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Merge pull request #104 from raphaeldussin/RGclim_add
expand RG clim notebook with annual and monthly clim of pottemp and salt
2 parents 0f5d29e + 26578d1 commit 3eae1f0

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‎data/RoemmichGilson_ARGO_based_climatology.ipynb‎

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},
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"cell_type": "code",
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"execution_count": null,
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"id": "supposed-essex",
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"metadata": {},
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"outputs": [],
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"import requests\n",
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"import warnings\n",
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"import subprocess as sp\n",
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"import seawater\n",
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"import pandas as pd\n",
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"\n",
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"warnings.filterwarnings(\"ignore\")\n",
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"\n",
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},
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"cell_type": "code",
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"execution_count": null,
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"id": "enabling-sweet",
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"id": "classified-modification",
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"cell_type": "code",
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"execution_count": null,
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"id": "rolled-uniform",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"retrieving RG_ArgoClim_201901_2019.nc.gz\n",
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"retrieving RG_ArgoClim_201902_2019.nc.gz\n",
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]
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}
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],
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"outputs": [],
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"source": [
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"files_ext = []\n",
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"lastyear = 2021\n",
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"id": "australian-villa",
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},
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"cell_type": "code",
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"id": "urban-contact",
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},
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"cell_type": "code",
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"execution_count": null,
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"id": "amber-connection",
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},
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": null,
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"id": "controversial-financing",
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},
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": null,
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"id": "pursuant-tribune",
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"metadata": {},
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"outputs": [],
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"source": [
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"ds.to_netcdf(f\"RG_ArgoClim_Extended_200401-{lastyear}12.nc\", format=\"NETCDF3_64BIT\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6492543e-a4d0-428d-80bb-8ba2f08a0952",
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"metadata": {},
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"source": [
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"## Create Annual and Monthly clim for salt and pot_temp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "691ced23-046c-4810-9809-cb4625d8ab05",
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"metadata": {},
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"outputs": [],
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"source": [
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"# compute potential temperature\n",
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"ptemp = xr.apply_ufunc(seawater.eos80.ptmp,\n",
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" ds[\"ARGO_SALINITY_MEAN\"] + ds[\"ARGO_SALINITY_ANOMALY\"],\n",
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" ds[\"ARGO_TEMPERATURE_MEAN\"] + ds[\"ARGO_TEMPERATURE_ANOMALY\"],\n",
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" ds[\"PRESSURE\"],\n",
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" dask='parallelized',\n",
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" output_dtypes=[ds[\"ARGO_TEMPERATURE_MEAN\"].dtype])\n",
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"\n",
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"# reconstruct salinity (mean + anomaly)\n",
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"salt = ds[\"ARGO_SALINITY_MEAN\"] + ds[\"ARGO_SALINITY_ANOMALY\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "19d1f60b-f918-40c0-b132-5b468ec45fba",
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"metadata": {},
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"outputs": [],
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"source": [
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"# create a more flexible time axis\n",
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"from datetime import timedelta\n",
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"delta = timedelta(days=15)\n",
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"time = pd.date_range(start='2004-01', periods=len(ds[\"TIME\"]), freq=\"1MS\") + delta"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "00a02b81-21bd-485b-a9af-761b33758947",
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"metadata": {},
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"outputs": [],
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"source": [
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"# replace time in arrays\n",
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"ptemp[\"TIME\"] = time\n",
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"salt[\"TIME\"] = time"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2d970b36-1676-4d39-b35a-4b7e789fb726",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Annual climatology\n",
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"ptemp_annual = ptemp.mean(dim=\"TIME\")\n",
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"salt_annual = salt.mean(dim=\"TIME\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "213284e0-0798-4066-932d-639452ebaa6b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Monthly climatology\n",
