Initial commit

d93fb967 · Johannes Hörner · d93fb967 · d93fb967 · d93fb967 · d93fb967
Commit d93fb967 authored 1 year ago by Johannes Hörner
--- a/.ipynb_checkpoints/Fig1-overview_bifurcation-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Fig1-overview_bifurcation-checkpoint.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "6e13661d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<module 'ICON_tools' from '../../python_packages/ICON_tools.py'>"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "from os import path\n",
+    "import sys, importlib\n",
+    "\n",
+    "sys.path.append(\"../../python_packages\")\n",
+    "import ICON_tools\n",
+    "\n",
+    "importlib.reload(ICON_tools)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "31e3b222",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ape_ia_7000_56_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_7000_56_3W\n",
+      "ape_ia_8000_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8000_90_3W\n",
+      "ape_ia_8500_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8500_90_3W\n",
+      "ape_ia_9000_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_9000_90_3W\n",
+      "ape_ia_15000_17_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_15000_17_3W\n",
+      "ape_ia_5000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_5000_13_0S\n",
+      "ape_ia_5500_90_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_5500_90_0S\n",
+      "ape_ia_6000_90_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6000_90_0S\n",
+      "ape_ia_6000_90_0S_cltlim_dtime10: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6000_90_0S_cltlim_dtime10\n",
+      "ape_ia_6500_90_0S_cltlim_dtime10: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6500_90_0S_cltlim_dtime10\n",
+      "ape_ia_8000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8000_13_0S\n",
+      "ape_ia_9000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_9000_13_0S\n",
+      "ape_ia_10000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_10000_13_0S\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_path = \"/jetfs/scratch/jhoerner/postprocessing\"\n",
+    "Wexplist, Wnexp = ICON_tools.get_explist(data_path, [\"ape_ia_7000_56_3W\", \"ape_ia_8000_90_3W\", \"ape_ia_8500_90_3W\", \"ape_ia_9000_90_3W\", \"ape_ia_15000_17_3W\"])\n",
+    "WDSlistgm, _ = ICON_tools.load_ds_2d(data_path, Wexplist, True)\n",
+    "\n",
+    "\n",
+    "Sexplist, Snexp = ICON_tools.get_explist(data_path, [\"ape_ia_5000_13_0S\", \"ape_ia_5500_90_0S\", \"ape_ia_6000_90_0S\", \"ape_ia_6000_90_0S_cltlim_dtime10\", \"ape_ia_6500_90_0S_cltlim_dtime10\", \"ape_ia_8000_13_0S\", \"ape_ia_9000_13_0S\", \"ape_ia_10000_13_0S\" ]) # , \"ape_ia_6500_90_0S\" , \"ape_ia_7000_62_0S\"\n",
+    "SDSlistgm, SDSlistzm = ICON_tools.load_ds_2d(data_path, Sexplist, True)\n",
+    "\n",
+    "SDSlistgmym = np.empty([Snexp], dtype=\"object\")\n",
+    "SDSlistzmym = np.empty([Snexp], dtype=\"object\")\n",
+    "WDSlistgmym = np.empty([Wnexp], dtype=\"object\")\n",
+    "\n",
+    "for i in range(Snexp):\n",
+    "    # fillna\n",
+    "    SDSlistgm[i] = SDSlistgm[i].where(SDSlistgm[i]['sic'] < 1e36)  \n",
+    "    SDSlistgmym[i] = xr.decode_cf(SDSlistgm[i]).groupby('time.year').mean(dim='time')\n",
+    "    SDSlistzm[i] = SDSlistzm[i].where(SDSlistzm[i]['sic'] < 1e36)  \n",
+    "    SDSlistzmym[i] = xr.decode_cf(SDSlistzm[i]).groupby('time.year').mean(dim='time')\n",
+    "\n",
+    "for i in range(Wnexp):\n",
+    "    # fillna\n",
+    "    WDSlistgm[i] = WDSlistgm[i].where(WDSlistgm[i]['sic'] < 1e36)\n",
+    "    WDSlistgmym[i] = xr.decode_cf(WDSlistgm[i]).groupby('time.year').mean(dim='time')\n",
+    "\n",
+    "\n",
