credit.nwp

credit.nwp#

Attributes#

gfs_map

level_map

upper_air

surface

Functions#

build_GFS_init(output_grid, date, variables[, ...])

Download GFS model level initial conditions, regrid to CREDIT model's grid, and vertically interpolate

Module Contents#

credit.nwp.gfs_map#
credit.nwp.level_map#
credit.nwp.upper_air#
credit.nwp.surface#
credit.nwp.build_GFS_init(output_grid: xarray.Dataset, date: pandas.Timestamp, variables: list, model_level_file: str = '', model_levels: numpy.ndarray = None, gdas_base_path: str = 'gs://global-forecast-system/', variable_mapping: str = 'wchapmanera5', n_procs: int = 1)#

Download GFS model level initial conditions, regrid to CREDIT model’s grid, and vertically interpolate 3D variables to CREDIT model levels.

Parameters:

  • output_grid (xr.Dataset) – netCDF file containing latitude and longitude coordinates of CREDIT model grid.

  • date (pd.Timestamp) – date of GFS initialization

  • variables (list) – list of variable names.

  • model_level_file (str) – Path to file containing output model level a and b coefficients on full and half levels.

  • model_levels (np.ndarray) – Subset of model levels to interpolate to.

  • gdas_base_path (str) – Path to GFS base directory on NOMADS (archives last 10 days) or Google Cloud (since 2021)

  • variable_mapping (str)

  • n_procs (int) – Number of processors to use in pool.

Returns:

(xr.Dataset) Interpolated GFS initial conditions