Challenges and prospects for reducing coupled climate model SST biases in the eastern tropical Atlantic and Pacific Oceans : the U.S. CLIVAR Eastern Tropical Oceans Synthesis Working Group

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Zuidema, Paquita
Chang, Ping
Medeiros, Brian
Kirtman, Benjamin
Mechoso, Roberto
Schneider, Edwin K.
Toniazzo, Thomas
Richter, Ingo
Small, R. Justin
Bellomo, Katinka
Brandt, Peter
de Szoeke, Simon
Farrar, J. Thomas
Jung, Eunsil
Kato, Seiji
Li, Mingkui
Patricola, Christina
Wang, Zaiyu
Wood, Robert
Xu, Zhao
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Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.
Author Posting. © American Meteorological Society, 2017. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 97 (2016): 2305-2327, doi:10.1175/BAMS-D-15-00274.1.
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Bulletin of the American Meteorological Society 97 (2016): 2305-2327
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