+    "colorlist = [\"C1\",\"C0\",\"C2\",\"C3\",\"C5\",\"C6\",\"C7\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "d3b41d22",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1,2,figsize=(12,4))\n",
+    "\n",
+    "# first plot: simoverview\n",
+    "for j in [0,1]:\n",
+    "    if j==0:\n",
+    "        DSlistgm=WDSlistgmym\n",
+    "        explist=Wexplist\n",
+    "        legend_label=\"Winton\"\n",
+    "    elif j==1:\n",
+    "        DSlistgm=SDSlistgmym\n",
+    "        explist=Sexplist\n",
+    "        legend_label=\"Semtner\"\n",
+    "    color=colorlist[j]\n",
+    "    for i, exp in enumerate(explist): # simulations\n",
+    "        ax[0].plot(DSlistgm[i].year,(DSlistgm[i][\"sic\"].squeeze()), color=color, \n",
+    "                            label= ICON_tools.find_co2_expname_vscicona(exp) +\"ppm\",  ls=\"-\", clip_on=False) \n",
+    "\n",
+    "#ax[0].legend(ncol=2)\n",
+    "ax[0].set_xlabel(\"time [years]\")\n",
+    "\n",
+    "\n",
+    "yticks=[90,60,45,30,20,10,0]\n",
+    "ax[0].set_yticks((ICON_tools.icelatosic(yticks)))\n",
+    "ax[0].set_yticklabels(yticks)\n",
+    "ax[0].invert_yaxis()\n",
+    "ax[0].set_xlim(0,400)\n",
+    "ax[0].set_ylim(1,0)\n",
+    "\n",
+    "ax[0].set_ylabel(\"ice-margin latitude [°]\")\n",
+    "ax[0].spines['left'].set_position(('outward',5))\n",
+    "ax[0].spines['bottom'].set_position(('outward',5))\n",
+    "\n",
+    "\n",
+    "ax[0].spines['top'].set_visible(False)\n",
+    "ax[0].spines['right'].set_visible(False)\n",
+    "\n",
+    "\n",
+    "\n",
+    "#second plot: bifurcation\n",
+    "color=colorlist[0]\n",
+    "for i, exp in enumerate(Wexplist):\n",
+    "    ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-WDSlistgmym[i][\"sic\"][-1]), color=color, clip_on=False)\n",
+    "\n",
+    "color=colorlist[1]\n",
+    "for i, exp in enumerate(Sexplist):\n",
+    "    #ax[1].vlines(float(ICON_tools.find_co2_expname_vscicona(exp))*1.006,(1-SDSlistgmym[i][\"sic\"][0]),(1-SDSlistgmym[i][\"sic\"][-1]), color=color, clip_on=False, lw=1)\n",
+    "    if exp==\"ape_ia_9000_13_0S\" or exp==\"ape_ia_10000_13_0S\":\n",
+    "        ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-SDSlistgmym[i][\"sic\"][-1]), color=color, clip_on=False, marker=\"^\")\n",
+    "    else:\n",
+    "        ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-SDSlistgmym[i][\"sic\"][-1]), color=color, clip_on=False, marker=\"o\")\n",
+    "\n",
+    "    \n",
+    "yticks_deg=[0,10,20,30,45,60,90]\n",
+    "ax[1].set_yticks(1-ICON_tools.icelatosic(yticks_deg))\n",
+    "ax[1].set_ylim(0,1)\n",
+    "ax[1].set_yticklabels(yticks_deg)\n",
+    "ax[1].set_xscale('log')\n",
+    "ax[1].set_xlim(4500,15000)\n",
+    "ax[1].set_xticks([5000,6000,7000,8000,9000,10000,15000])\n",
+    "ax[1].set_xticklabels([\"5e3\",\"6e3\",\"7e3\",\"8e3\",\"9e3\",\"1e4\",\"1.5e4\"])\n",
+    "ax[1].set_xlabel(\"CO$_2$ [ppmv]\")\n",
+    "#ax[1].set_ylabel(\"ice-margin latitude [°]\")\n",
+    "ax[1].spines['left'].set_position(('outward', 5))\n",
+    "ax[1].spines['bottom'].set_position(('outward', 5))\n",
+    "ax[1].spines['top'].set_visible(False)\n",
+    "ax[1].spines['right'].set_visible(False)\n",
+    "\n",
+    "ax[0].annotate(\"a)\", xycoords=\"axes fraction\", xy=(0.01,0.98), fontweight=\"bold\")\n",
+    "ax[1].annotate(\"b)\", xycoords=\"axes fraction\", xy=(0.01,0.98), fontweight=\"bold\")\n",
+    "\n",
+    "#ax[1].axhspan(1-0,1-ICON_tools.icelatosic(49), color='lightgray', alpha=0.4, lw=0)\n",
+    "#ax[1].axhspan(1-ICON_tools.icelatosic(16), 1-ICON_tools.icelatosic(11.5), color='lightgray', alpha=0.4, lw=0)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.savefig(\"plots/Fig1-overview_bifurcation.pdf\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7155417f-5a4d-4c2a-95ad-b6440b793082",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "baseenv - Python 3.7",
