Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model | |
Li, Xia1,2![]() | |
2018-11-01 | |
Source Publication | ADVANCES IN ATMOSPHERIC SCIENCES
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ISSN | 0256-1530 |
Volume | 35Issue:11Pages:1362-1372 |
Corresponding Author | Wang, Qiang(wangqiang@qdio.ac.cn) |
Abstract | Based on the high-resolution Regional Ocean Modeling System (ROMS) and the conditional nonlinear optimal perturbation (CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kuroshio large meander (LM) path, and the growth mechanism of optimal initial errors was revealed. For each LM event, two types of initial error (denoted as CNOP1 and CNOP2) were obtained. Their large amplitudes were found located mainly in the upper 2500 m in the upstream region of the LM, i.e., southeast of Kyushu. Furthermore, we analyzed the patterns and nonlinear evolution of the two types of CNOP. We found CNOP1 tends to strengthen the LM path through southwestward extension. Conversely, CNOP2 has almost the opposite pattern to CNOP1, and it tends to weaken the LM path through northeastward contraction. The growth mechanism of optimal initial errors was clarified through eddy-energetics analysis. The results indicated that energy from the background field is transferred to the error field because of barotropic and baroclinic instabilities. Thus, it is inferred that both barotropic and baroclinic processes play important roles in the growth of CNOP-type optimal initial errors. |
Keyword | Kuroshio large meander predictability ROMS optimal initial error growth |
DOI | 10.1007/s00376-018-8003-z |
Indexed By | SCI |
Language | 英语 |
Funding Project | National Natural Scientific Foundation of China[41230420] ; National Natural Scientific Foundation of China[41576015] ; Qingdao National Laboratory for Marine Science and Technology[QNLM2016ORP0107] ; NSFC Innovative Group[41421005] ; NSFC-Shandong Joint Fund for Marine Science Research Centers[U1606402] ; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06] ; National Natural Scientific Foundation of China[41230420] ; National Natural Scientific Foundation of China[41576015] ; Qingdao National Laboratory for Marine Science and Technology[QNLM2016ORP0107] ; NSFC Innovative Group[41421005] ; NSFC-Shandong Joint Fund for Marine Science Research Centers[U1606402] ; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06] |
WOS Research Area | Meteorology & Atmospheric Sciences |
WOS Subject | Meteorology & Atmospheric Sciences |
WOS ID | WOS:000444011500003 |
Publisher | SCIENCE PRESS |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.qdio.ac.cn/handle/337002/160257 |
Collection | 海洋环流与波动重点实验室 |
Corresponding Author | Wang, Qiang |
Affiliation | 1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Fudan Univ, Inst Atmospher Sci, Shanghai 200433, Peoples R China 4.Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao 266237, Peoples R China 5.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China |
First Author Affilication | Institute of Oceanology, Chinese Academy of Sciences |
Corresponding Author Affilication | Institute of Oceanology, Chinese Academy of Sciences |
Recommended Citation GB/T 7714 | Li, Xia,Wang, Qiang,Mu, Mu. Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2018,35(11):1362-1372. |
APA | Li, Xia,Wang, Qiang,&Mu, Mu.(2018).Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model.ADVANCES IN ATMOSPHERIC SCIENCES,35(11),1362-1372. |
MLA | Li, Xia,et al."Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model".ADVANCES IN ATMOSPHERIC SCIENCES 35.11(2018):1362-1372. |
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