SST biases over the Northwest Pacific and possible causes in CMIP5 models

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Abstract

In this paper, the features and possible causes of sea surface temperature (SST) biases over the Northwest Pacific are investigated based on a mixed-layer heat budget analysis in 21 coupled general circulation models (CGCMs) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5). Most CMIP5 models show cold SST biases throughout the year over the Northwest Pacific. The largest biases appear during summer, and the smallest biases occur during winter. These cold SST biases are seen at the basin scale and are mainly located in the inner region of the low and mid-latitudes. According to the mixed-layer heat budget analysis, overestimation of upward net sea surface heat fluxes associated with atmospheric processes are primarily responsible for the cold SST biases. Among the different components of surface heat fluxes, overestimated upward latent heat fluxes induced by the excessively strong surface winds contribute the most to the cold SST biases during the spring, autumn, and winter seasons. Conversely, during the summer, overestimated upward latent heat fluxes and underestimated downward solar radiations at the sea surface are equally important. Further analysis suggests that the overly strong surface winds over the Northwest Pacific during winter and spring are associated with excessive precipitation over the Maritime Continent region, whereas those occurring during summer and autumn are associated with the excessive northward extension of the intertropical convergence zone (ITCZ). The excessive precipitation over the Maritime Continent region and the biases in the simulated ITCZ induce anomalous northeasterlies, which are in favor of enhancing low-level winds over the North Pacific. The enhanced surface wind increases the sea surface evaporation, which contributes to the excessive upward latent heat fluxes. Thus, the SST over the Northwest Pacific cools.

Keywords

CMIP5 multi-model ensemble SST bias Mixed-layer heat budget analysis Atmospheric processes 

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Notes

Acknowledgements

This work was supported by the National Key Research and Development Program of China (Grant No. 2017YFA 0604004) and the R&D Special Fund for Public Welfare Industry (Meteorology) (Grant No. GYHY201506012).

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Copyright information

© Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.LASG, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Jiangsu Collaborative Innovation Center for Climate ChangeNanjingChina

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