From 31461de73a849c7109755fc4b13add6942d348d1 Mon Sep 17 00:00:00 2001 From: Aiko Voigt <aiko.voigt@univie.ac.at> Date: Mon, 15 Mar 2021 23:36:36 +0100 Subject: [PATCH] Work in progress for Pangeo example to reproduce Fig. 16 of 2016 JAMES introduction paper --- pangeo/james2016_figure16.ipynb | 469 ++++++++++++++++++++++++++++++++ 1 file changed, 469 insertions(+) create mode 100644 pangeo/james2016_figure16.ipynb diff --git a/pangeo/james2016_figure16.ipynb b/pangeo/james2016_figure16.ipynb new file mode 100644 index 0000000..1c2a7e2 --- /dev/null +++ b/pangeo/james2016_figure16.ipynb @@ -0,0 +1,469 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Reproduce Figure 16 of the 2016 JAMES Tracmip introduction paper\n", + "\n", + "We use approach 1 to access the Pangeo data in the Google Cloud. See load_data_from_pangeo.iypnb in the same folder." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import xarray as xr\n", + "import zarr\n", + "import gcsfs" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data loading and climatolgical mean over last 20 years" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Wrapper function to load data. Output is a dictionary of xarray data arrays." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def load_data(freq, var, exp):\n", + " df = pd.read_csv('https://storage.googleapis.com/cmip6/tracmip.csv')\n", + " # a somewhat cumbersome way to query the dataframe ... \n", + " df_var = df.query(\"frequency == \\'\"+freq+\"\\'\").query(\"variable == \\'\"+var+\"\\'\").query(\"experiment == \\'\"+exp+\"\\'\")\n", + " gcs = gcsfs.GCSFileSystem(token='anon')\n", + " datadict = dict()\n", + " for zstore in df_var.source.values:\n", + " mapper = gcs.get_mapper(zstore)\n", + " ds = xr.open_zarr(mapper, consolidated=True)\n", + " ntime = ds.time.size # number of timestep\n", + " ds_clim = ds.isel(time=slice(ntime-20*12, ntime)).groupby('time.month').mean('time')\n", + " # write only variable of interest to dictionary, so this becomes a data array\n", + " datadict[ds.attrs['model_id']] = ds_clim[var] \n", + " return datadict" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "pr_ldct = load_data('Amon', 'pr', 'landControl')\n", + "pr_ldor = load_data('Amon', 'pr', 'landOrbit')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note: not all models have the landOrbit simulations. We are identifying those models that provide both the landControl and the landOrbit simulations." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Models that have both landControl and landOrbit simulations:\n", + " ['CALTECH', 'CAM3', 'CAM4', 'CNRM-AM5', 'ECHAM61', 'ECHAM63', 'LMDZ5A', 'MIROC5', 'MPAS', 'MetUM-CTL', 'MetUM-ENT']\n" + ] + } + ], + "source": [ + "print(\"Models that have both landControl and landOrbit simulations:\\n\", [k for k in pr_ldct if k in pr_ldor])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And now we filter the landControl models for those that have the landOrbit simulation." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "pr_ldct = { model: pr_ldct[model] for model in pr_ldor.keys() }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Interpolation to a common lat-lon grid" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "# latintp is the latiudes on which data will be interpolated, likewise for lonintp\n", + "latintp = np.linspace(-89.5, 89.5, 180) \n", + "nlatintp = latintp.size\n", + "lonintp = np.linspace(-179.0, 179.0, 180) \n", + "nlonintp = lonintp.size" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "def make_latlon_interpolation(orig):\n", + " from scipy.interpolate import griddata\n", + " intp = np.zeros((12, nlatintp, nlonintp)) + np.nan\n", + " orig = orig.roll(lon=(orig['lon'].size//2))\n", + " auxlon = orig['lon'].values\n", + " auxlon[0:orig['lon'].size//2] -= 360\n", + " orig['lon'] = auxlon\n", + " lat = orig['lat'].values\n", + " lon = orig['lon'].values\n", + " # grid of original model data \n", + " x, y = np.meshgrid(lon, lat)\n", + " # grid on which we interpolate\n", + " xintp, yintp = np.meshgrid(lonintp, latintp)\n", + " # interpolate data\n", + " for mon in range(12):\n", + " intp[mon] = griddata((x.ravel(), y.ravel()), orig[mon].values.ravel(), (xintp, yintp))\n", + " return intp" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/fd8940/anaconda3/lib/python3.7/site-packages/xarray/core/dataarray.py:2823: FutureWarning: roll_coords will be set to False in the future. Explicitly set roll_coords to silence warning.\n", + " shifts=shifts, roll_coords=roll_coords, **shifts_kwargs\n" + ] + } + ], + "source": [ + "temp = make_latlon_interpolation(pr_ldct['CALTECH'])" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.contour.QuadContourSet at 0x7fa7fc045210>" + ] + }, + "execution_count": 59, + "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.contourf(temp[1])" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.contour.QuadContourSet at 0x7fa7f51f43d0>" + ] + }, + "execution_count": 60, + "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.contourf(pr_ldct['CALTECH'].isel(month=1))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 1. 3. 5. 7. 9. 11. 13. 15. 17. 19. 21. 23. 25. 27. 29.\n", + " 31. 33. 35. 37. 39. 41. 43.]\n" + ] + } + ], + "source": [ + "print(tm.lonint[90:112])\n", + "pr_land_ldct = np.nanmedian(pr_ldct[:, :, :, 90:112], axis=3)\n", + "pr_land_ldor = np.nanmedian(pr_ldor[:, :, :, 90:112], axis=3)\n", + "pr_ocea_ldct = np.nanmedian(np.concatenate((pr_ldct[:, :, :, 0:90], pr_ldct[:, :, :, 112:]), axis=3), axis=3)\n", + "pr_ocea_ldor = np.nanmedian(np.concatenate((pr_ldor[:, :, :, 0:90], pr_ldor[:, :, :, 112:]), axis=3), axis=3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calculate monthly-mean ITCZ position for land and ocean regions" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# my atmospheric python package for ITCZ calculation\n", + "import sys\n", + "sys.path.append('/home/fd8940/Dropbox/Python3/mymodules/')\n", + "import atmosphere as atm" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "month = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])\n", + "nmonth = month.size" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "itcz_land_ldct = np.zeros((tm.nmod,nmonth)) + np.nan\n", + "itcz_ocea_ldct = np.zeros((tm.nmod,nmonth)) + np.nan\n", + "itcz_land_ldor = np.zeros((tm.nmod,nmonth)) + np.nan\n", + "itcz_ocea_ldor = np.zeros((tm.nmod,nmonth)) + np.nan\n", + "for m in range(tm.nmod):\n", + " for t in range(nmonth):\n", + " itcz_land_ldct[m,t] = atm.get_itczposition(pr_land_ldct[m,t], tm.latint, 30, 0.1)\n", + " itcz_ocea_ldct[m,t] = atm.get_itczposition(pr_ocea_ldct[m,t], tm.latint, 30, 0.1)\n", + " itcz_land_ldor[m,t] = atm.get_itczposition(pr_land_ldor[m,t], tm.latint, 30, 0.1)\n", + " itcz_ocea_ldor[m,t] = atm.get_itczposition(pr_ocea_ldor[m,t], tm.latint, 30, 0.1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def make_niceplot(ax, modelname):\n", + " ax.xaxis.set_ticks([-120, -60, 0, 60, 120])\n", + " ax.xaxis.set_ticklabels([''], fontsize=11)\n", + " ax.yaxis.set_ticks([-0.5, 0, 0.5])\n", + " ax.yaxis.set_ticklabels([''], fontsize=11) \n", + " plt.text(0.03, 0.93, modelname, fontsize=15, ha='left', va='center', \\\n", + " transform=ax.transAxes, backgroundcolor='white')\n", + " plt.xlim(-175, 175), plt.ylim(-0.6, 0.6) " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "sinlat = np.sin(tm.latint*np.pi/180.