pywasp.wasp.downscale

pywasp.wasp.downscale(gwc, topo_map, output_locs, conf=None, interp_method='nearest', mesoclimate=None, mesoclimate_interp_method='nearest', return_site_effects=False, add_met=True, cfd_volume=None)[source]

Calculate site_effects, downscaled wind climate, and meteorlogical fields in a single step

Parameters:

  • gwc (xarray.Dataset) – Generalized wind climate xr.Dataset to downscale

  • topo_map (TopographyMap) – TopographyMap of the region to model

  • output_locs (xarray.Dataset) – Locations to calculate at created using create_dataset

  • conf (Config) – Configuration information from WAsP

  • interp_method (str, optional) – String indicating interpolation method, by default “nearest”. Options are {“nearest”, “linear”, “cubic”, “natural”, “given”}. If “given”, the function will not interpolate the generalized wind climate, but assumes that the gwc and output_locs have the same spatial structure. If “nearest”, it will use the nearest neighbor interpolation. If “linear”, it will use linear interpolation. If “cubic”, it will use cubic interpolation. If “natural”, it will use natural neighbor interpolation.

  • mesoclimate (xarray.Dataset, default None) – If None use the ERA5 reanalysis to obtain the mesoclimate, otherwise one can create a dataset using the pw.wasp.get_climate() method

  • mesoclimate_interp_method (str, optional) – Interpolation method for mesoclimate, by default ‘nearest’

  • return_site_effects (bool) – Include the site_effects in the output?

  • add_met (bool) – Calculate and include meteorlogical fields from add_met_fields in the output?

  • cfd_volume (xarray.Dataset or list of xarray.Datasets, default None) – WAsP CFD volume xarray dataset that is used for obtaining site effects

Returns:

xarray.Dataset – PyWAsP formated xr.Dataset containing sectorwise A, k, frequency, total A and k at site. Optionally include speedups, rix, elevation and other site_effects, and/or wind speeds, air and power densities.

Notes

Run WAsP’s wprms_nt function to perform the “down” part of the WAsP framework. This will take the generalized data and convert it to a site specific weibull distribution based on the local conditions.