
+ "\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "plt.title(\"\")\n",
+ "plt.legend(handles=[l1,l4,l2,l5,l3,l6],labels=[experiment1[9:-7], experiment4[9:-7], experiment2[9:-7], experiment5[9:-7], experiment3[9:-7], experiment6[9:-7]]\n",
+ " ,loc=1, \n",
+ " ncol=3, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"none\",\n",
+ " borderpad=0.5,borderaxespad=0.2)\n",
+ "plt.xlim(0,200)\n",
+ "plt.savefig(\"plots/winton_icelat_overview.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "lj1, = plt.plot(da1_Jor.time,np.squeeze(ice_lat1_Jor),'-',color='C0')\n",
+ "lj2, = plt.plot(da2_Jor.time,np.squeeze(ice_lat2_Jor),'-',color='C0')\n",
+ "lj3, = plt.plot(da3_Jor.time,np.squeeze(ice_lat3_Jor),'-',color='C1')\n",
+ "lj5, = plt.plot(da5_Jor.time,np.squeeze(ice_lat5_Jor),'-',color='C2')\n",
+ "lj6, = plt.plot(da6_Jor.time,np.squeeze(ice_lat6_Jor),'-',color='C2')\n",
+ "lj8, = plt.plot(da8_Jor.time,np.squeeze(ice_lat8_Jor),'-',color='C3')\n",
+ "lj4, = plt.plot(da4_Jor.time,np.squeeze(ice_lat4_Jor),'--',color='C1')\n",
+ "lj7, = plt.plot(da7_Jor.time,np.squeeze(ice_lat7_Jor),'--',color='C2')\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,62)\n",
+ "plt.xlim(0,50)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "plt.legend(handles=[lj1,lj3,lj5,lj8],\n",
+ " labels=[experiment1_Jor[9:-13], experiment3_Jor[9:-13], experiment5_Jor[9:-13], experiment8_Jor[9:-13]],loc=2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2,\n",
+ " ) # ,\n",
+ "plt.savefig(\"plots/winton_icelat_Jor_overview.svg\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'\\nf1_Jor=stability_index(DS1_Jor)\\nf2_Jor=stability_index(DS2_Jor)\\nf3_Jor=stability_index(DS3_Jor)\\nf4_Jor=stability_index(DS4_Jor)\\nf5_Jor=stability_index(DS5_Jor)\\nf6_Jor=stability_index(DS6_Jor)\\nf7_Jor=stability_index(DS7_Jor)\\nf8_Jor=stability_index(DS8_Jor)\\n\\n\\nprint(experiment1 +\" f=\" +str(f1[-1].values))\\nprint(experiment2 +\" f=\" +str(f2[-1].values))\\nprint(experiment3 +\" f=\" +str(f3[-1].values))\\nprint(experiment4 +\" f=\" +str(f4[-1].values))\\nprint(experiment5 +\" f=\" +str(f5[-1].values))\\nprint(experiment6 +\" f=\" +str(f6[-1].values))\\n\\n\\nprint(experiment1_Jor +\" f=\" +str(f1_Jor[-1].values))\\nprint(experiment2_Jor +\" f=\" +str(f2_Jor[-1].values))\\nprint(experiment3_Jor +\" f=\" +str(f3_Jor[-1].values))\\nprint(experiment4_Jor +\" f=\" +str(f4_Jor[-1].values))\\nprint(experiment5_Jor +\" f=\" +str(f5_Jor[-1].values))\\nprint(experiment6_Jor +\" f=\" +str(f6_Jor[-1].values))\\nprint(experiment7_Jor +\" f=\" +str(f7_Jor[-1].values))\\nprint(experiment8_Jor +\" f=\" +str(f8_Jor[-1].values))'"
+ ]
+ },
+ "execution_count": 32,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "#plot stability index\n",
+ "f1=stability_index(DS1)\n",
+ "f2=stability_index(DS2)\n",
+ "f3=stability_index(DS3)\n",
+ "f4=stability_index(DS4)\n",
+ "f5=stability_index(DS5)\n",
+ "#f6=stability_index(DS6)\n",
+ "\"\"\"\n",
+ "f1_Jor=stability_index(DS1_Jor)\n",
+ "f2_Jor=stability_index(DS2_Jor)\n",
+ "f3_Jor=stability_index(DS3_Jor)\n",
+ "f4_Jor=stability_index(DS4_Jor)\n",
+ "f5_Jor=stability_index(DS5_Jor)\n",
+ "f6_Jor=stability_index(DS6_Jor)\n",
+ "f7_Jor=stability_index(DS7_Jor)\n",
+ "f8_Jor=stability_index(DS8_Jor)\n",
+ "\n",
+ "\n",
+ "print(experiment1 +\" f=\" +str(f1[-1].values))\n",
+ "print(experiment2 +\" f=\" +str(f2[-1].values))\n",
+ "print(experiment3 +\" f=\" +str(f3[-1].values))\n",
+ "print(experiment4 +\" f=\" +str(f4[-1].values))\n",
+ "print(experiment5 +\" f=\" +str(f5[-1].values))\n",
+ "print(experiment6 +\" f=\" +str(f6[-1].values))\n",
+ "\n",
+ "\n",
+ "print(experiment1_Jor +\" f=\" +str(f1_Jor[-1].values))\n",
+ "print(experiment2_Jor +\" f=\" +str(f2_Jor[-1].values))\n",
+ "print(experiment3_Jor +\" f=\" +str(f3_Jor[-1].values))\n",
+ "print(experiment4_Jor +\" f=\" +str(f4_Jor[-1].values))\n",
+ "print(experiment5_Jor +\" f=\" +str(f5_Jor[-1].values))\n",
+ "print(experiment6_Jor +\" f=\" +str(f6_Jor[-1].values))\n",
+ "print(experiment7_Jor +\" f=\" +str(f7_Jor[-1].values))\n",
+ "print(experiment8_Jor +\" f=\" +str(f8_Jor[-1].values))\"\"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x720 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "save_plot = True\n",
+ "plot_winton = True\n",
+ "plot_unlim = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "\n",
+ "fig, ax = plt.subplots(2,figsize=(6,10))\n",
+ "ax[0].spines['left'].set_position(('outward',5))\n",
+ "ax[1].spines['left'].set_position(('outward',5))\n",
+ " \n",
+ " \n",
+ "# color_winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='lightgray'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation(ax[0],1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation(ax[0],2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation(ax[0],3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation(ax[0],3000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],5000, 38.9, 54.3, color_winton, 4)\n",
+ " plot_simulation(ax[0],10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation(ax[0],3000, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],4219, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[0],4219, 16.6, 0, color_winton, 1)\n",
+ " \n",
+ " \n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " \n",
+ " a=plot_simulation(ax[0],1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[0],1594, 90, 49.54, color_unlim, 3)\n",
+ " plot_simulation(ax[0],1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation(ax[0],1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation(ax[0],2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation(ax[0],3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation(ax[0],3000, 14.46, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[0],3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation(ax[0],3750, 14.46, 0, color_unlim, 1) \n",
+ " plot_simulation(ax[0],3750, 19.2, 18.7, color_unlim, 4)\n",
+ " plot_simulation(ax[0],3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation(ax[0],4063, 14.46, 11.5, color_unlim, 3)\n",
+ " plot_simulation(ax[0],4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation(ax[0],4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation(ax[0],5000, 14.46, 24, color_unlim, 4)\n",
+ " plot_simulation(ax[0],5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation(ax[0],5000, 90, 90, color_unlim, 1) # limited, but no ice at all\n",
+ " plot_simulation(ax[0],10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ "\n",
+ "ax[0].set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax[0].set_ylim(-0.1,1.1)\n",
+ "ax[0].set_xlim(1000,10500)\n",
+ "ax[0].set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax[0].set_ylabel(\"Ice Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax[0].spines['right'].set_color('none')\n",
+ "ax[0].spines['top'].set_color('none')\n",
+ "ax[0].yaxis.tick_left()\n",
+ "ax[0].xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "\n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='lightgray'\n",
+ " \n",
+ " a=plot_simulation(ax[1],1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[1],1594, 90, 49.54, color_unlim, 3)\n",
+ " plot_simulation(ax[1],1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation(ax[1],1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation(ax[1],2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation(ax[1],3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation(ax[1],3000, 14.46, 0, color_unlim, 1)\n",
+ " plot_simulation(ax[1],3000, 22.05, 22.83, color_unlim, 4)\n",
+ " plot_simulation(ax[1],3750, 14.46, 0, color_unlim, 1) \n",
+ " plot_simulation(ax[1],3750, 19.2, 18.7, color_unlim, 4)\n",
+ " plot_simulation(ax[1],3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation(ax[1],4063, 14.46, 11.5, color_unlim, 3)\n",
+ " plot_simulation(ax[1],4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation(ax[1],4375, 14.46, 18.2, color_unlim, 4)\n",
+ " plot_simulation(ax[1],5000, 14.46, 24, color_unlim, 4)\n",
+ " plot_simulation(ax[1],5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation(ax[1],5000, 90, 90, color_unlim, 1) # limited, but no ice at all\n",
+ " plot_simulation(ax[1],10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ " \n",
+ "# winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='C1'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation(ax[1],1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation(ax[1],2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation(ax[1],3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation(ax[1],3000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 15.3, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],5000, 38.9, 54.3, color_winton, 4)\n",
+ " plot_simulation(ax[1],10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation(ax[1],3000, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],4219, 30.2, 0, color_winton, 1)\n",
+ " plot_simulation(ax[1],4219, 16.6, 0, color_winton, 1)\n",
+ "\n",
+ "\n",
+ "ax[1].set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax[1].set_ylim(-0.1,1.1)\n",
+ "ax[1].set_xlim(1000,10500)\n",
+ "ax[1].set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax[1].set_ylabel(\"Ice Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax[1].spines['right'].set_color('none')\n",
+ "ax[1].spines['top'].set_color('none')\n",
+ "ax[1].yaxis.tick_left()\n",
+ "ax[1].xaxis.tick_bottom()\n",
+ "\n",
+ "ax[0].text(-0.1,1,\"a)\", transform=ax[0].transAxes, fontsize=14)\n",
+ "ax[1].text(-0.1,1,\"b)\", transform=ax[1].transAxes, fontsize=14)\n",
+ "\n",
+ "ax[0].set_xscale('log')\n",
+ "ax[1].set_xscale('log')\n",
+ "\n",
+ "ax[0].set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax[0].set_xticklabels([1000, '','','',5000,'','','','',10000] )\n",
+ "ax[1].set_xticks(np.linspace(1000,10000,10) )\n",
+ "ax[1].set_xticklabels([1000, '','','',5000,'','','','',10000] )\n",
+ "\n",
+ "ax[0].set_yticklabels([0,10,20,30,45,60,90])\n",
+ "ax[1].set_yticklabels([0,10,20,30,45,60,90])\n",
+ "\n",
+ "#plt.legend((a,b),(\"Winton\", \"Semtner hice_unlim\"))\n",
+ "if save_plot:\n",
+ " if plot_winton:\n",
+ " plt.savefig(\"plots/bifurcation_winton.svg\",dpi=500)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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ISHuWSg1kCqH/qi0A7j6HcPuuiIh0YqkkkF7u/lqTsoZcBCMiIsUjlQTyvpntQ+hUETM7E1iV06hERKTda+lBwrhvErpz/4SZrQDeJYPOFUVEpGNpNYG4+xLgBDPbBShx9/W5D0tERLKuaw+A+mxtzkKnu0lmmH23pRXd/XfZCqI1ZjYjGlhqhxDytX8RkQ7EsrWhlmog8X6wRhJGD3wkmv4C8EK2AhARkeLUbA1k2wJmTwNnxC9dmVkf4F53PzkP8cVjUA1ERCQ7slYDSeUurGHA5oTpzUBFtgIQEZHilMpdWP8DvGZmDxJ+9X8RuCOnUYmISLvX6iUsADMbAxwbTb7g7q/nNKqd969LWCIi2ZG1S1iptIEMS1bu7u9lK4jWKIGIiGRNXu7Ciqtm+5d1T2BvYBFwYLaCEBGR4pPKg4QHJ05Hl7O+nrOIRESkKKQ9Hoi7zyI8FyIiIp1YqzWQJk+klwBjgH/nLCIRESkKqbSB9El430BoE7k/N+GIiEixSCWBLHD3exMLzOzLwL3NLC8iIp1AKm0gV6RYJiIinUizNRAz+zxwCjDEzP6QMKsvGpFQRKTTa+kS1kpgBnAaMDOhfD3wnVwGJSIi7V8qT6J3cfeC1jj0JLqISNbk/kl0M7vH3c8CXjeznb6s3X1UtoIQEZHi09IlrMnR31PzEYiIiBSXZu/CcvdV0dtL3X1p4gu4ND/hiYhIe5XKbbwnJin7fLYDERGR4tJSG8g3CDWN4WY2J2FWH+ClXAcmIiLtW7N3YZlZGbAr8EugMmHWenf/IA+xJcaiu7BERLIjfwNKbVvQbADQIz6tAaVERIpS1hJIq20gZvYFM1sMvAtMB2qAJ1JYr4eZvWZmb5jZfDO7Kirf28xeNbPFZna3mXVr4zGIiEgBpNKI/jPgSOAtd98bGEdqbSCbgOPd/RBgNHCymR0J/Ar4vbuPAD4ELsoochFpH+qWh5fsrIOfm1QSyBZ3/w9QYmYl7v4cISG0yIMN0WTX6OXA8cB9UflUYEL6YYtIu7FlY3jJzjr4uUmlO/daM+sNvADcaWZrSbEzRTMrJfSjtS/wJ+AdoDaha5TlwJBm1p0ETIomd09lfyIikj+p1EBOBz4mdKD4JCEJpPR0urtvdffRQDlwBLB/ssWaWfdmdx8bNZ6/n8r+REQkf1qtgbj7R9HbRsIlJ8zsJeDoVHfi7rVm9jyhLaVfQgeN5YRef0VEpMikUgNJZlhrC5jZHmbWL3rfEzgBWAg8B5wZLTYReDjDGEREpIBSaQNJJpVnMAYBU6N2kBLgHnd/zMwWAHeZ2c+A14FbMoxBREQKqKWuTL7U3CygZ2sbdvc5wKFJypcQ2kNERKSItVQD+UIL8x7LdiAiIlJcmk0g7v61fAYiIiLFJdNGdBER6eSUQEREJCNKICIikpFUeuPtZWb/bWZToukRZqZx0kVEOrlUaiC3EXrW/VQ0vZzQQ6+IiHRiqSSQfdz918AWAHevJ4sDkoiISHFKJYFsjroicQAz24dQIxERkU4sla5MfkrohXeomd1J6ETxglwGJSIi7V8qvfE+Y2azCD3pGjDZ3dW9uohIJ5fKXVhjgL2AVYSu14eZ2T5mlmlHjCIiUgBr122korL6yYrK6oHZ2F4qSeAGYAwwh1ADOSh639/MLnH3p7MRiIiI5NZN05dA6Mz2B8B327q9VBrRa4BDo9EBDyP0sDuPML7Hr9sagIiI5N7adRu5d8YygK8CE7NRC0klgXzC3efHJ9x9ASGhLGnrzkVEJD9umr6Ezx04EGAJcAehFtImqSSQRWZ2o5kdF71uAN4ys+5Ez4aIiEj7tXbdRu6ftZyzDx8aL/o1WaiFpJJALgDeBr4NfIeQvS4gJI/PtmXnIiKSezdNX8IZY8rp37sbADVV41eRhVpIKrfx1gO/jV5NbWjLzkVEJPfmLK9lxtIPufWldwEWVVRWx2e91JbttjSk7VxaGPvc3Ue1ZcciIpIf933jKACW/HsDx/92+siaqvFvZWO7LdVA4j3ufjP6+z/R33OBj7OxcxERKV4tDWm7FMDMjnb3oxNmVZrZS8DVuQ5ORETar1Qa0Xcxs2PiE2Z2FLBL7kISEZFikMqT6BcBt5pZGaFNpA64MKdRiYhIu5fKXVgzgUPMrC9g7l6X+7BERKS9a/YSlpldl/B+sruviycPM7s9D7GJiEg71lIbyKcT3k9sMq/VW3jNbKiZPWdmC81svplNjsp3M7NnzGxx9HfXDOIWEZECaymBWDPvU9UAfM/d9yeMJfJNMzsAqASmufsIYFo0LSIiRaalNpCSqHZQkvA+nkhKW9uwu68ijCGCu683s4XAEOB04DPRYlOB54EfZhK8iIgUTksJpAyYyfakMSthXrNPqCdjZhWEbuBfBfaMkgvuvsrMBjSzziRgUjS5ezr7ExGR3GvpQcKKbOzAzHoD9wPfdvd1ZqldDXP3m4Gbo23MyEYsIiKSPak8SLiNmcXSXL4rIXnc6e4PRMVrzGxQNH8QsDadbYqISPuQVgIBTkt1QQtVjVuAhe7+u4RZj7D9rq6JwMNpxiAiIu1Augkknbuxjgb+CzjezGZHr1OAKuBEM1sMnBhNi4h0OmvXbeT8W19j7fqNhQ4lI6l0ZZLosFQXdPcXaT7hjEtzvyIiHc5N05fwxrJa/jx9Cf996gGFDidtrdZAzGw/M5tmZvPcvdHMRpnZT/IRnIhIR7V23UbunbGM674ymvtnLS/KWkgql7CmAFcQjX/u7nOAs3MZlIhIR3fT9CV87sCB7NW/F186tJw/T19S6JDSlkoC6eXurzUpa8hFMCIincHadRu5f9Zyzj58KACXHDe8KGshqSSQ981sH6KHB83sTKInzEVEJH03TV/CGWPK6d+7GwAD+vYoylpIKo3o3yQ80PcJM1sBvAucl9OoREQ6sDnLa5mx9ENufendHcrH7lVcfcumMh7IEuAEM9sFKHH39bkPS0Sk47rvG0cBsOTfGwAYvkfvQoaTsVTuwvqFmfVz94+iThF3NbOf5SM4EZGiVLc8vDq4VNpAPu/utfEJd/8QOCV3IYmIFLktG8Org0slgZSaWff4hJn1BLq3sLyIiHQCqTSi/xWYZma3Ee7EupAwjoeIiHRiqTSi/9rM5hK6HzHgGnd/KueRiUj71gmu8Xc469dwdumzA2H8W9nYXEp9Ybn7E8AT2dihiHQQneAaf4fTsIkyPuqRrc01m0DMbD3JRx40wN29b7aCEBGR4tPSiIR98hmIiIgUl3THAxERSWplbT0ra+sLHUZa2hpzMR5zNqU7HoiISFIbt2wtdAhpa2vMbV2/R9fSNq2f9v66GLta9npsVAIRESmQwf165nd/fbtySZfHVmdre7qEJSIiGVECERGRjCiBiIhIRpRAREQkI0ogIiKSEd2FJSKSpjNvfJkZSz/cqXzsXrtuGyyqM1ACERFJ06jyfowq78d5Rw4DwoiCVz+6ALMCB5ZnuoQlIpKmS44bzv2zlvOfDZsBWLtuIw+8vpyvHze8wJHllxKIiEiaBvTtwRljyrl35nJ6dC3lpulLOGNMOQP6ZK2j26KgBCIikoFLjhvOU/NX88FHmztl7QOUQEREMhKvhZz7l1c7Ze0DcphAzOxWM1trZvMSynYzs2fMbHH0d9dc7V9EJNcuOW44hwzt1ylrH5DbGsjtwMlNyiqBae4+ApgWTYuIFKUBfXtwx4VHdMraB+Qwgbj7C8AHTYpPB6ZG76cCE3K1fxERya18Pweyp7uvAnD3VWY2oLkFzWwSMCma3D0fwYmISOrabSO6u9/s7mPdfSzwfqHjERGRHeU7gawxs0EA0d+1ed6/iIhkSb4TyCPAxOj9RODhPO9fRESyJJe38f4d+Ccw0syWm9lFQBVwopktBk6MpkVEpAjlrBHd3c9pZta4XO1TRETyp902oouISPumBCIiIhlRAhERkYwogYiISEaUQEREJCNKICIikhElEBERyYgSiIiIZEQJREREMqIEIiIiGVECERGRjCiBiIhIRpRAREQkI0ogIiKSESUQERHJiBKIiIhkRAlEREQyogQiIiIZUQIREZGMKIGIiEhGlEBERCQjSiAiIpIRJRAREcmIEoiIiGRECURERDKiBCIiIhlRAhERkYwogYiISEaUQEREJCPm7vnfqdnJwPVAKfAXd69qZfkZ7j62SXH+A++AHnp9Bdc+tYiVtfUM7teTy08ayYRDhxQ6rNTMuQemXQ11y6GsHMZdCaPOKnRU7TeubLnpGFg9d9vkKZt+wQKv2GmxAwb15fHJx+YxsNSdcv0/WLBq3U7lbY65ybnZycCD4ZIXM99+ppqPazaxukMz3WzeayBmVgr8Cfg8cABwjpkdkO84JCSPKx6Yy4raehxYUVvPFQ/M5aHXVxQ6tNbNuQcevQzqlgEe/j56WShXXLlVfgSUdts2OaZkMV3ZssMiXUuNMXvtmu/IUjZmWD+6ltoOZVmJucm52UFptzC/EJLHtQl4uS2bLcQlrCOAt919ibtvBu4CTi9AHJ3etU8ton7L1h3K6rds5dqnFhUoojRMuxq21O9YtqU+lBdSe40rm477Adj2r47LujxISZMLAqVmXDZu33xHlrLLxo2gxHZMIFmJucm52YGVwHE/bNv2M5U8rkbgmrZsthAJZAiwLGF6eVS2AzObZGYzzGwG0CPJdkyvtr1W1NYnvQwYlRc8vhZfdcuSX8IM5Yorl68+A42GjTcSfsEywGr5cul0umyvhWza2NB4w4A+PQofazOvAX172KaGxm3HkLWYm5ybBJto2HgDffZsF/9m0d/biNWtpg0KkUAsSdlO/+nc/WZ3Hxu9DspDXJ3Re2mWtyftNfb2Gle2XUPC/9vLujxI6fbJNv+yzZPEY8hmzDucmxxsP1NZP95CJJDlwNCE6XJgZQHiEPgR8HGTso+j8m0qKqtj+QooDSnFXgCpxxUri+UhntyI1a0CbiN8Ec0bYLWNnyqZPy+avq2manybftnmQ03V+MRjyF7MTc5NfPtt/bWf5biyEk8hEsi/gBFmtreZdQPOBh4pQBydXk3V+L8BFwNLCb9MlgIXR+WJfprv2FoVq0sae1ReLHG1v/OanmuAF4FzgRdH2rJzo+lC/9JOR/wYsh3zDucmB9vPVFaPt1C38Z4CXEe4jfdWd/953oOQlFVUVntN1fhklx6lLWJlTqxO51WKVkESSDaY2TxgY6Hj6Ay6Ddz3sM2r355Z6DiybHfg/UIGcNigksNmrmrsKOe14Oczz4r5eHtkq125SzY2UiAbkzxcKDkQ1UA61Llu5uHU/Ao1kA5xXtvF+cyjYj7e6M7WrFBXJiIikhElEEnFVYUOoIPSeZWiVsxtIJPc/eZCxyHFSZ+f7Ops57OYjzebsRdtAhERkcLSJSwREclIMd+FJRmqqKy+FTgVWFtTNf6gqCxGeADu39FiP6qpGv94wjrDgAVArKZq/G8qKqtHAncnbHY4cGVN1fjr8nAI7VOsbChwBzCQ8LTvzcTqridWdg2hw9BGYC1wAbG6lQnrHQ68AnyFWN19CeV9gYXAg8TqvpWvwxBJVbupgZjZrWa2Nnq+I162m5k9Y2aLo7+7RuVmZn8ws7fNbI6ZjUlYZ2K0/GIzm1iIYykCtwMnJyn/fU3V+NHR6/Gm84An4hM1VeMXxZcFDiN01/FgrgJujZkNNbPnzGyhmc03s8lReT4/Qw3A94jV7Q8cCXyTWNkBwLXE6kYRqxsNPAZcuW2NWFkp8CvgqSTbuwaYnt6ZyB4z62Fmr5nZG9E5vSoq39vMXo3Oz91RjxKYWfdo+u1ofkXCtq6IyheZ2UmFOaLWmVmpmb1uZo9F00VxrGZWY2ZzzWx2/DbdfHz2200CIfmXWiUwzd1HANOiaQhjiYyIXpOAGyGcMEL3EJ8kdBv/0/hJk+1qqsa/AHyQ6vIVldUTgCXA/GYWGQe8U1M1fmkWwstUA/A9d9/25R2NM5O/z1CsbhWxulnR+/WE2sMQYnWJIxftwo4d7f1f4H5CzSRhW2WHAXsCT6e079zYBBzv7ocAo4GTzexIQsL7fXROPwQuipa/CPjQ3fcl/OD4FUD073A2cCDh//gN0bhA7dFkwr9bXK1Bsj8AAAj2SURBVDEd62fdfXTC8yk5/+y3mwTi7sm+1E4HpkbvpwITEsrv8OAVoJ+ZDQJOAp5x9w/c/UPgGZL/0pbkvlVRWT2norL61orK6l0BKiqrdwF+SMu3nJ4N/D0fATbH3Ve5+6zo/fYv70J9hmJlFcChwKvR9M+JlS0j9I10ZVQ2BPgicFOTdUuA3wKXp73fLIrOzYZosmv0cuB4IH6prek5jZ/r+4BxZmZR+V3uvsnd3wXeJnxBtStmVg6MB/4STRvFfaw5/+y3mwTSjD3dfRWELwhgQFTe3JgiKY01IkndCOxD+KW5ivAFBiFx/L6mavyGZCtVVFZ3A04D7s1HkKmILifEv7zz/xmKlfUm1Cq+va32Eav7MbG6ocCdQLw94zrgh8TqtjbZwqXA48TqllFg0SWd2YQa0jPAO0CtuzdEiySen23nLppfB/SneP5fXgf8gNBWBSH2YjlWB542s5lmNikqy/lnv1gb0ZsbUySlsUZkZzVV49fE31dUVk8hXKuHUJ09s6Ky+tdAP6CxorJ6Y03V+D9G8z8PzEpcv5DMbNuXt7uvM2u2r8LcfIZiZV2j/d9JrO6BJEv8DagmXCoYC9xFrAxC30qnECtrAD4FHEus7FKgN9CNWNkGYnWVSbaXU+6+FRhtZv0IbVz7J1ss+lu0/y/N7FRgrbvPNLPPxIuTLNpej/Vod19pZgOAZ8zszRaWzVrs7T2BrDGzQe6+Kqpixa8TNzemyHLgM03Kn89DnEWvorJ6UDQ+AoTLKvMAaqrGH5uwTAzYkJA8AM6hwJev4sxs25e3u8e/vPP3GYqVGXALsJBY3e8SykcQq1scTZ0GhP/csbq9E5a5HXiMWN1DwEMJ5RcAYwuRPBK5e62ZPU9oX+pnZl2iX96J4/nEz+lyM+sClBEuSxfDGEBHA6dZ6Cm8B9CXUCMpimN195XR37Vm9iDhslnOP/vt/RLWI0D8ToCJwMMJ5edHdxMcCdRFVbSngM+Z2a5R48/nSH53S6dWUVn9d+CfwMiKyurlFZXVFwG/rqisnltRWT0H+CzwnRS20ws4EUj2SzuvouvPtwAL3f13CbPy+Rk6Gvgv4HhiZbOj1ylAFbGyecTK5kTbm9yGQ80bM9sjqnlgZj2BEwhtS88BZ0aLNT2n8XN9JvCshyeVHwHOju5c2pvQePtafo4iNe5+hbuXu3sFoU3vWXc/lyI4VjPbxcz6xN8TPmPzyMdn393bxYvwK3YVsIWQCS8iXFOcBiyO/u4WLWvAnwjXY+cCYxO2cyGh4ept4GuFPi698vb5OYZQ3Z4DzI5ep+gz1KZzOgp4PTqn84Aro/LhhC/FtwltX92j8h7R9NvR/OEJ2/pxdK4XAZ8v9LG1ctyfAR4rlmONYnwjes0HfhyV5/yzr65MREQkI+39EpaIiLRTSiAiIpIRJRAREcmIEoiIiGRECURERDKiBCIiIhlRAhERkYwogUjOmdkXzczN7BPRdD8zu7SA8VRYwrgzGW7j5TSXH2hmd5nZO2a2wMweN7P9onnlZvZwNAbDO2Z2vUXjTqSw3Qozq486PMw7M+sZjUGx2cx2L0QMUjhKIJIP5wAvErqIgNApY8ESSFtE3T+UuPtR6axD6IjweXffx90PAH4E7BnNewB4yMO4DfsROlD8eRphvePuo9NYPmvcvT7ad3vr20ryQAlEcirqHfdoQtc08QRSBewT/XK9NvoV/aaZ/cXM5pnZnWZ2gpm9FP0qPyJhe9+NlplnZt+OynYxs2oLI+fNM7OvJGxzqoVR1+4zs14JoZWa2RQLI+09HfX1hJmdZ2EUvtlm9mcL3ZlXWBjp8AZgFjDUzDYkxHR+tI83zOx/kpyGzwJb3H3buB/uPtvd/0EYb2Kju98WlW8l9EN2YZN4Uz3fSY87hfIWz72Z/Sqx1mhmMTP7XrrxSQdT6H5n9OrYL+A84Jbo/cvAGKACmJewTAVhRMGDCT9qZgK3EvrsOZ3w6xzC0LlzCaP69Sb0+3MocAYwJWF7ZdE2ndDNNdH2vt9kf6Oj6XuiOPcHHgW6RuU3AOdHyzcCRybsY0P090BCn0e7R9O7JTkHlxFGtUt2fpLOI/RBNSqF85vsXO503K2Up3LuDwWmJ+xnATAsYbomfg706jwv1UAk184B7ore3xVNJ/Ouu89190ZCYpjm7k5IGBXRMscAD7r7Rx5GynsAODZa5oToV/Kx7l4XLb/M3V+K3v81Wj9xf/F2g5nRPsYRktS/ojaFcYSO6gCWehi9ranjgfvc/X0Ad095qOCIkXzMBQPczCZENaWHzexzKW6zueNurrzVc+/urwMDzGywmR1CGM71vTSOUzqg9j4eiBQxM+tP+II9yMwcKCV8Wd6QZPFNCe8bE6Yb2f45TTo6lLu/ZWaHEXrf/aWZPQ3cwc5fzInTifvbCvSMtj/V3a9ochwVwEfJ9k3zCSDRfLZ3CZ5s3hlN9teXMF7DO+4+F3go6l77N6Q2Rnpzx91ceSrnHsLQrWcCA9n+o0A6MdVAJJfOJIy9vJe7V7j7UOBdYBjQJ4PtvQBMiK7d70IY+OofZjYY+Njd/0r4kh0TLT/MzD4VvY835LdkGnCmhVHdMLPdzGyvFNY5K0qWmNluSZZ5FuhuZhfHC8zscDM7Llq/l5mdH5WXEoYTvt3dP07Yxk8IXXCnornjTvd8NHUXoR3rTLaPEy6dmBKI5NI5hLuPEt1P+BJ6KWq0vTbVjbn7LOB2wvgLrwJ/iS6tHAy8Fl12+jHws2iVhcBEM5sD7EYY972l7S8gfFE/Ha3zDDColXXmE+6Ymm5mbwC/S7KME5LdiRZu050PxICVCfO+bGaLgbeAjYS7tOJ3ff0KeCI6/lQ0d9xpnY9mjrUPsMKjsbalc9N4INIhRZedHnP3gwocSpuY2WWE0eT+Bcz2hDu5ovkVJBxnc8ed6/NhZjWEgYnez8X2pX1SG4hIO+bufwD+0MIiW4EyM5vtBXgWJLr9+Z9AV0KbiXQiqoGIiEhG1AYiIiIZUQIREZGMKIGIiEhGlEBERCQjSiAiIpIRJRAREcmIEoiIiGTk/wNn7kZzvRuAcgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "save_plot = True\n",
