Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
| 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 Publication | OCEAN MODELLING
 |
| ISSN | 1463-5003 |
| Volume | 176Pages:21 |
| Corresponding Author | Yang, Dezhou(yangdezhou@qdio.ac.cn) |
| Abstract | 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. |
| Keyword | 4D-Var Tidal forcing The East China Sea Observation impact Kuroshio transport Kuroshio onshore intrusion |
| DOI | 10.1016/j.ocemod.2022.102044 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | 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 Research Area | Meteorology & Atmospheric Sciences ; Oceanography |
| WOS Subject | Meteorology & Atmospheric Sciences ; Oceanography |
| WOS ID | WOS:000833411500001 |
| Publisher | ELSEVIER SCI LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.qdio.ac.cn/handle/337002/179840 |
| Collection | 海洋环流与波动重点实验室 |
| Corresponding Author | Yang, Dezhou |
| Affiliation | 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 |
| First Author Affilication | Institute of Oceanology, Chinese Academy of Sciences; Center for Ocean Mega-Science, Chinese Academy of Sciences |
| Corresponding Author Affilication | Institute 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. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment