南海海平面变化与ENSO的关系（英文）
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- 论文作者：常乐 ; 易爽 ; 孙文科
- 年：2016
- 作者机构：中国科学院大学;
- 会议召开时间：2016-10-15
- 会议录名称：2016中国地球科学联合学术年会论文集（三十一）——专题55：空间大地测量与地壳动力学、专题56：空间大地测量的全球变化研究、专题57：地震大地测量学
- 英文会议录名称：Proceedings of 2016 Annual Meeting of Chinese Geoscience Union(CGU)
- 语种：英文
- 分类号：P731.23;P732
- 学会代码：ZGDW
- 会议名称：2016中国地球科学联合学术年会
- 会议地点：中国北京
- 主办单位：中国地球物理学会、中国地震学会、全国岩石学与地球动力学研讨会组委会、中国地质学会构造地质学与地球动力学专业委员会、中国地质学会区域地质与成矿专业委员会
- 学会名称：中国地球物理学会
- 页数：2
- 文件大小：1113k
- 原文格式：D
- 会议级别：全国
摘要
Sea level variation is inhomogeneous in different locations,even in the same sea area.In this work,altimetry data is used to analyze the spatial characteristics of sea level change in the South China Sea.Overall,the average sea level variation is correlated with El Ni?o-Southern Oscillation(ENSO)with a coefficient of 0.65 and a time lag of 3 months;however,the coefficient value and the time lag vary in different areas.According to the spatial pattern of the maximum correlation and corresponding time lag,we divided the South China Sea into four parts:western shallow ocean(WSO),northwestern deep ocean(NDO),southwestern deep ocean(SDO),and eastern deep ocean(EDO).Their correlations with ENSO are calculated separately and compared with each other.It is found that the WSO has the modest interannual fluctuation and rising rate,implying that the coast areas are less influenced,comparing with the islands in the deep oceans.NDO has the strongest interannual variation and rising rate,which means the Xisha and Zhongsha islands here is the most susceptible to the ocean dynamics.Our work sheds light on the spatial variability in the changing patterns of sea level in the South China Sea.
Sea level variation is inhomogeneous in different locations, even in the same sea area. In this work, altimetry data is used to analyze the spatial characteristics of sea level change in the South China Sea. Overall, the average sea level variation is correlated with El Ni?o-Southern Oscillation(ENSO) with a coefficient of 0.65 and a time lag of 3 months; however, the coefficient value and the time lag vary in different areas. According to the spatial pattern of the maximum correlation and corresponding time lag, we divided the South China Sea into four parts: western shallow ocean(WSO), northwestern deep ocean(NDO), southwestern deep ocean(SDO), and eastern deep ocean(EDO). Their correlations with ENSO are calculated separately and compared with each other. It is found that the WSO has the modest interannual fluctuation and rising rate, implying that the coast areas are less influenced, comparing with the islands in the deep oceans. NDO has the strongest interannual variation and rising rate, which means the Xisha and Zhongsha islands here is the most susceptible to the ocean dynamics. Our work sheds light on the spatial variability in the changing patterns of sea level in the South China Sea.
Sea level variation is inhomogeneous in different locations, even in the same sea area. In this work, altimetry data is used to analyze the spatial characteristics of sea level change in the South China Sea. Overall, the average sea level variation is correlated with El Ni?o-Southern Oscillation(ENSO) with a coefficient of 0.65 and a time lag of 3 months; however, the coefficient value and the time lag vary in different areas. According to the spatial pattern of the maximum correlation and corresponding time lag, we divided the South China Sea into four parts: western shallow ocean(WSO), northwestern deep ocean(NDO), southwestern deep ocean(SDO), and eastern deep ocean(EDO). Their correlations with ENSO are calculated separately and compared with each other. It is found that the WSO has the modest interannual fluctuation and rising rate, implying that the coast areas are less influenced, comparing with the islands in the deep oceans. NDO has the strongest interannual variation and rising rate, which means the Xisha and Zhongsha islands here is the most susceptible to the ocean dynamics. Our work sheds light on the spatial variability in the changing patterns of sea level in the South China Sea.
引文
Cheng,X.and Qi,Y.(2007).Trends of sea level variations in the South China Sea from merged altimetry data.Global and Planetary Change.57:371-382
Cheng,X.,Qi,Y.(2010).On steric and mass-induced contributions to the annual sea-level variations in the South China Sea.Global and Planetary Change.72:227-233.
Fuwen Qiu et al.2012.Anomalous oceanic characteristics in the South China Sea associated with the large-scale forcing during 2006-2009[J].J Mar Syst,100-101(0):9-18.
Geruo,A.,J.Wahr,and S.Zhong(2013),Computations of the viscoelastic response of a 3-D compressible Earth to surface loading:An application to Glacial Isostatic Adjustment in Antarctica and Canada,Geophys.J.Int.,192(2),557-572.
Guohong Fang et al.2006.Trends and interannual variability of the South China Sea surface winds,surface height,and surface temperature in the recent decade[J].J Geophys Res,111:C11S16.
Wendong Fang et al.2006.Low frequency variability of South China Sea surface circulation from 11 years of satellite altimeter data[J].Geophys Res Lett,33:L22612.
Cheng,X.,Qi,Y.(2010).On steric and mass-induced contributions to the annual sea-level variations in the South China Sea.Global and Planetary Change.72:227-233.
Fuwen Qiu et al.2012.Anomalous oceanic characteristics in the South China Sea associated with the large-scale forcing during 2006-2009[J].J Mar Syst,100-101(0):9-18.
Geruo,A.,J.Wahr,and S.Zhong(2013),Computations of the viscoelastic response of a 3-D compressible Earth to surface loading:An application to Glacial Isostatic Adjustment in Antarctica and Canada,Geophys.J.Int.,192(2),557-572.
Guohong Fang et al.2006.Trends and interannual variability of the South China Sea surface winds,surface height,and surface temperature in the recent decade[J].J Geophys Res,111:C11S16.
Wendong Fang et al.2006.Low frequency variability of South China Sea surface circulation from 11 years of satellite altimeter data[J].Geophys Res Lett,33:L22612.