Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments
Judith Meyer, Irene Kohn, Kerstin Stahl, Kirsti Hakala, Jan Seibert, Alex J Cannon
Hydrology and Earth System Sciences | Copernicus Publications | Published : 2019
Alpine catchments show a high sensitivity to climate variation as they include the elevation range of the snow line. Therefore, the correct representation of climate variables and their interdependence is crucial when describing or predicting hydrological processes. When using climate model simulations in hydrological impact studies, forcing meteorological data are usually downscaled and bias corrected, most often by univariate approaches such as quantile mapping of individual variables, neglecting the relationships that exist between climate variables. In this study we test the hypothesis that the explicit consideration of the relation between air temperature and precipitation will affect h..View full abstract
Work for this study was based on data acquired and methods developed within the project "The snow and glacier melt components of the streamflow of the River Rhine and its tributaries considering the influence of climate change" (ASG-Rhein, see Stahl et al., 2017) funded by the International Commission for the Hydrology of the Rhine basin (CHR). We thank Urs Beyerle for his assistance with the retrieval of EURO-CORDEX data and further thank all data providers (see Data availability). The article processing charge was funded by the German Research Foundation (DFG) and the University of Freiburg in the funding programme Open Access Publishing. Valuable comments by the editor and the reviewers helped to improve the paper.