credit.nwp#
Attributes#
Functions#
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Create GFS initial conditions on model levels that are interpolated from ECMWF L137 model levels. |
Derive pressure and geopotential fields from model level data and to dataset |
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Create NOMADS filepaths for etiher upper air or surface data |
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Load GFS data directly from Nomads or Google Cloud server |
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Merge upper air and surface data |
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Spatially regrid (interpolate) from GFS grid to CREDIT grid |
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Verticallly interpolate GFS model level data to CREDIT model levels |
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Format data for CREDIT model ingestion |
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Format datetime string from CREDIT configuration file |
Module Contents#
- credit.nwp.gfs_map#
- credit.nwp.level_map#
- credit.nwp.upper_air = ['T', 'U', 'V', 'Q', 'Z']#
- credit.nwp.surface = ['SP', 't2m']#
- credit.nwp.build_GFS_init(output_grid, date, variables, model_level_indices, gdas_base_path='https://nomads.ncep.noaa.gov/pub/data/nccf/com/gfs/prod/')#
Create GFS initial conditions on model levels that are interpolated from ECMWF L137 model levels. :param output_grid: grid of ERA5 model levels :type output_grid: xr.DataArray :param date: date of GFS initialization :type date: pd.Timestamp :param variables: list of variable names :type variables: list :param model_level_indices: list of model level indices to extract from L137 model levels :type model_level_indices: list :param gdas_base_path: Path to GFS base directory on NOMADS (archives last 10 days) or Google Cloud (since 2021) :type gdas_base_path: str
- Returns:
(xr.Dataset) Interpolated GFS initial conditions
- credit.nwp.add_pressure_and_geopotntial(data)#
Derive pressure and geopotential fields from model level data and to dataset :param data: (xr.Dataset) GFS model level data
- Returns:
xr.Dataset
- credit.nwp.build_file_path(date, base_path, file_type='atm')#
Create NOMADS filepaths for etiher upper air or surface data :param date: (pd.Timestamp) date of GFS initialization :param base_path: (str) NOMADS base directory (archives last 10 days) :param file_type: (str) Type of analysis data (supports ‘atm’ or ‘sfc’)
- Returns:
(str) NOMADS filepaths
- credit.nwp.load_gfs_data(full_file_path, variables)#
Load GFS data directly from Nomads or Google Cloud server :param full_file_path: (str) NOMADS filepath :param variables: (list) list of variable names
- Returns:
xr.Dataset
- credit.nwp.combine_data(atm_data, sfc_data)#
Merge upper air and surface data :param atm_data: (xr.Dataset) GFS upper air data :param sfc_data: (xr.Dataset) GFS surface data
- Returns:
xr.Dataset
- credit.nwp.regrid(nwp_data, output_grid, method='conservative')#
Spatially regrid (interpolate) from GFS grid to CREDIT grid :param nwp_data: (xr.Dataset) GFS initial conditions :param output_grid: (xr.Dataset) CREDIT grid :param method: (str)
- Returns:
(xr.Dataset) Regridded GFS initial conditions
- credit.nwp.interpolate_to_model_level(regridded_nwp_data, output_grid, model_level_indices, variables)#
Verticallly interpolate GFS model level data to CREDIT model levels :param regridded_nwp_data: (xr.Dataset) GFS initial conditions on CREDIT grid :param output_grid: (xr.Dataset) CREDIT Grid :param model_level_indices: (list) list of model level indices to extract from L137 model levels :param variables: (list) list of variable names
- Returns:
Dictionary of xr.DataArrays of interpolated GFS model level data
- Return type:
(dict)
- credit.nwp.format_data(data_dict, regridded_data, model_levels)#
Format data for CREDIT model ingestion :param data_dict: (dict) Dictionary of xr.DataArrays of interpolated GFS model level data :param regridded_data: (xr.Dataset) GFS initial conditions on CREDIT grid :param model_levels: (list) list of model level indices to extract from L137 model levels
- Returns:
xr.Dataset of GFS initial conditions interpolated to CREDIT grid and model levels
- credit.nwp.format_datetime(init_time)#
Format datetime string from CREDIT configuration file :param init_time: (dict) Dictionary of Forecast times from configuration file
- Returns:
pd.Timestamp of initialization time