气候变化领域集成服务门户(CCPortal): The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth

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DOI	10.1007/s00382-019-05097-1
	The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth
	Wang Q.; Mu M.; Pierini S.
发表日期	2020
ISSN	0930-7575
起始页码	1953
结束页码	1971
卷号	54
英文摘要	In this study, the predictability of the Kuroshio Extension (KE) transition processes is explored from an error growth perspective. The fastest growing initial errors (FGIEs) are obtained through the conditional nonlinear optimal perturbation approach within a reduced-gravity shallow-water model forced by steady winds, which provides a fairly realistic simulation of the KE low-frequency variability of intrinsic origin. The large amplitudes of the FGIEs for both the transitions from a typical low-energy state to a typical high-energy state (LH) and the opposite transition (HL), are found mainly in the Kuroshio large meander region south of Japan and in the KE region. The FGIE grows more rapidly for the HL process than for the LH process, implying that the HL transition process may be more difficult to predict. The evolution processes of the FGIEs and the related mechanisms are revealed by investigating the evolution of the potential vorticity anomalies caused by the FGIEs. The dominant physical processes governing the FGIE growth are found to be different for the LH and HL processes. For the LH process, the evolution is mainly governed by linear advection processes and interfacial friction, while for the HL process, in addition to these two processes, the nonlinear advection process also plays a vital role in the evolution. This indicates that nonlinear intrinsic oceanic processes affect considerably the error growth, especially in the HL transition process, suggesting that the intrinsic processes should be carefully considered when exploring the predictability and forecast of the KE low-frequency variability. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
语种	英语
scopus关键词	amplitude; climate prediction; error analysis; growth rate; interface; meander; numerical model; shallow-water equation; weather forecasting; Kuroshio Extension; Pacific Ocean
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145615
作者单位	College of Oceanography, Hohai University, Nanjing, 210098, China; CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences and Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, China; Institute of Atmospheric Sciences, Fudan University, Shanghai, China; Dipartimento di Scienze e Tecnologie, Università di Napoli Parthenope, Naples, Italy; CoNISMa, Rome, Italy
推荐引用方式 GB/T 7714	Wang Q.,Mu M.,Pierini S.. The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth[J],2020,54.
APA	Wang Q.,Mu M.,&Pierini S..(2020).The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth.Climate Dynamics,54.
MLA	Wang Q.,et al."The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth".Climate Dynamics 54(2020).