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

doi:10.1016/j.ocemod.2022.102044

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

	Impact of 4D-Var data assimilation on modelling of the East China Sea dynamics
	He, Zhiwei 2,3,4,5,6; Yang, Dezhou 2,3,4,5,6; Wang, Yonggang 1,3; Yin, Baoshu 2,3,4,5,6
刊名	OCEAN MODELLING
	2022-08-01
卷号	176 页码:21
关键词	4D-Var Tidal forcing The East China Sea Observation impact Kuroshio transport Kuroshio onshore intrusion
ISSN号	1463-5003
DOI	10.1016/j.ocemod.2022.102044
通讯作者	Yang, Dezhou(yangdezhou@qdio.ac.cn)
英文摘要	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.
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
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000833411500001
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/179839]
专题	海洋研究所_海洋环流与波动重点实验室
通讯作者	Yang, Dezhou
作者单位	1.Minist Nat Resources, Key Lab Marine Sci & Numer Modeling, Inst Oceanog 1, Qingdao 266071, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, CAS Engn Lab Marine Ranching, Qingdao 266071, Peoples R China 3.Pilot Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China 4.Chinese Acad Sci, Ctr Ocean Megasci, 7 Nanhai Rd, Qingdao 266071, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
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.