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

南海海平面长期变化及其趋势研究

doi: 10.1007/s13131-016-0788-3

1.
中国海洋大学信息科学与工程学院, 山东青岛 266100;国家卫星海洋应用中心, 北京 100081;国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081
2.
国家卫星海洋应用中心, 北京 100081;国家海洋局空间海洋遥感与应用研究重点实验室, 北京 100081
3.
马里兰大学大气海洋系, 美国马里兰州学院公园市 20742

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出版历程
- 收稿日期: 2015-10-15
- 修回日期: 2015-12-07

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

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

摘要

摘要: 本文利用验潮站资料与南海研究区域全部MSLA网格点进行相关分析，以验潮站为基准研究南海海平面变化的区域相关性。发现在海平面变化的月均尺度上，东方站、海口站、汕尾站和闸坡站的变化与沿岸海域相关性大。在季节尺度上，夏季（5~9月）上述四站与太平洋区域不相关或负相关；冬季（11~2月）上述四站与太平洋区域相关性大，南海东部沿岸与太平洋区域相关性大。南海两个深海海盆内部在月、季、年时间尺度上均与沿岸海平面变化负相关。运用经验模态分解（EMD）方法得到了基于MSLA数据的南海海平面变化趋势和海平面上升速率分布，结果表明1993~2010年间，南海海平面变化趋势具有区域差异性，但整体海域趋势变化的波动性并不明显，18年来南海绝大部分区域海平面持续上升。南海研究区域海平面平均上升了90.8 mm，平均上升速率为（5.0 ±0.4）mm·a^-1，大幅高于全球平均值（3 mm·a^-1）。吕宋海峡南部-黄岩海山周边-中沙群岛-西沙群岛周边的海域海平面上升速率明显大于南海其他海域。
- 南海 /
- 海平面变化 /
- 趋势 /
- 相关分析 /
- 经验模态分解
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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南海海平面长期变化及其趋势研究

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

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