+   "language": "python",
+   "name": "baseenv"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
+%% Cell type:code id:6e13661d tags:
+
+``` python
+import numpy as np
+import xarray as xr
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+from os import path
+import sys, importlib
+
+sys.path.append("../../python_packages")
+import ICON_tools
+
+importlib.reload(ICON_tools)
+```
+
+%% Output
+
+    <module 'ICON_tools' from '../../python_packages/ICON_tools.py'>
+
+%% Cell type:code id:31e3b222 tags:
+
+``` python
+data_path = "/jetfs/scratch/jhoerner/postprocessing"
+Wexplist, Wnexp = ICON_tools.get_explist(data_path, ["ape_ia_7000_56_3W", "ape_ia_8000_90_3W", "ape_ia_8500_90_3W", "ape_ia_9000_90_3W", "ape_ia_15000_17_3W"])
+WDSlistgm, _ = ICON_tools.load_ds_2d(data_path, Wexplist, True)
+
+
+Sexplist, Snexp = ICON_tools.get_explist(data_path, ["ape_ia_5000_13_0S", "ape_ia_5500_90_0S", "ape_ia_6000_90_0S", "ape_ia_6000_90_0S_cltlim_dtime10", "ape_ia_6500_90_0S_cltlim_dtime10", "ape_ia_8000_13_0S", "ape_ia_9000_13_0S", "ape_ia_10000_13_0S" ]) # , "ape_ia_6500_90_0S" , "ape_ia_7000_62_0S"
+SDSlistgm, SDSlistzm = ICON_tools.load_ds_2d(data_path, Sexplist, True)
+
+SDSlistgmym = np.empty([Snexp], dtype="object")
+SDSlistzmym = np.empty([Snexp], dtype="object")
+WDSlistgmym = np.empty([Wnexp], dtype="object")
+
+for i in range(Snexp):
+    # fillna
+    SDSlistgm[i] = SDSlistgm[i].where(SDSlistgm[i]['sic'] < 1e36)
+    SDSlistgmym[i] = xr.decode_cf(SDSlistgm[i]).groupby('time.year').mean(dim='time')
+    SDSlistzm[i] = SDSlistzm[i].where(SDSlistzm[i]['sic'] < 1e36)
+    SDSlistzmym[i] = xr.decode_cf(SDSlistzm[i]).groupby('time.year').mean(dim='time')
+
+for i in range(Wnexp):
+    # fillna
+    WDSlistgm[i] = WDSlistgm[i].where(WDSlistgm[i]['sic'] < 1e36)
+    WDSlistgmym[i] = xr.decode_cf(WDSlistgm[i]).groupby('time.year').mean(dim='time')
+
+
+colorlist = ["C1","C0","C2","C3","C5","C6","C7"]
+```
+
+%% Output
+
+    ape_ia_7000_56_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_7000_56_3W
+    ape_ia_8000_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8000_90_3W
+    ape_ia_8500_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8500_90_3W
+    ape_ia_9000_90_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_9000_90_3W
+    ape_ia_15000_17_3W: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_15000_17_3W
+    ape_ia_5000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_5000_13_0S
+    ape_ia_5500_90_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_5500_90_0S
+    ape_ia_6000_90_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6000_90_0S
+    ape_ia_6000_90_0S_cltlim_dtime10: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6000_90_0S_cltlim_dtime10
+    ape_ia_6500_90_0S_cltlim_dtime10: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_6500_90_0S_cltlim_dtime10
+    ape_ia_8000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_8000_13_0S
+    ape_ia_9000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_9000_13_0S
+    ape_ia_10000_13_0S: directory is /jetfs/scratch/jhoerner/postprocessing/ape_ia_10000_13_0S
+
+%% Cell type:code id:d3b41d22 tags:
+
+``` python
+fig, ax = plt.subplots(1,2,figsize=(12,4))
+
+# first plot: simoverview
+for j in [0,1]:
+    if j==0:
+        DSlistgm=WDSlistgmym
+        explist=Wexplist
+        legend_label="Winton"
+    elif j==1:
+        DSlistgm=SDSlistgmym
+        explist=Sexplist
+        legend_label="Semtner"
+    color=colorlist[j]
+    for i, exp in enumerate(explist): # simulations
+        ax[0].plot(DSlistgm[i].year,(DSlistgm[i]["sic"].squeeze()), color=color,
+                            label= ICON_tools.find_co2_expname_vscicona(exp) +"ppm",  ls="-", clip_on=False)
+
+#ax[0].legend(ncol=2)
+ax[0].set_xlabel("time [years]")
+
+
