SCSIO OpenIR  > 热带海洋环境国家重点实验室(LTO)
A comparison of wind stress datasets for the South China Sea
Lian, Zhan; Fang, Guohong; Wei, Zexun; Wang, Gang; Sun, Baonan; Zhu, Yaohua; lianzhan@fio.org.cn
2015
Source PublicationOCEAN DYNAMICS
Volume65Issue:5Pages:721-734
Subtype1616-7341
AbstractThe wind stresses and their derived wind stress curls, and Sverdrup stream functions over the South China Sea (SCS) in typical winter and summer months from nine datasets are compared. The datasets include CCMP, CERSAT, ASCAT, QSCAT, NCEP, QSCAT-NCEP, HR, ERA-40, and ERA-Interim. Results show that the overall patterns of the wind stresses, wind stress curls, and Sverdrup stream functions from different datasets are similar. However, their magnitudes are remarkably different. Among them, ERA-40 is the smallest while HR is the largest. The former is about 40 % smaller than the mean value, while the latter is about 50 % greater than the mean value. The spatial resolution is important for the presentation of the wind stress features in the SCS. It can be expected that the same numerical ocean model driven by different wind stress would yield remarkably different results.
Department[Lian, Zhan; Fang, Guohong] Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Guangdong, Peoples R China; [Lian, Zhan] Univ Chinese Acad Sci, Beijing 100039, Peoples R China ; LTO
KeywordSouth China Sea Wind Stress Wind Stress Curl Sverdrup Circulation
Subject AreaOceanography
Document Type期刊论文
Identifierhttp://ir.scsio.ac.cn/handle/344004/15096
Collection热带海洋环境国家重点实验室(LTO)
Corresponding Authorlianzhan@fio.org.cn
Recommended Citation
GB/T 7714
Lian, Zhan,Fang, Guohong,Wei, Zexun,et al. A comparison of wind stress datasets for the South China Sea[J]. OCEAN DYNAMICS,2015,65(5):721-734.
APA Lian, Zhan.,Fang, Guohong.,Wei, Zexun.,Wang, Gang.,Sun, Baonan.,...&lianzhan@fio.org.cn.(2015).A comparison of wind stress datasets for the South China Sea.OCEAN DYNAMICS,65(5),721-734.
MLA Lian, Zhan,et al."A comparison of wind stress datasets for the South China Sea".OCEAN DYNAMICS 65.5(2015):721-734.
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