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Statistical correction and bias adjustment tools for xarray.
- Free software: Apache Software License 2.0
- Documentation: https://xsdba.readthedocs.io.
- 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/
How to make the most of xsdba: Basic Usage Examples and In-Depth Examples.
This package was created with Cookiecutter and the Ouranosinc/cookiecutter-pypackage project template.