Articles | Volume 16, issue 22
https://doi.org/10.5194/gmd-16-6479-2023
https://doi.org/10.5194/gmd-16-6479-2023
Model description paper
 | 
14 Nov 2023
Model description paper |  | 14 Nov 2023

pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information

Daniel Boateng and Sebastian G. Mutz

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Short summary
We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.