Seasonal extrema of sea surface temperature in CMIP6 models

Wang, Yanxin, Heywood, Karen J., Stevens, David P. and Damerell, Gillian M. (2022) Seasonal extrema of sea surface temperature in CMIP6 models. Ocean Science, 18 (3). pp. 839-855. ISSN 1812-0784

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Abstract

CMIP6 model sea surface temperature (SST) seasonal extrema averaged over 1981–2010 are assessed against the World Ocean Atlas (WOA18) observational climatology. We propose a mask to identify and exclude regions of large differences between three commonly used climatologies (WOA18, WOCE-Argo Global Hydrographic climatology (WAGHC) and the Hadley Centre Sea Ice and Sea Surface Temperature data set (HadISST)). The biases in SST seasonal extrema are largely consistent with the annual mean SST biases. However, the amplitude and spatial pattern of SST bias vary seasonally in the 20 CMIP6 models assessed. Large seasonal variations in the SST bias occur in eastern boundary upwelling regions, polar regions, the North Pacific and the eastern equatorial Atlantic. These results demonstrate the importance of evaluating model performance not simply against annual mean properties. Models with greater vertical resolution in their ocean component typically demonstrate better representation of SST extrema, particularly seasonal maximum SST. No significant relationship of SST seasonal extrema with horizontal ocean model resolution is found.

Item Type: Article
Additional Information: Data availability: The WOA18 climatology was obtained from https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18/ (Boyer et al., 2018) on 14 August 2019. The WAGHC climatology was obtained from https://doi.org/10.1594/WDCC/WAGHC_V1.0 (Gouretski, 2018b) on 15 August 2019. HadISST was obtained from http://www.metoffice.gov.uk/hadobs/hadisst/ (Rayner et al., 2003) on 17 May 2019. CMIP6 data were obtained between 23 July 2020 and 31 July 2020 and can be freely downloaded from the Earth System Grid Federation (e.g. https://esgf-index1.ceda.ac.uk/ CMIP, 2022). Financial support: This research has been supported by the China Scholarship Council (grant no. 201706310146) and the European Research Council, H2020 European Research Council (grant no. COMPASS (741120)).
Faculty \ School: Faculty of Science > School of Environmental Sciences
Faculty of Science > School of Mathematics
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Depositing User: LivePure Connector
Date Deposited: 08 Jun 2022 14:47
Last Modified: 16 Jun 2022 00:24
URI: https://ueaeprints.uea.ac.uk/id/eprint/85466
DOI: 10.5194/os-18-839-2022

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