+yticks=[90,60,45,30,20,10,0]
+ax[0].set_yticks((ICON_tools.icelatosic(yticks)))
+ax[0].set_yticklabels(yticks)
+ax[0].invert_yaxis()
+ax[0].set_xlim(0,400)
+ax[0].set_ylim(1,0)
+
+ax[0].set_ylabel("ice-margin latitude [°]")
+ax[0].spines['left'].set_position(('outward',5))
+ax[0].spines['bottom'].set_position(('outward',5))
+
+
+ax[0].spines['top'].set_visible(False)
+ax[0].spines['right'].set_visible(False)
+
+
+
+#second plot: bifurcation
+color=colorlist[0]
+for i, exp in enumerate(Wexplist):
+    ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-WDSlistgmym[i]["sic"][-1]), color=color, clip_on=False)
+
+color=colorlist[1]
+for i, exp in enumerate(Sexplist):
+    #ax[1].vlines(float(ICON_tools.find_co2_expname_vscicona(exp))*1.006,(1-SDSlistgmym[i]["sic"][0]),(1-SDSlistgmym[i]["sic"][-1]), color=color, clip_on=False, lw=1)
+    if exp=="ape_ia_9000_13_0S" or exp=="ape_ia_10000_13_0S":
+        ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-SDSlistgmym[i]["sic"][-1]), color=color, clip_on=False, marker="^")
+    else:
+        ax[1].scatter(float(ICON_tools.find_co2_expname_vscicona(exp)),(1-SDSlistgmym[i]["sic"][-1]), color=color, clip_on=False, marker="o")
+
+
+yticks_deg=[0,10,20,30,45,60,90]
+ax[1].set_yticks(1-ICON_tools.icelatosic(yticks_deg))
+ax[1].set_ylim(0,1)
+ax[1].set_yticklabels(yticks_deg)
+ax[1].set_xscale('log')
+ax[1].set_xlim(4500,15000)
+ax[1].set_xticks([5000,6000,7000,8000,9000,10000,15000])
+ax[1].set_xticklabels(["5e3","6e3","7e3","8e3","9e3","1e4","1.5e4"])
+ax[1].set_xlabel("CO$_2$ [ppmv]")
+#ax[1].set_ylabel("ice-margin latitude [°]")
+ax[1].spines['left'].set_position(('outward', 5))
+ax[1].spines['bottom'].set_position(('outward', 5))
+ax[1].spines['top'].set_visible(False)
+ax[1].spines['right'].set_visible(False)
+
+ax[0].annotate("a)", xycoords="axes fraction", xy=(0.01,0.98), fontweight="bold")
+ax[1].annotate("b)", xycoords="axes fraction", xy=(0.01,0.98), fontweight="bold")
+
+#ax[1].axhspan(1-0,1-ICON_tools.icelatosic(49), color='lightgray', alpha=0.4, lw=0)
+#ax[1].axhspan(1-ICON_tools.icelatosic(16), 1-ICON_tools.icelatosic(11.5), color='lightgray', alpha=0.4, lw=0)
+
+plt.tight_layout()
+plt.savefig("plots/Fig1-overview_bifurcation.pdf")
+```
+
+%% Output
+
+
+
+%% Cell type:code id:7155417f-5a4d-4c2a-95ad-b6440b793082 tags:
+
+``` python
+```
--- a/.ipynb_checkpoints/Fig2-bareicefrac-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Fig2-bareicefrac-checkpoint.ipynb
--- a/.ipynb_checkpoints/Fig3-toaalb_phase-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Fig3-toaalb_phase-checkpoint.ipynb
--- a/.ipynb_checkpoints/Fig4-climatefeedback-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Fig4-climatefeedback-checkpoint.ipynb
--- a/.ipynb_checkpoints/Fig5-0Sto3W-checkpoint.ipynb
+++ b/.ipynb_checkpoints/Fig5-0Sto3W-checkpoint.ipynb
--- a/ICON-runscripts/README.md
+++ b/ICON-runscripts/README.md
+# Snowball simulations on an aquaplanet using ICON-A
+
+
+Parent folder of all Snowball simulations in an aquaplanet setup with ICON-A. Compare to ape_snowball, which are the same simulations but with ICON-ES;
+
+Setup is: aquaplanet, Semtner & Winton sea-ice model, adapted Bergeron-Findeisen-Process (csecfrl = 5e-5), circular Kepler orbit with 23.5Â° obliquity, `TSI=0.9442*1360.875~=1285 W/m^2`, snow albedo 0.79-0.66, ice albedo 0.45-0.38, linearly interpolated from Tmelt to Tmelt-1K. 
+
+Starting timestep is 10m, with rayleigh_coeff=0.1. If the model becomes unstable, the timestep will be decreased to 8m and rayleigh_coeff=10.
+
+The naming convention is: 
+
+`ape_ia_{co2-content}_{initial sea-ice-edge latitude}`
+
+runscripts are adapted from HÃrner et al. (2022) and Braun et al. (2022)
--- a/ICON-runscripts/ape_ia_10000_13_0S/README.md
+++ b/ICON-runscripts/ape_ia_10000_13_0S/README.md
