Linear methods for the statistical transformation of daily precipitation sums from regional climate models

This paper presents two new methods for the linear transformation of climate model precipitation data. For verification of the developed methods, daily precipitation sums from the REMO climate model were transformed to observed data from the meteorological stations in the Malse River basin in the Czech Republic. Both methods are based on an analysis of the gamma distribution. The comparison between the observed and transformed data indicates their suitable applicability. The precipitation amounts of transformed data comply with an equivalent probability distribution as the observed data, a distribution of dry days in time drifts towards realistic values. In addition, the efficiency of the formerly published method for nonlinear transformation and newly introduced linear methods is compared.