Seasonal cycle of sea surface water characteristics in climate models

Wang, Yanxin (2021) Seasonal cycle of sea surface water characteristics in climate models. Doctoral thesis, University of East Anglia.

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Abstract

The seasonal cycle of sea surface water characteristics is important for the global climate system. Seasonal extrema of sea surface temperature (SST) and sea surface salinity (SSS) determine water mass properties below the surface. Evaluation of climate models typically focuses on annual or long-term mean state, not on seasonal extrema. In this thesis, the seasonal cycles of SST and SSS in HiGEM and SST seasonal extrema in 20 CMIP6 models are assessed globally.

Sparse sampling leads to large differences between observational climatologies in both SST and SSS in polar regions. There are also large SST differences in regions with strong SST horizontal gradient, likely because gridding on coarse resolution can smooth the gradient. To exclude regions with large differences between climatologies, masks are proposed for global model assessments.

The results demonstrate the importance of evaluating model performance not simply against annual mean properties. Although the biases in SST and SSS seasonal extrema are largely consistent with their annual means, the amplitude of SST and SSS biases has large seasonal variations in specific regions. Large seasonal variations of SST bias in CMIP6 models occur in eastern boundary upwelling regions, polar regions, the North Pacific and eastern equatorial Atlantic. Large seasonal variations of SSS bias in HiGEM occur in equatorial and polar regions. SST biases in some CMIP6 models have seasonal spatial patterns. Models with greater vertical resolution in the ocean typically demonstrate better representation of SST extrema, particularly seasonal maximum SST. However, no significant relationship is found with ocean model horizontal resolution.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Environmental Sciences
Depositing User: Chris White
Date Deposited: 22 Mar 2022 10:54
Last Modified: 22 Mar 2022 10:54
URI: https://ueaeprints.uea.ac.uk/id/eprint/84210
DOI:

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