+# ape_ia_10000_13_0S
+ICON-A run. Same settings as ape_ia_8000_13_0S, except for CO2.  Start from restart file ape_ia_6000_90_0S_restart_atm_00200101T000000Z.nc (sic=0.767578125000124). CO2 9000ppmv, time step =6min, damping=10.
+This simulation is expected to melt. csecfrl = 5e-5. Auto restart is enabled from the start. 
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 21.06.23 11:30 - simulation start at year 200, end year 400
+- 21-06-2023 11:40:45 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:43:38 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:44:17 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:44:53 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:45:29 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:46:07 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:46:43 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:47:22 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:47:56 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:48:31 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:49:04 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:49:39 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:50:14 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:50:49 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:51:27 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:52:03 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:52:39 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:53:14 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:53:50 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:54:27 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:55:04 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:55:39 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:56:14 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:56:47 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:57:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:57:58 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:58:30 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 00:59:06 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 00:59:42 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:00:17 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:00:49 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:01:24 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:01:57 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:02:32 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:03:05 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:03:40 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:04:15 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:04:50 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:05:26 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:06:03 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:06:38 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:07:16 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:07:52 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:08:28 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:09:03 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:09:40 crash, autorestart with hdiff_smag_fac=0.015
+- 26-06-2023 01:10:15 crash, autorestart with hdiff_smag_fac=0.015001
+- 26-06-2023 01:10:52 crash, autorestart with hdiff_smag_fac=0.015
+- 07-07-2023 03:00 continue until 350-01-01
+- 08-07-2023 03:00 timeout at 334-01-17, continue
+- 13-07-2023 00:00 finish at 350-01-01
--- a/ICON-runscripts/ape_ia_10000_13_0S/exp.ape_ia_10000_13_0S.run
+++ b/ICON-runscripts/ape_ia_10000_13_0S/exp.ape_ia_10000_13_0S.run
--- a/ICON-runscripts/ape_ia_10000_13_0Sto0S/README.md
+++ b/ICON-runscripts/ape_ia_10000_13_0Sto0S/README.md
+# ape_ia_10000_13_0Sto3W
+partner simulation to ape_ia_10000_13_0Sto3W.
