A study of sea level variability and its long-term trend in the South China Sea

XU Ying; LIN Mingsen; ZHENG Quan'an; SONG Qingtao; YE Xiaomin

doi:10.1007/s13131-016-0788-3

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Article Navigation > Acta Oceanologica Sinica > 2016 > 35(9): 22-33

XU Ying, LIN Mingsen, ZHENG Quan'an, SONG Qingtao, YE Xiaomin. A study of sea level variability and its long-term trend in the South China Sea[J]. Acta Oceanologica Sinica, 2016, 35(9): 22-33. doi: 10.1007/s13131-016-0788-3

Citation:

XU Ying, LIN Mingsen, ZHENG Quan'an, SONG Qingtao, YE Xiaomin. A study of sea level variability and its long-term trend in the South China Sea[J]. Acta Oceanologica Sinica, 2016, 35(9): 22-33. doi: 10.1007/s13131-016-0788-3

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A study of sea level variability and its long-term trend in the South China Sea

doi: 10.1007/s13131-016-0788-3

1.
College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China;National Satellite Ocean Application Service, State Oceanic Administration, Beijing 100081, China;Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration, Beijing 100081, China
2.
National Satellite Ocean Application Service, State Oceanic Administration, Beijing 100081, China;Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration, Beijing 100081, China
3.
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA

Received Date: 2015-10-15
Rev Recd Date: 2015-12-07

Abstract

Abstract

On the basis of the satellite maps of sea level anomaly (MSLA) data and in situ tidal gauge sea level data, correlation analysis and empirical mode decomposition (EMD) are employed to investigate the applicability of MSLA data, sea level correlation, long-term sea level variability (SLV) trend, sea level rise (SLR) rate and its geographic distribution in the South China Sea (SCS). The findings show that for Dongfang Station, Haikou Station, Shanwei Station and Zhapo Station, the minimum correlation coefficient between the closest MSLA grid point and tidal station is 0.61. This suggests that the satellite altimeter MSLA data are effective to observe the coastal SLV in the SCS. On the monthly scale, coastal SLV in the western and northern part of SCS are highly associated with coastal currents. On the seasonal scale, SLV of the coastal area in the western part of the SCS is still strongly influenced by the coastal current system in summer and winter. The Pacific change can affect the SCS mainly in winter rather than summer and the affected area mostly concentrated in the northeastern and eastern parts of the SCS. Overall, the average SLR in the SCS is 90.8 mm with a rising rate of (5.0±0.4) mm/a during 1993-2010. The SLR rate from the southern Luzon Strait through the Huangyan Seamount area to the Xisha Islands area is higher than that of other areas of the SCS.
- South China Sea,
- sea level variability,
- correlation analysis,
- empirical mode decomposition,

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References(36)

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