Analysis of monthly variability of thermocline in the South China Sea

彭汉帮; 潘爱军; 郑全安; 胡建宇

doi:10.1007/s00343-017-6151-0

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Analysis of monthly variability of thermocline in the South China Sea

Physics | Updated：2023-05-19

- Analysis of monthly variability of thermocline in the South China Sea
- Analysis of monthly variability of thermocline in the South China Sea
- 海洋湖沼学报（英文） 2018年36卷第2期页码：205-215
- Affiliations：
  
  1.State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361102, China
  2.Ocean Dynamics Laboratory, the Third Institute of Oceanography, State Oceanic Administration(SOA), Xiamen 361005, China
  3.Department of Atmospheric and Oceanic Science, University of Maryland, College Park 20742, USA
- Author bio：
  
  HU Jianyu, hujy@xmu.edu.cn
- Funds：
  
  the National Basic Research Program of China (973 Program)(2015CB954004);the Chinese Academy of Sciences Strategic Leading Science and Technology Projects(XDA1102030104);the National Natural Science Foundation of China(U1405233);the National Natural Science Foundation of China(41176031)
- DOI：10.1007/s00343-017-6151-0
  中图分类号：
- 收稿：2016-05-25，
  
  录用：2016-10-9，
  
  网络首发：2016-12-11，
  
  纸质出版：2018-03
- Accepted：
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彭汉帮, 潘爱军, 郑全安, 等. Analysis of monthly variability of thermocline in the South China Sea[J]. 海洋湖沼学报（英文）, 2018,36(2):205-215.

Hanbang PENG, Aijun PAN, Quan'an ZHENG, et al. Analysis of monthly variability of thermocline in the South China Sea[J]. Chinese Journal of Oceanology and Limnology, 2018, 36(2): 205-215.
彭汉帮, 潘爱军, 郑全安, 等. Analysis of monthly variability of thermocline in the South China Sea[J]. 海洋湖沼学报（英文）, 2018,36(2):205-215. DOI： 10.1007/s00343-017-6151-0.

Hanbang PENG, Aijun PAN, Quan'an ZHENG, et al. Analysis of monthly variability of thermocline in the South China Sea[J]. Chinese Journal of Oceanology and Limnology, 2018, 36(2): 205-215. DOI： 10.1007/s00343-017-6151-0.

摘要

Abstract

This study analyzes monthly variability of thermocline and its mechanism in the South China Sea (SCS). The study is based on 51-year (1960-2010) monthly seawater temperature and surface wind stress data from Simple Ocean Data Assimilation (SODA)

together with heat flux

precipitation and evaporation data from the National Centers for Environmental Prediction (NCEP)

the National Oceanic and Atmospheric Administration (NOAA) and the Woods Hole Oceanographic Institution

respectively. The results reveal that the upper boundary depth (

)

lower boundary depth (

low

)

thickness (△

) and intensity (

) of thermocline in the SCS show remarkable monthly variability. Being averaged for the deep basin of SCS

deepens gradually from May to the following January and then shoals from February to May

while

low

varies little throughout the whole year. Further diagnostics indicates that the monthly variability of

is mainly caused by the buoyancy flux and wind stress curl. Using a linear method

the impacts of the buoyancy flux and wind stress curl on

can be quantitatively distinguished. The results suggest that

tends to deepen about 4.6 m when the buoyancy flux increases by 1×10

-5

kg/(m·s

)

while it shoals about 2.5 m when the wind stress curl strengthens by 1×10

-7

N/m

关键词

Keywords

references

Carton J A, Chepurin G, Cao X H, Giese B. 2000a. A simple ocean data assimilation analysis of the global upper ocean 1950-95. Part Ⅰ:methodology. J. Phys. Oceanogr., 30(2):294-309.

Carton J A, Chepurin G, Cao X H. 2000b. A simple ocean data assimilation analysis of the global upper ocean 1950-95.Part Ⅱ:results. J. Phys. Oceanogr., 30(2):311-326.

Carton J A, Giese B S, Grodsky S A. 2005. Sea level rise and the warming of the oceans in the Simple Ocean Data Assimilation (SODA) ocean reanalysis. J. Geophys. Res., 110(C9):C09006, https://doi.org/10.1029/2004JC002817.

