Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

doi:10.1002/2017MS001222

IOCAS-IR > 海洋环流与波动重点实验室

	Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation
	Li, Shan 1,2; Zhang, Shaoqing 3,4; Liu, Zhengyu 5; Lu, Lv 6; Zhu, Jiang 2; Zhang, Xuefeng 7; Wu, Xinrong 7; Zhao, Ming 8; Vecchi, Gabriel A.9; Zhang, Rong-Hua4,10 ; Lin, Xiaopei 3,4
	2018-04-01
发表期刊	JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
ISSN	1942-2466
卷号	10 期号:4 页码:989-1010
通讯作者	Li, Shan(lucy_lishan@qq.com) ; Zhang, Shaoqing(szhang@ouc.edu.cn)
摘要	Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.
关键词	parameter estimation data assimilation coupled climate model convection
DOI	10.1002/2017MS001222
收录类别	SCI
语种	英语
资助项目	CMOST National Key Research & Development projects[2017YFC1404100] ; CMOST National Key Research & Development projects[2017YFC1404104] ; Chinese National Natural Science Foundation of China[41775100] ; China Postdoctoral Science Foundation[2016M601103] ; China Scholarship Council ; US NSF[1656907] ; [2017YFA0603801] ; [NSFC41630527] ; CMOST National Key Research & Development projects[2017YFC1404100] ; CMOST National Key Research & Development projects[2017YFC1404104] ; Chinese National Natural Science Foundation of China[41775100] ; China Postdoctoral Science Foundation[2016M601103] ; China Scholarship Council ; US NSF[1656907] ; [2017YFA0603801] ; [NSFC41630527]
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000432002600006
出版者	AMER GEOPHYSICAL UNION
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/154690
专题	海洋环流与波动重点实验室
通讯作者	Li, Shan; Zhang, Shaoqing
作者单位	1.Peking Univ, Sch Phys, Dept Atmospher & Ocean Sci, Lab Climate & Ocean Atmosphere Studies LaCOAS, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Atmospher Sci, ICCES, Beijing, Peoples R China 3.Ocean Univ China, Minist Educ, Key Lab Phys Oceanog, Qingdao, Peoples R China 4.Qingdao Natl Lab Marine Sci & Technol, Qingdao, Peoples R China 5.Ohio State Univ, Dept Geog, Atmospher Sci Program, Columbus, OH 43210 USA 6.Ocean Univ China, Coll Atmosphere & Oceanog, Qingdao, Peoples R China 7.Natl Marine Data & Informat Serv, Tianjin, Peoples R China 8.GFDL NOAA, Princeton, NJ USA 9.Princeton Univ, Dept Geosci, Princeton, NJ 08544 USA 10.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
推荐引用方式 GB/T 7714	Li, Shan,Zhang, Shaoqing,Liu, Zhengyu,et al. Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation[J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,2018,10(4):989-1010.
APA	Li, Shan.,Zhang, Shaoqing.,Liu, Zhengyu.,Lu, Lv.,Zhu, Jiang.,...&Lin, Xiaopei.(2018).Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation.JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,10(4),989-1010.
MLA	Li, Shan,et al."Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation".JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 10.4(2018):989-1010.

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