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Large biases and inconsistent climate change signals in ENSEMBLES regional projections

Abstract

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.

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Acknowledgements

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. The authors thank AEMET and UC for the data provided for this work (Spain02 gridded precipitation data set).

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Correspondence to Marco Turco.

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Turco, M., Sanna, A., Herrera, S. et al. Large biases and inconsistent climate change signals in ENSEMBLES regional projections. Climatic Change 120, 859–869 (2013). https://doi.org/10.1007/s10584-013-0844-y

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Keywords

  • Global Climate Model
  • Large Bias
  • Climate Change Signal
  • Nonlinear Amplification
  • Regional Climate Change Projection