Get CHIRPS-GEFS daily forecast data (16 days)
Automatic extraction of daily CHIRPS-GEFS forecasts. Up to 16 days forecast.
DatasetType: CHIRPS-GEFS_ mean
spatial resolution: 0.05 degrees
Num days forecast: 1 to 16 days
Data extraction methods
Range-based:
ClimateServ_CHIPS-GEFS.bat: Historical data extraction at global scale using the ClimateSERV API https://climateserv.servirglobal.net/
Operational extraction for the Mekong Basin region Domain [minLon: 89, Maxlon: 112, Minlat: 3 , MaxLat:36]
OP_CHIRPS-GEFS_Tiff_NetCDF.bat: Operational forecast for the Mekong region [ format tif and/or NetCDF].
OP_CHIRPS-GEFS_ASCII.bat: Operational forecast for the Mekong region adapted to the FEWS system (http://www.delft-fews.nl/)
requirements
Range-based:
climateserv = 0.0.12
Operational Mekong Basin:
netCDF4 >= 1.4.2
gdal >= 2.3.3
Python pip Installation
Run this command to start installing all python dependencies:
conda env create -f environment.yml
Parameters
ClimateServ_CHIPS-GEFS.bat:
-i [DatasetVariable] CHIRPS_GEFS_precip_mean
-o [Outfile in format.zip]
-b [boundary MinLon,Maxlon,Minlat,Maxlat]
-s [EarliestDate]
-t [LatestDate]
-n [post_netcdf 'yes' ] (optional)
OP_CHIRPS-GEFS_Tiff_NetCDF.bat
-o [Outfile]
-b [boundary]
-f [days_forecast] 1/16 days
-n [postNETCDF] 'yes' (optional)
OP_CHIRPS-GEFS_ASCII.bat
-o [Outfile]
-b [boundary]
-f [days_forecast 1/16 days ]
Examples:
ClimateServ_CHIPS-GEFS.bat:
python bin/ClimateServ_CHIPS-GEFS.py -i CHIRPS_GEFS_precip_mean -o CHIRPS_GEFSrange.zip -b 93,110,9,25 -s '2020-03-10' -t '2020-03-20' -n yes
OP_CHIRPS-GEFS_Tiff_NetCDF.bat
python bin/Op_MK_CHIPS-GEFS.py -o CHIRPS_GEFS -b 93,110,9,25 -f 10
OP_CHIRPS-GEFS_ASCII.bat
python bin/Op_MK_CHIPS-GEFS_ASCII.py -o CHIRPS_GEFS_ascii -b 89,112,3,36 -f 10