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 960x960 with 6 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 12), dpi=80, facecolor='w', edgecolor='k')\n", + "clev = np.array([-1.8, -1.4, -1.0, -0.6, -0.2, 0.2, 0.6, 1.0, 1.4, 1.8])\n", + "\n", + "ax = plt.subplot(3, 2, 1)\n", + "c = plt.contourf(month, sinlat, np.transpose(np.nanmedian((pr_ocea_ldor-pr_ocea_ldct)[tm.modlist_ldor], axis=0)), clev, extend='both', cmap=cm.BrBG)\n", + "plt.plot([-200, 200], [0, 0], 'k--')\n", + "plt.plot(month, np.sin(np.nanmedian(itcz_ocea_ldor, axis=0)*np.pi/180), 'k', linewidth=3)\n", + "plt.title('Over ocean', fontsize=14)\n", + "plt.xlim(1, 12), plt.ylim(-0.6, 0.6)\n", + "ax.xaxis.set_ticks(month)\n", + "ax.xaxis.set_ticklabels(['Jan', '', '', 'Apr', '', '', 'Jul', '', '' ,'Oct', '', ''], fontsize=10)\n", + "ax.yaxis.set_ticks([-0.5, 0, 0.5])\n", + "ax.yaxis.set_ticklabels(['30S', 'Eq', '30N'], fontsize=10) \n", + "plt.text(0.02, 0.92, 'a)', fontsize=14, ha='left', va='center', transform=ax.transAxes, backgroundcolor='white')\n", + "\n", + "ax = plt.subplot(3, 2, 5)\n", + "ax.axis('off')\n", + "cbar = plt.colorbar(c, ticks=[-1.8, -1.0, -0.2, 0.2, 1.0, 1.8], orientation='vertical', aspect=30)\n", + "cbar.ax.tick_params(labelsize=10)\n", + "ax.text(1, 1, 'mm/day', fontsize=10)\n", + "\n", + "ax = plt.subplot(3, 2, 2)\n", + "plt.contourf(month, sinlat, np.transpose(np.nanmedian((pr_land_ldor-pr_land_ldct)[tm.modlist_ldor], axis=0)), clev, extend='both', cmap=cm.BrBG)\n", + "plt.plot([-200, 200], [0, 0], 'k--')\n", + "plt.plot(month, np.sin(np.nanmedian(itcz_land_ldct, axis=0)*np.pi/180), 'k', linewidth=3)\n", + "plt.title('Over land', fontsize=14)\n", + "plt.xlim(1, 12), plt.ylim(-0.6, 0.6)\n", + "ax.xaxis.set_ticks(month)\n", + "ax.xaxis.set_ticklabels(['Jan', '', '', 'Apr', '', '', 'Jul', '', '' ,'Oct', '', ''], fontsize=10)\n", + "ax.yaxis.set_ticks([-0.5, 0, 0.5])\n", + "ax.yaxis.set_ticklabels(['30S', 'Eq', '30N'], fontsize=10) \n", + "plt.text(0.02, 0.92, 'b)', fontsize=14, ha='left', va='center', transform=ax.transAxes, backgroundcolor='white')\n", + "\n", + "ax = plt.subplot(3, 2, 3)\n", + "ax.spines['right'].set_color('none')\n", + "ax.spines['top'].set_color('none')\n", + "ax.xaxis.set_ticks_position('bottom')\n", + "ax.yaxis.set_ticks_position('left')\n", + "\n", + "plt.plot([-100, 100], [0, 0], 'k--')\n", + "for m in tm.modlist_ldor:\n", + " plt.plot(month, (itcz_ocea_ldor-itcz_ocea_ldct)[m,:], color=tm.modcolors[m])\n", + "plt.plot(month, np.nanmedian((itcz_ocea_ldor-itcz_ocea_ldct)[tm.modlist_ldor], axis=0), 'k', linewidth=3)\n", + "plt.xlabel('month')\n", + "plt.ylabel('ITCZ shift (deg lat)')\n", + "plt.xlim(1, 12), plt.ylim(-3, 3)\n", + "ax.xaxis.set_ticks(month)\n", + "ax.xaxis.set_ticklabels(['Jan', '', '', 'Apr', '', '', 'Jul', '', '' ,'Oct', '', ''], fontsize=10)\n", + "ax.yaxis.set_ticks([-3, -2, -1, 0, 1, 2, 3])\n", + "ax.yaxis.set_ticklabels([-3, -2, -1, 0, 1, 2, 3], fontsize=10) \n", + "plt.text(0.02, 0.95, 'c)', fontsize=14, ha='left', va='center', transform=ax.transAxes, backgroundcolor='white')\n", + "\n", + "ax = plt.subplot(3, 2, 4)\n", + "ax.spines['right'].set_color('none')\n", + "ax.spines['top'].set_color('none')\n", + "ax.xaxis.set_ticks_position('bottom')\n", + "ax.yaxis.set_ticks_position('left')\n", + "\n", + "plt.plot([-100, 100], [0, 0], 'k--')\n", + "for m in tm.modlist_ldor:\n", + " plt.plot(month, (itcz_land_ldor-itcz_land_ldct)[m,:], color=tm.modcolors[m])\n", + "plt.plot(month, np.nanmedian((itcz_land_ldor-itcz_land_ldct)[tm.modlist_ldor], axis=0), 'k', linewidth=3)\n", + "plt.xlabel('month')\n", + "plt.xlim(1, 12), plt.ylim(-3, 3)\n", + "ax.xaxis.set_ticks(month)\n", + "ax.xaxis.set_ticklabels(['Jan', '', '', 'Apr', '', '', 'Jul', '', '' ,'Oct', '', ''], fontsize=10)\n", + "ax.yaxis.set_ticks([-3, -2, -1, 0, 1, 2, 3])\n", + "ax.yaxis.set_ticklabels([-3, -2, -1, 0, 1, 2, 3], fontsize=10) \n", + "plt.text(0.02, 0.95, 'd)', fontsize=14, ha='left', va='center', transform=ax.transAxes, backgroundcolor='white')\n", + "\n", + "plt.tight_layout\n", + "plt.savefig('figs/corrigendumpaper_figure16.pdf')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} -- GitLab