hydromt_delft3dfm.workflows.compute_meteo_forcings#

hydromt_delft3dfm.workflows.compute_meteo_forcings(df_meteo: ~pandas.core.frame.DataFrame = None, fill_value: float = 0.0, is_rate: bool = True, meteo_location: tuple = None, logger=<Logger hydromt_delft3dfm.workflows.boundaries (WARNING)>) → DataArray[source]#

Compute meteo forcings.

Parameters:

  • df_meteo (pd.DataFrame, optional) –

    pd.DataFrame containing the meteo timeseries values. If None, uses fill_value.

    • Required variables: [“precip”]

  • meteo_value (float, optional) – Constant value to use for global meteo if df_meteo is None and to fill in missing data in df_meteo. By default 0.0 mm/day.

  • is_rate (bool, optional) – Specify if the type of meteo data is direct “rainfall” (False) or “rainfall_rate” (True). By default True for “rainfall_rate”. Note that Delft3DFM 1D2D Suite 2022.04 supports only “rainfall_rate”. If rate, unit is expected to be in mm/day and else mm.

  • meteo_location (tuple) – Global location for meteo timeseries

  • logger – Logger to log messages.

Returns:

da_meteo – xr.DataArray containing the meteo timeseries values. If None, uses df_meteo.

  • Required variables if netcdf: [precip]

Return type:

xr.DataArray