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Aristeidis G. Koutroulis, Aggeliki-Eleni K. Vrohidou, and Ioannis K. Tsanis

, earth science ( Ware et al. 1991 ; Ashraf et al. 1997 ; Cheng 1998 ), etc., and is commonly applied to estimate average precipitation and interpolate unknown rainfall ( Chang et al. 2005 ). Even though IDW is a dated method, recent techniques for precipitation interpolation (e.g., Teegavarapu et al. 2009 ) have not managed to dramatically improve its results. Palmer et al. (2009) compared ordinary kriging (OK), regression kriging (RK), and IDW interpolation techniques, resulting in similar

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Lukas Gudmundsson, Lena M. Tallaksen, Kerstin Stahl, Douglas B. Clark, Egon Dumont, Stefan Hagemann, Nathalie Bertrand, Dieter Gerten, Jens Heinke, Naota Hanasaki, Frank Voss, and Sujan Koirala

observations, but also investigate the behavior of the mean of all models, commonly referred to as the ensemble mean. Being widely applied in atmospheric science (e.g., Reichler and Kim 2008 ; Hagedorn et al. 2005 ; Palmer et al. 2004 ), so-called ensemble techniques are also increasingly used in the evaluation of large-scale hydrological models. So far most studies that employed ensemble techniques in the context of large-scale hydrological modeling have focused on the mean annual cycle of monthly

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Kerstin Stahl, Lena M. Tallaksen, Lukas Gudmundsson, and Jens H. Christensen

. The term “poor man” refers to the method of dynamical downscaling from a larger-scale reanalysis. Berg and Christensen (2008) used the Danish RCM HIRHAM5 [the model name HIRHAM (version 5) comes from combining the High-Resolution Limited-Area Model (HIRLAM) and the German “ECHAM” Model], which was nested into the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ERA Interim reanalysis data ( Uppala et al. 2005 ) for a domain covering most of Europe at a

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Stefan Hagemann, Cui Chen, Jan O. Haerter, Jens Heinke, Dieter Gerten, and Claudio Piani

dataset covers the period 1958–2001 and is based on the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40; Uppala et al. 2005 ). The ERA-40 data were interpolated to 0.5° and only considered over land points using the land–sea mask from the Climate Research Unit dataset TS2.1 (CRU; Mitchell and Jones 2005 ). A correction for elevation differences between ERA-40 and CRU was applied. For 2-m temperatures, a correction of the monthly means with CRU data was performed

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