Probabilistic downscaling of EURO-CORDEX precipitation data for the assessment of future areal precipitation extremes for hourly to daily durations

Abstract

This work presents a methodology to inspect the changing statistical properties of precipitation extremes with climate change. Data from regional climate models for the European continent (EURO-CORDEX 11) were used. The use of climate model data first requires an inspection of the data and a correction of the biases of the meteorological model. Corrections to the biases of the point precipitation data and those of the spatial structure were both performed. For this purpose, a quantile–quantile transformation of the point precipitation data and a spatial recorrelation method were used. Once corrected for bias, the data from the regional climate model were downscaled to a finer spatial scale using a stochastic method with equally probable outcomes. This allows for the assessment of the corresponding uncertainties. The downscaled fields were used to derive area–depth–duration–frequency (ADDF) curves and areal reduction factors (ARFs) for selected regions in Germany. The estimated curves were compared to those derived from a reference weather radar dataset. While the corrected and downscaled data show good agreement with the observed reference data over all temporal and spatial scales, the future climate simulations indicate an increase in the estimated areal rainfall depth for future periods. Moreover, the future ARFs for short durations and large spatial scales increase compared to the reference value, while for longer durations the difference is smaller.