A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation | |
Wang, Qiang2,5,6; Mu, Mu3,5; Sun, Guodong1,4 | |
刊名 | NATIONAL SCIENCE REVIEW
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2020 | |
卷号 | 7期号:1页码:214-223 |
关键词 | CNOP non-linear optimization atmosphere ocean |
ISSN号 | 2095-5138 |
DOI | 10.1093/nsr/nwz039 |
通讯作者 | Sun, Guodong(sungd@mail.iap.ac.cn) |
英文摘要 | 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. |
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 |
语种 | 英语 |
出版者 | OXFORD UNIV PRESS |
WOS记录号 | WOS:000519816200029 |
内容类型 | 期刊论文 |
源URL | [http://ir.qdio.ac.cn/handle/337002/165828] ![]() |
专题 | 海洋研究所_海洋环流与波动重点实验室 |
通讯作者 | Sun, Guodong |
作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China 3.Fudan Univ, Inst Atmospher Sci, Dept Atmospher & Ocean Sci, Shanghai 200438, Peoples R China 4.Chinese Acad Sci, Inst Atmospher Phys, LASG, Beijing 100029, Peoples R China 5.Chinese Acad Sci, CAS Key Lab Ocean Circulat & Waves, Inst Oceanol, Qingdao 266071, Peoples R China 6.Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao 266237, Peoples R China |
推荐引用方式 GB/T 7714 | 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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