Climate Dynamics

, Volume 54, Issue 1–2, pp 457–471 | Cite as

A revisit of the interannual variation of the South China Sea upper layer circulation in summer: correlation between the eastward jet and northward branch

  • Tingting Zu
  • Dongxiao WangEmail author
  • Qiang Wang
  • Mingting Li
  • Jun Wei
  • Bingxu Geng
  • Yunkai He
  • Ju Chen


The interannual variation of the South China Sea upper layer circulation in summer is revisited based on analysis of current derived from altimetry data, Acoustic Doppler Current Profilers moorings, and numerical simulations. Results show not only the interannual variation of the eastward jet (eastward branch), but also its anti-correlation with the northward branch. On interannual time scale, when the eastward branch is enhanced, the northward branch is weakened, and vice versa. Their variations are largely related to the change of the South China Sea summer monsoon (SCSSM), and are strongly influenced by the Luzon strait Transport (LST). Composite analysis reveals a stronger SCSSM and LST into the SCS in the developing phase of El Niño would lead to an eastward branch dominant circulation pattern, whereas a weaker SCSSM and reduced LST into the SCS in the decaying phase of El Niño favors a northward branch dominant circulation pattern. The distinct composite patterns appear in El Niño and Southern Oscillation cycles, rather than episodic event or multiyear El Niño or La Niña. Contribution of the transport of major straits in the SCS to the interannual variation of the SCS summer circulation is quantitatively evaluated for the first time, and the results show that the change of the planetary vorticity flux through three major straits (Luzon strait contributes most) is as equally important as the vorticity input change from local wind stress curl.


Interannual variability South China Sea South China Sea summer monsoon Luzon strait transport ENSO 



We are grateful to the editor and two anonymous reviewers for their thoughtful comments and suggestions. We thank Gengxin Chen for his helpful discussion. We also thank the Advanced Taiwan Ocean Prediction model group ( to provide codes for the model simulations used in this study. We benefited from numerous data sets made freely available, including AVISO (, CCMP ( HYCOM GLBu0.08 ( This research was supported by the National Natural Science Foundation of China (NSFC) under Project (41521005, 41731173, 41576002, 41776026, 41576003), by No. GML2019ZD0304 from Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), and by the research fund from the State Key Laboratory of Tropical Oceanography (LTOZZ1803). Qiang Wang is also sponsored by the Pearl River S&T Nova Program of Guangzhou (201906010051).

Supplementary material

382_2019_5007_MOESM1_ESM.docx (4.4 mb)
Supplementary material 1 (DOCX 4520 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Tropical Oceanography, South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhouPeople’s Republic of China
  2. 2.Guangzhou BranchSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou)GuangzhouPeople’s Republic of China
  3. 3.School of Atmospheric SciencesSun Yat-Sen UniversityGuangzhouPeople’s Republic of China

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