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DOI	10.1175/JCLI-D-20-0338.1
	On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature
	Ma H.-Y.; Cheska Siongco A.; Klein S.A.; Xie S.; Karspeck A.R.; Raeder K.; Anderson J.L.; Lee J.; Kirtman B.P.; Merryfield W.J.; Murakami H.; Tribbia J.J.
发表日期	2021
ISSN	0894-8755
起始页码	427
结束页码	446
卷号	34 期号:1
英文摘要	The correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multimodel Ensemble, and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and subtropics than over the extratropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with time scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean-atmosphere models. © 2021 American Meteorological Society. All rights reserved.
英文关键词	Atmospheric temperature; Climate models; Submarine geophysics; Surface properties; Surface waters; Time measurement; Tropics; Upper atmosphere; Coupled Model Intercomparison Project; Global climate model; Initial conditions; Initialization methods; Interannual variability; Multi-model ensemble; Ocean-atmosphere models; Sea surface temperature (SST); Oceanography; climate modeling; climate prediction; correspondence analysis; error analysis; general circulation model; hindcasting; numerical model; sea surface temperature; seasonal variation
语种	英语
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/170982
作者单位	Lawrence Livermore National Laboratory, Livermore, CA, United States; Jupiter, Boulder, CO, United States; National Center for Atmospheric Research, Boulder, CO, United States; Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL, United States; Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC, Canada; National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States; University Corporation for Atmospheric Research, Boulder, CO, United States
推荐引用方式 GB/T 7714	Ma H.-Y.,Cheska Siongco A.,Klein S.A.,et al. On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature[J],2021,34(1).
APA	Ma H.-Y..,Cheska Siongco A..,Klein S.A..,Xie S..,Karspeck A.R..,...&Tribbia J.J..(2021).On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature.Journal of Climate,34(1).
MLA	Ma H.-Y.,et al."On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature".Journal of Climate 34.1(2021).