+ "plot_winton = True\n",
+ "plot_unlim = True\n",
+ "\n",
+ "labelsize=10\n",
+ "ticksize=10\n",
+ "\n",
+ "offset=0.01\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ax.spines['left'].set_position(('outward',5))\n",
+ "ax.spines['bottom'].set_position(('outward',5))\n",
+ " \n",
+ " \n",
+ "# color_winton simulations\n",
+ "if plot_winton:\n",
+ " color_winton='C1'\n",
+ "\n",
+ " \n",
+ " a=plot_simulation_merged(ax,1875, 90, 0, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 0, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2437, 90, 50.5, color_winton, 1)\n",
+ " plot_simulation_merged(ax,2625, 90, 52.6, color_winton, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 56.3, color_winton, 1)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_winton, 1)\n",
+ " plot_simulation_merged(ax,3000, 15.3, 0, color_winton, 3, -offset)\n",
+ " plot_simulation_merged(ax,5000, 15.3, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,5000, 38.9, 54.3, color_winton, 4)\n",
+ " #plot_simulation_merged(ax,10000, 15.3, 6, color_winton, 3)\n",
+ " plot_simulation_merged(ax,3000, 30.2, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,4219, 30.2, 0, color_winton, 3)\n",
+ " plot_simulation_merged(ax,4219, 16.6, 0, color_winton, 3, -offset)\n",
+ " \n",
+ " \n",
+ "# hice_unlim simulations\n",
+ "if plot_unlim:\n",
+ " color_unlim='C0'\n",
+ " a=plot_simulation_merged(ax,1500, 90, 0, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1594, 90, 49.54, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1688, 90, 51.07, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,1875, 90, 53.20, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,2250, 90, 56.85, color_unlim, 1)\n",
+ " plot_simulation_merged(ax,3000, 90, 65, color_unlim, 1) #5m limited, but always under 5m\n",
+ " plot_simulation_merged(ax,3000, 14.46, 0, color_unlim, 3, offset)\n",
+ " plot_simulation_merged(ax,3750, 14.46, 0, color_unlim, 3) \n",
+ " #plot_simulation_merged(ax,3907, 14.46, 15.1, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4063, 14.46, 11.5, color_unlim, 3)\n",
+ " #plot_simulation_merged(ax,4219, 14.46, 16.23, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,4375, 14.46, 18.2, color_unlim, 4, )\n",
+ " plot_simulation_merged(ax,5000, 14.46, 24, color_unlim, 4)\n",
+ " #plot_simulation_merged(ax,5000, 11.6, 14.3, color_unlim, 2)\n",
+ " plot_simulation_merged(ax,5000, 90, 90, color_unlim, 1, offset) # limited, but no ice at all\n",
+ " #plot_simulation_merged(ax,10000, 14.46, 18, color_unlim, 4)\n",
+ "\n",
+ "\n",
+ "#ax.hlines([np.sin(np.radians(56.3)),np.sin(np.radians(50.5)),np.sin(np.radians(52.6))],1500,3500)\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(45)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_ylim(-0.1,1.1)\n",
+ "ax.set_xlim(1000,10500)\n",
+ "ax.set_xlabel(\"Atmospheric CO$_2$ [ppmv]\",size=labelsize)\n",
+ "ax.set_ylabel(\"Ice-Edge Latitude [°]\",size=labelsize)\n",
+ "\n",
+ "plt.tick_params(axis='both', which='major', labelsize=ticksize)\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.yaxis.tick_left()\n",
+ "ax.xaxis.tick_bottom()\n",
+ "\n",
+ "\n",
+ "ax.set_xscale('log')\n",
+ "\n",
+ "ax.set_xticks([1000,2000,3000,4000,5000,6000,7000,8000,9000,10000] )\n",
+ "ax.set_xticklabels([1000,2000,3000,4000,5000,'','','','',10000] )\n",
+ "ax.set_xlim(1000,5000)\n",
+ "ax.set_ylim(0,1)\n",
+ "\n",
+ "# extra ticks at bifurcation points\n",
+ "winton_bif=2344\n",
+ "#semtner_bif=1641\n",
+ "semtner_bif=1547\n",
+ "\n",
+ "ax.vlines([winton_bif],-0.04,-0.01,color=color_winton,lw=1,clip_on=False)\n",
+ "ax.vlines([semtner_bif],-0.04,-0.01,color=color_unlim,lw=1,clip_on=False)\n",
+ "#ax.axvline(semtner_bif,-20,0.1)\n",
+ "ax.annotate(winton_bif,(winton_bif,0.1),xytext=(winton_bif,-0.05),color=color_winton,ha='center',va='top',clip_on=False)\n",
+ "ax.annotate(semtner_bif,(semtner_bif,0.1),xytext=(semtner_bif,-0.05),color=color_unlim,ha='center',va='top',clip_on=False)\n",
+ "\n",
+ "ax.set_yticklabels([0,10,20,30,45,60,90])\n",
+ "legend_color(ax,[\"3L-Winton\", \"0L-Semtner\"],2)\n",
+ "#plt.legend((a,b),(\"Winton\", \"Semtner hice_unlim\"))\n",
+ "if save_plot:\n",
+ " if plot_winton:\n",
+ " plt.savefig(\"plots/bifurcation_winton_merged.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /cdo_pp.ipynb b/python_scripts /cdo_pp.ipynb
new file mode 100644
index 0000000..7d1a67e
--- /dev/null
+++ b/python_scripts /cdo_pp.ipynb
@@ -0,0 +1,347 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Postprocessing of ICON-AES output for Snowball experiments\n",
+ "\n",
+ "This scripts merges the 2d output data of ICON into a global and zonal mean. It does that by processing custom subperiods and then merging these output files. This is done so that not all the output data has to be reprocessed if the simulation is continued at a later time, as well as for a better overview of which period is processed and which is not. For this, it is reasonable to *not* delete the output files of the subperiods (*.yXXXX_XXXX.nc) until it's certain that this simulation is not continued.\n",
+ "Additionally, 3d data is copied."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Definition of paths "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/csecfrl_experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/ exists\n"
+ ]
+ }
+ ],
+ "source": [
+ "import os, glob, sys\n",
+ "from datetime import datetime\n",
+ "\n",
+ "#experiment = \"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\" #experiment name\n",
+ "experiment = \"mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1\" #experiment name\n",
+ "\n",
+ "base_path = \"/scratch/b/b380905/experiments/)\" #base path of experiment output data\n",
+ "#base_path = \"/scratch/b/b380782/experiments/\" #Christoph\n",
+ "data_path = base_path +experiment +\"/\"\n",
+ "\n",
+ "save_path = \"/work/bb1092/pp_JH/csecfrl_experiments/\" #saving path\n",
+ "\n",
+ "if not os.path.isdir(save_path +experiment): #check if experiment folder in saving path exists\n",
+ " print(\"creating folder \" +save_path +experiment)\n",
+ " os.mkdir(save_path +experiment)\n",
+ "else:\n",
+ " print(save_path +experiment +\"/ exists\")\n",
+ " \n",
+ "filename = experiment +\"_atm_2d_ml\" #basename of input and output file"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Process subperiod of a simulation into zonal and global mean\n",
+ "Output files are *gm.y0000_9999.nc and *zm.y0000_9999.nc."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0347*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [53.82s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0348*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [50.85s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0349*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [57.53s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0350*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [49.51s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0351*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [54.46s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0352*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [56.52s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0353*\n",
+ "cdo mergetime: Processed 330854400 values from 540 variables over 359 timesteps [50.91s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0354*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [44.30s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0355*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.27s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0356*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [50.75s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0357*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.14s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0358*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.34s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0359*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [47.18s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0360*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [46.44s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0361*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [38.40s 362MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0362*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [48.39s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0363*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [47.57s 364MB]\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1/mlo_aqua_5000ppmv_83sic_hice_unlim_csecfrl1_atm_2d_ml_0364*\n",
+ "cdo mergetime: Processed 331776000 values from 540 variables over 360 timesteps [46.41s 364MB]\n",
+ "cdo cat: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 91cdo cat: Processed 5968281600 values from 810 variables over 6476 timesteps [294.88s 452MB]\n",
+ "cdo fldmean: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 91cdo fldmean: Processed 1673314304 values from 45 variables over 6476 timesteps [185.01s 306MB]\n",
+ "cdo remapcon: YAC first order conservative weights from unstructured (20480) to lonlat (192x96) grid\n",
+ "cdo remapcon: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 910cdo remapcon: Processed 1673314304 values from 45 variables over 6476 timesteps [228.43s 482MB]\n",
+ "cdo zonmean: Processed 1076486144 values from 45 variables over 6476 timesteps [84.30s 323MB]\n",
+ "merging and averaging took 0:28:11.264509, 0:01:33.959139per year\n",
+ "removed temporary files\n"
+ ]
+ }
+ ],
+ "source": [
+ "startyear = \"0347\"\n",
+ "endyear = \"0364\"\n",
+ "\n",
+ "currentyear = startyear\n",
+ "\n",
+ "starttime = datetime.now()\n",
+ "for year in range(int(startyear,10),int(endyear,10)+1):\n",
+ " currentyear = str(year)\n",
+ " while len(currentyear)<4:\n",
+ " currentyear = \"0\" +currentyear\n",
+ " print(data_path +filename +\"_\" +currentyear +\"*\")\n",
+ " \n",
+ " checkFileList = glob.glob(data_path +filename +\"_\" +currentyear +\"*\", recursive=True)\n",
+ " if len(checkFileList)!=12:\n",
+ " sys.exit(\"Wrong number of files for year \" +currentyear +\"! \" +len(checkFileList) +\" files\")\n",
+ " \n",
+ " !cdo -O mergetime {data_path +filename +\"_\" +currentyear +\"*\"} {data_path +\"temp_y\" +currentyear +\".nc\"}\n",
+ "\n",
+ "\n",
+ "# merge files\n",
+ "!cdo -O cat {data_path +\"temp_y*.nc\"} {data_path +\"temp_merged.nc\"}\n",
+ "!cdo -O fldmean {data_path +\"temp_merged.nc\"} {save_path +experiment +\"/\" +filename +\".gm.y\" +startyear +\"_\" +endyear +\".nc\"}\n",
+ "!cdo -O remapcon,r192x96 {data_path +\"temp_merged.nc\"} {data_path +\"temp_remap.nc\"}\n",
+ "!cdo -O zonmean {data_path +\"temp_remap.nc\"} {save_path +experiment +\"/\" +filename +\".zm.y\" +startyear +\"_\" +endyear +\".nc\"}\n",
+ "\n",
+ "endtime = datetime.now()\n",
+ "duration = endtime-starttime\n",
+ "print(\"merging and averaging took \" +str(duration) +\", \" +str(duration/(int(endyear)-int(startyear)+1)) +\"per year\")\n",
+ "\n",
+ "\n",
+ "#remove files in SCRATCH directory\n",
+ "fileList = glob.glob(data_path +\"temp_y*.nc\", recursive=True)\n",
+ "\n",
+ "#for filePath in fileList:\n",
+ "# os.remove(filePath)\n",
+ "\n",
+ "os.remove(data_path +\"temp_merged.nc\")\n",
+ "os.remove(data_path +\"temp_remap.nc\")\n",
+ "print(\"removed temporary files\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Merge subperiods\n",
+ "Ouput files are *.gm.nc and *.zm.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "cdo mergetime: Processed 1101015 values from 180 variables over 24467 timesteps [730.82s 232MB]\n",
+ "cdo mergetime: Processed 105697440 values from 180 variables over 24467 timesteps [824.56s 266MB]\n"
+ ]
+ }
+ ],
+ "source": [
+ "#merge single files\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".gm.y*.nc\"} {save_path +experiment +\"/\" +filename +\".gm.nc\"}\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".zm.y*.nc\"} {save_path +experiment +\"/\" +filename +\".zm.nc\"}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Create monthly and yearly means\n",
+ "Output files are *.mm.gm.nc, *.ym.gm.nc, *mm.zm.nc, *ym.zm.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "cdo monmean: Processed 1101015 values from 45 variables over 25282 timesteps [109.40s 209MB]\n",
+ "cdo yearmean: Processed 1101015 values from 45 variables over 24534 timesteps [105.47s 176MB]\n",
+ "cdo yearmean: Processed 105697440 values from 45 variables over 24534 timesteps [132.00s 193MB]\n",
+ "cdo monmean: Processed 105697440 values from 45 variables over 25282 timesteps [141.59s 232MB]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# monthly & yearly means\n",
+ "!cdo -O monmean {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/\" +filename +\".mm.gm.nc\"}\n",
+ "!cdo -O yearmean {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/\" +filename +\".ym.gm.nc\"}\n",
+ "!cdo -O yearmean {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/\" +filename +\".ym.zm.nc\"}\n",
+ "!cdo -O monmean {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/\" +filename +\".mm.zm.nc\"}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optional: Merge additional subperiods \n",
+ "If the subperiod files have been deleted but the simulation is continued afterwards, this is used to merge additional subperiods into the final file. It works, but it's not recommended because it's easy to skip a time period or double it."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#merge additional single files\n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".zm.y0*.nc\"} {save_path +experiment +\"/\" +filename +\".zm.nc\"} {save_path +experiment +\"/temp.zm.nc\"} \n",
+ "!cdo -O mergetime {save_path +experiment +\"/\" +filename +\".gm.y0*.nc\"} {save_path +experiment +\"/\" +filename +\".gm.nc\"} {save_path +experiment +\"/temp.gm.nc\"} "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Remove subperiod files in work directory\n",
+ "Only do this if you're certain that the simulation will not be continued."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#remove files in WORK directory\n",
+ "fileList = glob.glob(save_path +experiment +\"/\" +filename +\"*.y0*\", recursive=True)\n",
+ "\n",
+ "for filePath in fileList:\n",
+ " os.remove(filePath)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Optional: copy 3D files into work directory"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/3D\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/3D/ exists\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0291*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0292*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0293*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0294*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0295*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0296*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0297*\n",
+ "/scratch/b/b380905/experiments/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml_0298*\n"
+ ]
+ }
+ ],
+ "source": [
+ "# copy 3D files\n",
+ "startyear = \"0291\"\n",
+ "endyear = \"0300\"\n",
+ "\n",
+ "currentyear = startyear\n",
+ "filename3D = experiment +\"_atm_3d_ml\"\n",
+ "filename3Dmean = experiment +\"_atm_3d_mean_ml\"\n",
+ "print(save_path +experiment +\"/3D\")\n",
+ "if not os.path.isdir(save_path +experiment +\"/3D\"): #check if experiment folder in saving path exists\n",
+ " print(\"creating folder \" +save_path +experiment +\"/3D\")\n",
+ " os.mkdir(save_path +experiment +\"/3D\")\n",
+ "else:\n",
+ " print(save_path +experiment +\"/3D/ exists\")\n",
+ " \n",
+ "\n",
+ "for year in range(int(startyear,10),int(endyear,10)+1):\n",
+ " currentyear = str(year)\n",
+ " while len(currentyear)<4:\n",
+ " currentyear = \"0\" +currentyear\n",
+ " print(data_path +filename +\"_\" +currentyear +\"*\")\n",
+ " !cp {data_path +filename3D +\"_\" +currentyear +\"*\"} {save_path +experiment +\"/3D/\"}\n",
+ " !cp {data_path +filename3Dmean +\"_\" +currentyear +\"*\"} {save_path +experiment +\"/3D/\"}\n",
+ "\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /energyflux_icelimit_comparison.ipynb b/python_scripts /energyflux_icelimit_comparison.ipynb
