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Climatology #140

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0f8dd54
add month2season12 and N
jukent Oct 22, 2024
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jukent Oct 29, 2024
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175 changes: 161 additions & 14 deletions ncl/ncl_entries/climatology_functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -16,10 +16,15 @@
"\n",
"- [calcDayAnomTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/calcDayAnomTLL.shtml)\n",
"- [calcMonAnomTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/calcMonAnomTLL.shtml)\n",
"- [clmDayHourTll](https://www.ncl.ucar.edu/Document/Functions/Contributed/clmDayHourTLL.shtml)\n",
"- [clmDayTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/clmDayTLL.shtml)\n",
"- [clmMon2clmDay](https://www.ncl.ucar.edu/Document/Functions/Contributed/clmMon2clmDay.shtml)\n",
"- [clmMonTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/clmMonTLL.shtml)\n",
"- [month_to_season](https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_season.shtml)\n",
"- [month_to_season12](https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_season12.shtml)\n",
"- [month_to_seasonN](https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_seasonN.shtml)\n",
"- [rmMonAnnCycTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/rmMonAnnCycTLL.shtml)\n",
"- [smthClmDayTll](https://www.ncl.ucar.edu/Document/Functions/Contributed/smthClmDayTLL.shtml)\n",
"- [stdMonTLL](https://www.ncl.ucar.edu/Document/Functions/Contributed/stdMonTLL.shtml)\n"
]
},
Expand All @@ -28,7 +33,7 @@
"metadata": {},
"source": [
"## calcDayAnomTLL\n",
"`calcDayAnomTLL` calculates daily anomalies from a daily data climatology"
"`calcDayAnomTLL` calculates daily anomalies from a daily data climatology."
]
},
{
Expand Down Expand Up @@ -64,7 +69,7 @@
"metadata": {},
"source": [
"## calcMonAnomTLL\n",
"`calcMonAnomTLL` calculates monthly anomalies by subtracting the long-term mean from each point"
"`calcMonAnomTLL` calculates monthly anomalies by subtracting the long-term mean from each point."
]
},
{
Expand Down Expand Up @@ -96,12 +101,34 @@
"calcMonAnomTLL[0, :, :].plot();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## clmDayHourTll\n",
"`clmDayHourTll` calculates climatological day-hour means at user specified hours for each day of the year."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab and Go"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## clmDayTLL\n",
"`clmDayTLL` calculates long-term daily means (daily climatology) from daily data"
"`clmDayTLL` calculates long-term daily means (daily climatology) from daily data."
]
},
{
Expand Down Expand Up @@ -131,12 +158,34 @@
"plt.ylabel(\"sea ice area\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## clmMon2clmDay\n",
"`clmMon2clmDay` creates a daily climatology from a monthly climatology.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab and Go"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## clmMonTLL\n",
"`clmMonTLL` calculates long-term monthly means (monthly climatology) from monthly data"
"`clmMonTLL` calculates long-term monthly means (monthly climatology) from monthly data."
]
},
{
Expand Down Expand Up @@ -173,7 +222,7 @@
"metadata": {},
"source": [
"## month_to_season\n",
"`month_to_season` computes a user-specified three-month seasonal mean (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ)\n",
"`month_to_season` computes a user-specified three-month seasonal mean (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ).\n",
"\n",
"```{note}\n",
"You can do something similar with directly with Xarray as shown in [this example in the Xarray documentation](https://docs.xarray.dev/en/stable/examples/monthly-means.html#Calculating-Seasonal-Averages-from-Time-Series-of-Monthly-Means). However, it requires substantially more code and doesn't have as much flexibility with respect to how the seasons are defined.\n",
Expand Down Expand Up @@ -210,12 +259,92 @@
"plt.title(\"2010 seasonal mean\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## month_to_season12\n",
"\n",
"`month_to_season12` computes three-month seasonal means (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab and Go"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import geocat.datafiles as gdf\n",
"from geocat.comp import month_to_season\n",
"\n",
"ds = xr.open_dataset(\n",
" gdf.get(\"applications_files/inputs/CMIP6_sea_ice_monthly_subset.nc\")\n",
")\n",
"aice = ds.aice\n",
"\n",
"month_to_season12 = {}\n",
"for month in [\"DJF\", \"JFM\", \"FMA\", \"MAM\", \"AMJ\", \"MJJ\", \"JJA\", \"JAS\", \"ASO\", \"SON\", \"OND\", \"NDJ\"]:\n",
" mon_to_season = month_to_season(aice, month)\n",
" mon_to_season = mon_to_season.assign_attrs(long_name=\"sea ice area\")\n",
" month_to_season12[month] = mon_to_season\n",
"\n",
"month_to_season12"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## month_to_seasonN\n",
"\n",
"`month_to_seasonN` computes a user-specified list of three-month seasonal means (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ). "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab and Go"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import xarray as xr\n",
"import geocat.datafiles as gdf\n",
"from geocat.comp import month_to_season\n",
"\n",
"ds = xr.open_dataset(\n",
" gdf.get(\"applications_files/inputs/CMIP6_sea_ice_monthly_subset.nc\")\n",
")\n",
"aice = ds.aice\n",
"\n",
"month_to_season12 = {}\n",
"for month in [\"DJF\", \"MAM\", \"JJA\", \"SON\"]:\n",
" mon_to_season = month_to_season(aice, month)\n",
" mon_to_season = mon_to_season.assign_attrs(long_name=\"sea ice area\")\n",
" month_to_season12[month] = mon_to_season\n",
"\n",
"month_to_season12"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## rmMonAnnCycTLL\n",
"`rmMonAnnCycTLL` removes the annual cycle from monthly data"
"`rmMonAnnCycTLL` removes the annual cycle from monthly data."
