Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
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Published:2024-01-15
Issue:1
Volume:17
Page:347-379
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Wang QiangORCID, Shu QiORCID, Bozec Alexandra, Chassignet Eric P.ORCID, Fogli Pier GiuseppeORCID, Fox-Kemper BaylorORCID, Hogg Andy McC.ORCID, Iovino DoroteaciroORCID, Kiss Andrew E.ORCID, Koldunov NikolayORCID, Le Sommer JulienORCID, Li YiwenORCID, Lin Pengfei, Liu HailongORCID, Polyakov Igor, Scholz PatrickORCID, Sidorenko Dmitry, Wang ShizhuORCID, Xu XiaobiaoORCID
Abstract
Abstract. This study evaluates the impact of increasing resolution on Arctic Ocean simulations using five pairs of matched low- and high-resolution models within the OMIP-2 (Ocean Model Intercomparison Project phase 2) framework. The primary objective is to assess whether a higher resolution can mitigate typical biases in low-resolution models and improve the representation of key climate-relevant variables. We reveal that increasing the horizontal resolution contributes to a reduction in biases in mean temperature and salinity and improves the simulation of the Atlantic water layer and its decadal warming events. A higher resolution also leads to better agreement with observed surface mixed-layer depth, cold halocline base depth and Arctic gateway transports in the Fram and Davis straits. However, the simulation of the mean state and temporal changes in Arctic freshwater content does not show improvement with increased resolution. Not all models achieve improvements for all analyzed ocean variables when spatial resolution is increased so it is crucial to recognize that model numerics and parameterizations also play an important role in faithful simulations. Overall, a higher resolution shows promise in improving the simulation of key Arctic Ocean features and processes, but efforts in model development are required to achieve more accurate representations across all climate-relevant variables.
Funder
Bundesministerium für Bildung und Forschung National Natural Science Foundation of China Natural Science Foundation of Shandong Province Australian Research Council Deutsche Forschungsgemeinschaft
Publisher
Copernicus GmbH
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