+
+Simulation restarted from 0L-Semtner in Waterbelt state, continued with 0L-Semtner sea-ice model (just with higher output to compare to simulation with 3L-Winton model). Same settings as ape_ia_10000_13_0S only with higher output. Restart file is adapted to include a approximation of initial ice-internal temperatures
+
+Start from restart file ape_ia_10000_13_0S_restart_atm_03500101T000000Z_icetemps.nc (created on jet by icetemps.ipynb). CO2 8000ppmv, time step =6min, damping=10.
+This simulation is expected to stay in a waterbelt state. csecfrl = 5e-5. Auto restart is enabled from the start. 
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 17-07-2022 15:00 - simulation start at 350-01-01, end date 360-01-01
+- 17-07-2023 21:23:48 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 22:20:05 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 22:38:19 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 22:56:49 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 23:12:15 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 23:23:14 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 23:32:18 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 23:46:18 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:10:21 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:13:47 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:16:20 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:18:25 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:22:21 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:24:21 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:26:26 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:28:22 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:30:21 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:32:22 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:34:26 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:36:52 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:38:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:40:26 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:44:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:46:23 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:48:24 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:50:23 crash, autorestart with hdiff_smag_fac=0.015
--- a/ICON-runscripts/ape_ia_10000_13_0Sto0S/exp.ape_ia_10000_13_0Sto0S.run
+++ b/ICON-runscripts/ape_ia_10000_13_0Sto0S/exp.ape_ia_10000_13_0Sto0S.run
--- a/ICON-runscripts/ape_ia_10000_13_0Sto3W/README.md
+++ b/ICON-runscripts/ape_ia_10000_13_0Sto3W/README.md
+# ape_ia_10000_13_0Sto3W
+Partner simulation to ape_ia_1000_13_0Sto0S
+
+Simulation restarted from 0L-Semtner in Waterbelt state, with 3L-Winton sea-ice model. Same settings as ape_ia_10000_13_0S, except for sea-ice mode. Restart file is adapted to include a approximation of initial ice-internal temperatures
+Start from restart file ape_ia_10000_13_0S_restart_atm_03500101T000000Z_icetemps.nc (created on jet by icetemps.ipynb). CO2 10000ppmv, time step =6min, damping=10.
+This simulation is expected to freeze to a Snowball due to the ice scheme. csecfrl = 5e-5. Auto restart is enabled from the start. 
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 17-07-2022 15:00 - simulation start at 350-01-01, end date 360-01-01
+- 17-07-2023 20:21:35 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 22:08:01 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 22:22:08 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 22:50:10 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 23:08:16 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 23:23:18 crash, autorestart with hdiff_smag_fac=0.015
+- 17-07-2023 23:32:18 crash, autorestart with hdiff_smag_fac=0.015001
+- 17-07-2023 23:44:26 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:11:09 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:14:52 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:18:25 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:20:22 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:22:21 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:24:21 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:26:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:28:22 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:30:21 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:32:23 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:34:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:36:46 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:38:22 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:42:08 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:42:23 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:44:23 crash, autorestart with hdiff_smag_fac=0.015
+- 18-07-2023 00:46:24 crash, autorestart with hdiff_smag_fac=0.015001
+- 18-07-2023 00:48:28 crash, autorestart with hdiff_smag_fac=0.015
--- a/ICON-runscripts/ape_ia_10000_13_0Sto3W/exp.ape_ia_10000_13_0Sto3W.run
+++ b/ICON-runscripts/ape_ia_10000_13_0Sto3W/exp.ape_ia_10000_13_0Sto3W.run
--- a/ICON-runscripts/ape_ia_10000_41_3W/README.md
+++ b/ICON-runscripts/ape_ia_10000_41_3W/README.md
+#ape_ia_10000_41_3W
+Winton run with ICON-A, branch off from ape_ia_8000_90_3W, year 190. All settings the same as there (except CO2...)  Damping parameter is 10. Time step is 6 min. csecfrl = 5e-5. Auto restart is enabled from the start. 