new file mode 100644
index 0000000..eaa6eae
--- /dev/null
+++ b/python_scripts /energyflux_icelimit_comparison.ipynb
@@ -0,0 +1,1459 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Calculation of the artificial heatflux out of zonal data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "mlo_aqua_1438ppmv_atm_2d_ml_0137to0338.mm.zm.nc\n",
+ "mlo_aqua_3000ppmv_Jor2_atm_2d_ml_0258to0425.mm.zm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import matplotlib as mpl\n",
+ "\n",
+ "experiment1 = \"mlo_aqua_1438ppmv\"\n",
+ "filename1 = experiment1 +\"_atm_2d_ml_0137to0338.mm.zm.nc\" \n",
+ "data_path1 = \"/work/bb1092/pp_JH/\" +experiment1 +\"/\"\n",
+ "\n",
+ "experiment2 = \"mlo_aqua_3000ppmv_Jor2\"\n",
+ "filename2 = experiment2 +\"_atm_2d_ml_0258to0425.mm.zm.nc\" \n",
+ "data_path2 = \"/work/bb1092/pp_JH/\" +experiment2 +\"/\"\n",
+ "\n",
+ "experiment3 = \"mlo_aqua_5000ppmv_Jor2\"\n",
+ "filename3 = experiment3 +\"_atm_2d_ml_0258to0306.mm.zm.nc\" \n",
+ "data_path3 = \"/work/bb1092/pp_JH/\" +experiment3 +\"/\"\n",
+ "\n",
+ "experiment4 = \"mlo_aqua_1500ppmv\"\n",
+ "filename4 = experiment4 +\"_atm_2d_ml.mm.zm.nc\" \n",
+ "data_path4 = \"/work/bb1092/pp_JH/\" +experiment4 +\"/\"\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "print(filename1)\n",
+ "print(filename2)\n",
+ "# load netcdf file\n",
+ "DS1 = xr.open_dataset(data_path1 +filename1, decode_times=False)\n",
+ "DS2 = xr.open_dataset(data_path2 +filename2, decode_times=False)\n",
+ "DS3 = xr.open_dataset(data_path3 +filename3, decode_times=False)\n",
+ "DS4 = xr.open_dataset(data_path4 +filename4, decode_times=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# qbot\n",
+ "da1 = DS1.qbot_icecl.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "\n",
+ "da2 = DS2.qbot_icecl.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "\n",
+ "da3 = DS3.qbot_icecl.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "\n",
+ "da4 = DS4.qbot_icecl.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "\n",
+ "qbot1=da1.values\n",
+ "qbot2=da2.values\n",
+ "qbot3=da3.values\n",
+ "qbot4=da4.values\n",
+ "\n",
+ "mqbot1 = np.pi/2* np.dot(da1.values,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "mqbot2 = np.pi/2* np.dot(da2.values,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "mqbot3 = np.pi/2* np.dot(da3.values,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "mqbot4 = np.pi/2* np.dot(da4.values,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(1962, 96)\n",
+ "(1962, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<xarray.DataArray 'lat' ()>\n",
+ "array(-4.6875, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float32 0.0\n",
+ " lat float32 -4.6875\n",
+ "Attributes:\n",
+ " standard_name: latitude\n",
+ " long_name: latitude\n",
+ " units: degrees_north\n",
+ " axis: Y\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# sea ice thickness tendency\n",
+ "da1 = DS1.dhidt_icecl.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "dhidt1 =da1.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da2 = DS2.dhidt_icecl.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "dhidt2 =da2.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da3 = DS3.dhidt_icecl.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "dhidt3 =da3.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "da4 = DS4.dhidt_icecl.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "dhidt4 =da4.values*60*60*24*30 # ice growth per month\n",
+ "\n",
+ "\n",
+ "# sea ice cover\n",
+ "da1 = DS1.sic.sel()\n",
+ "da1 = da1.assign_coords(time=(da1.time/360))\n",
+ "da1 = da1.squeeze()\n",
+ "sic1 = da1.values\n",
+ "\n",
+ "da2 = DS2.sic.sel()\n",
+ "da2 = da2.assign_coords(time=(da2.time/360))\n",
+ "da2 = da2.squeeze()\n",
+ "sic2 = da2.values\n",
+ "\n",
+ "da3 = DS3.sic.sel()\n",
+ "da3 = da3.assign_coords(time=(da3.time/360))\n",
+ "da3 = da3.squeeze()\n",
+ "sic3 = da3.values\n",
+ "\n",
+ "da4 = DS4.sic.sel()\n",
+ "da4 = da4.assign_coords(time=(da4.time/360))\n",
+ "da4 = da4.squeeze()\n",
+ "sic4 = da4.values\n",
+ "\n",
+ "# sea ice thickness\n",
+ "da1 = DS1.sit.sel()\n",
+ "da1 = da1.assign_coords(time=((da1.time-da1.time[0])/360))\n",
+ "da1 = da1.squeeze()\n",
+ "sit1 = da1.values\n",
+ "\n",
+ "da2 = DS2.sit.sel()\n",
+ "da2 = da2.assign_coords(time=((da2.time-da2.time[0])/360))\n",
+ "da2 = da2.squeeze()\n",
+ "sit2 = da2.values\n",
+ "\n",
+ "da3 = DS3.sit.sel()\n",
+ "da3 = da3.assign_coords(time=((da3.time-da3.time[0])/360))\n",
+ "da3 = da3.squeeze()\n",
+ "sit3 = da3.values\n",
+ "\n",
+ "da4 = DS4.sit.sel()\n",
+ "da4 = da4.assign_coords(time=((da4.time-da4.time[0])/360))\n",
+ "da4 = da4.squeeze()\n",
+ "sit4 = da4.values\n",
+ "\n",
+ "#temperature\n",
+ "da1 = DS1.ts.sel()\n",
+ "da1 = da1.assign_coords(time=((da1.time-da1.time[0])/360))\n",
+ "da1 = da1.squeeze()\n",
+ "ts1 = da1.values\n",
+ "\n",
+ "da2 = DS2.ts.sel()\n",
+ "da2 = da2.assign_coords(time=((da2.time-da2.time[0])/360))\n",
+ "da2 = da2.squeeze()\n",
+ "ts2 = da2.values\n",
+ "\n",
+ "da3 = DS3.ts.sel()\n",
+ "da3 = da3.assign_coords(time=((da3.time-da3.time[0])/360))\n",
+ "da3 = da3.squeeze()\n",
+ "ts3 = da3.values\n",
+ "\n",
+ "da4 = DS4.ts.sel()\n",
+ "da4 = da4.assign_coords(time=((da4.time-da4.time[0])/360))\n",
+ "da4 = da4.squeeze()\n",
+ "ts4 = da4.values\n",
+ "\n",
+ "ice_lat1 = np.arcsin(1-sic1) * (180./np.pi) \n",
+ "\n",
+ "print(dhidt2.shape)\n",
+ "print(sit2.shape)\n",
+ "\n",
+ "mdhidt1= np.pi/2* np.dot(dhidt1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, dhidt1,levels = np.linspace(-1,1,11),cmap='RdBu')\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1.time,mdhidt1)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(da1.time,dhidt1[:,45])\n",
+ "plt.ylim(-1.5,0.3)\n",
+ "plt.xlim(199,202)\n",
+ "plt.xticks([199,200,201,202])\n",
+ "print(da1.lat[45])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(630, 96)\n",
+ "(2412, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# points where sea ice thickness exceeds the sea ice limit\n",
+ "icelim1= np.where(sit1 + dhidt1>5) # inaccurate, because yearly mean of sea ice thickness + yearly mean of sea ice growth\n",
+ "icelim2= np.where(sit2 + dhidt2>5)\n",
+ "icelim3= np.where(sit3 + dhidt3>5)\n",
+ "icelim4= np.where(sit4 + dhidt4>5)\n",
+ "\n",
+ "\n",
+ "removed_thickness1 = np.zeros([da1.sizes[\"time\"],96])\n",
+ "removed_thickness2 = np.zeros([da2.sizes[\"time\"],96])\n",
+ "removed_thickness3 = np.zeros([da3.sizes[\"time\"],96])\n",
+ "removed_thickness4 = np.zeros([da4.sizes[\"time\"],96])\n",
+ "\n",
+ "print(removed_thickness3.shape)\n",
+ "print(sit1.shape)\n",
+ "# calculate removed sea ice thickness\n",
+ "removed_thickness1[icelim1] = sit1[icelim1] + dhidt1[icelim1] - 5\n",
+ "removed_thickness2[icelim2] = sit2[icelim2] + dhidt2[icelim2] - 5\n",
+ "removed_thickness3[icelim3] = sit3[icelim3] + dhidt3[icelim3] - 5\n",
+ "removed_thickness4[icelim4] = sit4[icelim4] + dhidt4[icelim4] - 5\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, removed_thickness1)\n",
+ "\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "fig2, ax2 = plt.subplots()\n",
+ "im2=ax2.contourf(da2.lat, da2.time, removed_thickness2)\n",
+ "\n",
+ "fig2.colorbar(im2)\n",
+ "plt.show()\n",
+ "\n",
+ "fig3, ax3 = plt.subplots()\n",
+ "im3=ax3.contourf(da3.lat, da3.time, removed_thickness3)\n",
+ "\n",
+ "fig3.colorbar(im3)\n",
+ "plt.show()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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ZWCdpaR7Gcibw1frDbIZicZyuTlgXbCcU02DETCPjhPyVhbNcAywFtkgCuNvMLjezByTdRpY7Pwdc0ZXIkWnIiHTBTpPQUSNtLkg67TNO9MjY4Sz5/h8APlBnUDHog9Xg0SPpMg0RJE4aTFVG5HzM5+5oW9BDhfwNcPFOi9DNfZsUbm85lh69Ee1U6ULfSKcesbqyt211e1f2dnDRpnxCNWV9h7aynemnKbF2oU0TF+2c2CIdU5hDW9fF+GyvO1Kf0KVZm3KReEJNmrho58TOjgzdiT0mg/RtLxgVhpDukaZdIi7c6eGiPQ9NuEhCuEeKguA+7XAMfnGELhY1zCSCXjZX2vZtO83ioj0PAwujCxX+wAU7NKG7sXfR2nYrOz1ctIdoO/yvCi7WadPldmMe8pceldLYnXCEsJr2n65Dbk5ahL6oprgO4jSHW9pDNB3+V/cEjGVle4W/8s+gqssklE97wKh5k0rijRMPF+0xWL3q8eglWquKd4zsRxfsw0nRv921BchQ7pRHg7xLd3HRLqFpCyJU15qQtbTBxTtFoQZPrkmNSfvoDr12B7CfrKfunJmtWeh4UyvaXfnp5v7JftCltQYX64m5iTH76I54/WvMbN+4B5ta0a478TyN3Tn24QPBrO2yX0FVhTxWRqSLdTUm7KNbm6kV7aq0YaHX9WsP8Op+4Rl2EYV0mdTJlIyRZDPO3J8WYZ+dXTzJub5c0tbC4015u8RxKfbRHcaAuyQZ8BfjvK+L9hBN9Icsw63t9Ajt0y5Sx10Sy6c9LYIcgX3j+JrLKOmjO8y5ZrZL0gqypjIPmdlX5ntPF+0SulA8qqlQP687Eo7U/dpl896FvDoj+ugegpntyv/ulXQ7cA5QT7RHrIyeQGburwZ2AG8xsyeV9R67DrgIeAa41My2jfMPpkTsWO2ipVQ31G9A6MgR8IJRoRl8R3XFO3aVPxfq+hT66P7HoT66xX1eABxhZvvz+xcA1y703uNY2jdx+Mro1cDfmtlGSVfnj68C3kjWzPdM4FXAR/K/naIrkScD3Icdh1Ehj3XdJiESbSa52E8q8CnM/y5dOCbpoyvpFOBjZnYRcBJwe/78YuCTZvb5hY43To/Iw1ZGgbX5IAFuBr5MJtprgY/nPwXulnScpJVmtnuh46REk37tVKNH+h6jXSSWb7uuxZ1qck2XBDcEk/TRzd0hF+X3HwFePunxqvq0TxoIsZntzp3oAKcC3y3sN5NvO0y0JW0ANgAsXbGs4jCcWDz1kqW9F+5UxToF+ibMKRF6IbJsNo5ywG8CNgEsO+vk1n/ft/WTMLVsSOd5QtbTDklsC9sFOW2qivaegdtD0kpgb759BjitsN8qYFedATZFW30iQ7lHPEY7PCHFukuNfb0ca9pUFe3NwHpgY/73jsL2KyXdSrYA+VTX/NlFYhaKKhJKuF2w+0VTvSKLVD0fXOzDMU7IX9nK6EbgNkmXATuBN+e7f47Myb6dLOTv7RHG7IzA3SRhCZ3G3rWCUQNccNNinOiRspVRgPNL9jXgirqDikkK4Uyho0VilmX1GO0wdFWwnfToXUbkOFZDE2F+A1LzZ3tyzaGEsrZDWdqx/dnDuJWdHr0T7XEYNVFjiHmoYlGh3SJ9D/crElK4i9QR8abEezDnXbzTwUV7AVJtNRbbd+1x2hkpRpB4N/Z+46LdUWIuOhbFus+ukdTiswc06SLpU7nWruCivQB96w8Jh1rZffZph4wegXB+bU+u6Tcu2iU0HWFSN047RsU/d4+k2yMyNjtmTnThThgX7RKaboSQYsEoJ7yl3SWG572LeDq4aI8ghXjuSfDokfCEFuyu1NMe4EKdJlMt2l0QXrey+0VXXCRw6PnjAp4OUy3aVSZaG/7sASn5td2nHZ4uLEIWcaFOk6kW7Ulp0zIPaXF7/ZEwhC7NGsI9Mu48CSHu454PLu7N4qJN+24Ud5GkSeqLkN4nsp+4aNNcLe2UC0UN8IJR8QlhcccQbBfqakzS/LzkteuB38kf/r6Z3bzQ8Vy0G2T4RKsr4rHiswd4wagwhF58bKP5QREX98O4ifGbnx8kF/bfA9aQdfi6T9LmMnEv4qI9gsHEjOk6CVUsyolDKJ922cU0lF/bS7W2z4TNz4u8AdhiZk8ASNoCXAjcMt/xei/a7s925iPFglHgYt0wyyVtLTzelPe4nY9Rzc+LjGqEPi+9F+3hn3pthfy5eKdJit1rvPZIfTSrSc65fWa2JsYwSrYt6OM8otYRpf8h6QFJ35B0i6SjJJ0h6R5J35b0KUmdUaO2re6U8BjtjFhZkXWIfYHfMXPiITenEnvypucMNT8vUqkRemXRlnQq8OvAmnzFdBGwDvgg8GEzOxN4Eris6jGaZvWqxw/eukjIn9+ph7s1QYyCUV2wtIt09VxIgEHzczi0+XmRLwAXSDpe0vHABfm2eanrHlkM/BtJ/wocDewGXgv8cv78zcD7gI/UPE7jNNWJHcJYTp5QE55UC0Y12YV90nOgjyI/SfNzSWuAy83snWb2hKT3A/fmb3XtYFFyPiqLtpk9JumP8wH9ELgLuA/4vpnN5buNdKxL2gBsAFi6YlnVYUSliQgSCOPXDl1b290jGS7ck9HHpgkTNj/fCryz8PhG4MZJjldZtHNzfi1wBvB94K+AN5bsWqoi+errJoBlZ50c1UxM0S+Xatq6J9c8Twx/dpfcI9MmrtNCHffI64DvmNnjAJI+C/wscJykxbm1PZZjPTaTTL6mBD5k1EhRCEIUihrgyTVh6VKFPxh9LriYt0sd0d4J/LSko8ncI+cDW4EvAZcAtzLaAZ8sTTdAqNu1ZoD7tMNT5iKqY32HSrIZNV+a9HO7cLdHHZ/2PZI+DWwD5oB/InN33AncKun38203hBhoGzS5GFkHF+w4pNxurA1/tgt1GtSKHjGz3yNbKS3yCHBOnfftC1Ut7Ngi7d3YnWFcsNOh9xmRCxHTXVLVrx2jUFQR78aeUbx4pRJB4uVYHRftAl1whZQROtwPvHPNgJBiXfx+qrpKBhf4GOLt7cW6gYt2gSbrkHitkf7RpeiRwdx38U4PF+2cNntDQtjQP1+YDEfoglHQHfF2wU6TXol2iu6P1JNs+urPHpBiadYUMyGd5qhV5a9rFAtCpWJFhDwBQxUkgufFavbsVUHer4uksvjoOEV6ZWkPs5BwN5kd6Qk26RE6eiSUe2R4rrTdfmyYVAyiaaXXoj2gTbdJXbF2oY5Ligk2Xnuk37ho072okVhCXRbi12efdor+bGiuwl/ZeeBC3j4u2iU0kVBTpG5yDcTpxA6eXJNaq7EmcYFOExftBWiqpraTHk20GqubZAPN+rRdyNvHRXsBYot1qJC//afLMyI7QBfD/lyo08JFe4gmLeqUFyE9TjssXa7w56VY06L3ot2m26NuqF/I5gdF3MLOGHwOIcP9IP2MSBfo8ZF0FvCpwqYXA79rZn9a2Oc8sr4C38k3fdbMrq16zN6LdtNND7qAV/nLiJVcU3dRMmbRKBfsyTCzbwGvAJC0CHgMuL1k1783s4tDHLP3ol2kbMJ2oamv0y1SjtX2FmO1OB942MwejXkQF+0FiN29JjW/tjf2jUcXFyEHDJ8DPRPx5ZK2Fh5vyhuTD7MOuGXEe/yMpK+R9cx9j5k9UHUwtURb0nHAx4CXkXVdfwfwLTIfz2pgB/AWM3uyznHGpSvuDbeq+4nHaqfDotmJDJ59ZrZmvh0kLQHeBFxT8vQ24HQz+4Gki4C/Bs6cZLxF6lra1wGfN7NL8kEfDbwX+Fsz2yjpauBq4KqaxxmLEBOsqWa+A+oKeOjFyIEf133aceiKcE+rWEfkjcA2M9sz/ISZPV24/zlJfy5puZntq3KgyqIt6YXAzwGX5oOZBWYlrQXOy3e7GfgyDYl2Vbpioc9HrOgRF+zwDH9Xk4r4fBf6UK6T+c4JF/RS3soI14ikk4E9ZmaSziGrrvovVQ9Ux9J+MfA48L8kvRy4D3gXcJKZ7QYws92SVpS9WNIGYAPA0hXLagyjPqMmYVNWd2oNEDyxJhwxrOo262m7YB+OpKOB1wO/Uth2OYCZfRS4BPhVSXPAD4F1Zlb5RK0j2ouBnwR+zczukXQdmStkLHJH/iaAZWed3Gipui5X9YM4STUu0nHoUnz2OHiizeGY2TPAjw1t+2jh/vXA9aGOV0e0Z4AZM7snf/xpMtHeI2llbmWvBPbWHWQoUnCDhGgzFqNgVFlM8rEPH+i1TztkwSgI589uou7IfLhwt0tl0Taz70n6rqSz8gDz84Fv5rf1wMb87x1BRhqAuhMthuiHcI94Te04xEiuCbkQ6XW1+0nd6JFfAz6RR448ArydzMl+m6TLgJ3Am2seoxHassJD+rMhnIC7uyRtvE9kf6kl2mZ2P1AWv3h+nfdtg9hJNLHx6JHwhKw9UiSEtd1EIwS3sNNkajIiuyy4IQgZPeJkpNhqDJqxsl2w02VqRDvmJEv1guACHZcYC5EQprGvu0f6y9SIdmi60Ik9VmlW53lCd2SHcO4RSK8T+yjccg+Hi/YIuubjDtm5xpNrDiXFBr8eOdJfei/aTQlz6CJRsav7Oc8TusFvkZQTblyw06T3ot1UCvsoyygV18hwoSjnUEL7t7vg1657Drjox6H3oj1Ml1wiTrOEbj/WBeEexoW4fXon2tMoyqE7sTuHE0Kou+bPLuJinQ5HtD2AppnGyRdSsGP1RXSy72lwq8PSnUsabaQxjedMl5kaS3saLehxcUu7W9S1uD25pt9MjWjHmGSxLwR1rKVYIu0LkfGpm2TTRJW/srnvQp4GUyPaIelaYs0At7a7Q8qhfqOY9LxwkY+Di3ZOG+6VUH7J0D5tt7azQlmzZ6+K8t4hBLvJxUgX37SYGtHukk875CKSJ9l0i65b2C7g7TM1oh17MoW8KITsxh4SF+z4hOxe411r0kDSDmA/8BwwZ2Zrhp4XcB1wEfAMcKmZbat6vKkR7ZjEsuJT61jjrpHRhCwcFapv5Kj500SmpAv3YbzGzPaNeO6NwJn57VXAR/K/lXDRnofYLpe6rcZCh/q5YI8mpRR2iCvMLsjBWQt8PO/Afrek4wZ9dKu8WW3RlrQI2Ao8ZmYXSzoDuBU4AdgGvM3MOlX8N6ZYp2Zdg4t1k3TBpz3J/O+JwC+XtLXweJOZbSo8NuAuSQb8xdBzAKcC3y08nsm3tSPawLuAB4EX5o8/CHzYzG6V9FHgMrKfA51heCLG8mfD5CI+fNKHLBYFLuCjCFEwqguCPR/TJNCLnrVJ5vq+YT/1EOea2S5JK4Atkh4ys68Uni/74iufuLVEW9Iq4D8BHwB+I3e4vxb45XyXm4H30QHR7mrIn7cZi0cx7C9UkahRTCroMRcip0mcm8DMduV/90q6HTgHKIr2DHBa4fEqYFfV49W1tP8U+C1gWf74x4Dvm9lc/njwM+AwJG0ANgAsXbGsbJdGKZuoqfu0Y+CLkc3QhVR2Z2EkvQA4wsz25/cvAK4d2m0zcKWkW8kWIJ+q6s+GGgWjJF0M7DWz+4qbS3YtNS/MbJOZrTGzNUced3TVYUSjyazIlHDBLie1zyXmxX7HzImdyntomZOAf5D0NeCrwJ1m9nlJl0u6PN/nc8AjwHbgL4H/XueAdSztc4E3SboIOIrMp/2nwHGSFufWdq2fAXXpwsRzS7sbhK5+WLf+iEePpIGZPQK8vGT7Rwv3Dbgi1DEri7aZXQNcAyDpPOA9ZvZfJP0VcAlZBMl64I4A46zEJJOvCwLfBC7Y3SBGY18X624QI077KuBWSb8P/BNwQ4RjBGe+CRtT0EP5tb08axwGi5Gh242FIuSCZMh57heAeAQRbTP7MvDl/P4jZKunnSfleG3wiJEmCBk9AmHD/rwjez/pZUZkk66QGD7rpopELXloJuhxukhoS7uuL7tpXLDTo5eivdBEjJlMUyS1TuxwqIDPnr2q98Id2tIOhS9E9pdeivZCxMyILFLHn+2ukWYoWtoDYiTaVEmuGSa2b9vFPA1ctEeQcqsx8IXHpohhaXepK7sLdXq4aI+gOFljCHiK2ZAe7tcMIUuzupukf7hot0iKwu0cyrB7JCXfdgzBdqFOHxftEXQh2SZ2sQFVvOYAAAsQSURBVKi+L0KWETpeu04nm4Uu+FVEvQvzvu+4aI9gYHH0KVbbU9jnJ0W/NqRXv8aJi4v2AsT0bdd1j3hT32ZJKSuyz4uQj7Y9gJaZOtHu0s+7lPzZLtgLk4pgQ5zaI8MMn0upinjfmDrR7lORqJBhfwNB8uSa0YS0tENEkPhCZD+ZOtGehNhhfU0QczHSBftwQifZQPXU9vl+qVUVdO8PmT69Fu0ioyZgyhX+YifXuKV9OKksRnp8dn9x0S4h9WxIX4BshxiNEOqG+8UQ7+L8dwFPDxftEmKH+xVPtCoCHroju3djH02qBaOawAU7TSr3iHTqk1qctnM4A/fQsQ8f6N0FzXtFLoyk0yR9SdKDkh6Q9K6Sfc6T9JSk+/Pb79Y5plva89C3+iN9E6VJScWfDd4AISHmgN80s22SlgH3SdpiZt8c2u/vzeziEAesLNqSTgM+DpwM/AjYZGbXSToB+BSwGtgBvMXMnqw/1Ph00aoIHfbnwn0oqbpHYsdpu1iPh5ntBnbn9/dLehA4FRgW7WDUsbRLrzDApcDfmtlGSVcDV5P1jYxO10Q3lJXtZVrjk1I2JMS3tD2xZnIkrQZeCdxT8vTPSPoasIusCfoDVY9Tpxv7qCvMWuC8fLebyXpHNiLaoSZWU+I/OPFSiiZxa7uclCJHIH5ZVphuodazs5OEsy6XtLXweJOZbTrk/aRjgM8A7zazp4devw043cx+IOki4K+BMysOPYxPe+gKc1Iu6JjZbkkrRrxmA7ABYOmKZSGGEYSmBDvVRUgX7HJSLM0aW7jHORemWdgL7DOzNaOelHQkmWB/wsw+O/x8UcTN7HOS/lzScjPbV2UwtUV7+AojjWc95FeqTQDLzjq5ld/2bbpTQixChu4VCW5pFxn4syGOWIdqhhCCnohvcJQJ3g3Ag2b2JyP2ORnYY2Ym6RyyqL1/qXrMWqI94gqzR9LK3MpeCeytc4zQtCHUsSJEQlraLtSHM2iAEIO2RXqYKueFCz0A5wJvA74u6f5823uBFwGY2UeBS4BflTQH/BBYZ2aVT9460SOjrjCbgfXAxvzvHVWPEYM2CkrF6MgO8SNH+p7CXhTsEAuRoYW6rTraLtbPY2b/AMz7xZrZ9cD1oY5Zx9IedYXZCNwm6TJgJ/DmekOMS5sukhAWeMiCUe4amZ+6xaJGfUehOtf0ucZ2n6gTPTLfFeb8qu/bNONOwlSTa0JZ2i7W49HHBBtwsU4Jz4jMadriTl2s3TVyuC87pcgRaCbsD1ywU8NFm3ZcJHWt7FD+7GEhcou7OarW0R4QWrBdnLtBrwtGtV0Qp+5Jt/90HbyFJlbUhJMuXcso7iu9trTbaHwQg1iuEm+CEI/UQv4GeC3t9Om1aI+ibLLGrq2dgqvEGU1KC5BNMZjzLt5p0VvRTsGaTimV3X3ZhxIzsaauL3tAUwuRZeeKC3l7dEq0UxDa1Cg78asIuXevaZYQ1raH/PWTTol2ExOnyxcGd5GEpWhthy4YFcLaHvVLLXbfyDJc1JujU6LdBLG71YTEq/zFJVbBqFA+be/I3k96J9ptCXHoolFNFIvqe+TIsKUd0spOfTHSmyCkS+9EO3an9VGUWUV1I0bKqOvPBre24fA49dQsbW+A0F96J9oD2qw5MiCl2iMDioLtcdrPU7dYVJEQdbSbaIDgwp0mvRXttklNrJ2FScnadn92f+l1GvsoBuntsa3sOiderPT11IoipUKMHpF1iNVYA9JfgO87bmnT7Ukao+WYEy+5pgv+bHD3SMq4pd1xlj1qB29OWGL480N8V0t3LolqaQ/osjEzzbilTbcLR8WqO+ILkPEI5dZqIo099jng1vzkRBNtSRcC1wGLgI+Z2cZYxwpJF4R6mJAtx5y4dCGxBlxMJ2EhrZO0FPg48FNkXdh/ycx2VD1eFNGWtAj4M+D1wAxwr6TNZvbNGMcrI0Xx9a7sTleKRY1z/riwj611lwFPmtm/lbQO+CDwS1WPGcvSPgfYbmaPAEi6FVgLNCbadSdUrJ6QRVKq8jfAm/s2QyjxjomL8liMo3Vrgffl9z8NXC9JZlbp5I0l2qcC3y08ngFeVdxB0gZgQ/7wB3/3ug99K/AYlgP7Ar9nCHxc49P+mL6X//3yIVvbH9fhBB/To2HeJsZndXrdN3h67vEvfP57f758zN2PkrS18HiTmW3K7y+odcV9zGxO0lPAj1Hxc4kl2mXmwyFXlfyf3lSyX5gBSFvNbE2s96+Kj2t8UhwTpDmuFMcE6Y7LzC4M9FYLat2Y+4xNrJC/GeC0wuNVwK5Ix3Icx2mLcbTu4D6SFgPHAk9UPWAs0b4XOFPSGZKWAOuAzZGO5TiO0xbjaN1mYH1+/xLg/1b1Z0Mk90jut7kS+AJZGMyNZvZAjGPNQzTXS018XOOT4pggzXGlOCZId1xBGKV1kq4FtprZZuAG4H9L2k5mYa+rc0zVEHzHcRynYTyN3XEcp0O4aDuO43SIqRNtSZ+SdH9+2yHp/nz7akk/LDz30YbH9T5JjxWOf1HhuWskbZf0LUlvaHBMfyTpIUn/T9Ltko7Lt7f6WeVjuDD/PLZLurrp4+djOE3SlyQ9KOkBSe/Kt4/8Lhsc2w5JX8+PvzXfdoKkLZK+nf89vsHxnFX4PO6X9LSkd6fwWU0bU+3TlvQh4Ckzu1bSauBvzOxlLY3lfcAPzOyPh7b/OHALWWbVKcAXgZea2XMNjOkCspXsOUkfBDCzqxL4rBYB/0whNRh4a5NlEPJxrARWmtk2ScuA+4CfB95CyXfZ8Nh2AGvMbF9h2x8CT5jZxvxCd7yZXdXC2BYBj5Elmbydlj+raWPqLO0BkkR2ct3S9lgWYC1wq5kdMLPvANvJBDw6ZnaXmc3lD+8mizFNgYOpwWY2CwxSgxvFzHab2bb8/n7gQbLstlRZC9yc37+Z7ALTBucDD5tZoKRKp8jUijbwamCPmX27sO0MSf8k6e8kvbqFMV2ZuyJuLPx0LUuDbUMY3gH8n8LjNj+rVD6Tg+S/Pl4J3JNvKvsum8SAuyTdl5eEADjJzHZDdsEBVrQwLshC2orGUtuf1VTRSdGW9EVJ3yi5Fa2xt3LoxNkNvMjMXgn8BvBJSS9scFwfAV4CvCIfy4cGLyt5q2A+q3E+K0m/DcwBn8g3Rf+sFhp2ybbW/HiSjgE+A7zbzJ5m9HfZJOea2U8CbwSukPRzLYzhMJQlmLwJ+Kt8Uwqf1VTRySYIZva6+Z5Xlir6i2T1awevOQAcyO/fJ+lh4KXA1tI3iTCuwvj+Evib/GHUlP8xPqv1wMXA+YMsrSY+qwVIpgyCpCPJBPsTZvZZADPbU3i++F02hpntyv/ulXQ7mUtpj6SVZrY798fvbXpcZBeRbYPPKIXPatropKU9Bq8DHjKzg+1XJJ2YL5Ag6cXAmcAjTQ0oP4kG/ALwjfz+ZmCdpKWSzsjH9dWGxnQhcBXwJjN7prC91c+KRMog5OsiNwAPmtmfFLaP+i6bGtcL8oVRJL0AuCAfQzFdej1wR5PjyjnkF27bn9U00klLewyGfWoAPwdcK2kOeA643MwqF22pwB9KegXZz/wdwK8A5Cmvt5HV350DrmgiciTnemApsCXTJ+42s8tp+bNKpAwCwLnA24CvKw8dBd4LvLXsu2yQk4Db8+9sMfBJM/u8pHuB2yRdBuwE3tzkoCQdTRbxU/w8Sue9U52pDvlzHMeZNqbVPeI4jjOVuGg7juN0CBdtx3GcDuGi7TiO0yFctB3HcTqEi7bjOE6HcNF2HMfpEP8fH5Nahq09fvcAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "text/plain": [
+ "<matplotlib.colorbar.Colorbar at 0x2b763088b588>"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#physical constants from icon\n",
+ "alv = 2.5008e6 # [J/kg] latent heat for vaporisation\n",
+ "als = 2.8345e6 # [J/kg] latent heat for sublimation\n",
+ "alf = als-alv # [J/kg] latent heat for fusion\n",
+ "rhoi = 917.0 # density of sea ice [kg / m**3]\n",
