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Fix global mean calculation in Google Cloud notebook #72

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merged 2 commits into from
Nov 28, 2023
Merged

Fix global mean calculation in Google Cloud notebook #72

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a985e23
Fix global mean calculation in Google Cloud notebook
r-ford Oct 26, 2023
f3c8e25
Merge pull request #75 from ProjectPythia/main
r-ford Nov 20, 2023
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35 changes: 24 additions & 11 deletions notebooks/foundations/google-cloud-basic.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -177,6 +177,8 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot the Data\n",
"\n",
"Plot a map from a specific date:"
]
},
Expand All @@ -193,28 +195,38 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Create a timeseries of global-average surface air temperature. For this we need the area weighting factor for each gridpoint."
"The global mean of a lat-lon field needs to be weighted by the area of each grid cell, which is proportional to the cosine of its latitude."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"df_area = df.query(\"variable_id == 'areacella' & source_id == 'CESM2'\")\n",
"ds_area = xr.open_zarr(fsspec.get_mapper(df_area.zstore.values[0]), consolidated=True)\n",
"ds_area"
"def global_mean(field):\n",
" weights = np.cos(np.deg2rad(field.lat))\n",
" return field.weighted(weights).mean(dim=['lat', 'lon'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can pass all of the temperature data through this function:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"total_area = ds_area.areacella.sum(dim=['lon', 'lat'])\n",
"ta_timeseries = (ds.tas * ds_area.areacella).sum(dim=['lon', 'lat']) / total_area\n",
"ta_timeseries = global_mean(ds.tas)\n",
"ta_timeseries"
]
},
Expand All @@ -241,8 +253,9 @@
"outputs": [],
"source": [
"ta_timeseries.plot(label='monthly')\n",
"ta_timeseries.rolling(time=12).mean().plot(label='12 month rolling mean')\n",
"ta_timeseries.rolling(time=12).mean().plot(label='12 month rolling mean', color='k')\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.title('Global Mean Surface Air Temperature')"
]
},
Expand All @@ -258,7 +271,7 @@
"metadata": {},
"source": [
"## Summary\n",
"In this notebook, we opened a CESM2 dataset with `fsspec` and `zarr`. We also used a cell area dataset to calculate and plot global average surface air temperature. \n",
"In this notebook, we opened a CESM2 dataset with `fsspec` and `zarr`. We calculated and plotted global average surface air temperature. \n",
"\n",
"### What's next?\n",
"We will open a dataset with ESGF and OPenDAP."
Expand Down Expand Up @@ -291,7 +304,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
"version": "3.10.12"
},
"nbdime-conflicts": {
"local_diff": [
Expand Down
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