The sea level change of Sansha seas

WANG Hui; LIU Kexiu; ZHANG Jianli; FAN Wenjing

doi:10.3969/j.issn.0253-4193.2013.03.002

Article Contents

Article Navigation > Haiyang Xuebao > 2013 > 35(3): 11-17

WANG Hui, LIU Kexiu, ZHANG Jianli, FAN Wenjing. The sea level change of Sansha seas[J]. Haiyang Xuebao, 2013, 35(3): 11-17. doi: 10.3969/j.issn.0253-4193.2013.03.002

Citation:

WANG Hui, LIU Kexiu, ZHANG Jianli, FAN Wenjing. The sea level change of Sansha seas[J]. Haiyang Xuebao, 2013, 35(3): 11-17. doi: 10.3969/j.issn.0253-4193.2013.03.002

WANG Hui, LIU Kexiu, ZHANG Jianli, FAN Wenjing. The sea level change of Sansha seas[J]. Haiyang Xuebao, 2013, 35(3): 11-17. doi: 10.3969/j.issn.0253-4193.2013.03.002

Citation:

WANG Hui, LIU Kexiu, ZHANG Jianli, FAN Wenjing. The sea level change of Sansha seas[J]. Haiyang Xuebao, 2013, 35(3): 11-17. doi: 10.3969/j.issn.0253-4193.2013.03.002

PDF( 4617 KB)

The sea level change of Sansha seas

doi: 10.3969/j.issn.0253-4193.2013.03.002

National Marine Data and Information Service, Tianjin 300171, China

Received Date: 2012-07-13
Rev Recd Date: 2012-11-02

Abstract

Abstract

Based on the 19 years sea surface height(SSH) of tide gauge stations and satellite altimeter, the seasonal variation and the long term trend of SSH in the Sansha seas are investigated. The results show that the sea level takes on significant seasonal variation and regional characteristics in the Sansha seas. The SSH also shows prominent inter-annual variation besides the seasonal variation. The prominent terms are 2~3 a, 4~7 a and quasi-9 a. According to 19 a SSH data in the Sansha seas, the SSH shows obvious increasing trend, the average rising rate is 4.9 mm/a, the increasing range in the south of Paracel Islands is the most, the weakest in the western of Nansha Islands. Affected by abnormal atmospheric circulation and other climate events, fluctuations in the inter-annual variability of the sea level in 1998 and 2010. According to the analyzing results of the sea level forecasting model, it is predicted that in the coming 20 a, 40 a, 60 a and 90 a, sea level of Sansha seas will rise by 11 cm, 20 cm, 30 cm and 45 cm in comparison with the multi-year average.
- Sansha seas,
- seasonal sea level,
- inter-annual,
- increasing trend,
- prediction

FullText(HTML)

References(15)

References

Intergovernmental Panel on Climate Change(IPCC). Climate Change 2007: The Physical Science Basis. Contribution of Working Group Ⅰ to the Fourth Assessment Report of the intergovernmental Panel on Climate Change[R/OL]. Cambridge, U.K.:Cambridge University Press,2007, http://ipccwgl.ucar.edu/wgl/wgl-report.html.

方国洪,郑文振,陈宗镛,等.潮汐和潮流的分析和预报[M].北京:海洋出版社,1986:268-281.

周天华,陈宗镛,田晖,等.近几十年来中国沿海海面变化趋势的研究[J].海洋学报,14(2):1-8.

左军成,于宜法,陈宗镛.中国沿岸海平面变化原因的探讨[J].地球科学进展,1994,9(5):48-53.

田晖, 周天华,陈宗镛.平均海面变化的一种随机动态模型[J].青岛海洋大学学报, 1993, 23(1):32-42.

国家海洋局.2009年中国海平面公报.2010.

Rong Zengrui,Liu Yuguang,Zong Haibo,et al.Interannual sea level variability in the South China Sea and its response to ENSO[J].Global and Planetary Change,2007,55(4):257-272.

Ding X L,Zheng D W,Chen Y Q,et al.Sea level change in Hong Kong from tide gauge records[J].Journal of Geospatial Engineering,2002,4(1):41-49.

Yamagata T, Shibao Y, Umatani S. Inter annual variability of the Kuroshio Extension and its relation to the Southern Oscillation/El Nino[J]. J Oceanogr Soc, 1985, 41: 274-281.

郑文振,陈宗镛.我国海平面年速率的分布和长周期分潮的变化[J].海洋学报,1999,65-74.

Farge M. Wavelet transforms and their applications to turbulence[J]. Annu Rev Fluid Mech,1992, 24: 95-457.

Lau K-M, Weng Hengyi. Climate signal detection using wavlet transform:how to make a time series sing[J]. American Meteorological Society,1995.

于非,许一.东海海表温度长期变化趋势研究[J].海洋科学进展,2003,21(4):477-481.

Ho C R, Kuo N J, Zheng Q, et al. Dynamically active areas in the South China Sea detected from TOPEX/Poseidon satellite altimeter data[J]. Remote Sens Environ,2000, 71: 320-328.

于宜法.中国近海海平面变化研究进展[J].中国海洋大学学报(自然科学版),2004,34(5):713-719.

Relative Articles

Supplements(0)

Cited By

Proportional views