+restart file ape_ia_8000_90_3W_restart_atm_01900101T000000Z.nc
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 31-07-2023 15:30 simulation start, end year 240
--- a/ICON-runscripts/ape_ia_10000_41_3W/exp.ape_ia_10000_41_3W.run
+++ b/ICON-runscripts/ape_ia_10000_41_3W/exp.ape_ia_10000_41_3W.run
--- a/ICON-runscripts/ape_ia_15000_17_3W/README.md
+++ b/ICON-runscripts/ape_ia_15000_17_3W/README.md
+# ape_ia_15000_17_3W
+Winton run with ICON-A, branch off from ape_ia_8000_90_3W, year 220. All settings the same as there (except CO2...)  Damping parameter is 10. Time step is 6 min. csecfrl = 5e-5. Auto restart is enabled from the start. 
+restart file ape_ia_8000_90_3W_restart_atm_02200101T000000Z.nc
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 12.05.23 14:45 - simulation start at year 1, end year 100
+- 23-06-2023 10:18:12 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 10:37:09 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 10:55:03 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 11:13:19 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 11:31:13 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 11:49:10 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 12:07:16 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 12:25:08 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 12:43:10 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 13:01:19 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 13:19:18 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 13:37:06 crash, autorestart with hdiff_smag_fac=0.015
+- 23-06-2023 13:55:23 crash, autorestart with hdiff_smag_fac=0.015001
+- 23-06-2023 14:15:08 crash, simulation is in Snowball, stop (238-10-23)
--- a/ICON-runscripts/ape_ia_15000_17_3W/exp.ape_ia_15000_17_3W.run
+++ b/ICON-runscripts/ape_ia_15000_17_3W/exp.ape_ia_15000_17_3W.run
--- a/ICON-runscripts/ape_ia_5000_13_0S/README.md
+++ b/ICON-runscripts/ape_ia_5000_13_0S/README.md
+# ape_ia_5000_13_0S
+6th production run using ICON-A. Same settings as ape_ia_8000_13_0S, except for CO2.  Start from restart file ape_ia_6000_90_0S_restart_atm_00200101T000000Z.nc (sic=0.767578125000124). CO2 5000ppmv, time step =6min, damping=10.
+This simulation is expected to fall into a Snowball. csecfrl = 5e-5. Auto restart is enabled from the start. 
+
+model version: [commit 01fa4282 in icon-aes-dkrz/icon-aes-mlo-jh](https://gitlab.phaidra.org/hoernerj21/icon-aes-dkrz/-/commit/01fa42823070f664f806b7d54c1d0ffef3e308df)
+
+5 nodes
+account p71767 (project nodes)
+24 hours time with 20 years restart interval
+
+
+## explog
+- 06.04.23 14:00 - simulation start at year 200, end year 300
+- 12.04.23 01:00 - finish at 300-01-01
+- 12-04-23 12:00 continue until 400-01-01
+- 15-04-23 07:00 abort at 352-12-17 due to time limit? (probably because of full disk quota)
+- 17-04-23 15:30 continue
+- 19-04-23 10:00 finish at 400-01-01
--- a/ICON-runscripts/ape_ia_5000_13_0S/exp.ape_ia_5000_13_0S.run
+++ b/ICON-runscripts/ape_ia_5000_13_0S/exp.ape_ia_5000_13_0S.run
--- a/ICON-runscripts/ape_ia_5500_90_0S/README.md
+++ b/ICON-runscripts/ape_ia_5500_90_0S/README.md
--- a/ICON-runscripts/ape_ia_5500_90_0S/exp.ape_ia_5500_90_0S.run
+++ b/ICON-runscripts/ape_ia_5500_90_0S/exp.ape_ia_5500_90_0S.run