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, Zhiwei1,2,3,4,5; Yang, Dezhou1,2,3,4,5; Wang, Yonggang4,6; Yin, Baoshu1,2,3,4,5
2022-08-01
Source PublicationOCEAN MODELLING
ISSN1463-5003
Volume176Pages:21
Corresponding AuthorYang, Dezhou(yangdezhou@qdio.ac.cn)
AbstractIn 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.
Keyword4D-Var Tidal forcing The East China Sea Observation impact Kuroshio transport Kuroshio onshore intrusion
DOI10.1016/j.ocemod.2022.102044
Indexed BySCI
Language英语
Funding ProjectNational 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 Research AreaMeteorology & Atmospheric Sciences ; Oceanography
WOS SubjectMeteorology & Atmospheric Sciences ; Oceanography
WOS IDWOS:000833411500001
PublisherELSEVIER SCI LTD
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/179840
Collection海洋环流与波动重点实验室
Corresponding AuthorYang, Dezhou
Affiliation1.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
First Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences;  Center for Ocean Mega-Science, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences;  Center for Ocean Mega-Science, Chinese Academy of Sciences
Recommended Citation
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.
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