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Chapter02_NC_and_bpch_diagnostics.ipynb

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@@ -31,7 +31,7 @@
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"import xarray as xr\n",
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"import xbpch\n",
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"\n",
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"import warnings; warnings.filterwarnings(\"ignore\") # hide some warnings for xbpch\n",
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"import warnings; warnings.filterwarnings(\"ignore\") # hide some xbpch warnings\n",
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"\n",
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"from gamap_colormap import WhGrYlRd"
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Each variable contains 3 time slices, since I run the model for 1 hour and the output frequency is 20min."
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"Each variable contains 3 time slices, since I run the model for 1 hour and a time slice is written out every 20min."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"ND49 (timeseries) is no wonder the most-used BPCH diagnostics. To replicate the same configuration as the NC diag module above, my `input.geos` file would look like:\n",
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"ND49 (timeseries) is no doubt the most-used BPCH diagnostics. To replicate the same configuration as the NC diag module above, my `input.geos` file would look like:\n",
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"\n",
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"```\n",
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"%%% ND49 MENU %%% :\n",

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