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Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region

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Abstract

One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.

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Acknowledgments

The work was partly funded by the projects iMar21 (CTM2010-15009) and GRACCIE (CSD2007-00067) from the Spanish government and the FP7 European project CoCoNet (287844). The authors would like to acknowledge the climate modeling groups which have generated the data used in this study, as well as the PCMDI and WDCC for facilitating access to it. The authors would like to thank the anonymous reviewers and B. P. Gouldby for their valuable comments and suggestions to improve the quality of the paper.

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Authors and Affiliations

  1. Environmental Hydraulics Institute “IH Cantabria”, Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria, 39011, Santander, Spain

    Jorge Perez, Melisa Menendez, Fernando J. Mendez & Inigo J. Losada

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  1. Jorge Perez
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  2. Melisa Menendez
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  3. Fernando J. Mendez
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  4. Inigo J. Losada
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Correspondence to Melisa Menendez.

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Perez, J., Menendez, M., Mendez, F.J. et al. Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region. Clim Dyn 43, 2663–2680 (2014). https://doi.org/10.1007/s00382-014-2078-8

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  • DOI: https://doi.org/10.1007/s00382-014-2078-8

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