Atmospheric forcing

The sflux/ directory is required if nws=2 in param.nml.

There are four types of files needed:

sflux_input.txt (required): a namelist file

sflux_air_1.[XXXX].nc (required): NetCDF files that have time (in days), wind speed at 10m above MSL (u, v), air temperatue and spedific humidity at 2m above MSL, sea level pressure;

sflux_prc_1.[XXXX].nc (needed if isconsv=1): NetCDF files that have time and precipitation rate;

sflux_rad_1.[XXXX].nc (needed if ihconsv=1): NetCDF files that have time, downward longwave and shortwave radiation fluxes.

PySCHISM supports three types of atmpsheric datasets.

Notes: startdate should be one day earlier than the actual run startdate, because there is no data at t00z. Acoordingly, add two more extra days for rnday in the following scripts.

ECMWF ERA5

ERA5 provides hourly estimates of a large number of atmoshperic, land and oceanic climate variables. The data cover the Earth on a 30km grid and resolve the atmoshpere using 137 levels from the surface up to a height of 80km. The dataset covers from 1950 to present. PySCHISM downloads ERA5 data through CDS API service. To do so, you need to install CDS API package. Here is the instruction about how to install the package.

The python script to generate sflux file from ERA5 is as follows:

from datetime import datetime
import pathlib

from pyschism.mesh.hgrid import Hgrid
from pyschism.forcing.nws.nws2.era5 import ERA5

if __name__ == '__main__'
    startdate=datetime(2022, 4, 1)
    rnday = 10
    hgrid=Hgrid.open('./hgrid.gr3',crs='EPSG:4326')
    bbox = hgrid.get_bbox('EPSG:4326', output_type='bbox')
    outdir = pathlib.Path('./')

    er=ERA5()
    er.write(outdir=outdir, start_date=startdate, rnday=rnday, air=True, rad=True, prc=True, bbox=bbox, output_interval=interval, overwrite=True)

GFS

The Global Forecast System (GFS) is weather forecast model produced by the National Centers for Environmental Prediction (NCEP). PySCHISM uses data hosted on AWS S3 bucket.

The python script to generate sflux from GFS is as follows:

from datetime import datetime

from pyschism.mesh.hgrid import Hgrid
from pyschism.forcing.nws.nws2.gfs2 import GFS

if __name__ == '__main__':
    startdate = datetime(2022, 3, 31)
    rnday = 10
    record = 1
    hgrid = Hgrid.open('./hgrid.gr3', crs='epsg:4326')
    pscr = '/sciclone/pscr/lcui01/GFS/'
    gfs = GFS(start_date=startdate, rnday=rnday, pscr=pscr, record=record, bbox=hgrid.bbox)

Parameter startdate should be one day earlier than the actual startdate in the param.nml becasue GFS have nodata at t00, pscr is the pre-generated directory to save dowloaded raw data (grib2), record is to specify how many days in each file. For hindcast, recommend record=1. For forecast, the maximum is 5, because GFS has 5-day forecast.

HRRR

The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model. The AWS archived data starts from August 2014 to present.

The python script to generate sflux from HRRR is as follows:

from datetime import datetime

from pyschism.mesh.hgrid import Hgrid
from pyschism.forcing.nws.nws2.hrrr3 import HRRR

if __name__ == '__main__':
    startdate = datetime(2022, 3, 31)
    rnday = 10
    record = 1
    hgrid = Hgrid.open('../../../data/hgrid.gr3', crs='epsg:4326')
    pscr='/sciclone/pscr/lcui01/HRRR/'

    hrrr = HRRR(start_date=startdate, rnday=rnday, pscr=pscr, record=record, bbox=hgrid.bbox)

Parameter startdate, pscr, and record are defined the same as GFS', except for forecast, the maximum of record for HRRR is 2, because HRRR only has 2-day forecast.