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.
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.
PZ, BK, and RM acknowledge support from NOAA Grant NA14OAR4310278, and PZ acknowledges support from NSF AGS-1233874. BM acknowledges support from the Regional and Global Climate Modeling Program of the U.S. Department of Energy’s Office of Science, Cooperative Agreement DE-FC02-97ER62402. PC acknowledges support from U.S. NSF Grants OCE-1334707 and AGS-1462127, and NOAA Grant NA11OAR4310154. PC also acknowledges support from China’s National Basic Research Priorities Programme (2013CB956204) and the Natural Science Foundation of China (41222037 and 41221063). TF acknowledges support from NSF Grant OCE-0745508 and NASA Grant NNX14AM71G. PB acknowledges support from the BMBF SACUS (03G0837A) project. TT and PB acknowledge support from the European Union Seventh Framework Programme (FP7 20072013) under Grant Agreement 603521 for the PREFACE Project. ES and ZW acknowledge support from NSF AGS-1338427, NOAA NA14OAR4310160, and NASA NNX14AM19G; and ES is grateful for further support from the National Monsoon Mission, Ministry of Earth Sciences, India.
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