Impact of increased resolution on the representation of the Canary upwelling system in climate models - Archive ouverte HAL Access content directly
Journal Articles Geoscientific Model Development Year : 2022

Impact of increased resolution on the representation of the Canary upwelling system in climate models

Abstract

Abstract. We investigate the representation of the Canary upwelling system (CUS) in six global coupled climate models operated at high and standard resolution as part of the High Resolution Model Intercomparison Project (HighResMIP). The models' performance in reproducing the observed CUS is assessed in terms of various upwelling indices based on sea surface temperature (SST), wind stress, and sea surface height, focusing on the effect of increasing model spatial resolution. Our analysis shows that possible improvement in upwelling representation due to the increased spatial resolution depends on the subdomain of the CUS considered. Strikingly, along the Iberian Peninsula region, which is the northernmost part of the CUS, the models show lower skill at higher resolution compared to their corresponding lower-resolution version in both components for all the indices analyzed in this study. In contrast, over the southernmost part of the CUS, from the north of Morocco to the Senegalese coast, the high-ocean- and high-atmosphere-resolution models simulate a more realistic upwelling than the standard-resolution models, which largely differ from the range of observational estimates. These results suggest that increasing resolution is not a sufficient condition to obtain a systematic improvement in the simulation of the upwelling phenomena as represented by the indices considered here, and other model improvements notably in terms of the physical parameterizations may also play a role.
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hal-03952858 , version 1 (26-01-2023)

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Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, Jorge López-Parages. Impact of increased resolution on the representation of the Canary upwelling system in climate models. Geoscientific Model Development, 2022, 15 (22), pp.8245-8267. ⟨10.5194/gmd-15-8245-2022⟩. ⟨hal-03952858⟩
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