pynldas2.pynldas2

Get hourly NLDAS2 forcing data.

Module Contents

pynldas2.pynldas2.get_bycoords(coords, start_date, end_date, coords_id=None, crs=4326, variables=None, to_xarray=False, n_conn=4, snow=False, snow_params=None, source='grib')

Get NLDAS-2 climate forcing data for a list of coordinates.

Parameters:

• coords (list of tuples) – List of (lon, lat) coordinates.

• start_date (str) – Start date of the data.

• end_date (str) – End date of the data.

• crs (str, int, or pyproj.CRS, optional) – The CRS of the input coordinates, defaults to EPSG:4326.

• variables (str or list of str, optional) – Variables to download. If None, all variables are downloaded. Valid variables are: prcp, pet, temp, wind_u, wind_v, rlds, rsds, and humidity (and psurf if source=netcdf)

• to_xarray (bool, optional) – If True, the data is returned as an xarray dataset.

• n_conn (int, optional) – Number of parallel connections to use for retrieving data, defaults to 4. The maximum number of connections is 4, if more than 4 are requested, 4 connections will be used.

• snow (bool, optional) – Compute snowfall from precipitation and temperature. Defaults to False.

• snow_params (dict, optional) – Model-specific parameters as a dictionary that is passed to the snowfall function. These parameters are only used if snow is True. Two parameters are required: t_rain (deg C) which is the threshold for temperature for considering rain and t_snow (deg C) which is the threshold for temperature for considering snow. The default values are {'t_rain': 2.5, 't_snow': 0.6} that are adopted from https://doi.org/10.5194/gmd-11-1077-2018.

• source ({"grib", "netcdf"}, optional) – Source to pull data rods from. Valid sources are: grib and netcdf.

Returns:

pandas.DataFrame – The requested data as a dataframe.

Return type:

pandas.DataFrame | xarray.Dataset

pynldas2.pynldas2.get_bygeom(geometry, start_date, end_date, geo_crs, variables=None, n_conn=4, snow=False, snow_params=None, source='grib')

Get hourly NLDAS-2 climate forcing within a geometry at 0.125 resolution.

Parameters:

• geometry (shapely.Polygon, shapely.MultiPolygon, or tuple of length 4) – Input polygon or a bounding box like so (xmin, ymin, xmax, ymax).

• start_date (str) – Start date of the data.

• end_date (str) – End date of the data.

• geo_crs (int, str, or pyproj.CRS) – CRS of the input geometry

• variables (str or list of str, optional) – Variables to download. If None, all variables are downloaded. Valid variables are: prcp, pet, temp, wind_u, wind_v, rlds, rsds, and humidity (and psurf if source=netcdf)

• n_conn (int, optional) – Number of parallel connections to use for retrieving data, defaults to 4. It should be less than 4.

• snow (bool, optional) – Compute snowfall from precipitation and temperature. Defaults to False.

• snow_params (dict, optional) – Model-specific parameters as a dictionary that is passed to the snowfall function. These parameters are only used if snow is True. Two parameters are required: t_rain (deg C) which is the threshold for temperature for considering rain and t_snow (deg C) which is the threshold for temperature for considering snow. The default values are {'t_rain': 2.5, 't_snow': 0.6} that are adopted from https://doi.org/10.5194/gmd-11-1077-2018.

• source ({"grib", "netcdf"}, optional) – Source to pull data rods from. Valid sources are: grib and netcdf.

Returns:

xarray.Dataset – The requested forcing data.

Return type:

xarray.Dataset

pynldas2.pynldas2.get_grid_mask()

Get the NLDAS-2 grid that contains the land/water/soil/vegetation mask.

Returns:

xarray.Dataset – The grid mask.