]
},
{
Expand Down Expand Up @@ -247,12 +376,35 @@
"plt.ylabel(\"sea ice area\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## smthClmDayTll\n",
"\n",
"`smthClmDayTll` calculates a smooth mean daily annual cycle for an array.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Grab and Go"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## stdMonTLL\n",
"`stdMonTLL` calculates standard deviations of monthly means"
"`stdMonTLL` calculates standard deviations of monthly means."
]
},
{
Expand Down Expand Up @@ -299,16 +451,11 @@
"- Project Pythia Foundations [Computations and Masks with Xarray tutorial](https://foundations.projectpythia.org/core/xarray/computation-masking.html)\n",
"- Xarray User Guide [section on time series data](https://docs.xarray.dev/en/stable/user-guide/time-series.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "geocat-applications",
"language": "python",
"name": "python3"
},
Expand All @@ -322,7 +469,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
"version": "3.12.5"
}
},
"nbformat": 4,
Expand Down
2 changes: 2 additions & 0 deletions ncl/ncl_index/ncl-index-table.csv
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Expand Up @@ -16,6 +16,8 @@ NCL Function,Description,Python Equivalent,Notes
`clmDayTLL <https://www.ncl.ucar.edu/Document/Functions/Contributed/clmDayTLL.shtml>`__,"Calculates long-term daily means (daily climatology) from daily data","``xarray.DataArray.groupby()``",`example notebook <../ncl_entries/climatology_functions.ipynb#clmdaytll>`__
`clmMonTLL <https://www.ncl.ucar.edu/Document/Functions/Contributed/clmMonTLL.shtml>`__,"Calculates long-term monthly means (monthly climatology) from monthly data","``xarray.DataArray.groupby()``",`example notebook <../ncl_entries/climatology_functions.ipynb#clmmontll>`__
`month_to_season <https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_season.shtml>`__,"Computes a user-specified three-month seasonal mean","``geocat.comp.month_to_season()``",`example notebook <../ncl_entries/climatology_functions.ipynb#month-to-season>`__
`month_to_season12 <https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_season12.shtml>`__,"Computes three-month seasonal means (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ).","``geocat.comp.month_to_season()``",`example notebook <../ncl_entries/climatology_functions.ipynb#month-to-season>`__
`month_to_seasonN <https://www.ncl.ucar.edu/Document/Functions/Contributed/month_to_seasonN.shtml>`__,"Computes a user-specified list of three-month seasonal means (DJF, JFM, FMA, MAM, AMJ, MJJ, JJA, JAS, ASO, SON, OND, NDJ).","``geocat.comp.month_to_season()``",`example notebook <../ncl_entries/climatology_functions.ipynb#month-to-season>`__
`rmMonAnnCycTLL <https://www.ncl.ucar.edu/Document/Functions/Contributed/rmMonAnnCycTLL.shtml>`__,"Removes the annual cycle from monthly data","``xarray.DataArray.groupby()``",`example notebook <../ncl_entries/climatology_functions.ipynb#rmmonanncyctll>`__
`stdMonTLL <https://www.ncl.ucar.edu/Document/Functions/Contributed/stdMonTLL.shtml>`__,"Calculates standard deviations of monthly means","``xarray.DataArray.groupby()``",`example notebook <../ncl_entries/climatology_functions.ipynb#stdmontll>`__
`abs <https://www.ncl.ucar.edu/Document/Functions/Built-in/abs.shtml>`__,"Returns the absolute value of numeric data","``abs()`` or ``numpy.abs()``",`example notebook <../ncl_entries/general_applied_math.ipynb#abs-fabs>`__
Expand Down