+ "\n",
+ "#calculate energy flux from the freezing of removed sea ice thickness, dhidt = F/(alf*rhoi) <-> F=dhidt*alf*rhoi\n",
+ "\n",
+ "energy1 = np.zeros([da1.sizes[\"time\"],96])\n",
+ "energy1 = removed_thickness1 * alf * rhoi / (60 * 60 * 24 * 30) # Joule per second per m^2 -> Watt per m^2\n",
+ "\n",
+ "energy2 = np.zeros([da2.sizes[\"time\"],96])\n",
+ "energy2 = removed_thickness2 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "energy3 = np.zeros([da3.sizes[\"time\"],96])\n",
+ "energy3 = removed_thickness3 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "energy4 = np.zeros([da4.sizes[\"time\"],96])\n",
+ "energy4 = removed_thickness4 * alf * rhoi / (60 * 60 * 24 * 30) \n",
+ "\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, energy1)\n",
+ "\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "fig2, ax2 = plt.subplots()\n",
+ "im2=ax2.contourf(da2.lat, da2.time, energy2)\n",
+ "\n",
+ "fig2.colorbar(im2)\n",
+ "plt.show()\n",
+ "\n",
+ "fig3, ax3 = plt.subplots()\n",
+ "im3=ax3.contourf(da3.lat, da3.time, energy3)\n",
+ "\n",
+ "fig3.colorbar(im3)\n",
+ "\n",
+ "plt.show()\n",
+ "\n",
+ "fig4, ax4 = plt.subplots()\n",
+ "im4=ax4.contourf(da4.lat, da4.time, energy4)\n",
+ "\n",
+ "fig4.colorbar(im4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.5107632826463103\n"
+ ]
+ }
+ ],
+ "source": [
+ "#global mean flux \n",
+ "msit1 = np.pi/2* np.dot(sit1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "msit2 = np.pi/2* np.dot(sit2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "msit3 = np.pi/2* np.dot(sit3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "msit4 = np.pi/2* np.dot(sit4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "msic1 = np.pi/2* np.dot(sic1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "msic2 = np.pi/2* np.dot(sic2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "msic3 = np.pi/2* np.dot(sic3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "msic4 = np.pi/2* np.dot(sic4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "mts1 = np.pi/2* np.dot(ts1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "mts2 = np.pi/2* np.dot(ts2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "mts3 = np.pi/2* np.dot(ts3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "mts4 = np.pi/2* np.dot(ts4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "\n",
+ "\n",
+ "#energy1 * np.cos(np.radians(da1.lat))\n",
+ "menergy1= np.pi/2* np.dot(energy1,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "menergy2= np.pi/2* np.dot(energy2,np.cos(np.radians(da2.lat))) / np.size(da2.lat)\n",
+ "menergy3= np.pi/2* np.dot(energy3,np.cos(np.radians(da3.lat))) / np.size(da3.lat)\n",
+ "menergy4= np.pi/2* np.dot(energy4,np.cos(np.radians(da4.lat))) / np.size(da4.lat)\n",
+ "\n",
+ "ymenergy1=np.zeros(int(menergy1.shape[0]/12))\n",
+ "ymenergy2=np.zeros(int(menergy2.shape[0]/12))\n",
+ "ymenergy3=np.zeros(int(menergy3.shape[0]/12))\n",
+ "ymenergy4=np.zeros(int(menergy4.shape[0]/12))\n",
+ "\n",
+ "ymsic1=np.zeros(int(msic1.shape[0]/12))\n",
+ "ymsic2=np.zeros(int(msic2.shape[0]/12))\n",
+ "ymsic3=np.zeros(int(msic3.shape[0]/12))\n",
+ "ymsic4=np.zeros(int(msic4.shape[0]/12))\n",
+ "\n",
+ "for y in range(0,int(menergy1.shape[0]/12)):\n",
+ " ymenergy1[y] = np.mean(menergy1[(y*12):(y*12)+11])\n",
+ " ymsic1[y] = np.mean(msic1[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy2.shape[0]/12)):\n",
+ " ymenergy2[y] = np.mean(menergy2[(y*12):(y*12)+11])\n",
+ " ymsic2[y] = np.mean(msic2[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy3.shape[0]/12)):\n",
+ " ymenergy3[y] = np.mean(menergy3[(y*12):(y*12)+11])\n",
+ " ymsic3[y] = np.mean(msic3[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(menergy4.shape[0]/12)):\n",
+ " ymenergy4[y] = np.mean(menergy4[(y*12):(y*12)+11])\n",
+ " ymsic4[y] = np.mean(msic4[(y*12):(y*12)+11])\n",
+ "\n",
+ "\n",
+ "print(ymenergy4[-1])\n",
+ "\n",
+ "\n",
+ "# sea ice latitude\n",
+ "ice_lat1 = np.arcsin(1-msic1) * (180./np.pi) \n",
+ "ice_lat2 = np.arcsin(1-msic2) * (180./np.pi) \n",
+ "ice_lat3 = np.arcsin(1-msic3) * (180./np.pi) \n",
+ "ice_lat4 = np.arcsin(1-msic4) * (180./np.pi) \n",
+ "\n",
+ "yice_lat1=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "menergy1m=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "msit1m=np.zeros(int(ice_lat1.shape[0]/12))\n",
+ "yice_lat2=np.zeros(int(ice_lat2.shape[0]/12))\n",
+ "yice_lat3=np.zeros(int(ice_lat3.shape[0]/12))\n",
+ "yice_lat4=np.zeros(int(ice_lat4.shape[0]/12))\n",
+ "\n",
+ "for y in range(0,int(ice_lat1.shape[0]/12)):\n",
+ " yice_lat1[y] = np.mean(ice_lat1[(y*12):(y*12)+11])\n",
+ " menergy1m[y] = np.mean(menergy1[(y*12):(y*12)+11])\n",
+ " msit1m[y] = np.mean(msit1[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat2.shape[0]/12)):\n",
+ " yice_lat2[y] = np.mean(ice_lat2[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat3.shape[0]/12)):\n",
+ " yice_lat3[y] = np.mean(ice_lat3[(y*12):(y*12)+11])\n",
+ " \n",
+ "for y in range(0,int(ice_lat4.shape[0]/12)):\n",
+ " yice_lat4[y] = np.mean(ice_lat4[(y*12):(y*12)+11])\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "5.877783718381085\n",
+ "-0.002561321\n"
+ ]
+ }
+ ],
+ "source": [
+ "\n",
+ "\n",
+ "#plt.plot(da1.time,menergy1)\n",
+ "#plt.plot(da2.time,menergy2)\n",
+ "#plt.plot(da3.time,menergy3)\n",
+ "plt.plot(ymenergy1)\n",
+ "plt.plot(ymenergy4)\n",
+ "plt.plot(ymenergy2)\n",
+ "plt.plot(ymenergy3)\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "#plt.title(\"hice_5m: heat flux from removed ice\")\n",
+ "plt.title(\"\")\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"qbot_removed [W/m²]\")\n",
+ "plt.xlim(0,210)\n",
+ "plt.ylim(0,8)\n",
+ "plt.savefig(\"plots/heatflux_comparison.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.plot(da1.time,-mqbot1)\n",
+ "plt.plot(da2.time,-mqbot2)\n",
+ "plt.plot(da3.time,-mqbot3)\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.title(\"hice_5m heat flux at ice-ocean interface\")\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"qbot [W/m²]\")\n",
+ "plt.show()\n",
+ "\n",
+ "print(ymenergy2[-1])\n",
+ "print(ice_lat2[-1])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[9.97476504 9.95405141 9.91329416 9.85666766 9.78738901 9.70786213\n",
+ " 9.61864082 9.5195548 9.41147772 9.29436578 9.16798005 9.03156576\n",
+ " 8.88439149 8.72548441 8.55926759 8.38940794 8.21621948 8.037763\n",
+ " 7.8515717 7.65525129 7.44725733 7.22527701 6.98781972 6.73510113\n",
+ " 6.46956634 6.19633454 5.92231988 5.65367407 5.39498701 5.14938465\n",
+ " 4.91887989 4.70132238 4.49178427 4.28434979 4.07285187 3.85964338\n",
+ " 3.0176455 0.23082593 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0. 0.\n",
+ " 0. 0. 0. 0. 0.29442812 2.75719823\n",
+ " 3.84660383 4.05760446 4.26950946 4.47652428 4.68492956 4.900759\n",
+ " 5.12918388 5.37283742 5.63050608 5.89908285 6.17299601 6.44550724\n",
+ " 6.71064504 6.96331186 7.20101106 7.42327846 7.63115569 7.82682259\n",
+ " 8.0123467 8.19025323 8.36338272 8.53355504 8.70095354 8.86200317\n",
+ " 9.0113924 9.15081557 9.28159445 9.40375439 9.51690881 9.62097496\n",
+ " 9.71453295 9.79837862 9.8704476 9.92841808 9.97077964 9.99313491]\n",
+ "(96,)\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b7630986ba8>]"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# time means\n",
+ "\n",
+ "tenergy2= np.mean(energy2[0:160*12,:],axis=0)\n",
+ "print(tenergy2)\n",
+ "print(np.shape(tenergy2))\n",
+ "\n",
+ "plt.plot(da2.lat,np.squeeze(tenergy2))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b76304a5898>]"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# co2 equivalent of artifical heat flux\n",
+ "alpha = 5.35\n",
+ "mco21 = 1438 * np.exp(menergy1/alpha)\n",
+ "mco22 = 3000 * np.exp(menergy2/alpha)\n",
+ "mco23 = 5000 * np.exp(menergy3/alpha)\n",
+ "mco24 = 1500 * np.exp(menergy4/alpha)\n",
+ "\n",
+ "mco21r = np.exp(menergy1/alpha)\n",
+ "mco22r = np.exp(menergy2/alpha)\n",
+ "mco23r = np.exp(menergy3/alpha)\n",
+ "mco24r = np.exp(menergy4/alpha)\n",
+ "\n",
+ "plt.plot(da1.time,mco21)\n",
+ "plt.plot(da4.time,mco24)\n",
+ "plt.plot(da2.time,mco22)\n",
+ "plt.plot(da3.time,mco23)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(630,)\n",
+ "(630, 96)\n",
+ "(630,)\n",
+ "0.9916648749327626\n",
+ "0.9420278794069241\n",
+ "0.9797683783641139\n",
+ "(0.0, 1.0)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "pltsize=2\n",
+ "\n",
+ "print(msit3.shape)\n",
+ "print(sit3.shape)\n",
+ "print(menergy3.shape)\n",
+ "\n",
+ "print(np.corrcoef(msit1,menergy1)[1,0])\n",
+ "print(np.corrcoef(msit2,menergy2)[1,0])\n",
+ "print(np.corrcoef(msit3,menergy3)[1,0])\n",
+ "\n",
+ "# far - sit\n",
+ "fig, ax = plt.subplots()\n",
+ "plt.plot(msit1, menergy1,'.',markersize=pltsize)\n",
+ "plt.plot(msit4, menergy4,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, menergy2,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, menergy3,'.',markersize=pltsize)\n",
+ "plt.grid()\n",
+ "plt.xlim(0,5)\n",
+ "\n",
+ "ylim=plt.ylim(0,8.2)\n",
+ "plt.xlabel(\"$h_I$ [m]\")\n",
+ "plt.ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2,markerscale=6)\n",
+ "\n",
+ "\n",
+ "ax2 = ax.twinx()\n",
+ "co2_fac=np.linspace(1,5,9)\n",
+ "print(plt.ylim())\n",
+ "\n",
+ "np.exp(menergy1/alpha)\n",
+ "\n",
+ "ax2.set_yticks(np.log(co2_fac)*alpha)\n",
+ "ax2.set_ylim(0,8.2)\n",
+ "_=ax2.set_yticklabels(co2_fac)\n",
+ "plt.ylabel(\"equivalent CO$_2$ increase\")\n",
+ "plt.savefig(\"plots/heatflux_scatter_flux_sit.svg\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.show() \n",
+ "\n",
+ "plt.plot(msic1, msit1,'.',markersize=pltsize)\n",
+ "plt.plot(msic4, msit4,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, msit2,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, msit3,'.',markersize=pltsize)\n",
+ "\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"sit [m]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(msic1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msic4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "#plt.ylim(1,3.1)\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(msit1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msit4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(menergy1, mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy4, mco24r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy2, mco22r,'.',markersize=pltsize)\n",
+ "plt.plot(menergy3, mco23r,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"heat flux [W/m^2]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(mts1, menergy1,'.',markersize=pltsize)\n",
+ "plt.plot(mts4, menergy4,'.',markersize=pltsize)\n",
+ "plt.plot(mts2, menergy2,'.',markersize=pltsize)\n",
+ "plt.plot(mts3, menergy3,'.',markersize=pltsize)\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.xlabel(\"surface temperature [K]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "plt.plot(mts1, msit1,'.',markersize=pltsize)\n",
+ "plt.plot(mts4, msit4,'.',markersize=pltsize)\n",
+ "plt.plot(mts2, msit2,'.',markersize=pltsize)\n",
+ "plt.plot(mts3, msit3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"surface temperature [W/m^2]\")\n",
+ "plt.ylabel(\"sit [m]\")\n",
+ "plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.9938529939485001\n",
+ "0.8676139722084588\n",
+ "0.9821811371639458\n",
+ "(0.0, 1.0)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "ylim=(0,6)\n",
+ "# far - icelat\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "print(np.corrcoef(msic1,menergy1)[1,0])\n",
+ "print(np.corrcoef(msic2,menergy2)[1,0])\n",
+ "print(np.corrcoef(msic3,menergy3)[1,0])\n",
+ "plt.scatter(ymsic1, ymenergy1,marker='o',s=6)\n",
+ "plt.scatter(ymsic4, ymenergy4,marker='o',s=6)\n",
+ "plt.scatter(ymsic2, ymenergy2,marker='o',s=6)\n",
+ "plt.scatter(ymsic3, ymenergy3,marker='o',s=6)\n",
+ "\n",
+ "ax.set_xticks([1-np.sin(np.radians(0)),1-np.sin(np.radians(10)),1-np.sin(np.radians(20)),1-np.sin(np.radians(30)),1-np.sin(np.radians(45)),1-np.sin(np.radians(60)),1-np.sin(np.radians(90))])\n",
+ "ax.set_xticklabels([0,10,20,30,45,60,90])\n",
+ "\n",
+ "plt.xlim(0,1.01)\n",
+ "\n",
+ "plt.ylim(ylim)\n",
+ "plt.xlabel(\"Ice-Edge Latitude [°]\")\n",
+ "plt.ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "#plt.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ "# ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ "# borderpad=0.5,borderaxespad=0.2,markerscale=2)\n",
+ "legend_color(ax,[\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],2)\n",
+ "\n",
+ "ax2 = ax.twinx()\n",
+ "co2_fac=np.linspace(1,5,9)\n",
+ "print(plt.ylim())\n",
+ "\n",
+ "np.exp(menergy1/alpha)\n",
+ "\n",
+ "ax2.set_yticks(np.log(co2_fac)*alpha)\n",
+ "ax2.set_ylim(ylim)\n",
+ "_=ax2.set_yticklabels(co2_fac)\n",
+ "plt.ylabel(\"Equivalent CO$_2$ Increase []\")\n",
+ "\n",
+ "#ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax2.spines['top'].set_color('none')\n",
+ "\n",
+ "plt.savefig(\"plots/heatflux_scatter_flux_icelat.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(2412, 96)\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ 48.539627 50.596096 53.38318 ... 219.82147 218.7206 217.7329 ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "ts1_sic = ts1\n",
+ "ts1_sic[sic1<1]=0\n",
+ "mts1_sic = np.pi/2* np.dot(ts1_sic,np.cos(np.radians(da1.lat))) / np.size(da1.lat)\n",
+ "\n",
+ "print(np.shape(ts1_sic))\n",
+ "\n",
+ "fig1, ax1 = plt.subplots()\n",
+ "im1=ax1.contourf(da1.lat, da1.time, ts1_sic)\n",
+ "fig1.colorbar(im1)\n",
+ "plt.show()\n",
+ "\n",
+ "#plt.plot(da1.time,mts1)\n",
+ "#plt.plot(da1.time,mts1_sic)\n",
+ "print(mts1_sic)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.9773656235942157\n",
+ "0.9704530181574433\n",
+ "0.9820133574839562\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(msit1, -mqbot1,'.',markersize=pltsize)\n",
+ "plt.plot(msit2, -mqbot2,'.',markersize=pltsize)\n",
+ "plt.plot(msit3, -mqbot3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show()\n",
+ "\n",
+ "print(np.corrcoef(msic1,-mqbot1)[1,0])\n",
+ "print(np.corrcoef(msic2,-mqbot2)[1,0])\n",
+ "print(np.corrcoef(msic3,-mqbot3)[1,0])\n",
+ "plt.plot(msic1, -mqbot1,'.',markersize=pltsize)\n",
+ "plt.plot(msic2, -mqbot2,'.',markersize=pltsize)\n",
+ "plt.plot(msic3, -mqbot3,'.',markersize=pltsize)\n",
+ "plt.xlabel(\"sic []\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "plt.legend([\"1438ppmv\",\"3000ppmv_Jor2\",\"5000ppmv_Jor2\"],loc = 2)\n",
+ "plt.show() \n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b763180cda0>]"
+ ]
+ },
+ "execution_count": 16,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.plot(da1.time,menergy1)\n",
+ "plt.plot(da2.time,menergy2)\n",
+ "plt.plot(da3.time,menergy3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 504x504 with 2 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ "fig1, (ax1, ax2) = plt.subplots(2, 1, sharex=False,figsize=(7,7))\n",
+ "ax1.plot(yice_lat1)\n",
+ "ax1.plot(yice_lat4)\n",
+ "ax1.plot(yice_lat2)\n",
+ "ax1.plot(yice_lat3)\n",
+ "\n",
+ "ax1.set_ylim(0,90)\n",
+ "ax1.set_xlim(0,210)\n",
+ "ax1.set_xlabel(\"time [years]\")\n",
+ "ax1.set_ylabel(\"ice latitude [°]\")\n",
+ "ax1.legend([\"1438ppmv\",\"1500ppmv\",\"3000ppmv\",\"5000ppmv\"],loc = 2, \n",
+ " ncol=4, labelspacing=0.2,columnspacing=2,handletextpad=0.1, handlelength=2, mode=\"expand\",\n",
+ " borderpad=0.5,borderaxespad=0.2)\n",
+ "ax1.text(-0.1,1,\"a)\", transform=ax1.transAxes, fontsize=14)\n",
+ "#plt.title(\"hice_5m: global sea ice border \")\n",
+ "\n",
+ "\n",
+ "ax2.plot(ymenergy1)\n",
+ "ax2.plot(ymenergy4)\n",
+ "ax2.plot(ymenergy2)\n",
+ "ax2.plot(ymenergy3)\n",
+ "\n",
+ "ax2.set_xlabel(\"time [years]\")\n",
+ "ax2.set_ylabel(\"$F_{ar}$ [W/m²]\")\n",
+ "ax2.set_ylim(0,6)\n",
+ "ax2.set_xlim(0,210)\n",
+ "ax2.text(-0.1,1,\"b)\", transform=ax2.transAxes, fontsize=14)\n",
+ "plt.savefig(\"plots/hice5m_sic_qbot.svg\",dpi=500)\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[3.19146303e+02 5.37758229e-01 1.06490622e+03]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[ 1.39134715 -0.84883122]\n",
+ "[-0.1278794 0.54114959 0.2003112 ]\n",
+ "[0.01143275 0.01283542 0.00298047]\n",
+ "[ 2.80987065 0.272662 -3.08239936]\n",
+ "[0.06881618 0.00409829 0.07651853]\n",
+ "[-6.77852209 0.2970746 1.7242942 6.71992723]\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "# fit\n",
+ "from scipy.optimize import curve_fit\n",
+ "\n",
+ "def exponential_func(x, a, b, c):\n",
+ " return a*np.exp(b*x)+c\n",
+ "def linear_func(x, a, b):\n",
+ " return a*x+b\n",
+ "def arcsin_func(x, a, b,c,d):\n",
+ " return a*np.arcsin(b*x+c)+d\n",
+ "def sin_func(x, a, b,c,d):\n",
+ " return a*np.sin(b*x+c)+d\n",
+ "def poly_func(x, a, b,c):\n",
+ " return a+b*x+c*x**2\n",
+ "\n",
+ "msit1m=msit1\n",
+ "mco21r=mco21\n",
+ "menergy1m=menergy1\n",
+ "\n",
+ "#exponential fit of equivalent co2\n",
+ "popt, pcov = curve_fit(exponential_func, msit1, mco21r, p0=(1, 1e-6, 1))\n",
+ "\n",
+ "print(popt)\n",
+ "plt.plot(msit1,mco21r,'.',markersize=pltsize)\n",
+ "plt.plot(msit1,exponential_func(msit1,popt[0],popt[1],popt[2]))\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"equivalent CO$_2$ factor []\")\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "\n",
+ "#linear fit of heat flux\n",
+ "popt, pcov = curve_fit(linear_func, msit1m, menergy1m, p0=(1, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,linear_func(msit1m,popt[0],popt[1]))\n",
+ "\n",
+ "\n",
+ "\n",
+ "#quadratic fit of heat flux\n",
+ "popt, pcov = curve_fit(poly_func, msit1m, menergy1m, p0=(1, 1,1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,poly_func(msit1m,popt[0],popt[1],popt[2]))\n",
+ "\n",
+ "\n",
+ "#exponential fit of heat flux\n",
+ "popt, pcov = curve_fit(exponential_func, msit1m, menergy1m, p0=(1, 1e-6, 1))\n",
+ "\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "plt.plot(msit1m,exponential_func(msit1m,popt[0],popt[1],popt[2]))\n",
+ "\n",
+ "\n",
