Adds jupyter notebook to plot global mean time series of icon nextgems ngc4008 simulation

4ef72c0d · Aiko Voigt · 6d793e95 · 4ef72c0d
Commit 4ef72c0d authored 1 week ago by Aiko Voigt
--- a/analysis/icon-nextgems/icon-ngc4008-globalmean.ipynb
+++ b/analysis/icon-nextgems/icon-ngc4008-globalmean.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "735830fd-62b6-4962-aa55-f90dc7a741da",
+   "metadata": {},
+   "source": [
+    "# Gobal mean time series of ngc4008"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4dc8fe11-d0e4-4d46-9568-1af7e147fd9b",
+   "metadata": {},
+   "source": [
+    "On Teachinghub, use the MagicPy Kernel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cb932c48-e396-4bfd-beb1-a7a2a16cf393",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import intake\n",
+    "import healpy as hp\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import dask\n",
+    "import zarr\n",
+    "import easygems\n",
+    "import easygems.healpix as egh\n",
+    "import xarray as xr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e61a8fba-237b-423f-9492-59c76fd4fbaf",
+   "metadata": {},
+   "source": [
+    "Load simulation data from publicly available cloud. The number in front of \".zarr\" is the zoom level. A higher zoom level leads to much larger data. Zoom levels 0 to 9 are available."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c71c9d41-1d62-4a0a-92db-58041a61fc90",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "icon = xr.open_zarr(\"https://s3.eu-dkrz-1.dkrz.cloud/nextgems/rechunked_ngc4008/ngc4008_P1D_0.zarr\").resample(time=\"ME\").mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "192e609e-ba30-4efe-9f51-a9005e0767b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "icon=icon.groupby(icon.time.dt.year).mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2942963e-00e5-48d4-9b37-dd43f43093e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f8241abd3f0>]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(icon[\"ts\"].mean(\"cell\")[1:29],\"x-\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "44a5236d-63a7-44f6-8b97-242c41b71e38",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "MagicPy",
+   "language": "python",
+   "name": "magicpy"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
+%% Cell type:markdown id:735830fd-62b6-4962-aa55-f90dc7a741da tags:
+
+# Gobal mean time series of ngc4008
+
+%% Cell type:markdown id:4dc8fe11-d0e4-4d46-9568-1af7e147fd9b tags:
+
+On Teachinghub, use the MagicPy Kernel.
+
+%% Cell type:code id:cb932c48-e396-4bfd-beb1-a7a2a16cf393 tags:
+
+``` python
+import intake
+import healpy as hp
+import matplotlib.pyplot as plt
+import numpy as np
+import dask
+import zarr
+import easygems
+import easygems.healpix as egh
+import xarray as xr
+```
+
+%% Cell type:markdown id:e61a8fba-237b-423f-9492-59c76fd4fbaf tags:
+
+Load simulation data from publicly available cloud. The number in front of ".zarr" is the zoom level. A higher zoom level leads to much larger data. Zoom levels 0 to 9 are available.
+
+%% Cell type:code id:c71c9d41-1d62-4a0a-92db-58041a61fc90 tags:
+
+``` python
+icon = xr.open_zarr("https://s3.eu-dkrz-1.dkrz.cloud/nextgems/rechunked_ngc4008/ngc4008_P1D_0.zarr").resample(time="ME").mean()
+```
+
+%% Cell type:code id:192e609e-ba30-4efe-9f51-a9005e0767b1 tags:
+
+``` python
+icon=icon.groupby(icon.time.dt.year).mean()
+```
+
+%% Cell type:code id:2942963e-00e5-48d4-9b37-dd43f43093e2 tags:
+
+``` python
+plt.plot(icon["ts"].mean("cell")[1:29],"x-")
+```
+
+%% Output
+
+    [<matplotlib.lines.Line2D at 0x7f8241abd3f0>]
+
+
+
+%% Cell type:code id:44a5236d-63a7-44f6-8b97-242c41b71e38 tags:
+
+``` python
+```