A Central European precipitation climatology – Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS)
Rauthe, Monika; Steiner, Heiko; Riediger, Ulf; Mazurkiewicz, Alex; Gratzki, Annegret
A new precipitation climatology (DWD/BfG-HYRAS-PRE) is presented which covers the river basins in Germany and neighbouring countries. In order to satisfy hydrological requirements, the gridded dataset has a high spatial resolution of 1 km2 and a daily temporal resolution that is based on up to 6200 precipitation stations within the spatial domain. The period of coverage extends from 1951 to 2006 for which gridded, daily precipitation fields were calculated from the station data using the REGNIE method. This is a combination between multiple linear regression considering orographical conditions and inverse distance weighting. One of the main attributes of the REGNIE method is the preservation of the station values for their respective grid cells. A detailed validation of the data set using cross-validation and Jackknifing showed both seasonally- and spatially-dependent interpolation errors. These errors, through further applications of the HYRAS data set within the KLIWAS project and other studies, provide an estimate of its certainty and quality. The mean absolute error was found to be less than 2 mm/day, but with both spatial and temporal variability. Additionally, the need for a high station network density was shown. Comparisons with other existing data sets show good agreement, with areas of orographical complexity displaying the largest differences within the domain. These errors are largely due to uncertainties caused by differences in the interpolation method, the station network density available, and the topographical information used. First climatological applications are presented and show the high potential of this new, high-resolution data set. Generally significant increases of up to 40% in winter precipitation and light decreases in summer are shown, whereby the spatial variability of the strength and significance of the trends is clearly illustrated.