+ "\n",
+ "#sin fit of heat flux\n",
+ "popt, pcov = curve_fit(sin_func, msit1m, menergy1m, p0=(-1, 1, 0, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "#plt.plot(msit1m,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(msit1m,sin_func(msit1m,popt[0],popt[1],popt[2],popt[3]))\n",
+ "\n",
+ "\n",
+ "plt.xlabel(\"sit [m]\")\n",
+ "plt.ylabel(\"heat flux [W/m^2]\")\n",
+ "\n",
+ "plt.legend([\"data\",\"linear\",\"quadratic\",\"exponential\",\"sinusoidal\"],loc = 2)\n",
+ "plt.savefig(\"plots/F_sit_fit.pdf\",dpi=500)\n",
+ "plt.show()\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[-0.08474864 24.13225415]\n",
+ "[9.52501758e-05 2.55617904e-02]\n",
+ "-0.9984813316701636\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "[<matplotlib.lines.Line2D at 0x2b763184dbe0>]"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "\n",
+ "#linear fit of heat flux & surface temperature\n",
+ "popt, pcov = curve_fit(linear_func, mts1, menergy1m, p0=(1, 1))\n",
+ "#popt=[4,1/4,0]\n",
+ "print(popt)\n",
+ "print(np.sqrt(np.diag(pcov)))\n",
+ "print(np.corrcoef(mts1,menergy1)[1,0])\n",
+ "plt.plot(mts1,menergy1m,'.',markersize=pltsize)\n",
+ "plt.plot(mts1,linear_func(mts1,popt[0],popt[1]))\n",
+ "\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "celltoolbar": "Tags",
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /overview.ipynb b/python_scripts /overview.ipynb
new file mode 100644
index 0000000..ad8dfa7
--- /dev/null
+++ b/python_scripts /overview.ipynb
@@ -0,0 +1,498 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "import cycler\n",
+ "import glob\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " DA = get_var(DS,'sic',False)\n",
+ " icelat = np.squeeze(np.arcsin(1-DA) * (180./np.pi) )\n",
+ " time=DA.time\n",
+ " return time, icelat # returns the name of the experiment & the actual dataset & icelat array\n",
+ "\n",
+ "def load_experiment2(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml*.mm.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_icon_aes/MLO/AQUA/\" +expname +\"/\" #simulation path\n",
+ " fpath = glob.glob(dpath +fname)[0]\n",
+ " DS = xr.open_dataset(fpath, decode_times=False) #loading of dataset\n",
+ " print(fpath)\n",
+ " DA = get_var(DS,'sic',False)\n",
+ " icelat = np.squeeze(np.arcsin(1-DA) * (180./np.pi) )\n",
+ " time=DA.time\n",
+ " return time, icelat # returns the name of the experiment & the actual dataset & icelat array\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "test=glob.glob('/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml*gm.nc')[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml_0001to0150.mm.gm.nc'"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "test"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### hice_unlim experiments"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv_hice_unlim/mlo_aqua_1594ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1688ppmv_hice_unlim/mlo_aqua_1688ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_hice_unlim/mlo_aqua_1875ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_hice_unlim/mlo_aqua_2250ppmv_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_61sic_hice_unlim/mlo_aqua_3000ppmv_61sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_69sic_hice_unlim/mlo_aqua_3750ppmv_69sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3750ppmv_77sic_hice_unlim/mlo_aqua_3750ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3907ppmv_77sic_hice_unlim/mlo_aqua_3907ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4063ppmv_77sic_hice_unlim/mlo_aqua_4063ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_77sic_hice_unlim/mlo_aqua_4219ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4375ppmv_77sic_hice_unlim/mlo_aqua_4375ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_83sic_hice_unlim/mlo_aqua_5000ppmv_83sic_hice_unlim_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_77sic_hice_unlim/mlo_aqua_10000ppmv_77sic_hice_unlim_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(16,dtype=object)\n",
+ "icelatarray=np.zeros(16,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "timearray[1], icelatarray[1] = load_experiment(\"mlo_aqua_1594ppmv_hice_unlim\")\n",
+ "timearray[2], icelatarray[2] = load_experiment(\"mlo_aqua_1688ppmv_hice_unlim\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_1875ppmv_hice_unlim\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_2250ppmv_hice_unlim\")\n",
+ "\n",
+ "timearray[5], icelatarray[5] = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "timearray[6], icelatarray[6] = load_experiment(\"mlo_aqua_3000ppmv_61sic_hice_unlim\")\n",
+ "timearray[7], icelatarray[7] = load_experiment(\"mlo_aqua_3750ppmv_69sic_hice_unlim\")\n",
+ "timearray[8], icelatarray[8] = load_experiment(\"mlo_aqua_3750ppmv_77sic_hice_unlim\")\n",
+ "timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_3907ppmv_77sic_hice_unlim\")\n",
+ "timearray[10], icelatarray[10] = load_experiment(\"mlo_aqua_4063ppmv_77sic_hice_unlim\")\n",
+ "timearray[11], icelatarray[11] = load_experiment(\"mlo_aqua_4219ppmv_77sic_hice_unlim\")\n",
+ "timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_4375ppmv_77sic_hice_unlim\")\n",
+ "timearray[13], icelatarray[13] = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "timearray[14], icelatarray[14] = load_experiment(\"mlo_aqua_5000ppmv_83sic_hice_unlim\")\n",
+ "timearray[15], icelatarray[15] = load_experiment(\"mlo_aqua_10000ppmv_77sic_hice_unlim\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "l1,=plt.plot(timearray[0],icelatarray[0],'-',label='1500ppmv 90°')\n",
+ "l2,=plt.plot(timearray[1],icelatarray[1],'-',label='1594ppmv 53°')\n",
+ "l3,=plt.plot(timearray[2],icelatarray[2],'-',label='1688ppmv 53°')\n",
+ "l4,=plt.plot(timearray[3],icelatarray[3],'-',label='1875ppmv 90°')\n",
+ "l5,=plt.plot(timearray[4],icelatarray[4],'-',label='2250ppmv 90°')\n",
+ "\n",
+ "\n",
+ "lj1, = plt.plot(timearray[5],icelatarray[5],'-',label='3000ppmv 14°')\n",
+ "lj2, = plt.plot(timearray[6],icelatarray[6],'-',label='3000ppmv 22°')\n",
+ "lj3, = plt.plot(timearray[7],icelatarray[7],'-',label='3750ppmv 19°')\n",
+ "lj4, = plt.plot(timearray[8],icelatarray[8],'-',label='3750ppmv 14°')\n",
+ "#lj5, = plt.plot(timearray[9],icelatarray[9],'-',label='3907ppmv 14°')\n",
+ "lj6, = plt.plot(timearray[10],icelatarray[10],'-',label='4063ppmv 14°')\n",
+ "#lj7, = plt.plot(timearray[11],icelatarray[11],'-',label='4219ppmv 14°')\n",
+ "lj8, = plt.plot(timearray[12],icelatarray[12],'-',label='4375ppmv 14°')\n",
+ "lj9, = plt.plot(timearray[13],icelatarray[13],'-',label='5000ppmv 14°')\n",
+ "#lj10, = plt.plot(timearray[14],icelatarray[14],'-',label='5000ppmv 12°')\n",
+ "lj11, = plt.plot(timearray[15],icelatarray[15],'-',label='10000ppmv 14°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,600)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=4,edgecolor='none', facecolor='none', \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_semtner_unlim.pdf\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Winton experiments"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_1875ppmv_winton/mlo_aqua_1875ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2250ppmv_winton/mlo_aqua_2250ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2437ppmv_winton/mlo_aqua_2437ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_2625ppmv_winton/mlo_aqua_2625ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton/mlo_aqua_3000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_winton_50sic/mlo_aqua_3000ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_74sic_winton/mlo_aqua_3000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_winton_50sic/mlo_aqua_4219ppmv_winton_50sic_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart/mlo_aqua_4219ppmv_71sic_winton_semtnerrestart_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_winton/mlo_aqua_5000ppmv_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_37sic_winton/mlo_aqua_5000ppmv_37sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_74sic_winton/mlo_aqua_5000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_10000ppmv_74sic_winton/mlo_aqua_10000ppmv_74sic_winton_atm_2d_ml.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(13,dtype=object)\n",
+ "icelatarray=np.zeros(13,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment(\"mlo_aqua_1875ppmv_winton\")\n",
+ "timearray[1], icelatarray[1] = load_experiment(\"mlo_aqua_2250ppmv_winton\")\n",
+ "timearray[2], icelatarray[2] = load_experiment(\"mlo_aqua_2437ppmv_winton\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_2625ppmv_winton\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_3000ppmv_winton\")\n",
+ "\n",
+ "timearray[5], icelatarray[5] = load_experiment(\"mlo_aqua_3000ppmv_winton_50sic\")\n",
+ "timearray[6], icelatarray[6] = load_experiment(\"mlo_aqua_3000ppmv_74sic_winton\")\n",
+ "timearray[7], icelatarray[7] = load_experiment(\"mlo_aqua_4219ppmv_winton_50sic\")\n",
+ "timearray[8], icelatarray[8] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")\n",
+ "timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_5000ppmv_winton\")\n",
+ "timearray[10], icelatarray[10] = load_experiment(\"mlo_aqua_5000ppmv_37sic_winton\")\n",
+ "timearray[11], icelatarray[11] = load_experiment(\"mlo_aqua_5000ppmv_74sic_winton\")\n",
+ "timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_10000ppmv_74sic_winton\")\n",
+ "\n",
+ "#timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "\n",
+ "#timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "_, = plt.plot(timearray[0],icelatarray[0],'-',label='1875ppmv 90°')\n",
+ "_, = plt.plot(timearray[1],icelatarray[1],'-',label='2250ppmv 90°')\n",
+ "_, = plt.plot(timearray[2],icelatarray[2],'-',label='2437ppmv 59°')\n",
+ "_, = plt.plot(timearray[3],icelatarray[3],'-',label='2625ppmv 59°')\n",
+ "_, = plt.plot(timearray[4],icelatarray[4],'-',label='3000ppmv 90°')\n",
+ "_, = plt.plot(timearray[5],icelatarray[5],'-',label='3000ppmv 30°')\n",
+ "_, = plt.plot(timearray[6],icelatarray[6],'-',label='3000ppmv 15°')\n",
+ "_, = plt.plot(timearray[7],icelatarray[7],'-',label='4219ppmv 30°')\n",
+ "_, = plt.plot(timearray[8],icelatarray[8],'-',label='4219ppmv 17°')\n",
+ "_, = plt.plot(timearray[9],icelatarray[9],'-',label='5000ppmv 90°')\n",
+ "_, = plt.plot(timearray[10],icelatarray[10],'-',label='5000ppmv 39°')\n",
+ "_, = plt.plot(timearray[11],icelatarray[11],'-',label='5000ppmv 15°')\n",
+ "_, = plt.plot(timearray[12],icelatarray[12],'-',label='10000ppmv 15°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,210)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=3,edgecolor='none', facecolor='none',loc=1, \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_winton.pdf\")\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Semtner 5m simulations"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1250ppmv/mlo_aqua_1250ppmv_atm_2d_ml_0121to0222.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1375ppmv/mlo_aqua_1375ppmv_atm_2d_ml_0136to0269.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_1438ppmv/mlo_aqua_1438ppmv_atm_2d_ml_0137to0338.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1594ppmv/mlo_aqua_1594ppmv_atm_2d_ml.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2000ppmv_Jor2/mlo_aqua_2000ppmv_Jor2_atm_2d_ml_0258to0277.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2000ppmv_Jor5/mlo_aqua_2000ppmv_Jor5_atm_2d_ml_0318to0356.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2500ppmv_Jor2/mlo_aqua_2500ppmv_Jor2_atm_2d_ml_0258to0341.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_2500ppmv_Jor5/mlo_aqua_2500ppmv_Jor5_atm_2d_ml_0318to0369.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv/mlo_aqua_3000ppmv_atm_2d_ml_0001to0089.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor/mlo_aqua_3000ppmv_Jor_atm_2d_ml_0298to0337.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor2/mlo_aqua_3000ppmv_Jor2_atm_2d_ml_0258to0425.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_3000ppmv_Jor3/mlo_aqua_3000ppmv_Jor3_atm_2d_ml_0253to0502.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv/mlo_aqua_5000ppmv_atm_2d_ml_0001to0079.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor/mlo_aqua_5000ppmv_Jor_atm_2d_ml_0298to0307.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor2/mlo_aqua_5000ppmv_Jor2_atm_2d_ml_0258to0306.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_5000ppmv_Jor4/mlo_aqua_5000ppmv_Jor4_atm_2d_ml_0421to0490.mm.gm.nc\n",
+ "/work/bb1092/pp_icon_aes/MLO/AQUA/mlo_aqua_10000ppmv_Jor/mlo_aqua_10000ppmv_Jor_atm_2d_ml_0298to0307.mm.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "timearray=np.zeros(18,dtype=object)\n",
+ "icelatarray=np.zeros(18,dtype=object)\n",
+ "\n",
+ "timearray[0], icelatarray[0] = load_experiment2(\"mlo_aqua_1250ppmv\")\n",
+ "timearray[1], icelatarray[1] = load_experiment2(\"mlo_aqua_1375ppmv\")\n",
+ "timearray[2], icelatarray[2] = load_experiment2(\"mlo_aqua_1438ppmv\")\n",
+ "timearray[3], icelatarray[3] = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "timearray[4], icelatarray[4] = load_experiment(\"mlo_aqua_1594ppmv\")\n",
+ "timearray[5], icelatarray[5] = load_experiment2(\"mlo_aqua_2000ppmv_Jor2\")\n",
+ "timearray[6], icelatarray[6] = load_experiment2(\"mlo_aqua_2000ppmv_Jor5\")\n",
+ "timearray[7], icelatarray[7] = load_experiment2(\"mlo_aqua_2500ppmv_Jor2\")\n",
+ "timearray[8], icelatarray[8] = load_experiment2(\"mlo_aqua_2500ppmv_Jor5\")\n",
+ "timearray[9], icelatarray[9] = load_experiment2(\"mlo_aqua_3000ppmv\")\n",
+ "timearray[10], icelatarray[10] = load_experiment2(\"mlo_aqua_3000ppmv_Jor\")\n",
+ "timearray[11], icelatarray[11] = load_experiment2(\"mlo_aqua_3000ppmv_Jor2\")\n",
+ "timearray[12], icelatarray[12] = load_experiment2(\"mlo_aqua_3000ppmv_Jor3\")\n",
+ "timearray[13], icelatarray[13] = load_experiment2(\"mlo_aqua_5000ppmv\")\n",
+ "timearray[14], icelatarray[14] = load_experiment2(\"mlo_aqua_5000ppmv_Jor\")\n",
+ "timearray[15], icelatarray[15] = load_experiment2(\"mlo_aqua_5000ppmv_Jor2\")\n",
+ "timearray[16], icelatarray[16] = load_experiment2(\"mlo_aqua_5000ppmv_Jor4\")\n",
+ "timearray[17], icelatarray[17] = load_experiment2(\"mlo_aqua_10000ppmv_Jor\")\n",
+ "\n",
+ "\n",
+ "#timearray[12], icelatarray[12] = load_experiment(\"mlo_aqua_5000ppmv_77sic_winton_semtnerrestart\")\n",
+ "\n",
+ "#timearray[9], icelatarray[9] = load_experiment(\"mlo_aqua_4219ppmv_71sic_winton_semtnerrestart\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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MCq/UzK0REGvR6XSMHTuWxx9/nDFjxsjlHTt2JC8vD1dXV/Ly8uTHHW5ubpw6daqK3Z06dapTeyr7vDb/q1Qq7O3tq1zkK/wfExPD8uXLcXFxoW/fvrRqZf0j0r179zJ+/HgA8vPz2bJlC2q1mkcffdTqfVSmIgJyu7Rp04awsDCSkpKYMWMGly5dQq/Xo1arq/TlCv+7ubmh1+u5fPkyLi4uZs8LmPexpdeV/X/rd6Gy/9euXYu3tzejR4+2eIPWvHlzRo4cyaZNm4iIiDDbv26XighIXanwUYcOHRg9ejRpaWkMGDDgruv/dnZ2xMTE8M477/D000+b7Ue24K6LmJhDd9DyfIOmhGRvh31PJafJrSQlJbFo0SISExO555575PKLFy/Kk/pOnDhBdnY2np6euLq60qpVK3bv3o0QgtWrV1e5g6i4U/jll19wcnLCycmUEG/Tpk2UlpZSUFBASkoKffv2tdpGR0dHgoKCeOmll4iMjKzx7jsvL09+nZiYKD+aGTx4MNu2baOoqIiioiK2bdtWZRJmQyCEYNKkSfj4+PDyyy9X2TZy5Eh5ZcGqVatkX44cOZLVq1cjhGD37t04OTnh6upqsT1Go1Fe9fL111/z4IMPyscxd16sISwsjP379/P555/X6TEOmB4HarVatFotUVFRfPzxx7c9KLldLl68KN8hX79+nR9//BFvb28kSSI8PFz22a3+rzgv69evZ+DAgUiSxMiRI0lISKCsrIzc3Fyys7MJCgoC4OTJk3I0JD4+vkb/r1mzhtDQ0DrZP2bMGDZu3Eh8fHyN/r927Zrc//V6PVu2bMHb27taOyq3ryEpLi7m6tWr8utt27bJqwPvhv4vhJDnDQkh2Lx5c43+r9yPbMHdFzFpoBWy9gFdwCjQHThVe2UboGrfCpWrE+gMGPOvYR/ojm6vFrh7V+NUMGHCBFJSUsjPz8fNzY0FCxYwadIk/vrXv1JWVkZERARgmgD76aefsmPHDl577TXUajV2dnZ8+umn8kj/k08+YeLEiVy/fp2hQ4dWuYtydnamX79+XLlyhS+//FIuDwoKYvjw4Zw8eZJ58+bRqVMnjh07ZrX9MTExjBs3rsrdUmU+/PBDEhMTUavVuLi4sHLlSgBcXFyYN2+ePBB67bXXbHbHYo6dO3fy1VdfycslAd566y2GDRvGnDlziI6OZsWKFXTp0kVeTTFs2DC2bNmCl5cX99xzD//+979rbU/Lli3JzMykT58+ODk5VVmGa+68WIOdnR2RkZGsXLnS7PLMDz/8kMWLF3Pu3Dn8/f0ZNmxYlSXbjUleXh6xsbEYDAaMRiPR0dFERkYCsGjRIsaPH8+rr75KQEAAkyZNAkzLP5988km8vLxwcXEhISEBAF9fX6Kjo+nRowdqtZrly5fLA2UfHx9WrVrFlClT0Gg08koSMC0bDQ4Oxmg0Eh8fXyf7nZ2d6dGjB4cPH5YHQZUpLi5m5MiRlJWVYTAYGDhwoLy831z/akjOnz/P6NGjAdPA6bHHHpMfmdwN/V8IQWxsrPyou2fPnnzyySeA+X5kC6Q7IW9DbQQGBorKy7IsYbxWRvnP1v9I3C4V6eb1uRfRn8hH1ao5xuIy7FydsPd2tfnxa0IIgbhSiurWZckKdSYsLIx33323Sp4CMM1+d3R0lCcCKtgGR0dHOX9CZcydF4X6Q6vVEhkZKU+qrIy7uzt79+6lXTvL89wU/hh/kv5vNozQJCImxpI6LP1tgIiJvf/NlRxqj/aoPdrb/qBWIElS9VwpCgoKCgoKTYgmETHp1a2HyDh22Kq6xuIyObGaLbDvcz92HSyvQlBQUFBQUFCwiNkwgk0nv0qSNF2SpExJkg5JkhQvSVJzSZI8JEn6TZKkbEmS1kiS1Kz2PTUyze2x6+yMQ7i3MihRUFBQUFCwITYbmEiSdB/wIhAohHgAsAPGA4uAD4QQGqAImFTPB67X3QFILeyxf8ANqXn1RFgKCgoKCgoK9YetlwurgRaSJKmBe4A8YCBQoX61CqjX9XbG89ZlEq0L6s4Nu/JBQUFBQUHhz4rNBiZCiDPAu8BJTAOSy8A+4JIQoiIf/Gngvno7ZqkO/dG82ivWAamlA3b3OdfrPhUUFBQUFBRqxpaPcpyBUYAH0AloCdSUaq/G2beSJD0rSdJeSZL2WjtBVxhtMJFX/afJQddkiIuLo0OHDnJiowrmzZuHv78/vXr1YtCgQZw9exaAd955h169etGrVy8eeOAB7OzsKCwsBMxLmDcmK1eupH379rLNlXNomJNJT0lJITAwsIpImi04deqUrMfj6+vL0qVL5W2K7Hv9yb6bo7S0lKCgIHr27Imvry+vv/66vC03N5fg4GA0Gg0xMTGUl5fXavfChQvx8vKie/fubN261aa2W8vcuXPp3LmzLFZ4K+vXr0eSpCrKvg3lfzB/zbhb+v+yZcvw8vJCkiTy86tnGN+zZw92dnZyAjgwKRL37t27Sr6VP4QQwiZ/wDhgRaX3TwGfAPmA+kZZKLC1tn311PgIazCWlIvrWw7W65+xpMyqYys0HKmpqWLfvn3C19e3Svnly5fl10uXLhVTpkyp9tnExEQRHh4uv7///vvFxYsXbWfsbfDvf/9bPP/889XKCwoKhIeHhygoKBCFhYXCw8NDFBYWCiGEiI6OFiUlJeLll18WR44csZltZ8+eFfv27RNCCHHlyhWh0WhEZmamEEKImTNnioULFwohhFi4cKGYNWuWEEKI7777TgwZMkQYjUaxa9cuERQUVGt7GpPK/Wj69Olym5YvXy73qfj4eBEdHS2EEOLIkSPib3/7myguLhbjxo2zqW1Go1FcvXpVCCFEeXm5CAoKErt27RJCCDFu3DgRHx8vhBBiypQp4uOPP7Zod2ZmpvD39xelpaXixIkTwtPTU+j1epvabw27du0SZ8+eFS1btqy27cqVK+Khhx4SwcHBYs+ePUKIhvW/EOavGXdL/9+/f7/Izc2tsZ16vV6Eh4eLoUOHinXr1gkhhLh69aqYMGGC0Ol0YuTIkXU5lNnffFuGA04CIZIk3SOZ8tY+AhwGfgKibtSJBTb9kYMIgxH98QuIUh26zDO1f8AC9r0603yoH82CPVG5OtHsIQ1Sizt/0dCfjQEDBtSY8bSymFxxcXGN6ZLj4+NlESxLWJIXf/LJJxk4cCAajYbPP/8cMEUsHn74YaKjo+nWrRtz5szhP//5D0FBQfj5+ZGTk8Ply5dxd3fHaDQCUFJSQufOndHpdFa125JMutFoNAk92lj63dXVld69ewMmVV0fHx9ZEVWRfa8/2XdzSJIkRxJ0Oh06nU4+bnJysqzEe6v/a7J706ZNjB8/