MIdAS bias adjustment of extremes using Theil-Sen extrapolation: Data and plotting scripts for GMD-publication

When bias adjusting climate model data using quantile mapping approaches, one needs to prescribe what to do at the tails of the distribution, where a larger range of data is likely encountered outside the calibration period. The end results is highly dependent on the method used. For the current study, submitted to the journal Geoscientific Model Development, under the name 'Robust handling of extremes in quantile mapping - "Murder your darlings"' by Berg et al. (2024), the MIdAS bias adjustment method is evaluated and extended with additional functionality to deal with issues with bias adjustment of extreme precipitation. This entry contains data for the annual precipitation sums, and annual maximum daily precipitation, for a domain over Scandinavia, including a reference data set and a large ensemble of Euro-CORDEX regional climate models before and after bias adjustment using a range of experiments, as well as scripts for analysing the data and producing the figures of the paper.