A study of long-term sea level variability in the East China Sea  

作　　者：XU Ying LIN Mingsen ZHENG Quanan YE Xiaomin LI Junyi ZHU Benlu 

机构地区：[1]College of Information Science and Engineering, Ocean University of China [2]National Satellite Ocean Application Service,State Oceanic Administration [3]Key Laboratory of Space Ocean Remote Sensing and Application,State Oceanic Administration [4]Department of Atmospheric and Oceanic Science, University of Maryland, College Park [5]State Key Laboratory of Marine Environmental Science, College of Ocean & Earth Sciences, Xiamen University [6]Fujian Marine Forecasts

出　　处：《Acta Oceanologica Sinica》2015年第11期109-117,共9页海洋学报（英文版）

基　　金：The Public Science and Technology Research Funds Projects of Ocean under contract Nos 201105032 and 201305032;the National High Technology Research and Development Program(863 Program) of China under contract No.2013AA09A505;the National Natural Science Foundation of China under contract No.41506207

摘　　要：From the analyses of the satellite altimeter Maps of Sea Level Anomaly （MSLA） data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea （ECS）. Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition （EMD） method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of （2.5_＋0.4） mm/a which is slower than global average. The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.From the analyses of the satellite altimeter Maps of Sea Level Anomaly （MSLA） data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea （ECS）. Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition （EMD） method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of （2.5_＋0.4） mm/a which is slower than global average. The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.

关 键 词：East China Sea sea level variability correlation analysis empirical mode decomposition 

分 类 号：P731.23[天文地球—海洋科学] P731.27