HgcHBzw8PPDy8iItLQ2tVou3tzexsbFy1KikpAQwRQtmz55NUFAQQUFBcvryiRMnMnXqVMLDw/H09CQ1NZW4uDh8fHyYOHEiYMqyXDmit3LlSl544YVqbQwJCZFVem9l3rx5zJo1i+bNb2a3bkj/W+Ju6f8BAQG4u7vX2MaPPvqIsWPHVtEpqvB5faant1mCNSHEb5IkrQf2A3ogHfgM+A5IkCTpnzfKVtzuMfSnCtEfMl0U9dnn/5jBKgk71zamly4taebS8o/tT6FWDmqvcrnYuh9lp5b2+LvXLrg2d+5cVq9ejZOTEz/99FOVbSUlJSQlJcny4WBewhzMy4sfPHiQ3bt3U1xcTEBAAMOHDwfgwIEDHDlyBBcXFzw9PZk8eTJpaWksXbqUjz76iCVLltCzZ09SU1MJDw9n8+bNDB48GHv76qu9vvnmG3bs2EG3bt344IMP6Ny5s0WZ9MmTJ9OvXz/5MYs1nHvrLcqOHLWqroOPN/f+/e9VyrRaLenp6QQHBwOK7HtdZd9P7P6Z4gLrxDhbtm2HZ8hDgOmHuE+fPhw/fpznn3+e4OBg8vPzadOmDWq1upovzdl95swZQkJCqvnf1dWVrKwsVqxYQf/+/YmLi+Pjjz+Wsx23bt2atLQ0Vq9ezbRp0/j2228BKCoqIjk5mcTEREaMGMHOnTv54osv6Nu3LxkZGURFRREaGsrixYsBk+bL3LlzrfZXeno6p06dIjIyknfffVcuv13/a7VaiouLrarbsmVL+cfa3DXjbur/NXHmzBk2bNhAcnIye/bskctbtWqFn58fgYGBzJw50+r9WcKmEyiEEK8LIbyFEA8IIZ4UQpQJIU4IIYKEEF5CiHFCiNrTupoZBFcMSuoDZYLr3cGbb77JqVOnePzxx6sMQAA2b95M//79q0RbLEmYm5MXHzVqFC1atKBdu3aEh4fLdy19+/bF1dUVBwcHunbtyqBBg4CbsuNg0smpeA6bkJBQ44VhxIgRaLVaDh48yF/+8hf5Lqymu8GKu5TBgwezf/9++UfU1ly7do2xY8eyZMmSKpGqmjBnt6X2/Nll3y1hZ2dHRkYGp0+fJi0tjUOHDlm07Xb837lzZ/r37w+Y9/+ECRNkoT8w9VtJkvDz86Njx474+fmhUqnw9fVFq9XSvn17PD092b17NwUFBWRlZcnHqA2j0cj06dPN9u+G9L+la0ZNNMX+XxPTpk1j0aJFNQqPvvLKK6Snp/PYY49ZvT9LNImU9LbCzr0tqg6tkZrbK49sGgFrIiC3y2OPPcbw4cNZsGCBXJaQkFDtMY45CXMwLy9em+w4VJV+ryw7PnLkSF555RUKCwvNXkjbtm0rv37mmWeYPXs2QJ1k0q3h1giIteh0OsaOHcvjjz/OmDFj5HJF9r1uVERAbpc2bdoQFhZGUlISM2bM4NKlS+j1etRqtexjwKzd5s4LmPexpdeV/X/rd6Gy/9euXYu3tzejR4+2Ovx/9epVDh06JPePc+fOMXLkSBITE2970rq5xxW1Ye6acbf1/1vZu3cv48ePByA/P58tW7agVqttorDdZJec1MezRLV7O+zaOqJq6YCkaiBZYgWbkZ2dLb9OTEyU5boBLl++TGpqapU7BEsS5mBeXnzTpk2UlpZSUFBASkqKrA5qDY6OjgQFBfHSSy8RGRlZ491Hhex7RTsqHs1YkklvKIQQTJo0CR8fH15++eUq2xTZd9tz8eJF+Q75+vXr/Pjjj3h7eyNJEuHh4bLPbvV/TXaPHDmShIQEysrKyM3NJTs7W1b8PXnypBwNiY+Pr9H/a9asITQ0tE72jxkzho0bNxIfH1+nxwhOTk7k5+ej1WrRarWEhIT8oUHJ7WLpmnE39H9L5Obmyv6Piori448/tsmgBJpwxER//MJtfa7Zgxp0+7SI6zpQV/9RULjzmTBhAikpKeTn5+Pm5saCBQuYNGkSc+bMISsrC5VKxf3338+nn34qf2bDhg0MGjSIli1vzh2yJGEO5uXFg4KCGD58OCdPnmTevHl06tSJY8es12eKiYlh3LhxVe6WKvPhhx+SmJiIWq3GxcWFlStXApZl0huKnTt38tVXX8nLJQHeeusthg0bpsi+NwB5eXnExsZiMBgwGo1ER0cTGRkJwKJFixg/fjyvvvoqAQEBTJo0yaLdvr6+REdH06NHD9RqNcuXL5cHyj4+PqxatYopU6ag0WiYOnWqbENZWRnBwcEYjUbi4+PrZL+zszM9evTg8OHD8iDoVmbNmsXXX39NSUkJbm5uTJ48mfnz59fVVTbB0jXjbuj/YLr+LF68mHPnzuHv78+wYcOqpCxoCJqGiJ+mh8jIririV/r9/+q8HzuvDthrOiL0BkRxOSpFiVfBDObkxefPn4+jo6M8EVDBNvxJZN/vSLRaLZGRkfKkysq4u7uzd+9e2rVr1wiW/Xn4k/R/s+HGJhkxMRbXPl+2JtSe7QGQ1HZIyqBEQUFBQUHhjqNJREwCND1EevZhjFeug95I+W8nrP+wgxq7jq1R+3RS5pEoKCgoKCjcGdwdEZPyncfrVF9yvodmwZ4NPkFNQUFBQUFB4fZoEgMTQd0z+tm5t0Ptfa8yKFFQUFBQUGhCNImBiR1Q+r8z5uM+t9Ds4e6o7lHykigoKCgoKDQ1mk4ek/yrZjfZ97qZ1rf5UD9lUKKgoKCgoNBEaTIDE6lMX2O5fe/7ZY0bhT8HcXFxdOjQoUoytMq8++67VSS7N23ahL+/vyxTXjm986xZs/D19SYbnwkAACAASURBVMXHx4cXX3yxUUXAKpg4cSIeHh706tWLXr16kZGRAViWT6932XEznDp1Stbj8fX1ZenSpfK2+fPnc99998l2b9myRd62cOFCvLy86N69O1u3bpXLk5KS6N69O15eXrz99ts2td1a1q1bh6+vLyqVir1791bbfvLkSRwdHavotSQkJNC7d2+WLFliU9tKS0sJCgqiZ8+e+Pr68vrrr8vbcnNzCQ4ORqPREBMTQ3l5OWDKOxITE4OXlxfBwcGyPAKYPy+Nydy5c+ncubMsVliZtWvX0qNHD3x9faukP2+o/g+mJdMVeXwqL9stLCwkIiICjUZDREQERUVFgOXv7apVq9BoNGg0GrN5RRqaZcuW4eXlVeUaCpavo/Xuf0vSw3fKX2+vHuL6loM1/lVgLCkThmulteosKzR9UlNTxb59+4Svr2+1bSdPnhSDBg0SXbp0kSW7r169KoxGoxBCiAMHDoju3bsLIYTYuXOn6Nevn9Dr9UKv14uQkBDx008/NVg7zBEbGytLilfGnHz6H5AdrzNnz54V+/btE0KYJOg1Go3IzMwUQgjx+uuvi3feeafaZzIzM4W/v78oLS0VJ06cEJ6enrLPPT09RU5OjigrKxP+/v7yvhqTw4cPi6NHj4qHH35Y7Nmzp9r2MWPGiKioqCptHTVqlNDr9SImJkZcvXrVZrYZjUZ5/+Xl5SIoKEjs2rVLCCHEuHHjRHx8vBBCiClTpoiPP/5YCCHE8uXLxZQpU4QQQsTHx4vo6GghhPnz0tjs2rVLnD17VrRs2bJK+bFjx0SvXr1EYWGhEEKI8+fPCyEatv8LIcT9998vX1sqM3PmTLFw4UIhhBALFy4Us2bNEkKY/94WFBQIDw8PUVBQIAoLC4WHh4fctsZk//79Ijc3t1o7zV1H/4D/zf7mN5mISU2oOt2MlEgtmqFq6WChtsLdwoABA8xmPJ0+fTqLFy+uMunZ0dFRfl9cXFxF86a0tJTy8nLKysrQ6XR07NhR/kxjyY6bw5x8urCB7Lg5XF1d6d27N2BSFfXx8ZEVUS3ZPX78eBwcHPDw8MDLy4u0tDTS0tLw8vLC09OTZs2aMX78eDZt2gSY7kpnz55NUFAQQUFBcpr4iRMn8txzz/HQQw/RrVs3Wdl25cqVPProo4wYMQIPDw+WLVvG+++/T0BAACEhIRQWFnLkyJEq2Ua1Wi3+/v7V7PXx8aF79+41tmXjxo14enri6+tbpbzyOah4bQskSZIjCTqdDp1OJx8zOTmZqKgoAGJjY9m4cSNg8n+FEGRUVBTbt29HCGH2vGi1Wry9vYmNjcXf35+oqChKSkoAy+dl6tSphIeH4+npSWpqKnFxcfj4+DBx4kQAPvnkE2bNmiW3ZeXKlbzwwgvV2hgSEiKr9Fbm888/5/nnn8fZ2SS4WqFF05D93xKV/Xyr/2v63m7dupWIiAhcXFxwdnYmIiKCpKQkoHGvPwEBATXqCJm7jtrC/01i8mtNSI4ONOvZufaKCncu38+Bc1Zm8L3XD4ZaDvUnJiZy33330bNnz2rbNmzYwCuvvMKFCxf47rvvAAgNDSU8PBxXV1eEEPz1r3+VdWkaW3Z87ty5vPHGGzzyyCO8/fbbODg4mJVJDwwMvD3Z8Z2/QEGBdXXbtoX+D1Yp0mq1pKenExwcLJctW7aM1atXExgYyHvvvYezszNnzpwhJCSkmt1Atfb89ttv8vvWrVuTlpbG6tWrmTZtmjwI0Wq1pKamkpOTQ3h4uPzjeOjQIdLT0yktLcXLy4tFixaRnp7O9OnT5X2Ul5dz4sQJPD09WbNmTZULdW0UFxezaNEifvjhhyqPccCkARMYGMgTTzxhtTDapc05lJ8ttqpus04taTOiKwAGg4E+ffpw/Phxnn/+eYKDg8nPz6dNmzao1aZLemUfV+43arUaJycnCgoKzJ4XV1dXsrKyWLFiBf379ycuLo6PP/5YznZs7rwUFRWRnJxMYmIiI0aMYOfOnXzxxRf07duXjIwMoqKiCA0NZfHixYBJ82Xu3LlWtR+QZR/69++PwWBg/vz5DBkyhFatWt1W/z927B9cvXbEqrqtHH3o1m0eYPoBHjRoEJIkMWXKFJ599lnAlK6+YkDl6urKhQsm2RRz31tz5dD41x9z1HQdvV3/W6JJRkwk55Y0C3RvbDMU7iBKSkp48803eeONN2rcPnr0aI4ePcrGjRuZN890gTl+/DhHjhzh9OnTnDlzhuTkZFnCvDFlxxcuXMjRo0fZs2cPhYWFLFq0CDAvnw71LzteG9euXWPs2LEsWbKE1q1bAzB16lRycnLIyMjA1dWVGTNmWLTbUnvgpp8nTJggC8oBREdHo1Kp0Gg0eHp6cvToUQDCw8Np1aoV7du3x8nJSb4brPB/xWfXrl0LUOcL8+uvv8706dNrnPsQGxtLenq63GZbYmdnR0ZGBqdPnyYtLY1Dhw5Z9OXt+L9z5870798fMN//bz0vI0aMQJIk/Pz86NixI35+fqhUKnx9fdFqtbRv3x5PT092795NQUEBWVlZ8jGsQa/Xk52dTUpKCvHx8UyePFn+7jVk/9+5cyf79+/n+++/Z/ny5fI1wxy34//GvP5YoqbrKNS//5tcxETf1wPHdtUvDApNkFoiIHUhJyeH3NxcOVpy+vRpevfuTVpaGvfee69cb8CAAeTk5JCfn8+GDRsICQmRf2iGDh3K7t27GTBgQLX9N6TseMVdl4ODA08//bR8d25Jpv62uCUCYi06nY6xY8fy+OOPM2bMGLm84jEYwDPPPCOLy1my21J7zPm8Nv+DyeeVz0dl/48bN44xY8YgSRIajcbqdv/222+sX7+eWbNmcenSJVQqFc2bN+evf/2r1fuoTEUE5HZp06YNYWFhJCUlMWPGDC5duoRer0etVlfxZYX/3dzc0Ov1XL58GRcXF4vnxZyPLb2u7O9bz0Vl/69duxZvb29Gjx5dp/C/m5sbISEh2Nvb4+HhQffu3cnOzq6TundlKiIgdaXCRx06dGD06NGkpaUxYMAAOnbsSF5eHq6uruTl5cmPmsz52c3NrYqQ5+nTpwkLC6vxmA15/bGGytdRW+gm2SxiIklSd0mSMir9XZEkaZokSS6SJP0gSVL2jf/OddlvWbnRViYrNGH8/Py4cOGCLMvt5ubG/v37uffeezl+/Lh8d7J//37Ky8tp27YtXbp0ITU1Fb1ej06nIzU1VX6U05iy43l5eYDpTmvjxo1VZNVrkk9vSIQQTJo0CR8fH15++eUa7QZTyLey3QkJCZSVlZGbm0t2djZBQUH07duX7OxscnNzKS8vJyEhgZEjR8r7qPDzmjVrCA0NlcvXrVuH0WgkJyeHEydOmJ0PUhNdu3bFzs6Of/zjH3UOY//8889y/5o2bRp///vfb3tQcrtcvHhRvkO+fv06P/74I97e3kiSRHh4uNxnV61aJd8Njxw5Ul7xsX79egYOHIgkSWbPC5hWHlVEQ+Lj42vs/7eeF2sYM2YMGzduJD4+vs7+f/TRR/npp58AyM/P59ixY3h6etZpH3+U4uJirl69Kr/etm1blX5e4edb/V/T93bw4MFs27aNoqIiioqK2LZtG4MHDwYa9/pjDnPXUVtgs4iJECIL6AUgSZIdcAbYAMwBtgsh3pYkac6N97Ot2WeJEa4WXcfFtRXCKFDZNcknUQp/kAkTJpCSkkJ+fj5ubm4sWLBAlniviW+++YbVq1djb29PixYtWLNmDZIkERUVRXJyMn5+fkiSxJAhQ+Twf2PKjj/++ONcvHgRIQS9evXi008/BczLpzckO3fu5KuvvpKXSwK89dZbDBs2jFmzZpGRkYEkSbi7u/Ovf/0LAF9fX6Kjo+nRowdqtZrly5djZ2cHmOakDB48GIPBQFxcXJVJpWVlZQQHB2M0GomPj5fLu3fvzsMPP8z58+f59NNPad68eZ3aEBMTw8yZM8nNza1x+4YNG3jhhRe4ePEiw4cPp1evXnfMUtq8vDxiY2MxGAwYjUaio6PlyNSiRYsYP348r776KgEBAfJ3YtKkSTz55JN4eXnh4uJCQkICYPm8+Pj4sGrVKqZMmYJGo2Hq1KmyDebOizU4OzvTo0cPDh8+XGUicmVmzZrF119/TUlJCW5ubkyePJn58+fLP+Q9evTAzs6Od955x2Y/jOY4f/48o0ePBkyPlh577DH5kcmcOXOIjo5mxYoVdOnShXXr1gHmv7cuLi7MmzdPjvi89tpr8qT+xrz+fPjhhyxevJhz587h7+/PsGHD+OKLL8xeR21Bg4j4SZI0CHhdCNFfkqQsIEwIkSdJkiuQIoSweMvjr/EVaR8mUGyELL2dXB44SEOzFva2NV7hT8mfRHb8jsXd3Z29e/dWCxNPnDiRyMhIefWJQv2j1WqJjIyUJ1VWxtx5Uahf/iTXH7OjmoYKOYwHKobWHYUQeQA3/neo6QOSJD0rSdJeSZL2Gm4Mnm41Ni+3EABhFJSX1pyATUFBQUFBQaHpYPOIiSRJzYCzgK8Q4rwkSZeEEG0qbS8SQlicZ9KnWyex6f1tXDBKlIqqg6z7e3Sg7LqOc7lFdPJqy9njBfgN8KCVcwubtEdBQUFBQUHhD9OoEZOhwH4hxPkb78/feITDjf8XatuBhOCkQVVtUALw++ELnMs1pf49e9yUk+F/O2p+dqygoKCgoKBwZ9MQA5MJ3HyMA5AIxN54HQtssmYnXZvtqr1SJRpi7oyCgoKCgoJC/WLTgYkkSfcAEcB/KxW/DURIkpR9Y5tVySw62h9HJVk/2LiSX4LBoCwtVlBQUFBQaErYNMGaEKIEaHtLWQHwyO3sr0+Anj37rVuFk/nr7/Lr4GHdsbO3s1BbQUFBQUFB4U6gSSUCsbeHnmF1T6jz25YsMndqKb5cSvHlUgrOXuH0sYvV6hVfKeXXTYe5WnRdLjPoDBj0Rln1UKHxiYuLo0OHDnJiowrmz5/PfffdR69evejVqxdbtmyRt5mTd09KSqJ79+54eXnx9tv1l4n2j3DgwAFCQ0Px8/NjxIgRXLlyRd5mrh0JCQn07t2bJUuW2NS2U6dOER4ejo+PD76+vixdulTedrf4f968ebK8+6BBgzh79ixgWb6+3mXfLeDu7i7nkam8bLSwsJCIiAg0Gg0REREUFRXVaveqVavQaDRoNBqzeS0amuTkZHr37s0DDzxAbGysnLX0TvG/uetPffp/3759+Pn54eXlxYsvvnhH/PZMnz5d/m5369aNNm1uiujWu/8tSQ/fKX99NPcK8cMcIX6cK+sl63UGsWvzYbFzY+Zt/1Vw7dJ1cf1amTh97KLYuTFTZO05JfYkZYl9P2RXqZ/2fZbp2HqDKDpfu7R5WUm5yNpzSmgzz4uy67pa61uL0WgUunKTPHl5qU6c/71IlqOu8E3x5ev1drw7jdTUVLFv3z7h6+tbpfz111+vIkVfgTl5d71eLzw9PUVOTo4oKysT/v7+IjMzs9rnG5rAwECRkpIihBBixYoV4tVXXxVCWJapHzVqlNDr9SImJkZcvVp737xdzp49K/bt2yeEEOLKlStCo9HIPrtb/H/58mX59dKlS8WUKVOEEObl6/+A7PttcascfQUzZ84UCxcuFEIIsXDhQjFr1iyLdhcUFAgPDw9RUFAgCgsLhYeHhygsLLS5/ZYwGAzCzc1NZGWZrrXz5s0TX3zxhRDizvG/uetPffq/b9++4tdffxVGo1EMGTJEbNmyxebtqgsffvihePrpp4UQf8j/Zn/zm0bE5J4bT4OEQS6yU6sIifShfWdTOt62nVrTxbs9bt2tT/xzPP0svx++wIGUE+z/8Th5J0x5UfLPXKG8VE9pcXmV+royPb9uOsxv3x7l8K6T/Jp4mGuXrlNeVjWHitFgJD05h73bssk/c4Uz2flk7tTy66bDnP+9iKuFJRiNtz8CzjtRSNqWLMqu69iTdIzj6WfJ3n+W0uJyk33fHSXjpxP8uukwep0BXbmB0uJyThw8x/GMsxzNPc6FvELO5RbeESPxujJgwAA5Q6I1mJN3T0tLw8vLC09PT5o1a8b48ePZtMk0F9uSvPtzzz3HQw89RLdu3WRl1ZUrV/Loo48yYsQIPDw8WLZsGe+//z4BAQGEhIRQWFjIkSNHqmS71Gq1+Pv7V7M3KytL1uuJiIjgm2++sdgOqCo9bstz6urqSu/evQGTqqiPj4+siGqOpub/ClFCqCrvbk6+vrLvG5NNmzYRG2taVxAbG8vGjRvl8prs3rp1KxEREbi4uODs7ExERARJSUmAKcHXjBkz6N27N4888ggXL5oizGFhYUybNo1+/frxwAMPyP1v/vz5xMbGMmjQINzd3fnvf//LrFmz8PPzY8iQIeh0Or7//vsqas4pKSlypuUKCgoKcHBwoFu3bkD1/n8n+N/c9ae+/J+Xl8eVK1cIDQ1FkiSeeuopeV+W/P/kk08ycOBANBoNn3/+OWDy8cMPP0x0dDTdunVjzpw5/Oc//yEoKAg/Pz9ycnK4fPky7u7uGI2mOZklJSV07twZnU5n1gfx8fGymKAt/N80RPzUlVJOl10Fh5vCQ5re96HpfV/V6vZ2aA+dpzYunLxU5X2dk7QJOJhqWpocOLgbKpXE5fxisvacrlb1+jXTICcn46aeSAvHZvj2dyfjpxx6hHbBsc3N3CvCKLhw6jL6cj2durZFUkkYjYIr+cUUnDWF9s9ri+T6+acvk3/6crXjpm3JqtH0Qs4BcOLgOfqN6lG3dtcXWZvhal7t9QBauUL3EbVWW7ZsGatXryYwMJD33nsPZ2dns/LuQDXZ8d9++01+b07eXavVkpqaSk5ODuHh4fKP5qFDh0hPT6e0tBQvLy8WLVpEeno606dPl/dRXl7OiRMn8PT0ZM2aNVUu1BU88MADJCYmMmrUKNatWycLgFlqx5gxYwgMDOSJJ56wWpjr57XHyD9VPbtkTbTr7MhD0d2qlGm1WtLT0wkODpbL7gb/A8ydO5fVq1fj5OQk67OYk6kPDAy8Ldl33eGzGK+WWlVX1ao59j1uCuwNGjQISZKYMmUKzz77LGBKl16hneTq6sqFCxcs2m2uHEwDst69e/Pee+/xxhtvsGDBApYtWyZv+/XXX9mxYwdxcXFyhticnBx++uknDh8+TGhoKN988w2LFy9m9OjRfPfdd0RGRjJlyhSKi4tp2bJljerO7dq1Q6fTsXfvXgIDA1m/fn2V/l+f/r948SfKyqo/0q8JB4f2tG8fbrFOffn/zJkzuLm5VSuvwJz/Dx48yO7duykuLiYgIIDhw4cDpkfDR44cwcXFBU9PTyZPnkxaWhpLly7lo48+YsmSJfTs2ZPU1FTCw8PZvHkzgwcPxt6+5vmcv//+O7m5uQwcOBAw3aDcjv8t0TQiJpW5fKrWKq6e1t9N1xcHUk5wNO1UjYMSc1y/Vs7hX39HX27gYGouv246LH/+SNopcjJMEZ1dm4+gKzewe/MRDu86ydVC0xyY08fybdKWpsrUqVPJyckhIyMDV1dXWYK+pghCbbLjYF7ePTo6GpVKhUajwdPTk6NHjwIQHh5Oq1ataN++PU5OTvLdYIXseMVn165dC1DjhRngyy+/ZPny5fTp04erV6/SrFkzi+0A0x1aenq63GZbc+3aNcaOHcuSJUvkCMPd4n+AN998k1OnTvH444/LP8iW7K1v2XdL7Ny5k/379/P999+zfPlyduzYYbH+7fhfpVLJvnniiSf45Zdf5DoV52XAgAFcuXJFFhUcOnQo9vb2+Pn5YTAYZA2ZCv+r1WqGDBnC5s2b0ev1fPfdd7LQXeXjJyQkMH36dIKCgmjVqhVqtdpiO6Bh/V9X6up/a78Xt/p/1KhRtGjRgnbt2hEeHi5HU/r27YurqysODg507dqVQYMGAVW/FzExMfL8kISEBIsCfwkJCURFRcm6SlD//m8aEZPKWBEukiQJ7+DOGA2CKwXFlF/XU3juqk3N0pXp0ZXVPS1+ydWyKu8Lzl7h102Hq9Xb833NkY/6QFduwL5ZI6xasiICUhc6duwov37mmWdkcTNL8u7mysE6qffK72+Veq8sQ15ZdnzcuHGMGTMGSZLQaDTV2uHt7c22bdsAOHbsGN99912t7bgdbo2AWItOp2Ps2LE8/vjjjBkzRi6/W/xfmccee4zhw4ezYMGCevd/RQSkrlQcs0OHDowePZq0tDQGDBhAx44dycvLw9XVlby8PDp0MKl9mLPbzc2NlJSUKuVhYWE1HrMu/lepVNjb21cZ5FT2//Lly3FxcaFv3741RvdCQ0P5+eefAdi2bRvHjh2z2I7bpbYISF2pL/+7ublx+vTpavUrMOf/P/K9GDlyJK+88gqFhYXs27dPjobUREJCAsuXL6/dIX+AphcxOX/Qqmou97ai3X2t8fR3xTu4M/1G9SB0pA+9BnalpVPd1EjvdspKymuv1ATIy7v5WGjDhg1V5Mhrknfv27cv2dnZ5ObmUl5eTkJCAiNHjpT3YU7efd26dRiNRnJycjhx4gTdu1vUoKxC165dsbOz4x//+IfZu5KKELDRaOSf//wnzz33nMV2NCRCCCZNmoSPjw8vv/xylW13i/+zs7Pl14mJiXh7e8vtqEm+viEpLi7m6tWr8utt27ZV8XPFyo5Vq1bJ0Qhzdleo9RYVFVFUVMS2bdsYPHgwYOp769evB+Drr7/mwQcflG2oOC+//PILTk5OODk5WW1/WFgY+/fv5/PPP6+1/5eVlbFo0aIq/b+x/W+J+vK/q6srrVq1Yvfu3QghWL16dZXIkjn/b9q0idLSUgoKCkhJSZFVi63B0dGRoKAgXnrpJSIjI6tEQyqTlZVFUVFRle+jLWg6EROPgZCbDOcy4AHzYSZLSJLEPa0c6BnmyZ6kYzS/x77K0mAAdTM7uge6UXKllNxD5/EK6ESHLqZlUeXXdezdZrpode3lWmW+SGPiFdCJ4+ln5fctnZpTfNm6Z9dAk1NonjBhAikpKeTn5+Pm5saCBQuYNGkSs2bNIiMjA0mScHd351//+hdgWd592bJlDB48GIPBQFxcHL6+vvJxzMm7d+/enYcffpjz58/z6aef0rx53Qa6MTExzJw5k9zcmqUT4uPj5TuSMWPG8PTTT9fajoZi586dfPXVV/JyVYC33nqLYcOG3TX+nzNnDllZWahUKu6//34+/fRTwLx8fUNy/vx5Ro8eDYBer+exxx6TH5nMmTOH6OhoVqxYQZcuXVi3bp1Fu11cXJg3b578A/baa6/JkzpbtmxJZmYmffr0wcnJqcoyUGdnZ/r168eVK1f48ssv62S/nZ0dkZGRrFy50uzy5HfeeYdvv/0Wo9HI1KlT5bv3O8H/YP76U5/+/+STT5g4cSLXr19n6NChDB06VD6+Of8HBQUxfPhwTp48ybx58+jUqZMcbbKGimhi5SjOrcTHxzN+/HibTzS2uYhffRAYGCj2/vwD7FxsKnj4NbCvH5G+69fKsXeww06twqA3oq4lEZu+3ICdvQpJktDrDGYnl/oP8MDRuQXCKCg6fw3nex0xGgS/fXe0XuyuoJNXW9x9O9Y4M7q8VM/erce4T9MW53tNIVPHNi2YuXYuDzcbRDs7U6ix0Sa/3sGYk3efOHEikZGRREVFNZJlfw4U/zcujo6OXLtWfWJ0WFgY7777bpX8KQoNhzn/z58/H0dHR/72t781kmW3hdnRTdOJmLSoJEBckg9Onc3XrctuHZvJr2sblIApolK5vm//+8nceTPLbJceHbjPq+3N534qCRdX06DATi0RNKw7xZdKcWrf0jSw+T6LZg5qeoZ7orJT8du3NwcuISN8uH61jAMpJwBwat8Sn5AuCKPAoDNw8cwVeaJvTSPYZs3VNQ46xoeNJm5rHA81e4TnQp6ttc0KCgoKCgoNRdOJmOzdCz++YipwDQDfmpf5NQbFl0tR2UkYDYJ7Wjv8oTCXrkyPnVqFyq7q9B+D3ojKTqq3EJrfKj/59f9i/1cv+1RQUFBQULASsz9mTW/yK0BeOtxBA6qWTs1p4ehAS6fmf3jgYO+grjYoAVNCufp8rjfUY2jtlRQUFBQUFBqYpjUw6Vfp+dnl383XU6iVNx98U36dXZRtoaaCgoKCgkLD0bQGJvdUEireX7fZ4ApVsVfdXIkzbvO4RrREQUFBQUHhJk1rYFIZo/k8/grWEdXNtLLBUEmDSEFBQUFBoTGx6cBEkqQ2kiStlyTpqCRJRyRJCpUkyUWSpB8kScq+8d+59j1VwjXg5usC69doK1Tn70F/l1/P/WVukxH0Myc7Pn/+fO677z5ZmnvLli0AlJeX8/TTT+Pn50fPnj1rXKc/cuTIavtrTNauXUuPHj3w9fWtkubZzs5Obl/lZGSZmZmEhoYSGxsri3HZgtLSUoKCgujZsye+vr68/vrr8rbc3FyCg4PRaDTExMRQXm5K3FdWVkZMTAxeXl4EBwfLabABFi5ciJeXF927d2fr1q02s7surFmzBn9/f3x9fZk1a5ZcbqkdM2fOJDAwkNTU1EawWEHh7sLWEZOlQJIQwhvoCRwB5gDbhRAaYPuN99ZTeTVOeuMk2LlbsLe7+TgnMSeRdcfWNaI11jNx4kRZBfVWpk+fTkZGBhkZGQwbNgxAVtr83//+xw8//MCMGTOq/Hj/97//xdHR0faGW0l2djYLFy5k586dZGZmsmTJEnlbixYt5PYlJibK5e+//z6JiYkEBgbK6extgYODA8nJyRw4cICMjAySkpLYvXs3ALNnz2b69OlkZ2fj7OzMihUrAFixYgXOzs4cP36c6dOnM3v2bAAOHz5MQkICmZmZJCUl8X//938YDI0bvSsoKGDmzJls376dzMxMzp8/z/bt2wHz7ajQ6tmxY4fNU3UrKPwZsNnARJKk1sAAYAWAEKJcCHEJGAVUpPxbBTxa5513qpRc5ue3Qdjuh6bTWAAAIABJREFUDvFu5z7Hm8rMRwqPNKIl1mNOdtwchw8f5pFHHgFM+iJt2rRh7969gEmM7v333+fVV1+t8pnGlBf//PPPef7553F2dpZtrg2DwYAkSahUKptGviRJkgdxOp0OnU4nC48lJyfLic9ulX2vkIOPiopi+/btCCHYtGkT48ePx8HBAQ8PD7y8vEhLS0Or1eLt7U1sbCz+/v5ERUVRUlICmBKvzZ49m6CgIIKCgmRl4YkTJzJ16lTCw8Px9PQkNTWVuLg4fHx8mDhxImDKplk5ArJy5UpeeOGFKu07ceIE3bp1o3379gD85S9/4ZtvvrHYDoPBgEqlMivApqCgUDdsmWDNE7gI/FuSpJ7APuAloKMQIg9ACJEnSVKNV11Jkp4FngXo0qVL1Y0de8JZ0w8LZZfhah60vg+FuvNGvzeYtG0SAOuPrUd7WcvyR5Zzj/09Nj/2orRFHC20LhOut4s3s4Nm11pv2bJlrF69msDAQN577z2cnZ3p2bOn/CN46tQp9u3bx6lTpwgKCmLevHnMmDGDe+6p3t7GkhevSCPdv39/DAYD8+fPl9OOl5aWEhgYiFqtZs6cOTz6qGlc/9JLLzF8+HA0Go2sLVIbuf87Z7V0QUun5nj43QuYBkF9+vTh+PHjPP/88wQHB5Ofn0+bNm1kJdjKUu2V5d3VajVOTk4UFBRw5swZQkJC5GNUfMbV1ZWsrCxWrFhB//79iYuL4+OPP5azWrZu3Zq0tDRWr17NtGnT+PbbbwEoKioiOTmZxMRERowYwc6dO/niiy/o27cvGRkZREVFERoayuLFpgzSa9asYe7cuVXa6eXlxdGjR9Fqtbi5ubFx40b5kZS5dvj6+lJSUsKDDz7IO++8Y5U/FRQUzGPLRzlqoDfwiRAiACimDo9thBCfCSEChRCBFXcvMi6e4Hjvzfdpy+rD3j8lQa5BDPMYJr/fe34vH+z7oBEtun2mTp1KTk4OGRkZuLq6MmPGDMA0J8XNzY3AwEA5CqJWq8nIyOD48eOy9sitNJa8uF6vJzs7m5SUFOLj45k8ebJ87JMnT7J3716+/vprpk2bRk5ODgABAQH89ttv/L//9/9srp9jZ2dHRkYGp0+fJi0tjUOHDlmUar8deffOnTvTv39/AJ544gl++eUXuU7FeZkwYQK7du2Sy0eMGIEkSfj5+dGxY0f8/PxQqVT4+vqi1Wpp3749np6e7N69m4KCArKysuRjVODs7Mwnn3xCTEwMDz30EO7u7vJgy5K9H330Ua2qrAoKCtZhMWIiSdLLlrbfoFgI8a8ayk8Dp4UQv914vx7TwOS8JEmuN6IlrsCFOlkMIKkg+AXYXuluRxhN5Qp15p8P/pMtuVvk9wlZCbRq1ooXAl6wqViTNRGQutCxY0f59TPPPENkZCRgurv94IObg61+/fqh0WhITU1l3759uLu7o9fruXDhAmFhYfLk2MaSF3dzcyMkJAR7e3s8PDzo3r072dnZ9O3bV5Y/9/T0JCwsjPT0dLp27Vp3Z4EcAbld2rRpQ1hYGElJScyYMeP/s3fe8VFXWR9+7rRMek8ICSEQCJ3QwUYREbB3fXUtuyq+uq9l7e66trXtumtZ14a77trLWrGLFCkC0ntLQiBAem/T7/vHL8xkSDLpmQm5z+eDzr2/W86EkPnm3HPPoaKiAofDgcFg8CrVfqzse0pKCg6Hg8rKSmJiYnyWsW/pa+zrdeOv9/F/F8e+/pdffjkfffQRw4cP58ILL2z2+/vcc8/l3HPPBWDhwoVuodfS+1AoFF1La5/k9wBhQLiPP3c1N1FKWQDkCSGO1SSfDewCFgHXNvRdC3zRIcuFDpKnetq1xR1aRqHlNLk582avvte3v84/tvQuT1R+vqfa82effea+ZVNXV0dtbS0AixcvxmAwMHLkSG6++WaOHj1Kbm4uq1atIiMjw+vGjr/Ki19wwQUsW7YMgJKSEvbt28fgwYMpLy/HarW6+1evXs3IkT1bgLG4uNjtvamvr+fHH39k+PDhCCGYNWsWH3/8MdC07PuxSrIff/wxp59+OkIIzjvvPD744AOsVisHDhxg//79TJkyBdA8Q8e8Ie+//z6nnnqq24Zjfy8ffvhhu8uvX3TRRXz++ee8//77zXqrAIqKtN+VysvLefnll7nhhht8vg+FQtG1tBZj8raU8jFfA4QQoT4e3wq8K4QwATnAr9HE0EdCiOuBQ0DHs3uNuACONDhk1j4PZzzV4aX6Ojdn3sza/LVsLtrs7lu4bSGZ8ZlMT5nuR8ua0lLZ8XvvvZctW7YghCAtLY3XXtMceUVFRcydOxedTkdycjJvv/12m/bxV3nxuXPn8sMPPzBy5Ej0ej3PPPMMsbGx/Pzzz9x0003odDpcLhf3339/jwuT/Px8rr32WpxOJy6Xi8suu8ztmfrzn//MFVdcwYMPPsj48eO5/notdun666/n6quvZsiQIcTExPDBBx8AMGrUKC677DJGjhyJwWDgpZdecgu1ESNG8Oabb3LTTTcxdOhQbr7ZI5ytVitTp07F5XLx/vvvt8v+6OhoRo4cya5du9wi6Hhuv/12tm7dCmil6DMyMny+D4VC0bX0riJ+zXFoNezTgt+Ydrt37Imi3Wwv3s6V31zp1bfhVxsI0ge1MOPE5AQrL96ryM3N5ZxzznEHGzcmLS2NDRs2EBcX5wfLFApFF9LxIn5CiDOFEHNFoPoskxv91rP2Bagp9J8tJwBj4scwN22uV99Ni2/ykzUKhUKh6Gv49JgIIf4NbAAkME1KeU1PGdYYnx4TgB8f8G7PehT0pu416gTnruV38cNBT6KuG8bcwO0TbvejRQqFQqE4geiwx2QY8AHwIZDRlRZ1KWOv8m4vexhstf6x5QTh6dOe9mr/c/s//WSJQqFQKPoSrQmTG4A/A88Abcva5A8SRjeNLVnxOEipssJ2EKPeyJJLl3j1vbj5RX7KU7VAFAqFQtF99P7g12NIF2x5s/nCfrOfhAANkQl0SupLmPXRLK++zVdvxqDrzqTBCoVCoTjB6dhRjhBiQqsrt2FMjyB0MP7XkHpa02dLfg/b3tU8KIp2ERfc9PbDlV9fSaW10g/WKBQKheJEp7Xg163ATHwoG7RKweO72C4v2uQxOYbLAUv/6HvMqfdpMSiqvk6byKvO46xPz2rSv/LylUSZo/xgkUKhUCh6OS3qitaESS7g8rUAUCylbD5TURfRLmEC4HLC0gdbH3c8k2+ByAHtn9cH2F++n4XbFvJd7nde/YsvWUxiSKLKgKlQKBSK9tAxYRIotFuYNGbnx5C/sX1zZj4Chr6VUKwt1NnrmPreVJ9j/j7r74xLGEd2RTZj4sf0ucRsCoVCoWgTfViYuBxQtAvqyyD7+7bPM5ih/ySoL4finZA0Ubv5E5YI4f3B5CsT/4nLysMruWXJLW0amxKWwvOznuelLS8xIWECSWFJTZK3KRQKhaJP0oeFSWMq82D9y51fB2DGHzXRozOCMbhr1uwl2J125nw8h1JLabvn/njJj0SboymzlCEQ2Jw2CusKmZA4AZ2qDq1QKBR9BSVM3EgXlB8Aa5UWT2IKg4MrQeghZ3Hb14kfpXlSAOJGaEnedHoozdLW7QNHQTtLd3LFV1e0e96YuDFsL9nu1WfQGfji/C8w6U30C2293lGNrYZVR1Yxb9C8du+vUCgUCr/TOWHSUCfnKmCwlPIxIUQq0E9K+UvX2dgyXSpMfGGr0Y599nzW+bX6SO6UQ1WHOPuzs7lz4p28seMNKqwVnV7z24u+JSU8xd3+IusLUiNSGZ+gXf56deurvLTlJQDemPsGk/tN7vSeCoVCoehROi1MXkG7nXO6lHKEECIa+EFK2SOfCD0mTI5hqdDyouz4EMyRYK2GoAjtKKiuuG1rxKRDzBDNm2KO1GJWTnCklLy16y0SQxOZlzaPZ9Y/w1u73urQWht/tZGtxVsptZRyz0/3ADA9ZTr9Q/vzwV7vcvNDo4eyv3w/UUFRPDvzWTLjMzE1qpVUZauitL6UQZGDOv7mOkC1rZpwU3iP7qlQKBS9hE4Lk01SyglCiM3HcpYIIbZKKTO70MgW6XFh0hrHFw1sC5lXQ2yGdpTUUoHBop2gN2rjTjDq7HV8n/s9D/38UI/sd+OYG7ltwm04XU7GvT0OgLFxY/nP/P9g1Bnd455c9yRHa45y/pDzmTNwTqf3PVR1CIHgrM88eV9uybyFl7e+THRQNG/OfxOBYOWRlZw7+Fw+y/qM0XGjmZQ4yeeV65L6Es757Bx06Pj4vI/pH9a/07YqFAqFH+m0MFkHnAysbxAo8WgeE5+J1RryoFQDTsAhpZwkhIhBKwqYBuQCl0kpy32tE3DCxFIJq54Gc7R2O6fqcPvXSJ4Mwy+EmgLY8zmMvhxWP+N5nj4XBp4KJ1jq9zFvjgHgdxN/xxXDruBQtfZBfsmXl3T5Xp+e9ykXLbqoXXMm95vMG3PfAGBr8Vaig6IJN4Xz4OoH2VO6h8lJkwkxhLC5aDMfnvMhJr2JfeX7uHjRxZ2yNS0ijUsyLmFGygzSItMAcEkXU96dwhkDz+DrnK/dY1PDU/n6oq9bWEmhUCh6BZ0WJlcBlwMTgDeBS4AHpZT/bWVeLjBJSlnSqO8vQJmU8mkhxP1AtJTyPl/rBJwwOZ7qfDi0Goafr3k8OuJRaYlBs2DgdO0oyF4PpXuh37iuW7+H2VCwAYPOwLgE7/fwVc5X7Cvbx8CIgTyy5pFW13n4pId5dM2j3WSlf7kl8xauG30dty+9nTX5a5o8Hxo9lE/P+9QPlikUCkWX0flbOUKI4cDshsWWSCl3t2FOLk2FyV5gppQyXwiRBCyXUg7ztU7AC5PjcVhh+SNdu+bIS2FXgw4cdZn2/6QGh5WlQqsDFBSuXWFe/ReIGwmpp0B4Utfa0RkclqaxNi4n5C6HASdB/hZc/SeS+e4kryGPnPSIW6xMT5nOHRPuYGj0UADe2vgCa0q287dZL/Denvd4YfPfe+CN+Je35r/lDgRWKBSKXkqHU9LH+FpVSlnmc1chDgDlgARek1IuFEJUSCmjGo0pl1JGNzN3AbAAIDU1deLBgwd9bRWYOO1QlqUJCnt9168f3h9qizQx0hKzn9ACeUG7Jm2pgJ0fwcDTtODcw78AEoJj4dBKGDwHBp/eflus1dp7PSaWSvfDvq9g4o3alezCHbD9Xe1oype9QL6jnr32KmYGJ3o602ZC9CDY/G/t9ZC5lBYVEbvtuSbzc0NjOXffm+72hNhRvDn/be765Gx+qM9vMn5kxGB2VeW0/z37IF4XxI/9zuBnazGvV2dx1FnHB/GnMbOgHVfSjyMxJJG/zvhrE2+TQqFQ9EI6LEwOoIkKAaSiiQwBRAGHpJQ+rzkIIfpLKY8KIRKAxcCtwKK2CJPG9DqPyfHYamHF49rr6X+AikOw7W3P85RpcHitVh05Zggs+UPX7T32V5rXpOKgJkjaytRbNSGTMk3Lz3IMKZteg27sIZpwA9jrYPt7nudCD9LZ4bfQHAX6NPo5c1t8Xuis51fFq3kwcgwzGgSOlJKllkI+qzvESUHxXBGahr7hveTYq8lx1FDtcvBQxdZm13wyehy/L98CwDVhg3mrxiNmbgnP4NyQFJL1wW2uG1ThtGHW6bFKJ+cVr6LMUedz/Pbkc+DkuyCkacVnhUKh6GV0OsbkVTRB8U1Dez5whpTyrjZbIMQjQA1wIyf6UU5zOCya5+LYjRyHVfMwxA5tekvHVqt5QkxhsObZnre1MbEZkHG2ltI/63stWDf1VEgYrb0fc5QWvFu8y792djF77VWk6ENwIdluq2CsKYownRGrdGJChxACp5S4kBi7MGPtkvoC7ijTvtdPCYrnkaixlLisDDaEEXIsEDrzGogf0WV7KhQKhR/otDDZKKWceFzfBinlJB9zQgGdlLK64fVi4DG0OJXSRsGvMVLKe33tf0IIk45ir9fS6NeVQFgS9J+oHZG0RuPMtL2RYefC3i/bNLS2ooLQqKjWB7aHkASoK2rfnIGnaVmEGzPpJgiKhOBore7S6r+0usxRRx0x+iDMQt/8gLAkmHZb+2xTKBSKwKLTwuR7YCXwDtrRzq+A6VLKFiuyCSEGA8dSqBqA96SUTwghYoGP0I6GDgGXthar0qeFCWi5T1yOpp6Vsmwo3afd2jGFQk0hZP+gBccagpq/HTR0PkQM0OJe6ssheQoc+UU7bhlxoZaqP/uHrrF76m2w7rhg1HHXal6XpAlQfoAv91v46pc97KwOo9apZ1JUFZsqwrn5zEzmZ4SSXL9H8ypte0ezN/Ma2NooadueH6AkCxAQlaIdGY25oHl7qgshZzWYgmHEfKgq0I6dIpM9JQR+XuiJgQkKh+l3asdg6XPg8Gqt3xACp90PTpvm+XJYIKIhr0jRTs3WIXO1WJjm2PpO50RjxjlaYLNCoVD0XjotTGKAh4HpDV0rgEdbExRdRZ8XJh3l2IckQESK9kE69TbvmBHQUvEbzJ6cKbXFnT9CGnWZFghrr4MDS7W8LHpjk2FSSp75fi8vL89udpmV985ic14Ff/56B4tumUxsVDRUHYFf/gE5q+DottZtGXYmhMXBxvd8j2tDYK6bi/4JBhOMPF9r22qhaDfEDYXyg1rgc2w6BDfjyZESnFZtr9wVmrBBQtxwTbQNnK7lxgnvrx2XOa3asZ50aULIYO4T5Q4UCsUJjSri12epLdYESURy++dKl5b0zdKo/s3Jd8OO97XXhhCIGqh5a/pP1hLPSSeExrdrG6dLkv77b1odNzQhjMV3ztAa+Vvhtem+J7SR/Wm/oSo8g4nb7+/4IqYwTeAdz80/Q+IoqDwMeeugXybEDen4PgqFQnFi0GmPyTK0IxwvpJQduFfafpQwOfFxuSQvLs1ieFI4N729scVxs4cn8Po1k9DpGr6nXU6c2T/hSpmC8c/e4utQ//Moij2VQXkfUBfcH5OtgsTSVQDkx5/Orow7qAof7h6fnP81U7b+ruvfXHNc/i6MOKdn9lIoFIrAo9PCpHHgqxm4GC3FvM+g1a5CCZO+xbqcUh7/ejfbj1Q2+zzIoGPv4/Obn/zRNbDrC5j/DLWZ1xNkFNgckr1HasktqkfntJJQuoqChNnNTh908B1KYqZQHZ5BkLWEWT9fyK6M33XOm9IS6bNh4Ekw/R5w2DQPlfHEL/aoUCgUdMdRjhDiJynljA6b1A6UMOmbFFVZ+M/PuVw4Ppk5z63wevbni8dw+eTUdq0npSSnoJ5tB6vdfZOHRJIYZeKrDb6rRpuspcwfYkOXNAaHtR79wlMR5QeaDhx/NWx+G+b8CRb/sW2GpZ0GuQ23eSJTIeNMWP9Prf27nRCZ4hm7cCYc3Qy3bdFibbJ+hFXPwdl/g8k3tG0/hUKh8D9dEvx6DB0wEfh7a/lHugolTBSlNVYmPv6jV9/0jHgeOmcENVYnyVHBxIcHtXm9smobLglxEZ6bTjkFdcSEGwkN0nOw2ML2RgKmOQb3CyanoJ4R+55jeM4r2G/fgTF6gGdATTG8kAn2Wi3vyNSb4Ks72mxju7knG0LjtOBaKWHty5AxF0qzwBwJn9wIv/kOoga0vpZCoVB0L50WJo0zwDqAA8BjUspVXWWhL5QwUYAWhzLmke+ptTWfRXb3Y/MINrWQ+6MDFJRbWbO3ovWBDYSZ9ZyRGes782tdmeYNWfZEF1jYDLP+oHlsKg61PGbQDJh2ixasGzMYjmzUrprn/QIXvKJdn1YoFIrupdPCxCyltBzXFySltHaBca2ihIniGFJKBj3g+wbPffOGc/PM9C7Zz+mSHC2zsCGrqs1zMtPCqap3EGzSk5YQTJCxmcywlirNo5G3DrKXdomtXcYtayE0AUJj/W2JQqE4cem0MNkkpZzQWl93oYSJojEOp4uHFu3kvXUtewXumTuM387qumu5VXUOlmwrBbQUIu0JzbpwWqLvAYW7tMR2cRmw8m9asraTfgvLnoKfnvYee80Xmmh45SStPeUmzcOx+KF2vJs2csV7MPxsLT+LIUjzrhx74yqPikKh6BwdLuLXD0hGy/h6ZaOFIoBXpZTDW5rblShhomiOw+V1vLQsi7AgA6+vbBqIevbYJF66snu0s5SS/fl1pCUEIyWs2FlGjaXlQoWTh0SSEteBGzcuF7jsmoclJKZpcrxjbHoLFt3a/LPT7tYS3VmqYMs77ds/YZSWqA8gdogWr3KMSb+B+X9pNnGeQqFQtEKHhcm1wHXAJKCxMqgG/iOl/LSLDPSJEiaK1thfWN3k5s4xThsax33zhjM6ObLb9pdSsiuvhn1HfVcInjc+DpvDRXiwwZOLpatwOqB4D+z7FlJPgtSTIXsJDDnD28Ox4d9aErxPbgBHvXajRx+kZZ1d+nj79x0wFUZfrCXYG32xVjpBBdgqFArfdPoo52Ip5SddalI7UMJE0VZsDhcZD37b7LOf7z+d/lHB3W5DvdWJBOptTlbsLG92jF4H00fFEB5sQN/VAqUz1BRpuWAOren8Wg9XqCMfhULREh32mPxKSvmOEOIums/82smCKm1DCRNFe5BSMuKh77DYXU2eLbx6ImeO6tdjtizfUUZ5jd3nmHGDwhmYEIwukD7Eq/Lh2U6e1BpD4calYI7QPDTqyEehUHjosDC5SUr5mhDi4WYeSynlY11hXWsoYaJoL1JK7vtkGx9tONzk2QtXjCOrqIa7zuz+NDxSSoqrbGw9UO0zBuUYZ2TGEh5s6Ha72kzZAS0YN3uZ9v9tH8KAKZAxH45sgH+3kIG3Je7erxVLDI4+ob0pNlsZUjoJCmpf3SiFog/R6aOcU6SUq1vr6y6UMFF0lFqrg8IqC6f/7acmz3KfPrtHbXG5JDvzarDZXRwqsfgcO35wBHERRsLMASRSmqNgh5aBdtciCEvQYlwKdkCljzwqx7htC8QM6n4b/UBBwVdYrSUMHHidv01RKAIVdV1Y0bd56IsdvLXmoFffnJGJvH7NJL/YY3O42HO4luwC38GyAOdPTQisY562sPE/8OXtrY+b+QAsfwpmPwSn3dXtZvUUWVnPYjTGKGGiULRMh49yTgJOBu4Anmv0KAK4UEqZ2erOQujRbvQckVKeI4QYBHwAxACbgKullDZfayhhougs9TYnH286zB8/3+HVv/SuGQyOD/OTVdpRz76jdezKq2lxTJBRx1kTe+mRQGk2rP8X5G+Bg210sN78M4Qlaun1eyF2eyUHD/4LgCFD7vSzNQpFwNKiMGkmJaUXJiAMMADhjf5UAZe0cfPbgd2N2n8GnpNSDgXKgevbuI5C0WGCTXqunjaQ++YNJ9joyQVy+t9+4sUl+/1mlxCCjP4hXDA1gemjopsdY7W7+HZTMblF9T1sXRcQmw7znoRffwP3H4JT2uBFeeVkeCYddn8FxXshdzU4fQcQBxI2WxkAoaFD/WyJQtE7aetRzkAp5cFWBzadlwK8CTwB3AmcCxQD/aSUjgaPzCNSyrm+1lEeE0VX88Evh7j/0+3u9ilDYrl62kDmjU7yo1Uax/5NHi238su+Sq9nrWaR7S2UZsOL7TwJfqSy9TEBQFbWc4AkOflygoNV3SGFogU67DE5Rp0Q4hkhxDdCiKXH/rRh3vPAvcCxe5uxQIWU0tHQPoyWWbapxUIsEEJsEEJsKC72XZJeoWgvV0xJ9fKcrM4q5X/f2URJTY+Uf/KJEAIhBMkxZk4b6e1Fqay1Y3c0vQbd64hNhz+Wwm/Xwx9LICKl9TlFe7rfri7AaIwAICgowc+WKBS9k7YKk3eBPcAg4FEgF1jva4IQ4hygSEq5sXF3M0ObddlIKRdKKSdJKSfFx/fS83VFQLPl4TncNH2wV9/N72xsYbR/iA33zv2xdHsZX20oxulqR7GeQEVvgPgMLb/JnTs1j8jl78DYK5of//JULfX+4Y2+qyf7EZfLjt2ueXZ0OpW3RaHoCG0VJrFSyn8BdinlT1LK3wDTWplzCnCeECIXLdj1dDQPSpQQ4tgdyBTgaPvNVig6T5BBzwNnjeC8zP7uvvW55SzaGjjfkkIIzp+SwMzRMV79i34pwuE8AcTJ8Yw4Fy56TRMpfyiE6fd4P190K/zzdHh+DGx62z82+qCg4Gt/m6BQ9HraKkyORZ7lCyHOFkKMRxMVLSKlfEBKmSKlTAOuAJZKKa8CluEJnL0W+KL9ZisUXcff/2c8WU94EoXd9v5mCip95xnpSXQ6QXSYkcgQ75wmG7J6R8xFhzGa4fQHNZEy7qqmzxf9HzwaDbUlPW9bC9TV5QCQlHShny1RKHovbRUmjwshIoG7gLuBfwK/6+Ce9wF3CiGy0GJO/tXBdRSKLsOg13H6cE9MwLSnllBlCaybIKePjeWcyZ5jzfxyK1X1Dh8zTiAueBnmPtm0X7q0GzwlWU2f9TBOp+fWVEjIQD9aolD0btp0K8ffqFs5ip7izg+38OnmI+72ezdM5eQhgZVPo9bi5IctHi/BCXNTp604rLD+n/D977377z8E5u6rIN0aNlsphw69Caj8JQpFG+hwgrUXaSE4FUBKeVvn7GobSpgoepK0+73jBP593WRmDQ+sGxZr91aQX67dIBqYEMz4QeGI3pYdtrPY6+GJRgUZzVFwf7uzGnQZNTX7KSj4koSEuUREjOrRvVd/9C6/fP4RUkqu/etLxCYP6NH9FYoO0OHrwhuAjT7+KBQnHHefmeHV/vV/fF5A8wtThno8AweL6vl8XRG9wfvZpRiDtQDZY1gqYOEs8NPXoaDgSwAMhvAe27OyqIDX/+83rP3kfVxOJ9LlYs+q5d2+r83iYMM3ueRu1zx3lcX17Fp9tO99Dyq6BXWUo1C0wN+X7OfZxfsAePmqCZw1xv/J1xpTY3GweEupu2026Zg7Lg6dro95Tmy18KTnZhW3b4XotB41weGoJTf3NQBSU3+NydR8Ft+upDCYXP/HAAAgAElEQVQni3ceuKNJ//++9jahUZ3fX0rJtqWHCYkwMXSydlxoq3egN+p49f+Wu8eljY0jd5vnaPG3r57e6b0VfYLOFfHzN0qYKPxF42OdN38zhRkZgZVT51BxPRuzq7z6Zo+NJSRIj0HfhwTK/h/h3Ys97QtegXFX9tj2VmsJeXlvYTLFk5p6dbft43TY2b50MXWV5az5+H2vZ+fd/QcGjByDObTztZ/y9pSx6PktHZqrhImijShholB0hIJKC9OeWuJub334TCKDAytxlpSSz9cVefUlRQcxNSOyb8Wd5K6G/5zlad/8MyT2TKxHcfESKiu3kpR0AaGhg1uf0AGcDgfPX3VBk/6xs+cx+/qb0en1zcxqHbvVydYlhxh5ajJGs55fFuWw5ce8Dq016ew0pp7bPe9fccKhhIlC0VE+Wp/HvZ9sAyA8yMD2R32WdvILdqeLr9Y3Ld1wwdSEviVOVjwDSx/3tC9/F4afDd38NcjKehaA1NTrMJliWhndPmrKyzAFB/PNi38le8M6r2djZ89jzoL/6/DaO1ceYfm7ezs099qnTubNB34mbkAYF987EYOxY8JI0WfpnDARQmQArwCJUsrRQoixwHlSysdbmdolKGGi8Df3fryVjzYcBuBP54/i6pPS/GtQM7ik5IvjPCcAZ2TGEh5saGbGCcrxxzon3wpndt+PqsbxJceuCW/cuJGamhpmzJjR4XWllBQdyG42juTiBx4lLCaW2AED2yU8LbV2aiusuFySj57wHdR92uUZjDq1P7WVVlZ8sI+Y/qGcfNEQrHV2TMGGviV4Fd1Bp4XJT8A9wGtSyvENfTuklKO7zEQfKGGiCAQax5tsePAM4sKC/GhNy+SV1LMhyzvuZO74OEKC+tBvtO9eCvt/8LQX/AT9x3XLVocPf4jFcoTw8BEkJs5n1apV/PjjjwA88sgj7V7PbrVQnn+Ut+9rPhvD7e98hsHY9uNEKSV5u8qoqbCy7O22FUK88K7x9B/a/QG8ij5Ni8Kkrb9GhUgpfzlOIfeRlJMKhcaKe2Yx/ZllAFz22hqW3jXTvwa1wIC4YJKizXy53uM9+X5zSd9KxHbVf+HIRni9IRBz4Qw441E4tan3obNYLFpCvujoqbhcLrcoaQ8Ht2uBpnk7t7Hus49aHNecKKkpt6A36AgKNVJTZuGrf2yltsLK7OtGcnh3GYUHqynKrWphRbjq0WlEJgTjsLswmvqQeFUELG0VJiVCiHQakq0JIS4B8rvNKoUiAEmNDeGL357C+S+tJqe4lh1HKhmd7L9Mo74w6AUXTktkzd5yCsptAOw4WM3ogT2XY8PvJE+EOX+CxX/U2j8+DAOmwMCTu2wLu93zgW8yxVBS4rk2e+utt7ZpDZulno8ff7DF5+Fxg7jmL89iDjW684RUl1moq7Tx7Wvbqa2wNjvv21e3+9z37FvGkjbWk9VYiRJFoNDWo5zBwELgZKAcOAD8SkqZ263WNaCOchSBROMjnXvmDuO3s4b40ZrWOVhUz6Yc7QN09thYIkL6ULwJwOoXYPFD3n137ICozmdHzc39Fw5HJSEhgwgLm82zz2pBsIMHD+aaa65pdX5lUQH/vPWGZp/pgyZjDDmt0zYeIyk9kjN+PZKIuOAuW1Oh6ARdcytHCBEK6KSU1V1hVVtRwkQRSGw8WM7Fr/zsbu9+bB7BAf7b5mdrPRlSZ4yKISY8sK48dzu2OnjyuAR5nYw7kdJFdvbzAKSkXMXTT7/ifnb99dczYEDzwid322a+/cffqKusaPZ5UOQChK7juUjOvH4UlcX1rFuUw4iTk6goqmPegjGERJg6vKZC0Q10LsZECPEk8BcpZUVDOxq4S0rZsv9RoThBmTgwmp/vP52Tn14KwNtrc1kwPd3PVvlm1pgYlm0vA+CnnWV9LxjWFAJn/w2+vsvTt3AGPFQGuo59HWprs92v8/I8RzoDBw5sVpTU11Szfcn3rHzvP02eGcMuQWcY0OxNl4FjYjm4vbRJf1RiCP0GR3DKxUOpq7JRXlBL+gRPTadJZ6W18x0pFIFBW49yNh+7jdOob5OUckK3WdYI5TFRBCKbDpVz0cua52TJXTNIj+98xs3u5GiZhXX7Kt3t0alhDEkK6XvXPp8aANZGwaC/2wmRKe1e5ljuErM5lX/+c4e7/6GHHkKn85Qhqy4t4b0H76KmrKm4ANCbp2AMPtXdztz6IhHVeRgdtQCkvvUmoVOmIKXse39XihOZTl8X3gZMllJaG9rBwAYpZY+kVVTCRBGISCkZ9MA37vaUQTF8dNNJfrSodTZmVXKoxOJuh5r1zMmM7VsfeFJCwXZ4rSF+I2qgVl+nHV8Dl8tOTs6LAHz6aTV1ddrP0RtvvJHk5GT3uP3rfmbRs082mX/pH59gwKixuJySot35VFx6BhIBDf9tCWE0MuiLLwgaPAhrTg766GgM0epar6JX0mlhci9wHvBvtJs5vwEWSSn/4mOOGVgBBKEdGX0spXxYCDEI+ACIATYBV0spbb72V8JEEaj8nF3Cla97snH+8vvZJESY/WhR61TXO/hxq+e395RYM5OHBubtom5lwxvw1e887QXLof/4lkZ7UV+fx5Ej/wX0vPNOOQCZmZlceOGF7jGrP3ybtZ9+6DUvPjWNC+57mIg475pLUkqQEqHT4ayowFVbS+HTf6Z68eI22WPOHEvkOecSPucM9OHh6EJD2zRPofAjnQ9+FULMB2Y3LPaDlPL7VsYLIFRKWSOEMAKrgNuBO4FPpZQfCCFeBbZKKV/xtZYSJopAprzWxvg/eT5A9j8xH6Ne52OG/6m3Ovlus+dqa2y4kemjujaVeq/glVOg0HMMw6TrtViUVrwnx45xtm83srVB5N19+22U5B1kzacfUnQgG4el3j3+ovsfYdD4Se02r/LLrzh6zz3tnhd7440YkvoRc+WVSIcD6XSiCwrMhICKPot/a+UIIULQhMnNwNdAPymlQwhxEvCIlNJn8RElTBSBztqcUq5YuNbdPm1oHG9fP9WPFrWO0yVZ9IsnCZtOwHlT+lhtHYC/DIa6RvEfM+7T/rQQFCulk+zsFwD44IMqHA6YOWwwGz//iLhhoxh2luY1Wf2clgb/ln+9T3BY1+SPqd++g9xLL+3Q3ORn/0bY7NkIk3Y7p8/9PSsCjY4JEyHEKinlqUKIahqSqzVaUEopI3zuKoQe2AgMAV4CngHWSimHNDwfAHzbXGp7IcQCYAFAamrqxIMHD/raSqHwOzOfWUZuaZ27fc7YJP5xZY/Eh3cYm8PF1xs8xf/iI02cOqIPxiwc2QSvz/LuGzANfv0t6Ly9X1ZrMXl5b1NT4+Lzz2vA6SR832YMQWam3nK3e9zq5x5vd/r49mLZtQtj6kDq1v/C4Ztvadfcge++Q/AEz/eno6gYoRO4LBZMLVx1Vii6EL97TKKAz4CHgH8fJ0y+kVKO8TVfeUwUvQGbw8XEPy2m2uqp1vDY+aO4JgAL/jXG6ZL8sr/CnSF2YnoEqfF9MAlXaTa82IyQHHY2/M977ubRo4uoq8tixYo6Dh1yELZ7AwI45Xee7AnDMjKIjun5ozFXXR3o9RQ+/gQV//1vp9ZKfvHvhM+ejdAF9rGkotfiX2ECIIR4GKgD7kMd5ShOYJwuSfrvPbd1rjs5jYfPHRnwrvP1+ys5XKrd2Bk5IIxhyX0wgLI8F774P8hd2fTZgKnw6+/IytGSqr37bhXG4nyCio/Qb+xE0mfPB2DIkCHExcU1nd/DSJsNy/796CMisOzZw9G77kbafN4zaMKQn5ZjTOxDNZYUPUnPCxMhRDxgl1JWNFwv/gH4M3At8Emj4NdtUsqXfa2lhImit1FQaWHaU0u8+k4dEsc7NwRu3IlLSr5Y54k5yUwLZ3C/ED9a5EdcTvj2Plj/uld3mSGGsiu0GjjvvFNF+O4NXPv8QrIOHgIgOjqaYcOG9bi57cVZWcm+qdNaHTd8x3aEoY+VMFD0FH4RJmOBNwE9oAM+klI+1lB359h14c1oNXear0LVgBImit5IZb2dzEd/8Oq7dGIKz1ya6SeLWie/zMLaRknYokINzBoT60eL/IzDCo97sqmunHwrScNi2LXLinVbHRfe9xAbNm50P582rfUP+0BBOhxYs3MwD8vw7pcSabUiHU70YX3Qa6boKfx/lNMZlDBR9FZKa6yc/9JqDpd7ro5+d8dpDO/nM27cr1hsTr7d5LlKPGpAGBl98VinMZYqeHoAO+yDKJv7PxR9uZqLw1aybu637iFDhw4lNrYPiziFon0oYaJQ+BOXSzK4UdzJA/OHs2D64ICNO7HaXXyz0XNbZ864WMLMyqXPt/fhWPMaBp1kf+b9lCZpN3l0Oh1Tpkzxs3EKRa9CCROFwt9Y7E6G//E7d1snIOeps/1okW+klHzeKOYkPFjPKcOjCe5Lxf+ao/IwjhensuGMT9xdUwdFIhJH+NEohaLX0aIwUffAFIoewmzUk/3kWcSFaQmuXFKLQwlUhBDMGOXJaVJdr2WLtdpdfrTK/5TYzd6i5Lu5iFemaTd6FApFp1HCRKHoQfQ6wYYH57jbmY/+wLfb8/1okW9iwk0MT/GOL/lmYzE2R98UJ3a7naysLHd7gm2d59e+FzJh3w9akUCFQtFhlDBRKPzA17d5ytzf/O4m8srqfIz2LyNSwpg7Po6xAz1p1X9oVGenryClZGOjGzjp6emYpt8Od+31DHrvUnhWHekoFJ1BCROFwg+M6h/J+zd6rpae9pdlvLM2cMsuhATpSU8KISJYC4C1OyWl1e1L1tXbWbfOU0U6JSWF+PiGCsHh/eAqz9EO1fmw+8setk6hOHFQwkSh8BMnpcfyXqOEaw9+voO1OaU+Zvif08d60qyv2FmOw9k3ji2qqqrcr9PT00lJSfEeMGQ2nP0sGBuOvT78FXz/B3Wso1B0ACVMFAo/cvKQOJ6/fJy7fcXCtQTyTTkhBHPHe9Ktf7m+KKDt7QpKSkrYtWsXAEFBQR5PSWOEgMnXw30HPH1r/gFf3tZDVioUJw5KmCgUfuaC8cnsf2K+u33Hh1v8aE3rhATpOWV4lLv9/Qkcb2K1Wr2CXTMzW8naawiC6xd72pvegjfP6ybrFIoTEyVMFIoAwKjXMSND+038iy1HGfPw9+wtqPazVS2TEBXkfl1vc7HzUPUJ5TmRUlJdXc3mzZvdfZMmTULXlkq7A6bArZs87QM/gS1wg5sVikBDCROFIkB47eqJ7tfVVgdzn19BWW3gBpieN8VTQ2bf0To+X1fEzkM1frSo68jPz2fnzp3u9rBhwzC0p5hdbDo84qk5xJNJUJrdhRYqFIFL9eoj1G4uan1gCyhholAECGajng0PnuHVN+FPi7E7AzNniF4nOL+ROAHYd7S21ydgs1gsHDp0yN0eNmwY0dHRPmb44KYVntcvTuikZQpFYGLJrqB2fQHWg1Ucvn8llV/mUP7h3tYntoBKSa9QBCBZRTWc8exP7vb+J+Zj1Afm7xEOp+TL9d6/HV04LdFP1nSOqqoqd6ArwODBg0lISPAxow1kLYF3LvK0f7se4jNaHq9Q9BJq1xdQtSwPZ5ml2ecpT5/ma7pKSa9Q9CaGJISx+v7T3e1Jj/9ISY3Vjxa1jEGv3dSZmhHp7rPYnH60qGMcOXLES5Skp6d3XpSAdpV4oCehHi9N7vyaCkUP46i0Ur3qCM4aGzVr8zn6+FrKP9nfoihJ/tMpHd5LeUwUigDm56wSrvynJ7HXnj/Nw2wM3CJ6q3eXU1Rpw6ATnDulCz7UewCr1eoV5Aowbtw4zGZz123idMDzo7XkawD3ZENonO85CkUP4rI5seZUogsxEJQagXRJnBVWatflI0x6qhb7TgAZefZg6neVEvurEehDjW3ZsuerCwshBgBvAf0AF7BQSvmCECIG+BBIA3KBy6SU5b7WUsJE0ZepsToY/fD3AEwbHMMHC07ys0UtY3e4+GpDMQDxkSZOGR6FEC3+/PE7NTU17Nixw6svMTGRQYMGdc+GH/8GdjRkib1pJSSN7Z59FIp24Ky1k/+ntR2am/SHqejDTR2Z6hdhkgQkSSk3CSHCgY3ABcB1QJmU8mkhxP1AtJTyPl9rKWGi6Ot8t6OA/31Hq9Py21np3DN3uJ8tapkVO8sorfZUTQ7UeJPc3FwKCgq8+rrcU3I8ZTnw9/GeduObOwpFFyGlpOqHgwQNjsQ81Dtw22V1UrepEPOwGIRBR/6T61pYpSkhkxIRRh2m5HBcVgehExLRBbfjtpo3LQqTDq/YGlLKfCC/4XW1EGI3kAycD8xsGPYmsBzwKUwUir7OvNH93K9fWpbN2WP6M7J/hB8tapnpo2L4an0R9oZ09TaHC5MhcMLZbDYbO3bswGbzXMUeOnQosbGx3b95zGCYcT/89LTWXrcQpi7o/n0VvQ7pkgidwFllxZpTSdkH2i2X4LFx1G/zJDU0xAcTMiERY78Q9FFm6jYVUrPyCADVy/LQx5iRNif6MBP2gtpGOzS9vm4eHoNlT5m7rY8xEzohAXQC84hYjAkhCH33e0B7JMZECJEGrABGA4eklFGNnpVLKZvcxRNCLAAWAKSmpk48eDBwC5wpFD1BXlkdp/1lmbsd6PEmn60tdL8OFK9JUVEROTk5Xn2jR48mLCysZw1Z+TdY8pj2WsWb+AUpZUAcMzqrrDir7Riig6hamkfNqiM9boMh1kz8/2Z29Eimo/T8UY57AyHCgJ+AJ6SUnwohKtoiTBqjjnIUCo3G8SYAy++eSVpcqB8tahmbw8XXDfEmZ02MJ8jY814Tl0vLqVJbW8uBAweoq/NkYBVCMGHCBIzGNgXqdS1SwqOetP48VA5tySqr6DTSJTny+1VefdGXZRA6wSOepcPlPvKQNhfmkbGYkrR/Z7bD1ZS8sQNXnQOA+FsyMaWEg9OFs9aOIcqMdEpK397l5X3ocQw6cDSfU8g8LBrL3nJMqeHELxiL8I9H0z/CRAhhBL4CvpdSPtvQtxeYKaXMb4hDWS6lHOZrHSVMFAoPpTVWJj7+o7u9/ZEzCTf74cO1DazdW0F+uXbNefqoaGJ78DeyyspKdu/e3eyziRMn+keQNOboFlg4Q3vdfwIsWOZ7vKLDOGvtSIsD6ZQUPr9Ru47Ri0i8ayLCqMcQFYR0SXBJt5iw7C3DUWHFWWbBZXViHhJF0JAodGYD0imxHa7GEG3GsrcMY/8wjP1DA8JThJ+CXwVaDEmZlPKORv3PAKWNgl9jpJT3+lpLCROFwptPNh7mrv9udbeznpiPIQATsEkp+XydJ/na1IxI+sd0X3CplBIpJXl5eeTn5zc7Ztq0ad22f7tZ8xJ8/3vt9Z17ICLJv/YEELbD1SAEQi8ofHEzMZdmEDIuAemUlH+yD2t2BYl3TqTw2U04K60EDYnClBqOPsKEPsqMPtxE0UtbwBWgKTH0QvOcuSB0Sj+CM+Ox59cSPDwGQ1ywv63rCfwiTE4FVgLb8ejT3wPrgI+AVOAQcKmU0qe/SwkThaIp3+8s4Ka3N7rbWx6aQ1RIj54RtwmLzcm3mzzBenPHxxES1HWxMU6nk+LiYnJzc5t9HhERgcvlIioqisTERP97So7n6VSwNNzO6cZbOtLpQhwnXu3FdRjigr1+g3ZW2yj51w5i/mcYxsTWjwmlSyLtLnTH/Z1KlwSnRBx3hCel1l+/uwxTUii6MCP2glpMA8KRVif24nqKX9lKd2JKiyDhfzPd9lR9n0v18sNeY6IuSNeEkM1FyRs73IGjxpQwEm4eh9AL7IW1VC3Nw3awCmeFdwLEyPlphM8YAGjJyYRB19b8Hn0F/8WYdAVKmCgUzbM7v4r5L6x0t3OfPtuP1rTM8Z6TcycnYOhkdL+UktLSUrKyspp9bjAYmDhxYkC4rV02J7aDVeijgjDEBuMst2DZU0bIxESkxYL++WSkNMA5zyEmX9PqevW7S9GFGglKbXozy1VnR5gNOIrqsOZWUfG599cnYl4aVd/levVFnZ9O7bp87AVNqyCHTksi8qxB6Ex6nFU20IEtt4qKbw/gLG0+66cXBoE+1ETIpESqlxxqfXw3EDIpkZBxCdiP1qCPCiJkbHyz41wWByJI36nvGVedHSlRIqR1lDBRKE5UFm09ym3va5lL1//hDOLDg/xsUfMcL06G9g9hdGp4q/NcVqfXb+NSSo4cOcLhw4ebjA0JCSE5OZmoqCj0eu851T8dJmhgBEGDInHZnNSuzccQG4wuWI9pYCTS7qTi8yzCzxiIMS4Y6XQhnRL70RrQCYz9QqlafBBh0hM2LYnCFzZhTArFur8CY0oYkXPTsOyvQFocOKttGBNDkC4IHhlD8avb2vW1ChocSfDYOEIn9aNmXT6uGjvmETHIegcVX+XgKK73Gh85fxD6CBNlnSicFmgEj4kjfHoKtqM16MNN1KzNx3aoCvPwGMJPSUbaXdhL6gjJjEcXZMBZbdM8N6EGalYdJWhwJM4aO8GjYwNCnCqaoISJQnEi88iinfzn51wAcp48C50uMH8QN76pAzBlaCTJsWbsxXXoQ41IuwsRpKd+RwmOMgvVS/MACJ3cDwyC4rwCyiY1Tb+UsNxBZEYCIaPiKP94PxGzBqCPDsJZZqF2feFx+Rv6HkHpkViz23ZMFDI+AfOIGGx51e58GG3BOCAce1619rpfKLpwI9b9FU3GhU7ph72wjpDxCRgTgqlacoiQCYnYDlZR+0sBoVP7EXXOYEQAX4VXdAlKmCgUJzJFVRamPLkEgJMGx/L+ggAK8DyOxp4T4ZJM/iEHafFd9E8KyJ9rwGX2/lkWkucicrsTva2FiQFE9CVDkU5J3cZCIuYM1D68gw1UrzrS5GilNUImJSIMOuq3FbuvrR5DF2ZE2pxEnavFSCBw3+CQLu2Whql/mNcVUWl3ark0mglMdlbZsOVVUbethPDpKQiDwH60Fl2YsUlWUUeZBel0YYwPOW4NK+hVjIXCCyVMFIoTnYOltcx4ZjkAP945gyEJPZw0rJ18traQzO+yMfkQJS4DHD2n6YdZzEYXIXmN5ukFOFv+WWaIDybmsmFUrzhM/fYSQif3I2RCAvpoM9LqoOTNXQQNiiR4dCxl7+1B2rV4/ZirhmNMDMWaXYG9sI7gMXHoQ404Suoxj4xFNHimHGUWpMOFPsKkXdOUEvuRGgwxZqwHqzD2C8UQ3YbbSGtewvXdo7iIoH7Sv6nLDSP6oqEYE0JwVFgaYkAkIWO8YyRcFge1GwsJndSvSRCqQhGgKGGiUPQFfvvuJr7enk9yVDCr7z/d3+b4xCUlRx/QEl05BkeScFISumAjhrhg9BEmkLBuvXcdD7PZzJgxY9Dr9UinC6THG+CssiKMenftDkdpPYbYXnjt8qWpULxHe33lfyHjTP/ao1B0D0qYKBR9hbT7vwbg9tlD+d2cDD9b45ttByo5eLAGh9nAvAlxBJu03/allGzevNldzyYxMZGUlJTAu+rbHbhc8FijI5KHK0AFbyp6GKdTC7C2WI4ihIGQkIFdvUWL39SBl5FJoVB0ir9equVneGHJfhauaFqoK5AYkxZBdIIWj/DdphIcDccxJSUlblEyYsQIBg0a5BYlLqcT6ep86k6n3VMBWUpJfVUlNSVFPmb0EDqdJkaO8fVd/rNF0aew2yuorNzEsuUjWf7TaJb/NJq1685kzdrTWbI0HZutpPVFuoBuqy6sUCj8wyUTUzhSXs9zP+7jyW/2MH90EgNiQlqf6AeEEEzJiHTf1Fm+o5TZY2PJztYE1bBhw4iMjAQ08WCrrWHDh2+hN5qYevUNFO7dRVVhPtVFBSAlhiCzl7gYMedsogcMxFpTTcHuHTjsNhxWC7WlJViqWr6lkjFzDqExsTjtdoLCwhFCR2XBUUpzs7FUVxESFU1sWjrmiEjMERHodF0c1yEEPFgMj8fDhn9B0liYeF3X7qHo0zgc1eh0ZnbtvpeoqMnkHvgHVluhzzkGQ2SP2KaOchSKExCbw8Wsvy7nSIXmjj3w1FkBncvB7nTx1XpNnJw61Ez2fq3GjXPnRiKjY6ksL/WneW0madRYQqKiyV79Ezq9gQmXXkVQaFjHK9lu/xg+uV57feMySJ7QtQYrTnjq6/PYuu1Gamv3t2vegAG/YeiQ+7Haitm8+RqGpN9NfHyXxjupGBOFoq/hdEnSf/8NAPfNG87NM9P9bJFvjpZZWLevkhhrFkFBepy5+6C2ukNrxaalU5rr+xhLbzJhDovQPCDRMQwYPxlDkJlti/7boT3bStLIsUQmJRObNhhrbQ0VR/JwWC2ExsYTGhOL3VKPdLkIiYohf/d2Erb9DcPeL7TJv88HU2B6vxSdR0rJ0fyPiIk+leDg5DbOcbF7933kF3zq1Z+W9ltyc19q1/6JCecwfPjjGAytJz7sApQwUSj6Ij/uKuSGt7R/O7sfm+cOLg1UPltbSD/rbkSQGf2OjdiO+9E13CmImTSVwuoKsrP2MGzWmUSlDERvNOKwWXFarZgjPO5ml9NJbVkJVYX5xKdnaLEpUmIMDkGn9/21cDmdICUV+YfJ37GNiqN5TL36RvSNAnDL8w5yYN0qn8dCXUGYNY/B5YuwBCWxL/oiUidMJSw+gfrKCpJGjMZaW4MQAlNoGA6bFSF07FnyLUkjxoCAqOQB6A3egcMOqwVbXS0h0bHdaruieerqcgkK6oeUWqzTTyvGeT0/fdY+hPB8jzoc1Rw5+iFZWU91aL+EhLOoqtqOyRRH5thXkdJJWdkqoqNPxmz2S/FIJUwUir7KsVs6Z49J4qWrAvsooM7qZOfir7A77JxUWITFCJvSbZyyp4U0+zNmgsMJw4aBXq8FjvqR6uJC6isriB88FKfDQU1JIUe2bcEcHk7Bnp1+tS1j5hz2LV8MQFz6UEqyNdd+TGoalupqXA47xuAQqosKGDB+MjEDB1G4dxd6o4m0ySdRVbHQhmUAABTnSURBVFiA027DHB5BdVEB+1csof+oTJIzJ1BfUYEhKIjgyKhWBV9fwuWyY7EcoapqK0ZTLIUFi5C4KCj4rFv20+u13EVOZw0AYWEjSE6+kv5Jl6LTBdyNNiVMFIq+SlmtjQl/0j6Qltw1g/T4wE68Vmtx8t+cz7CGHPB0SpiUbWJidhuqJ0dFQf9k2LUTRo3WBIvRCJnjtP/7GSklNSVFFO7bTURCPwxBZswRkTjtNhxWK+V5udjq6yg/dJCx517Mli8+gl7wc7oxkUnJxKVncHD9GiZcchVVhUexWyyYw8K1oyu7DVNwCJFJKRza/Atpk08mODIKa8OxmtAdy1Tr4tDm9QghSBk3seuDjLsYl8vB/qwnOHz4LfT6EJzOpkURW6NfvwsoKPi8zeNDQtIZOHAB/RIvQKfrVfdZlDBRKPoy855fwZ4CLV4jUCsQN8bmcLF8exnVNgt1odupC9vh9XxwsYk5m9ogUpojJBROOhmGDOkCS3sG6XLhtFmw/XUsIY5i7CffjWPqrRiDQyjPyyU4KprDWzY2CIKhuOx2DOZgHJZ6hE7H+vf/414rNDae2lIt0FhvCkK6nLgcjhZ29g/RKamUH25aiXj0WRdSX1lO6YFsUidNIzw+wQ/WadjtVRQX/0Bo2FA2bLioXXOjIiczaNCt2B1VlJevpaR4MZnj3iA8bLh7zIEDL1JWvgaL5QgWy2FiY2cwdsxrgej56ChKmCgUfRmrw8mwB78D4G+XZnLxxBQ/W9Q2NudUkVtUj1NfQ2m8d3CfyQ6X7UqBoRmEHiyEulooaUeehXHjobIC8vIgOgZOmw7x8a3P8yff3gfrXtVeX/EeDG+byJRSUpKzH1NIKJFJzQdVarEpAp3BiLWmmpKc/YTGxmEKDmXPkm+JHTSEmNQ07PV1RPTrj9Ec7Pb+VBcVEpmUzJbPPuiqd9ouwuISSD91JuawcAxBbUj93wny8v7Dvv1/8jkmKmoqFRXrMJniyBj6R6KipuJwVBEcrP270+kCswJ4D9PzwkQI8QZwDlAkpRzd0BcDfAikAbnAZVLK8tbWUsJEoeg8+wqrOfO5FQDsf2I+Rn3g51eUUrIrr5Z9R2uxmHOoilrV7LhxkVOZGHkyhmOubIcDsvaD2QzhEdoRTnYW/LKu2flu5s6DtEFd/C66mEca5ZL43U6IDDyR6XI4KD2YQ1hcAps+fpekkWPoP1oL7jSHR2hjGoKLhV5PfWUFhzb9Qk1RAdbaGvc6EYlJRKWkEpOaxpbPPmzT3okZI7FUV1KZf4SY1DTKDuUSFp/I6LMuQG/o3FHHnr0Pc+TIO80+y8h4hPyj/2XEiKcIDx/VqX36CH4RJtOBGuCtRsLkL0CZlPJpIcT9QLSU8r7W1lLCRKHoGo4Fwt45J4PbZg/1szVto3E14pEDwsjoH0KJrZBP89/2GhduiOSS/tdh0rXhiOe1V1p+Fh6uBdUmB94HPgBHNsLrjeogPdK9N4J6GltdLXpTUBMR4XI4qCoqoLqogLjBQ6kuzGf/iiXtXj/z/MsIiY7BXl+HMSSkzXErlVVbmxzZnHrKGoQwYDLFtNsOhZ+OcoQQacBXjYTJXmCmlDJfCJEELJdSDmttHSVMFIquYXd+FfNfWAlAzpNnodMFbtK1xhSUW1mzV0vTfuG0RHf/rqotrCxb7DX2prR7Wl9QSljzs+Yd6d8f7Hb4abnmVWnMpZdBTABep60vhz+naa/v3g9h/ou1CASstbVkr15OeV5uh+aPv/hKQqKiW3xeWrqCLVt/DYDBEMWpp6xGr+/eI6M+QMAIkwopZVSj5+VSypa/GxpQwkSh6DqOeU3OGZvEP64M7OvDjflsrZYuOyk6iGnD3D9GOFyfy4/FX2J1WQAYFjaGmXHz2r+BlLDw1ab9/3MVRER0yOZu5dEYkE7t9QnmNekoluoqjMHBCKHDabNhq68jNCaWI9u3kPvLap9zw+ITGHvuJU0y9LpcNpYtH+Fuz5yxU4mSrqH3FfETQiwQQmwQQmwoLi72tzkKxQnDA/O1yP+vtuVjsTv9bE3bGTdIy0aZX27lcInF3Z8SnMZ1qbeiR3PJ763Z3rENhIAF/6vd2GnM++9Cbm7H1uxO7tzleX1orf/sCCDM4RHoDUZ0ej3G4GBCG7xdyWPGcfKvb2bcBZcDYDCbiUoe4DW3priIn9942euGUn39YS9RMnnyF0qU9ADqKEeh6GPU25yMeEi7ofOraak8fsEYP1vUdo55TcD7SAfA4bLzr0PPAzAyfBynxc7p3GY52bD4B097wkSYPKVza3Y1jQNhldekQ+Tv2k7OmhXudkRSMmPOugCAJUs9ZRzGjH6ZhIS5PW7fCUzAeEwWAdc2vL4W+KKH91co+jzBJj13zskA4J21TXNFBDIzR3uCDB1Ol9czg87IabFakbFd1Vs6v9ngdDj5FE9708bOr9nV3NHIO7T3W//Z0YtJGjmGadcucLer8o9QXVxIebnHC5WaeoMSJT1ItwkTIcT7wBpgmBDisBDieuBp4P/bu/8gu8q7juPvz927dzfZ3WTDbiAQCD9CaIsR0jZDaKEIKXWoraIjHduitILDdBStI1XBP7R2rFXpSNVWHdpS6U9toUXgDym2MNTW8qOE31CJ/EoISYRkk2yy2c3ufv3jPDdckt1kk5y95+zez2tm59zz457z7P0mZ7/3eZ7zPO+S9AzwrrRuZk32u6uzwcVWnTyzniZY0N3OwnnZUzdPrd+53/5lXafvfb1h97ojv+DPngHnvuO19e3bj/yceepdwt4vnpufPOChNrm2ajsrf+0yAIJx7n/s7Ty05tK9+09dek1RRWtJ05aYRMQHIuLYiGiPiOMj4osR8WpEvDMilqXllum6vplNThLvXr6I/9m0Y0b1MwE467Ss+aKxn0lde6Wd3mqWbK0fej6fC/7Mcjjv57LX3745n3Pm6eqfZsuXHiq2HDNcR3cPZ116OVF9/YzWK8780n4dYm16lbbzq5lNr4uWL2Lrrj2seXGg6KIcklq1wsJ5NUZGx5moj9wvLso6OK7ZlmOH0DemDpDDw+Wbt6Yn9bV5+o5iyzELtHfOYU7/a+OanLr0Wvr6ziuwRK3JiYlZi3rridmT+nc8uqHgkhy6RQtqjAeMjO6fJMytdlPJ+9YmQX9/9nrHjgMfW4Tll2TL3e4Ae6ROOONcKrtOpLbuco49+oNFF6clOTExa1GLe+fQVhGbdwwXXZRD1tWZjQo6sHPPhPtXzF8FwNBhzO46qfpjxM8/d+DjirD0gmz51O3FlmMWOOaEc1h63KeojPay8xUPVVEEJyZmLUoS55+2kKc3lqxD5xT09WQzrA7snHhW3P5a1rzx0tAL+V302OOy5dBQfufMy+kXZ8vBzcWWY5Y46sRTANjwxKMFl6Q1OTExa2En93exbssQ67bkWLPQBLVqhfY2Tdpxd/GcJQAMjuXY7CLB/Pmw8eX8zpmXjh7oWgjr7i+6JLNCd99CehYew+7tM6v/1WzhxMSshZ132kIANgyUsBbgIDprFQaHJk5MapUOOitzWD+Uc7PL4uNh48Zs9uKyOeV8ePG/iy7FrDH/uMXs3rGdkV37P5Zu08uJiVkL6+/uAGDLzpGCS3Lo+ufV+L/tIxM+mQOweM6JbN2T84gE9eacbSXsZNr/Btg9AKMzr89QGc1btBiA3dtLGOtZzomJWQs7Zl6WmDyyfubdfOfNqRIBw3vGJ95f7WXX2CDjMfH+w9KXBqR74fn8zpmX7qz2i3X3FVuOWaIzTdy4ffPGgkvSepyYmLWwvu4Oeue28+rgzPuWPacjG29isg6wve3Z49Abd6/P76ILUmIyXMLPa/HKbLk1xw6/LayzZz5t7TWGBrYWXZSW48TErMX1ddXYNTKzRn8F6EqJydAkZe+vLQJg13jOHXu7u2H3/qPOFm5eamYacZ+IPEiis2cee4ZLGOtZzomJWYvr6qgyOFzCzpwHMacju32Njk3cx6Rd2SPFo+MTj3Vy2Do6YXAw33PmodadLUdKWLYZqtrZyWgZk9BZzomJWYvrqlXZOQMTk7ZKNn/J2PjEiUm1khKTyDkxWbAAtpXwMdJqDSrtTkxy1Nkzj10DntKt2ZyYmLW47s6ZWWNSkaho8sSkXmOyZzznJ446Osr5uDBArctNOTmqze1ibGSEGM+xA7UdlBMTsxbXPUObciCrNZksMWlTNmz9nrxrTKpVGCtpn5xatxOTHFWq2b+h8bGZ+f9jpnJiYtbiujtmZlMOZInJ6CRfZiXRrlr+TTltbVmNSdlmGYZUY+KmnLxU2uqJSUkT0VnKiYlZi6s35Uw2UFmZtbWJsUk6vwK0V9rZk3fn1/QtmjJW77spJ1d7a0zK2nQ3SxWSmEi6SNJPJa2VdE0RZTCzTHdHlT1jwfBkVQ8ldqCmHICq2qenxgTK2c/EiUmuKinWrjFprqYnJpLagM8B7wZOBz4g6fRml8PMMt0d2bfCmdicc7DEpF3TWGNSxj9WtW435eRob1NOGZPQWaxawDXPAtZGxLMAkv4VuBh4soCymLW8ns7sNvDWv/hP7v3DC1jSN7fgEk1drSo2DYzw3KZdnHzM/uWeW+3mhaG1vLjrWZbMPSWfi9YTk298LVtK+Zw3D6PnQozC5/8Z0h9VVl8IJ51UaLFmqrb27DN89PZboCJWffDyvc07Nn3U7HZlSZcAF0XEb6X13wBWRcRV+xx3JXBlWl0OPN7UgtpE+oFXii6EAY5FWTgO5eFYlMNU4/BKRFw00Y4iUr+Jvl7slx1FxA3ADQCSHoyIldNdMDswx6E8HItycBzKw7EohzziUETn1/XACQ3rxwMbCiiHmZmZlUwRickDwDJJJ0uqAe8HbiugHGZmZlYyTW/KiYhRSVcBdwJtwI0R8cRB3nbD9JfMpsBxKA/Hohwch/JwLMrhiOPQ9M6vZmZmZpPxyK9mZmZWGk5MzMzMrDRKnZh46PrmknSjpM2SHm/YdpSkuyQ9k5YL0nZJ+vsUm0clvaW4ks8ukk6QdLekpyQ9Iemjabtj0WSSOiXdL+mRFIs/T9tPlnRfisW/pY78SOpI62vT/pOKLP9sI6lN0hpJd6R1x6EAkp6X9JikhyU9mLbldn8qbWLioesL8S/AvgPeXAN8LyKWAd9L65DFZVn6uRL4pyaVsRWMAldHxJuAs4HfSf/2HYvmGwZWR8SZwArgIklnA38NXJ9isRW4Ih1/BbA1Ik4Frk/HWX4+CjzVsO44FOeCiFjRMGZJbven0iYmNAxdHxEjQH3oepsmEXEvsGWfzRcDN6XXNwG/3LD9y5H5MdAr6djmlHR2i4iXI+Kh9HoH2Y14MY5F06XPtD75THv6CWA1cHPavm8s6jG6GXinVKYx62cuSccD7wG+kNaF41Amud2fypyYLAbWNayvT9usuY6JiJch+4MJHJ22Oz5NkKqg3wzch2NRiNR88DCwGbgL+F9gICLqM7s1ft57Y5H2bwP6mlviWeszwB8B9Wmw+3AcihLAdyX9JE0fAznen8o8G9GUhq63wjg+00xSN3AL8PsRsf0AX/gci2kUEWPACkm9wHeAN010WFo6FtNA0nuBzRHxE0nn1zdPcKjj0BznRMQGSUcDd0l6+gDHHnIsylxj4qHry2FTvdotLTen7Y7PNJLUTpaUfC0ivp02OxYFiogB4B6yfj+9kupf7Bo/772xSPvns3/zqB26c4BfkvQ8WbP+arIaFMehABGxIS03kyXrZ5Hj/anMiYmHri+H24APpdcfAv69Yftlqcf12cC2ejWeHZnUFv5F4KmI+NuGXY5Fk0lamGpKkDQHuJCsz8/dwCXpsH1jUY/RJcD3w6NYHrGIuDYijo+Ik8j+Fnw/Ii7FcWg6SV2SeuqvgZ8HHifH+1OpR36V9AtkWXF96PpPFlykWU3SN4Dzyaat3gT8GXAr8E1gCfAi8L6I2JL+eH6W7CmeXcBvRsSDRZR7tpF0LvAD4DFea0//E7J+Jo5FE0k6g6wjXxvZF7lvRsQnJJ1C9s39KGAN8OsRMSypE/gKWb+gLcD7I+LZYko/O6WmnI9FxHsdh+ZLn/l30moV+HpEfFJSHzndn0qdmJiZmVlrKXNTjpmZmbUYJyZmZmZWGk5MzMzMrDScmJiZmVlpODExMzOz0nBiYmavI6lX0m83rB8n6eYDvecwr/NxSS9J+kTe557i9e+WNChp5cGPNrNmcWJiZvvqBfYmJhGxISIuOcDxR+L6iPjTaTp3fdTPCUXEBYDHezErGScmZravvwKWSnpY0nWSTpL0OICkD0u6VdLtkp6TdJWkP5C0RtKPJR2Vjlsq6T/SJF8/kPTGA11QUkXSM5IWNqyvldSfRl+9RdID6eecdMxZkn6Urv0jSW9oKOO3JN1ONtHYsZLuTb/P45LeMZ0fnpkdmTJP4mdmxbgGWB4RK2DvDMeNlpONqNkJrAX+OCLeLOl64DKy0ZpvAD4SEc9IWgX8I9n8JhOKiHFJXwUuTe+/EHgkIl6R9HWympX/krQEuJNsIr2ngfMiYlTShcBfAr+aTvk24Iw08uTVwJ1pdMo2YO4RfTpmNq2cmJjZobo7InYAOyRtA25P2x8DzkizIr8d+FbDjMgdUzjvjWTza3wGuBz4Utp+IXB6w7nmpbk65gM3SVpGNltpe8O57oqI+qRtDwA3pokRb42Ihw/ptzWzpnJiYmaHarjh9XjD+jjZPaUCDNRrXKYqItZJ2iRpNbCKrPaEdL63RcRQ4/GS/oEsSfqVVKtzT8PunQ3nvVfSecB7gK9Iui4ivnwoZTOz5nEfEzPb1w6g53DfHBHbgeckvQ+y2ZIlnTnFt38B+CrZZHljadt3gavqB0iqJzzzgZfS6w9PdkJJJwKbI+LzZLM2v2WKZTGzAjgxMbPXiYhXgR+mjqLXHeZpLgWukPQI8ARw8RTfdxvQzWvNOAC/B6yU9KikJ4GPpO1/A3xK0g/JZv+dzPnAw5LWkPVB+bsp/xZm1nSeXdjMCiHp48BgRHy6YdtKso6uTXlyRtI9wMcONg27mTWPa0zMrCiDwJX1AdYkXQPcAlzbjItLuhs4BdjTjOuZ2dS4xsTMzMxKwzUmZmZmVhpOTMzMzKw0nJiYmZlZaTgxMTMzs9JwYmJmZmal8f9hm4IOmhiCUgAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<Figure size 648x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "#plot\n",
+ "\n",
+ "n = 20\n",
+ "color = plt.cm.tab20(np.linspace(0, 1,n))\n",
+ "\n",
+ "fig, ax = plt.subplots(figsize=(9,4))\n",
+ "ax.set_prop_cycle(cycler.cycler('color', color))\n",
+ "\n",
+ "_, = plt.plot(timearray[0],icelatarray[0],'-',label='1250ppmv 50°')\n",
+ "_, = plt.plot(timearray[1],icelatarray[1],'-',label='1375ppmv 50°')\n",
+ "_, = plt.plot(timearray[2],icelatarray[2],'-',label='1438ppmv 50°')\n",
+ "_, = plt.plot(timearray[3],icelatarray[3],'-',label='1500ppmv 90°')\n",
+ "_, = plt.plot(timearray[4],icelatarray[4],'-',label='1594ppmv 65°')\n",
+ "_, = plt.plot(timearray[5],icelatarray[5],'-',label='2000ppmv 14°')\n",
+ "_, = plt.plot(timearray[6],icelatarray[6],'-',label='2000ppmv 30°')\n",
+ "_, = plt.plot(timearray[7],icelatarray[7],'-',label='2500ppmv 14°')\n",
+ "_, = plt.plot(timearray[8],icelatarray[8],'-',label='2500ppmv 30°')\n",
+ "_, = plt.plot(timearray[9],icelatarray[9],'-',label='3000ppmv 90°')\n",
+ "_, = plt.plot(timearray[10],icelatarray[10],'-',label='3000ppmv 30°')\n",
+ "_, = plt.plot(timearray[11],icelatarray[11],'-',label='3000ppmv 14°')\n",
+ "_, = plt.plot(timearray[12],icelatarray[12],'-',label='3000ppmv 16°')\n",
+ "_, = plt.plot(timearray[13],icelatarray[13],'-',label='5000ppmv 90°')\n",
+ "_, = plt.plot(timearray[14],icelatarray[14],'-',label='5000ppmv 30°')\n",
+ "_, = plt.plot(timearray[15],icelatarray[15],'-',label='5000ppmv 14°')\n",
+ "_, = plt.plot(timearray[16],icelatarray[16],'-',label='5000ppmv 13°')\n",
+ "_, = plt.plot(timearray[17],icelatarray[17],'-',label='10000ppmv 7°')\n",
+ "\n",
+ "\n",
+ "\n",
+ "plt.ylim(0,90)\n",
+ "plt.xlim(0,510)\n",
+ "plt.xlabel(\"time [years]\")\n",
+ "plt.ylabel(\"ice latitude [°]\")\n",
+ "#plt.title(\"hice_unlim global sea ice border\")\n",
+ "plt.legend(ncol=4,edgecolor='none', facecolor='none',loc=1, \n",
+ " columnspacing=1, labelspacing=0.5, handlelength=1, handletextpad=0.2)\n",
+ "ax.spines['top'].set_color('none')\n",
+ "ax.spines['right'].set_color('none')\n",
+ "plt.savefig(\"overview_semtner_5m.pdf\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<pre><xarray.DataArray 'sic' ()>\n",
+ "array(49.547176, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float64 0.0\n",
+ " lat float64 0.0</pre>"
+ ],
+ "text/plain": [
+ "<xarray.DataArray 'sic' ()>\n",
+ "array(49.547176, dtype=float32)\n",
+ "Coordinates:\n",
+ " lon float64 0.0\n",
+ " lat float64 0.0"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "icelatarray[1][-50*12:].mean()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /paper_5000_and_3000ppmv_and_1500ppmv_plot.ipynb b/python_scripts /paper_5000_and_3000ppmv_and_1500ppmv_plot.ipynb
new file mode 100644
index 0000000..ffc6192
--- /dev/null
+++ b/python_scripts /paper_5000_and_3000ppmv_and_1500ppmv_plot.ipynb
@@ -0,0 +1,193 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Temporal evolution of sea-ice edge latitude for selected simulations of 0L-Semtner unlimited and limited"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%matplotlib inline\n",
+ "import xarray as xr\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy import stats\n",
+ "\n",
+ "\n",
+ "def load_experiment(expname): #loads the dataset of a simulation\n",
+ " fname = expname +\"_atm_2d_ml.ym.gm.nc\" #filename of global yearly mean\n",
+ " dpath = \"/work/bb1092/pp_JH/\" +expname +\"/\" #simulation path\n",
+ " DS = xr.open_dataset(dpath +fname, decode_times=False) #loading of dataset\n",
+ " print(dpath +fname)\n",
+ " return expname, DS # returns the name of the experiment & the actual dataset\n",
+ "\n",
+ "def get_var(dataset, varname, offsettime): #gets the dataarray with one specific variable\n",
+ " da=getattr(dataset,varname) #read dataarray\n",
+ " da.squeeze() #squeeze dataarray (time is the only dimension)\n",
+ " if offsettime:\n",
+ " da=da.assign_coords(time=((da.time-da.time[0])/360)) #change time units from days to years & move the origin to 0\n",
+ " else:\n",
+ " da=da.assign_coords(time=((da.time)/360)) #change time units from days to years \n",
+ " return da\n",
+ "def legend_color(ax, handle_array, pos):\n",
+ " legend = ax.legend(handle_array,handlelength=0, handletextpad=0, edgecolor='none', facecolor='none', markerscale=0, loc=pos)\n",
+ " for item in legend.legendHandles:\n",
+ " item.set_visible(False)\n",
+ " for text in legend.get_texts():\n",
+ " if text.get_text()=='Winton':\n",
+ " text.set_color('C1')\n",
+ " if text.get_text()=='3L-Winton':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='0L-Semtner':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='Semtner_5m':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='0L-Semtner-lim5':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='1438ppmv':\n",
+ " text.set_color('C0')\n",
+ " elif text.get_text()=='1500ppmv':\n",
+ " text.set_color('C1')\n",
+ " elif text.get_text()=='3000ppmv':\n",
+ " text.set_color('C2')\n",
+ " elif text.get_text()=='5000ppmv':\n",
+ " text.set_color('C3')\n",
+ " \n",
+ " return legend"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_77sic_hice_unlim/mlo_aqua_3000ppmv_77sic_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_77sic_hice_unlim/mlo_aqua_5000ppmv_77sic_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv_hice_unlim/mlo_aqua_1500ppmv_hice_unlim_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_3000ppmv_Jor2/mlo_aqua_3000ppmv_Jor2_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_5000ppmv_Jor2/mlo_aqua_5000ppmv_Jor2_atm_2d_ml.ym.gm.nc\n",
+ "/work/bb1092/pp_JH/mlo_aqua_1500ppmv/mlo_aqua_1500ppmv_atm_2d_ml.ym.gm.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "experiment1, DS1 = load_experiment(\"mlo_aqua_3000ppmv_77sic_hice_unlim\")\n",
+ "experiment2, DS2 = load_experiment(\"mlo_aqua_5000ppmv_77sic_hice_unlim\")\n",
+ "experiment3, DS3 = load_experiment(\"mlo_aqua_1500ppmv_hice_unlim\")\n",
+ "\n",
+ "experiment1_5m, DS1_5m = load_experiment(\"mlo_aqua_3000ppmv_Jor2\")\n",
+ "experiment2_5m, DS2_5m = load_experiment(\"mlo_aqua_5000ppmv_Jor2\")\n",
+ "experiment3_5m, DS3_5m = load_experiment(\"mlo_aqua_1500ppmv\")\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "da1=get_var(DS1,\"sic\",True)\n",
+ "da2=get_var(DS2,\"sic\",True)\n",
+ "da3=get_var(DS3,\"sic\",True)\n",
+ "da1_5m=get_var(DS1_5m,\"sic\",True)\n",
+ "da2_5m=get_var(DS2_5m,\"sic\",True)\n",
+ "da3_5m=get_var(DS3_5m,\"sic\",True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# sea ice latitude\n",
+ "fig, ax = plt.subplots(figsize=(6,4))\n",
+ "ice_lat1 = np.arcsin(1-da1) * (180./np.pi) \n",
+ "ice_lat1_5m = np.arcsin(1-da1_5m) * (180./np.pi) \n",
+ "\n",
+ "ice_lat2 = np.arcsin(1-da2) * (180./np.pi) \n",
+ "ice_lat2_5m = np.arcsin(1-da2_5m) * (180./np.pi) \n",
+ "\n",
+ "ice_lat3 = np.arcsin(1-da3) * (180./np.pi) \n",
+ "ice_lat3_5m = np.arcsin(1-da3_5m) * (180./np.pi) \n",
+ "\n",
+ "(1-da1).plot(color='C0',ls='-.')\n",
+ "(1-da1_5m).plot(color='C2',ls='-.')\n",
+ "\n",
+ "(1-da2).plot(color='C0',ls='--')\n",
+ "(1-da2_5m).plot(color='C2',ls='--')\n",
+ "\n",
+ "(1-da3).plot(color='C0',ls='-')\n",
+ "(1-da3_5m).plot(color='C2',ls='-')\n",
+ "plt.xlim(0,310)\n",
+ "plt.xlabel(\"Time [years]\")\n",
+ "plt.ylabel(\"Ice-Edge Latitude [°]\")\n",
+ "\n",
+ "ax.spines['right'].set_color('none')\n",
+ "ax.spines['top'].set_color('none')\n",
+ "\n",
+ "ax.set_yticks([np.sin(np.radians(0)),np.sin(np.radians(10)),np.sin(np.radians(20)),np.sin(np.radians(30)),np.sin(np.radians(40)),np.sin(np.radians(50)),np.sin(np.radians(60)),np.sin(np.radians(90))])\n",
+ "ax.set_yticklabels([0,10,20,30,40,50,60,90])\n",
+ "plt.ylim(0,1)\n",
+ "\n",
+ "plt.title(\"\")\n",
+ "#plt.legend([\"Semtner (5000ppmv)\", \"Semtner-limited (5000ppmv)\", \"Semtner (3000ppmv)\", \"Semtner-limited (3000ppmv)\"])\n",
+ "legend_color(ax,['0L-Semtner','0L-Semtner-lim5'],1)\n",
+ "#ax.annotate('5000ppmv',(35,0.36))\n",
+ "#ax.annotate('3000ppmv',(40,0.17))\n",
+ "ax.annotate('5000ppmv',(42,0.4))\n",
+ "ax.annotate('3000ppmv',(40,0.17))\n",
+ "ax.annotate('1500ppmv',(20,0.85))\n",
+ "\n",
+ "plt.savefig(\"plots/icelat_comparison.pdf\",bbox_inches='tight')"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 bleeding edge (using the module anaconda3/bleeding_edge)",
+ "language": "python",
+ "name": "anaconda3_bleeding"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.6.10"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/python_scripts /plots/.ipynb_checkpoints/TOA_balance-checkpoint.csv b/python_scripts /plots/.ipynb_checkpoints/TOA_balance-checkpoint.csv
new file mode 100644
index 0000000..e69de29
diff --git a/python_scripts /plots/.ipynb_checkpoints/bifurcation_5mlim_merged-checkpoint.pdf b/python_scripts /plots/.ipynb_checkpoints/bifurcation_5mlim_merged-checkpoint.pdf
new file mode 100644
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diff --git a/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_freezing_2-checkpoint.pdf b/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_freezing_2-checkpoint.pdf
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diff --git a/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.pdf b/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.pdf
new file mode 100644
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diff --git a/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.png b/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_icon-checkpoint.png
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diff --git a/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_snow-checkpoint.pdf b/python_scripts /plots/.ipynb_checkpoints/model_hi_qtop_qbot_melting_snow-checkpoint.pdf
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diff --git a/python_scripts /plots/TOA_balance.csv b/python_scripts /plots/TOA_balance.csv
new file mode 100644
index 0000000..1ca84f4
--- /dev/null
+++ b/python_scripts /plots/TOA_balance.csv
@@ -0,0 +1,5 @@
+simulation,SW in,SW out,LW out,SW cs out,LW cs out
+mlo_aqua_2437ppmv_winton,321.23425,98.25365,222.16487,56.06923,243.2054
+mlo_aqua_1688ppmv_hice_unlim,321.23425,97.2439,223.32451,54.820316,244.82646
+mlo_aqua_3000ppmv_winton,321.23425,94.45228,225.86537,48.326496,248.45163
+mlo_aqua_2250ppmv_hice_unlim,321.23425,93.05864,227.3154,46.583275,250.22746
diff --git a/python_scripts /plots/bifurcation.svg b/python_scripts /plots/bifurcation.svg
new file mode 100644
index 0000000..bd04fef
--- /dev/null
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diff --git a/python_scripts /plots/bifurcation_winton_merged.pdf b/python_scripts /plots/bifurcation_winton_merged.pdf
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diff --git a/python_scripts /plots/model_hi_qtop_qbot_melting_icon.pdf b/python_scripts /plots/model_hi_qtop_qbot_melting_icon.pdf
new file mode 100644
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GitLab