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In hydrological climate-change impact studies, regional climate models(RCMs) are commonly used to transfer large-scale global climate model (GCM)data to smaller scales and to provide more detailed regional information.Due to systematic and random model errors, however, RCM simulations oftenshow considerable deviations from observations. This has led to thedevelopment of a number of correction approaches that rely on the assumptionthat RCM errors do not change over time. It is in principle not possible totest whether this underlying assumption of error stationarity is actuallyfulfilled for future climate conditions. In this study, however, wedemonstrate that it is possible to evaluate how well correction methodsperform for conditions different from those used for calibration with therelatively simple differential split-sample test.  For five Swedish catchments, precipitation and temperature simulations from15 different RCMs driven by ERA40 (the 40 yr reanalysis product of the European Centre forMedium-Range Weather Forecasts (ECMWF)) were corrected with differentcommonly used bias correction methods. We then performed differentialsplit-sample tests by dividing the data series into cold and warm respectivedry and wet years. This enabled us to cross-evaluate the performance ofdifferent correction procedures under systematically varying climateconditions. The differential split-sample test identified major differencesin the ability of the applied correction methods to reduce model errors andto cope with non-stationary biases. More advanced correction methodsperformed better, whereas large deviations remained for climate modelsimulations corrected with simpler approaches. Therefore, we question theuse of simple correction methods such as the widely used delta-changeapproach and linear transformation for RCM-based climate-change impactstudies. Instead, we recommend using higher-skill correction methods such asdistribution mapping

Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions?