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DownscaleR: An R-based package for statistical downscaling and bias correction within the climate4R framework

The climate4R bundle of R packages provides a unique framework for climate harmonized data access, collocation and post-processing, where most common tasks can be straightforwardly performed using a few lines of code. This allows end-to-end experimental reproducibility and facilitates the description (metadata) and documentation of the whole data flow. Bias correction is one of those tasks and is performed by using the downscaleR package, which implements parametric and non-parametric methods for bias correction and allows for a fine tunning of different configurations. An additional element of climate4R is the User Data Gateway (UDG), a data service providing free access to a variety of state-of-the-art datasets. Here we introduce the climate4R ecosystem and illustrate the main functionalities through a fully reproducible practical case over the Iberian Peninsula, describing the calculation of typical climate indices from an ensemble of future regional climate projections (EURO-CORDEX) and the sensitivity to bias correction including the potential reduction of uncertainty.