Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics

doi:10.1016/j.ocemod.2022.102044

IOCAS-IR > 海洋环流与波动重点实验室

	Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics
	He, Zhiwei 1,2,3,4,5; Yang, Dezhou 1,2,3,4,5; Wang, Yonggang 4,6; Yin, Baoshu 1,2,3,4,5
	2022-08-01
发表期刊	OCEAN MODELLING
ISSN	1463-5003
卷号	176 页码:21
通讯作者	Yang, Dezhou(yangdezhou@qdio.ac.cn)
摘要	In this work, the four-dimensional variational (4D-Var) data assimilation (DA) of the Regional Ocean Modelling System (ROMS) is applied in the East China Sea (ECS). The unique capability of optimizing the initial condition (IC), boundary condition (BC) and surface forcing (FC) in ROMS 4D-Var facilitate the simulation of dynamical processes associated with both local and remote forcing. The assimilated data in this study include sea surface temperature (SST), sea surface height (SSH), in situ temperature and salinity profiles, as well as surface drifters and a surface ocean current analysis (OSCAR). Overall, 4D-Var performs well in reducing model-data misfit for all observation types. As tidal forcing plays important roles in the shelf circulations of the ECS, tidal forcing was included in 4D-Var and its impact was evaluated by comparing two experiments with and without fides. The biases of SST in DA analyses are small on the continental shelf in both experiments. However, compared with experiments with tides, the absence of tidal forcing will make temperature higher near the surface layer and lower below mixed layer in the background simulation (3-day forecast using DA analyses as IC) in the warm season of 2014. The difference in temperature profile is associated with two factors: stratification and tidal mixing. The relative importance of the two factors varies with depth. With the aid of the adjoins model, the impacts on the Kuroshio volume transport (KVT) and the Kuroshio onshore intrusion (KOI) contributed by different types of observations are evaluated, as well as the contributions of IC, BC and FC. SSH, SST and in situ temperatures have large total impacts while in situ temperatures have the largest impact per datum. The geographical distributions of observation impacts are similar for different observation types. Large observation impacts extend along the Kuroshio path from the northeast of Taiwan to the southwest of Japan. Several factors control the geographical distribution, which include the model forecast skills, the dynamic processes that are responsible for the transferring of assimilated information, and the specified error covariance. Tracking how the assimilated information propagate in space helps to advance the understanding of the dynamics of KVT and KOI.
关键词	4D-Var Tidal forcing The East China Sea Observation impact Kuroshio transport Kuroshio onshore intrusion
DOI	10.1016/j.ocemod.2022.102044
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[92158202] ; National Natural Science Foundation of China[41876019] ; National Natural Science Foundation of China[42076022] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB42000000] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060203] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060202] ; Key Deployment Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Sciences[COMS2020Q01] ; NSFC-Shandong Joint Fund for Marine Science Research Centers[U1806227] ; Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao)[2021QNLM040001] ; Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao)[2022QNLM010302] ; CAS-CSIRO BAU project[133137KYSB20180141] ; High Performance Computing Center at the IOCAS, Yellow Sea & East China Sea ocean observation and research station of OMORN
WOS研究方向	Meteorology & Atmospheric Sciences ; Oceanography
WOS类目	Meteorology & Atmospheric Sciences ; Oceanography
WOS记录号	WOS:000833411500001
出版者	ELSEVIER SCI LTD
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/179840
专题	海洋环流与波动重点实验室
通讯作者	Yang, Dezhou
作者单位	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.Chinese Acad Sci, Ctr Ocean Megasci, 7 Nanhai Rd, Qingdao 266071, Peoples R China 4.Pilot Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China 5.Chinese Acad Sci, Inst Oceanol, CAS Engn Lab Marine Ranching, Qingdao 266071, Peoples R China 6.Minist Nat Resources, Key Lab Marine Sci & Numer Modeling, Inst Oceanog 1, Qingdao 266071, Peoples R China
第一作者单位	中国科学院海洋研究所; 中国科学院海洋大科学研究中心
通讯作者单位	中国科学院海洋研究所; 中国科学院海洋大科学研究中心
推荐引用方式 GB/T 7714	He, Zhiwei,Yang, Dezhou,Wang, Yonggang,et al. Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics[J]. OCEAN MODELLING,2022,176:21.
APA	He, Zhiwei,Yang, Dezhou,Wang, Yonggang,&Yin, Baoshu.(2022).Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics.OCEAN MODELLING,176,21.
MLA	He, Zhiwei,et al."Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics".OCEAN MODELLING 176(2022):21.