CCdownscaling: an Open-Source Python Package for Multivariable Statistical Climate Model Downscaling V1.0

Abstract. Statistical downscaling methods provide an essential bridge between low resolution global climate models and localized information needed by decision makers. As the demand for localized climate information continues to grow to make projections for a wide variety of applications, the need for software that can provide this sort of downscaled data grows with it. The CCdownscaling package described in the article provides a number of downscaling methods, including Self Organizing Maps, as well as a number of evaluation metrics for assessing downscale model skill. In this article, we describe the features of the CCdownscaling package, and show an example use case for downscaling temperature and precipitation. It is open-source and freely available for use in generating downscaled projections.