Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model

doi:10.1007/s11430-016-9020-8

CORC > 海洋研究所 > 中国科学院海洋研究所 > 海洋环流与波动重点实验室

	Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model
	Zhang Kun1,2 ; Mu Mu 3; Wang Qiang 1,4
刊名	SCIENCE CHINA-EARTH SCIENCES
	2017-05-01
卷号	60 期号:5 页码:866-875
关键词	Sensitive Area Adaptive Observation The Upstream Kuroshio Transport Conditional Nonlinear Optimal Perturbation (Cnop)
DOI	10.1007/s11430-016-9020-8
文献子类	Article
英文摘要	Using the conditional nonlinear optimal perturbation (CNOP) approach, sensitive areas of adaptive observation for predicting the seasonal reduction of the upstream Kuroshio transport (UKT) were investigated in the Regional Ocean Modeling System (ROMS). The vertically integrated energy scheme was utilized to identify sensitive areas based on two factors: the specific energy scheme and sensitive area size. Totally 27 sensitive areas, characterized by three energy schemes and nine sensitive area sizes, were evaluated. The results show that the total energy (TE) scheme was the most effective because it includes both the kinetic and potential components of CNOP. Generally, larger sensitive areas led to better predictions. The size of 0.5% of the model domain was chosen after balancing the effectiveness and efficiency of adaptive observation. The optimal sensitive area OSen was determined accordingly. Sensitivity experiments on OSen were then conducted, and the following results were obtained: (1) In OSen, initial errors with CNOP or CNOP-like patterns were more likely to yield worse predictions, and the CNOP pattern was the most unstable. (2) Initial errors in OSen rather than in other regions tended to cause larger prediction errors. Therefore, adaptive observation in OSen can be more beneficial for predicting the seasonal reduction of UKT.
语种	英语
WOS记录号	WOS:000400551600004
内容类型	期刊论文
版本	出版稿
源URL	[http://ir.qdio.ac.cn/handle/337002/137054]
专题	海洋研究所_海洋环流与波动重点实验室
作者单位	1.Chinese Acad Sci, Inst Oceanol, 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.Qingdao Natl Lab Marine Sci & Technol, Lab Ocean & Climate Dynam, Qingdao 266237, Peoples R China
推荐引用方式 GB/T 7714	Zhang Kun,Mu Mu,Wang Qiang. Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model[J]. SCIENCE CHINA-EARTH SCIENCES,2017,60(5):866-875.
APA	Zhang Kun,Mu Mu,&Wang Qiang.(2017).Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model.SCIENCE CHINA-EARTH SCIENCES,60(5),866-875.
MLA	Zhang Kun,et al."Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model".SCIENCE CHINA-EARTH SCIENCES 60.5(2017):866-875.