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

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 twentyfirst 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, ECEARTH, 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.

Otras publicaciones de la misma revista o congreso con autores/as de la Universidad de Cantabria

 Fuente: Clim Dyn (2014) 43:2663–2680

Editorial: Springer

 Año de publicación: 2014

Nº de páginas: 18

Tipo de publicación: Artículo de Revista

 DOI: 10.1007/s00382-014-2078-8

ISSN: 0930-7575,1432-0894

Proyecto español: CTM2010-15009 ; CSD2007-00067

Proyecto europeo: info:eu-repo/grantAgreement/EC/FP7/287844/EU/Towards Coast to Coast NETworks of marine protected areas (from the shore to the high and deep sea), coupled with sea-based wind energy potential/COCONET/