Carton J A, Giese B S. 2008. A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon.Wea. Rev., 136(8):2 999-3 017.

Chen M Y, Xie P P, Janowiak J E, Arkin P A. 2002. Global land precipitation:a 50-yr monthly analysis based on gauge observations. J. Hydrometeorol., 3(3):249-266.

China State Bureau of Technical Supervision (CSBTS). 2008. GB/T 12763. 7-2007 The specifications for oceanographic survey-Part 7: exchange of oceanographic survey data. China Standards Press, Beijing. (in Chinese)

Fang X J, Wang C X, Xu J J. 2013. Seasenal and interannual variations of the thermocline depth in the South China Sea. Trans. Oceanol. Limnol ., (3): 45-55. (in Chinese with English abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-HYFB201303006.htm

Fofonoff P, Millard Jr R C. 1983. Algorithms for computation of fundamental properties of seawater. UNESCO Tech. Papers in Marine Science 44, UNESCO. 53p.

Ge R F, Qiao F L, Yu F, Jiang Z X, Guo J S. 2003. A method for calculating thermocline characteristic elements in shelf sea area-Quasi-step function approximation method. Adv. Mar. Sci. , 21 (4): 393-400. (in Chinese with English abstract) http://europepmc.org/abstract/CBA/552627

Giese B S, Ray S. 2011. El Niño variability in simple ocean data assimilation (SODA), 1871-2008. J. Geophys. Res., 116(C2):C02024, https://doi.org/10.1029/2010JC006695.

Gill A E. 1982. Atmosphere-Ocean Dynamics. Academic Press, San Diego, USA.

Hao J J, Chen Y L, Wang F, Lin P F. 2012. Seasonal thermocline in the China Seas and northwestern Pacific Ocean. J.Geophys. Res, 117(C2):C02022, https://doi.org/10.1029/2011JC007246.

Hao J J, Chen Y L, Wang F. 2008. A study of thermocline calculations in the China Sea. Mar. Sci. , 32 (12): 17-24. (in Chinese with English abstract) http://en.cnki.com.cn/Article_en/CJFDTOTAL-HYKX200812005.htm

Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds B, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo K C, Ropelewski C, Wang J, Jenne R, Joseph D. 1996. The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77(3):437-472.

Lan J, Bao Y, Yu F, Sun S W. 2006. Seasonal variabilities of the circulation and thermocline depth in the South China Sea deep water basin. Adv. Mar. Sci. , 24 (4): 436-445. (in Chinese with English abstract) http://en.cnki.com.cn/article_en/cjfdtotal-hbhh200604003.htm

Liu Q Y, Jia Y L, Liu P H, Wang Q, Chu P C. 2001. Seasonal and intraseasonal thermocline variability in the central South China Sea. Geophys. Res. Lett., 28(23):4 467-4 470.

Liu Q Y, Yang H J, Wang Q. 2000. Dynamic characteristics of seasonal thermocline in the deep sea region of the South China Sea. Chin. J. Oceanol. Limnol., 18(2):104-109.

Lozovatsky I, Figueroa M, Roget E, Fernando H J S, Shapovalov S. 2005. Observations and scaling of the upper mixed layer in the North Atlantic. J. Geophys. Res., 110(C5):C05013, https://doi.org/10.1029/2004JC002708.

McDougall T J. 1987. Neutral surfaces. J. Phys. Oceanogr., 17(11):1 950-1 964.

Schmitt R W, Bogden P S, Dorman C E. 1989. Evaporation minus precipitation and density fluxes for the North Atlantic. J. Phys. Oceanogr., 19(9):1 208-1 221.

Yu L S, Jin X Z, Weller R A. 2008. Multidecade global flux datasets from the objectively analyzed air-sea fluxes(OAFlux) project: latent and sensible heat fluxes, ocean evaporation, and related surface meteorological variables. Woods Hole Oceanographic Institution, OAFlux Project Technical Report. OA-2008-01, Woods Hole, Massachusetts, USA. 64p.

Zhou F X, Gao R Z. 2001. Intraseasonal variability of the subsurface temperature observed in the South China Sea(SCS). Chin. Sci. Bull., 47(4):337-342.

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