Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation

doi:10.1007/s10236-022-01531-x

IOCAS-IR

	Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation
	Zhou, Li 1; Zhang, Kun 2,3; Wang, Qiang 4,5; Mu, Mu 2,6,7
	2022-11-01
发表期刊	OCEAN DYNAMICS
ISSN	1616-7341
页码	16
通讯作者	Zhang, Kun(kzhang@qdio.ac.cn)
摘要	Initial errors critically affect the performance of short-term ocean predictions. To investigate the effects of initial errors on the 30-day prediction of the sudden shift in the Antarctic Circumpolar Current (ACC) transport through the Drake Passage (DP), the optimally growing initial error (OGIE) is explored based on the Conditional Nonlinear Optimal Perturbation (CNOP) approach and an eddy-permitting Regional Ocean Modeling System. In the four selected cases, the OGIEs are primarily located under 2000 m in the middle DP of (57 degrees S-62 degrees S, 73 degrees W-64 degrees W). All OGIEs undergo localized evolutions and cause significant transport prediction errors of approximately 40.0 Sv by exciting anomalous dipolar circulations. The vorticity budget analysis indicates linear advection contributes to error vorticity evolutions, whereas nonlinear advection and ageostrophic divergence show damping effects. Moreover, eastward motions exerted by linear advection and westward motions exerted by nonlinear advection together maintain the localized vorticity evolutions. Finally, targeted observation is applied in the OGIE-determined sensitive areas. Observing system simulation experiments suggest that improving initial condition qualities in the OGIE-determined sensitive areas (especially in the deep layers) can effectively enhance the ACC transport predictions. This study reveals the spatial structures and growth mechanism of the OGIEs related to the short-term ACC transport prediction and provides scientific guidance on designing observing networks in the DP.
关键词	The Antarctic Circumpolar Current Initial errors CNOP Targeted observation Ocean prediction
DOI	10.1007/s10236-022-01531-x
收录类别	SCI
语种	英语
资助项目	Fundamental Research Funds for the Central Universities[B200201011] ; National Natural Science Foundation of China[92158202] ; National Natural Science Foundation of China[41576015] ; National Natural Science Foundation of China[41806013] ; National Key Research and Development Program of China[2021YFC3100705]
WOS研究方向	Oceanography
WOS类目	Oceanography
WOS记录号	WOS:000876900400001
出版者	SPRINGER HEIDELBERG
WOS关键词	NONLINEAR OPTIMAL PERTURBATION ; OCEAN CIRCULATION MODEL ; KUROSHIO LARGE MEANDER ; DRAKE PASSAGE ; ADAPTIVE OBSERVATION ; SENSITIVE AREAS ; WIND STRESS ; SEA ; PREDICTABILITY ; ADJOINT
引用统计
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/180490
通讯作者	Zhang, Kun
作者单位	1.Inst Def Engn, PLA, AMS, Luoyang 471023, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 3.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China 4.Hohai Univ, Key Lab Marine Hazards Forecasting, Minist Nat Resources, Nanjing 210098, Peoples R China 5.Hohai Univ, Coll Oceanog, Nanjing 210098, Peoples R China 6.Fudan Univ, Dept Atmospher & Ocean Sci, Shanghai 200433, Peoples R China 7.Fudan Univ, Inst Atmospher Sci, Shanghai 200433, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Li,Zhang, Kun,Wang, Qiang,et al. Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation[J]. OCEAN DYNAMICS,2022:16.
APA	Zhou, Li,Zhang, Kun,Wang, Qiang,&Mu, Mu.(2022).Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation.OCEAN DYNAMICS,16.
MLA	Zhou, Li,et al."Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation".OCEAN DYNAMICS (2022):16.