Abstract: Model Output Statistics (MOS) has been recently proposed as an alternative to the standard perfect prognosis statistical downscaling approach for Regional Climate Model (RCM) outputs. In this case, the model output for the variable of interest (e.g. precipitation) is directly downscaled using observations. In this paper we test the performance of a MOS implementation of the popular analog methodology (referred to as MOS analog) applied to downscale daily precipitation outputs over Spain. To this aim, we consider the state-of-the-art ERA40-driven RCMs provided by the EU-funded ENSEMBLES project and the Spain02 gridded observations data set, using the common period 1961?2000. The MOS analog method improves the representation of the mean regimes, the annual cycle, the frequency and the extremes of precipitation for all RCMs, regardless of the region and the model reliability (including relatively low-performing models), while preserving the daily accuracy. The good performance of the method in this complex climatic region suggests its potential transferability to other regions. Furthermore, in order to test the robustness of the method in changing climate conditions, a cross-validation in driest or wettest years was performed. The method improves the RCM results in both cases, especially in the former.

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