xsdba: Statistical Downscaling and Bias Adjustment library¶

Statistical correction and bias adjustment tools for xarray.

Features¶

The xsdba submodule provides a collection of bias-adjustment methods meant to correct for systematic biases found in climate model simulations relative to observations. Almost all adjustment algorithms conform to the train - adjust scheme, meaning that adjustment factors are first estimated on training data sets, then applied in a distinct step to the data to be adjusted. Given a reference time series (ref), historical simulations (hist) and simulations to be adjusted (sim), any bias-adjustment method would be applied by first estimating the adjustment factors between the historical simulation and the observation series, and then applying these factors to sim`, which could be a future simulation:
Time grouping (months, day of year, season) can be done within bias adjustment methods.
Properties and measures utilities can be used to assess the quality of adjustments.

xsdba can be installed from PyPI:

$ pip install xsdba

The official documentation is at https://xsdba.readthedocs.io/

xsdba was first developed as the submodule sdba of xclim. A migration guide is available for users of sdba.

This package was created with Cookiecutter and the Ouranosinc/cookiecutter-pypackage project template.