V12Cdev

Climatologies/MVR/download_data.py

@@ -0,0 +1,16 @@
+import copernicusmarine
+
+# no more ppn
+
+copernicusmarine.subset(
+  dataset_id="cmems_mod_med_bgc_my_4.2km-climatology_P1M-m",
+  variables=["chl_avg", "chl_std", "no3_avg", "no3_std", "o2_avg", "o2_std"],
+  minimum_longitude=-5.541666507720947,
+  maximum_longitude=36.29166793823242,
+  minimum_latitude=30.1875,
+  maximum_latitude=45.97916793823242,
+  start_datetime="1999-01-01T00:00:00",
+  end_datetime="1999-12-01T00:00:00",
+  minimum_depth=1.0182366371154785,
+  maximum_depth=4152.89599609375,
+)

Climatologies/MVR/launcher.sh

@@ -0,0 +1,75 @@
+#! /bin/bash
+
+#SBATCH --job-name=Cl_CMEMS
+#SBATCH -N1
+#SBATCH --ntasks-per-node=16
+#SBATCH --time=00:20:00
+#SBATCH --mem=300gb
+#SBATCH --account=OGS_test2528
+#SBATCH --partition=g100_meteo_prod
+#SBATCH --qos=qos_meteo
+
+. ../../profile.inc
+module load autoload
+module load intel/oneapi-2021--binary
+module load intelmpi/oneapi-2021--binary
+module load mkl/oneapi-2021--binary
+module load netcdf/4.7.4--oneapi--2021.2.0-ifort
+module load netcdff/4.5.3--oneapi--2021.2.0-ifort
+source /g100_work/OGS23_PRACE_IT/COPERNICUS/py_env_3.9.18_new/bin/activate
+
+INPUTDIR="/g100_scratch/userexternal/gbolzon0/V12C/MVR"
+OUTDIR="/g100_scratch/userexternal/gbolzon0/V12C/MVR/OUTPUT"
+INPUTFILE=$INPUTDIR/cmems_mod_med_bgc_my_4.2km-climatology_P1M-m_multi-vars_5.54W-36.29E_30.19N-45.98N_1.02-4152.90m_1999-01-01-1999-12-01.nc
+
+mkdir -p $OUTDIR
+
+#if [ ! -f "$INPUTFILE" ]; then
+#    python download_data.py
+#else
+#    echo "File $INPUTFILE already exists. Skipping download."
+#fi
+MASKFILE="/g100_work/OGS_prodC/OPA/Interim-dev/etc/static-data/MED24_125/meshmask.nc"
+
+my_prex_or_die "python netcdf_clim_generator.py -i $INPUTFILE -o $OUTDIR -v o2_avg  --least_significant_digit 2 -m $MASKFILE"
+my_prex_or_die "python netcdf_clim_generator.py -i $INPUTFILE -o $OUTDIR -v no3_avg --least_significant_digit 3 -m $MASKFILE"
+my_prex_or_die "python netcdf_clim_generator.py -i $INPUTFILE -o $OUTDIR -v chl_avg  --least_significant_digit 4 -m $MASKFILE"
+exit 0
+
+
+OUTPUT_DIR=3D_LINKS
+mkdir -p $OUTPUT_DIR
+
+for YEAR in {2024..2025}; do
+    # Ciclo sulle variabili CHL, O2, NO3
+    for VAR in CHL O2 NO3; do
+        # Assegna il nome corretto della variabile a vv
+        if [[ "$VAR" == "CHL" ]]; then
+            vv="P_l"
+        elif [[ "$VAR" == "O2" ]]; then
+            vv="O2o"
+        else
+            vv="N3n"
+        fi
+
+        INPUT_DIR="${VAR}_CLIM"  # Supponendo che le cartelle siano CHL_CLIM, O2_CLIM, NO3_CLIM
+
+        # Controlla se la cartella esiste prima di procedere
+        if [[ -d "$INPUT_DIR" ]]; then
+            for file in "$INPUT_DIR"/ave.yyyy*15-00:00:00.${vv}.nc; do
+                # Controlla se il file esiste per evitare errori
+                [[ -e "$file" ]] || continue
+
+                filename=$(basename "$file")
+
+		MM=${filename:8:2}  # Estrai il mese dal nome del file
+		#echo "Filename: $filename, Estratto MM: $MM"
+                new_filename="ave.${YEAR}${MM}15-00:00:00.${vv}.nc"
+		ln -s "$(realpath --relative-to="$OUTPUT_DIR" "$file")" "$OUTPUT_DIR/$new_filename"
+
+            done
+        fi
+    done
+done
+
+#o2_std no3_std chl_std

Climatologies/MVR/netcdf_clim_generator.py

@@ -0,0 +1,64 @@
+import xarray as xr
+import numpy as np
+import argparse
+from bitsea.commons.mask import Mask
+from bitsea.utilities.argparse_types import existing_dir_path, existing_file_path
+
+
+# Parsing command-line arguments
+parser = argparse.ArgumentParser(description="Adjust coordinates in NetCDF files.")
+parser.add_argument('-i', '--input',    type=existing_file_path, required=True, help="Input NetCDF file")
+parser.add_argument('-o', '--outdir',   type=existing_dir_path, required=True, help="string for output directory")
+parser.add_argument('-v', '--variable', type=str, required=True, choices=['chl_avg', 'no3_avg', 'o2_avg'], help="variable NetCDF file")
+parser.add_argument('-m', '--maskfile', type=existing_file_path, required=True, help="meshmask file")
+parser.add_argument('-d', '--least_significant_digit', type=int, required=False, default=0, help="least significant digit for compression")
+args = parser.parse_args()
+
+VAR=args.variable
+
+VARMOD={
+    'chl_avg':'P_l',
+    'no3_avg':'N3n',
+    'o2_avg':'O2o'
+}
+varmod=VARMOD[VAR]
+if args.least_significant_digit == 0:
+    least_significant_digit = None
+else:
+    least_significant_digit = args.least_significant_digit
+
+TheMask = Mask.from_file(args.maskfile)
+jpk,jpi,jpj = TheMask.shape
+
+with xr.open_dataset(args.input) as ds:
+    var = ds.variables[VAR][:]
+fill_value = 1.e+20
+
+
+for month in range(12):
+    fileout = args.outdir / f"ave.yyyy{month+1:02d}15-00:00:00.{varmod}.nc"
+    print(f"Saving to {fileout} with least_significant_digit = {least_significant_digit}", flush=True)
+    cmems_clim = var[month,:,:,:]
+
+    new_data = np.full(TheMask.shape, fill_value, dtype=np.float32)
+    new_data[:,:,80:] = cmems_clim.values
+
+    new_ds = xr.Dataset(
+            {varmod: (["depth", "latitude", "longitude"], new_data)},
+        coords={
+            "longitude": (["longitude"], TheMask.lon),
+            "latitude": (["latitude"], TheMask.lat),
+            "depth": (["depth"], TheMask.zlevels),
+        }
+    )
+
+    new_ds.to_netcdf(fileout,
+                     encoding={varmod:{ 
+                         "zlib":True,  
+                         "_FillValue": fill_value, 
+                         "complevel": 9, 
+                         "least_significant_digit": least_significant_digit,
+                         }
+                         }
+                     )
+    new_ds.close()