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

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 r...

Full description

Saved in:
Bibliographic Details
Published inActa oceanologica Sinica Vol. 35; no. 9; pp. 22 - 33
Main Authors Xu, Ying, Lin, Mingsen, Zheng, Quan’an, Song, Qingtao, Ye, Xiaomin
Format Journal Article
LanguageEnglish
Published Beijing The Chinese Society of Oceanography 01.09.2016
Springer Nature B.V
College of Information Science and Engineering, 0cean University of China, Qingdao 266100, China%National Satellite 0cean Application Service, State 0ceanic Administration, Beijing 100081, China%Department of Atmospheric and 0ceanic Science, University of Maryland, College Park, MD 20742, USA
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary: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 during1993–2010.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.
Bibliography: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 during1993–2010.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.
11-2056/P
South China Sea, sea level variability, correlation analysis, empirical mode decomposition
ISSN:0253-505X
1869-1099
DOI:10.1007/s13131-016-0788-3