Large biases and inconsistent climate change signals in ENSEMBLES regional projections

In this paper we analyze some caveats found in the state-of-the-art ENSEMBLES regional projections dataset focusing on precipitation over Spain, and highlight the need of a task-oriented validation of the GCM-driven control runs. In particular, we compare the performance of the GCM-driven control runs (20C3M scenario) with the ERA40-driven ones (>perfect> boundary conditions) in a common period (1961-2000). Large deviations between the results indicate a large uncertainty/bias for the particular RCM-GCM combinations and, hence, a small confidence for the corresponding transient simulations due to the potential nonlinear amplification of biases. Specifically, we found large biases for some RCM-GCM combinations attributable to RCM in-house problems with the particular GCM coupling. These biases are shown to distort the corresponding climate change signal, or >delta>, in the last decades of the 21st century, considering the A1B scenario. Moreover, we analyze how to best combine the available RCMs to obtain more reliable projections. © 2013 Springer Science+Business Media Dordrecht.This work was supported by esTcena (Exp. 200800050084078) and EXTREMBLES (CGL2010-21869) projects, from Plan Nacional de I+D+i 2008–2011. For the RCM data used in this study, we acknowledge the ENSEMBLES project, funded by the European Commission’s 6th Framework Programme through contract GOCE-CT-2003-505539.Peer Reviewe