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"ptemp_monthly = ptemp.groupby(ptemp.TIME.dt.month).mean(dim=\"TIME\")\n",
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"salt_monthly = salt.groupby(salt.TIME.dt.month).mean(dim=\"TIME\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "980e2f0d-80ad-4dc4-a631-17f6e94e9e54",
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"metadata": {},
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"outputs": [],
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"source": [
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"# create a depth array\n",
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"import numpy as np\n",
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"pressure3d = np.broadcast_to(ds[\"PRESSURE\"].values[:, np.newaxis, np.newaxis],\n",
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" (len(ds[\"PRESSURE\"]),\n",
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" len(ds[\"LATITUDE\"]),\n",
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" len(ds[\"LONGITUDE\"])))\n",
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"latitude3d = np.broadcast_to(ds[\"LATITUDE\"].values[np.newaxis, :, np.newaxis],\n",
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" (len(ds[\"PRESSURE\"]),\n",
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" len(ds[\"LATITUDE\"]),\n",
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" len(ds[\"LONGITUDE\"])))\n",
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"\n",
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"depth3d = seawater.eos80.dpth(pressure3d, latitude3d)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7f665c1d-c623-4a19-8ddd-113d92a3af68",
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"metadata": {},
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"outputs": [],
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"source": [
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"annual_clim = xr.Dataset()\n",
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"annual_clim[\"ptemp\"] = ptemp_annual.fillna(1.e+20)\n",
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"annual_clim[\"salt\"] = salt_annual.fillna(1.e+20)\n",
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"annual_clim[\"depth\"] = xr.DataArray(depth3d, dims=(\"PRESSURE\", \"LATITUDE\", \"LONGITUDE\"))\n",
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"\n",
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"annual_clim = annual_clim.rename({\"LONGITUDE\": \"lon\", \n",
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" \"LATITUDE\": \"lat\",\n",
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" \"PRESSURE\": \"pres\"})\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2267e443-2d68-4d5b-8dd0-be327141cca1",
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"metadata": {},
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"outputs": [],
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"source": [
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"monthly_clim = xr.Dataset()\n",
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"monthly_clim[\"ptemp\"] = ptemp_monthly.fillna(1.e+20)\n",
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"monthly_clim[\"salt\"] = salt_monthly.fillna(1.e+20)\n",
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"monthly_clim[\"depth\"] = xr.DataArray(depth3d, dims=(\"PRESSURE\", \"LATITUDE\", \"LONGITUDE\"))\n",
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"\n",
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"monthly_clim = monthly_clim.rename({\"LONGITUDE\": \"lon\", \n",
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" \"LATITUDE\": \"lat\",\n",
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" \"PRESSURE\": \"pres\"})\n",
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"\n",
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"monthly_clim = monthly_clim.transpose(*(\"month\", \"pres\", \"lat\", \"lon\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0fd0618c-2b46-4300-8d76-5fc46eb116c5",
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"metadata": {},
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"outputs": [],
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"source": [
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"annual_clim"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "79759369-4c10-48c7-82c5-9d93856e10da",
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"metadata": {},
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"outputs": [],
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"source": [
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"monthly_clim"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a9db469c-fa3d-41ae-886a-7419ba82e78a",
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"metadata": {},
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"outputs": [],
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"source": [
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"annual_clim.to_netcdf(f\"RG_ArgoClim_Extended_200401-{lastyear}12_annual_clim_ptemp+salt.nc\",\n",
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" encoding = {\"ptemp\": {\"_FillValue\": 1.e+20},\n",
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" \"salt\": {\"_FillValue\": 1.e+20}},\n",
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" format=\"NETCDF3_64BIT\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9c03e734-a6a5-4a0b-8991-3f25983a9cdd",
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"metadata": {},
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"outputs": [],
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"source": [
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"monthly_clim.to_netcdf(f\"RG_ArgoClim_Extended_200401-{lastyear}12_monthly_clim_ptemp+salt.nc\",\n",
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" encoding = {\"ptemp\": {\"_FillValue\": 1.e+20},\n",
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" \"salt\": {\"_FillValue\": 1.e+20}},\n",
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" format=\"NETCDF3_64BIT\", unlimited_dims=\"month\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "P3-om4labs",
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"display_name": "om4labs",
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"language": "python",
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"name": "om4labs"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.6"
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"version": "3.8.12"
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}
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},
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"nbformat": 4,

‎data/checksums_RG_ARGOClim.txt‎

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fb8837b0f2a61f25c16f4f3d2aba5378 RG_ArgoClim_Extended_200401-202112.nc
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49c4ccac20835fc246d04657587c611d RG_ArgoClim_Extended_200401-202112_annual_clim_ptemp+salt.nc
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fa1f0722b68f0971cb44eff952a250b8 RG_ArgoClim_Extended_200401-202112_monthly_clim_ptemp+salt.nc

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