globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-13-00406.1
Scopus记录号: 2-s2.0-84907057525
论文题名:
Ensemble-based parameter estimation in a coupled general circulation model
作者: Liu Y.; Liu Z.; Zhang S.; Jacob R.; Lu F.; Rong X.; Wu S.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期:18
起始页码: 7151
结束页码: 7162
语种: 英语
Scopus关键词: Coupled general circulation models ; atmosphere-ocean coupling ; atmospheric convection ; climatology ; data assimilation ; general circulation model ; parameterization ; sea surface salinity ; sea surface temperature
英文摘要: Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean-atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after &tild;40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parameter estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in &tild; 8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by &tild; 90%. Overall, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model. © 2014 American Meteorological Society.
资助项目: NSF, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51350
Appears in Collections:气候变化事实与影响

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作者单位: Center for Climate Research, Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, United States; Laboratory of Ocean-Atmosphere Studies, School of Physics, Peking University, Beijing, China; Center for Climate Research, Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI, United States; NOAA/GFDL, Princeton University, Princeton, NJ, United States; Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, United States; Chinese Academy of Meteorological Sciences, Beijing, China

Recommended Citation:
Liu Y.,Liu Z.,Zhang S.,et al. Ensemble-based parameter estimation in a coupled general circulation model[J]. Journal of Climate,2014-01-01,27(18)
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