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A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation
Wang, Qiang1,2,3; Mu, Mu1,4; Sun, Guodong5,6
2020
发表期刊NATIONAL SCIENCE REVIEW
ISSN2095-5138
卷号7期号:1页码:214-223
通讯作者Sun, Guodong(sungd@mail.iap.ac.cn)
摘要In atmospheric and oceanic studies, it is important to investigate the uncertainty of model solutions. The conditional non-linear optimal perturbation (CNOP) method is useful for addressing the uncertainty. This paper reviews the development of the CNOP method and its computational aspects in recent years. Specifically, the CNOP method was first proposed to investigate the effects of the optimal initial perturbation on atmosphere and ocean model results. Then, it was extended to explore the influences of the optimal parameter perturbation, model tendency perturbation and boundary condition perturbation. To obtain solutions to these optimal perturbations, four kinds of optimization approaches were developed: the adjoint-based method, the adjoint-free method, the intelligent optimization method and the unconstrained optimization method. We illustrate the calculation process of each method and its advantages and disadvantages. Then, taking the Zebiak-Cane model as an example, we compare the CNOPs related to initial conditions (CNOP-Is) calculated by the above four methods. It was found that the dominant structures of the CNOP-Is for different methods are similar, although some differences in details exist. Finally, we discuss the necessity and possible direction for designing a more effective optimization approach related to the CNOP in the future.
关键词CNOP non-linear optimization atmosphere ocean
DOI10.1093/nsr/nwz039
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[41576015] ; Qingdao National Laboratory for Marine Science and Technology[QNLM2016ORP0107] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA20060502] ; NSFC Innovative Group[41421005] ; National Programme on Global Change andAirSea Interaction[GASI-IPOVAI-06] ; NSFC-Shandong Joint Fund forMarine Science Research Centers[U1606402] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[2015060]
WOS研究方向Science & Technology - Other Topics
WOS类目Multidisciplinary Sciences
WOS记录号WOS:000519816200029
出版者OXFORD UNIV PRESS
引用统计
被引频次:23[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/337002/165829
专题海洋环流与波动重点实验室
通讯作者Sun, Guodong
作者单位1.Chinese Acad Sci, CAS Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China
2.Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao 266237, Peoples R China
3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China
4.Fudan Univ, Inst Atmospher Sci, Dept Atmospher & Ocean Sci, Shanghai 200438, Peoples R China
5.Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing 100029, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
第一作者单位中国科学院海洋研究所;  中国科学院海洋大科学研究中心
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Wang, Qiang,Mu, Mu,Sun, Guodong. A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation[J]. NATIONAL SCIENCE REVIEW,2020,7(1):214-223.
APA Wang, Qiang,Mu, Mu,&Sun, Guodong.(2020).A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation.NATIONAL SCIENCE REVIEW,7(1),214-223.
MLA Wang, Qiang,et al."A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation".NATIONAL SCIENCE REVIEW 7.1(2020):214-223.
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