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Pure and Applied Geophysics

, Volume 176, Issue 4, pp 1847–1861 | Cite as

Spatial–Temporal Variations and Mechanisms of the Upper Ocean Heat Content in the South China Sea

  • Hongwei LiuEmail author
  • Qilong Zhang
  • Chongguang Pang
  • Rongshuo Cai
  • Qinghua Qi
  • Dongmei Zheng
Article
  • 58 Downloads

Abstract

The variability of the upper ocean heat content (OHC) of the South China Sea (SCS) has a significant regional climate impact on the surrounding East and Southeast Asian countries. In this paper, the spatial–temporal variations of the upper OHC in the SCS and their relations to El Niño-Southern Oscillation (ENSO) are analyzed using empirical orthogonal functions and correlation analysis. The mechanisms for the interannual OHC variability associated with ENSO and regime shift in 1998 are further examined using composite and correlation analysis methods. The results show that the OHC anomaly field is mainly composed of two leading modes, i.e., an in-phase oscillation mode and a zonal anti-phase oscillation mode. The in-phase oscillation mode exhibits strong interannual variability with periods of 2–5 years, which is well related to ENSO at a lead of 6 months, and experienced a regime shift in 1998. The anti-phase oscillation mode shows only a strong interannual variability with periods of 2–4 years well related to ENSO at a lag of 4 months. The composite analysis reveals that horizontal thermal advection mainly controlled by wind forcing plays a primary role in modulating the interannual OHC variability associated with ENSO, while net surface heat flux is the secondary source. And the OHC regime shift in 1998 primarily results from both the strong cold advection during the extremely strong El Niño in 1997 and the subsequent warm advection during the strong La Niña in 1998.

Keywords

The South China Sea Heat content spatial and temporal variation regime shift 

Notes

Acknowledgements

The authors duly acknowledge the various data sources for the freely available data: Japan Meteorological Agency data from http://rda.ucar.edu/datasets/ds285.3/, SODA data from http://apdrc.soest.hawaii.edu/dods/public_data/SODA/soda_pop2.2.4, NCEP reanalysis data from https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.derived.surfaceflux.html, and the ENSO indexes from http://www.cpc.ncep.noaa.gov/data/indices. Also, the authors gratefully acknowledges the National Natural Science Foundation of China (Project Nos. 41406012, 41576060), National Key R&D Program of China (Project No. 2016YFC0301203), Open Fund of Key Laboratory of Global Change and Marine-Atmospheric Chemistry, State Oceanic Administration, China (Project No. GCMAC1501), Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics (Second Institute of Oceanography) (Project No. SOED1613) and NSFC-Shandong Joint Fund for Marine Science Research Centers (Project No. U1406401).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Hongwei Liu
    • 1
    • 4
    Email author
  • Qilong Zhang
    • 1
    • 4
  • Chongguang Pang
    • 1
    • 4
  • Rongshuo Cai
    • 2
  • Qinghua Qi
    • 2
  • Dongmei Zheng
    • 3
  1. 1.Key Laboratory of Ocean Circulation and Waves, Institute of OceanologyChinese Academy of Sciences and Qingdao National Laboratory for Marine Science and TechnologyQingdaoPeople’s Republic of China
  2. 2.Key Laboratory of Global Change and Marine-Atmospheric Chemistry, Third Institute of OceanographyState Oceanic AdministrationXiamenChina
  3. 3.Marine Environmental Forecasting and Disaster Preventing and Reeducing Center of Liaoning ProvinceShenyangChina
  4. 4.Center for Ocean Mega-ScienceChinese Academy of SciencesQingdaoPeople’s Republic of China

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