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

XU Ying; LIN Mingsen; ZHENG Quanan; YE Xiaomin; LI Junyi; ZHU Benlu

doi:10.1007/s13131-015-0754-0

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Article Navigation > Acta Oceanologica Sinica > 2015 > 34(11): 109-117

XU Ying, LIN Mingsen, ZHENG Quanan, YE Xiaomin, LI Junyi, ZHU Benlu. A study of long-term sea level variability in the East China Sea[J]. Acta Oceanologica Sinica, 2015, 34(11): 109-117. doi: 10.1007/s13131-015-0754-0

Citation:

XU Ying, LIN Mingsen, ZHENG Quanan, YE Xiaomin, LI Junyi, ZHU Benlu. A study of long-term sea level variability in the East China Sea[J]. Acta Oceanologica Sinica, 2015, 34(11): 109-117. doi: 10.1007/s13131-015-0754-0

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

doi: 10.1007/s13131-015-0754-0

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, Maryland 20742, USA
4.
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland 20742, USA;State Key Laboratory of Marine Environmental Science, College of Ocean & Earth Sciences, Xiamen University, Xiamen 361102, China
5.
Fujian Marine Forecasts, Fuzhou 350003, China

Received Date: 2015-03-19
Rev Recd Date: 2015-06-02

Abstract

Abstract

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.
- East China Sea,
- sea level variability,
- correlation analysis,
- empirical mode decomposition

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References

Baart F, Koningsveld M V, Stive M J F. 2012. Trends in sea-level trend analysis. Journal of Coastal Research, 28(2): 311-315

Bindoff N, Willebrand J, Artale V, et al. 2007. Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press, 385-432

Cabanes C, Cazenave A, Le Provost C. 2001. Sea level rise during past 40 years determined from satellite and in situ observations. Sci-ence, 294(5543): 840-842

Cazenave A, Nerem R S. 2004. Present-day sea-level change observa-tions and causes. Reviews of Geophysics, 42: RG3001

Carton J A, Giese B S, Grodsky S A. 2005. Sea level rise and the warm-ing of the oceans in the Simple Ocean Data Assimilation (SODA) ocean reanalysis. Journal of Geophysical Research, 110: C09006

Cheng Yongcun, Andersen O B, Knudsen P. 2012. Integrating Non-Tidal Sea Level data from altimetry and tide gauges for coastal sea level prediction. Advances in Space Research, 50(8): 1099-1106

Church J A, Gregory J M, Huybrechts P, et al. 2001. Changes in sea level, in Climate Change 2001: The Scientific Basis, Contribu-tion of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. New York, NY, USA: Cambridge University Press, 639-693

Church J A, White N J, Coleman R, et al. 2004. Estimates of the region-al distribution of sea level rise over the 1950-2000 period. Journal of Climate, 17(13): 2609-2625

Church J A, White N J. 2006. A 20th century acceleration in global sea-level rise. Geophysical Research Letters, 33: L01602

Church J A, White N J. 2011. Sea-level rise from the late 19th to the early 21st Century. Surveys in Geophysics, 32(4-5): 585-602

Dean R G, Houston J R. 2013. Recent sea level trends and accelera-tions: Comparison of tide gauge and satellite results. Coastal Engineering, 75: 4-9

Douglas B C. 1992. Global sea level acceleration. Journal of Geophys-ical Research, 97(C8): 12699-12706

Ezer T. 2013. Sea level rise, spatially uneven and temporally unsteady: Why the U. S. East Coast, the global tide gauge record, and the global altimeter data show different trends. Geophysical Re-search Letters, 40(20): 5439-5444

Fenoglio-Marc L. 2002. Long-term sea level change in the Mediter-ranean Sea from multi-satellite altimetry and tide gauges. Phys-ics and Chemistry of the Earth, Parts A/B/C, 27(32-34): 1419-1431

Fischlin A, Midgley G F, et al. 2007. Ecosystems, their properties, goods and services. Climate Change 2007: Impacts, Adaptation and Vulnerablity. Contribution of Working Group II to the Fouth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge: Cambridge University Press, 211-272

Guo Binghuo, Huang Zhenzong, Li Peiying, et al. 2004. The Marine Environment of Chinese Offshore Waters and Adjacent Sea Area (in Chinese). Beijing: China Ocean Press

Huang N E, Shen Z, Long S R, et al. 1998. The empirical mode decom-position and the Hilbert spectrum for nonlinear and non-sta-tionary time series analysis. Proc Roy Soc Land A, 454(1971): 903-995

Huang N E, Shen S S P. 2005. Hilbert-Huang Transform and Its Ap-plications. Hackensack, NJ, USA: World Scientific Publishing Co. Pte. Ltd.

IPCC. 2007. Climate Change: The Physical Science Basis.Contribu-tion of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA: Cambridge Uni-versity Press

Liu Xueyuan, Liu Yuguang, Guo Lin, et al. 2009. Change of mean sea level of low-frequency on East China Sea and its relation with ENSO. Journal of Geodesy and Geodynamics, 29(4): 55-63

Mangiarotti S. 2007. Coastal sea level trends from TOPEX-Poseidon satellite altimetry and tide gauge data in the Mediterranean Sea during the 1990s. Geophys J Int, 170(1): 132-144

Nicholls R J, Cazenave A. 2010. Sea-level rise and its impact on coastal zones. Science, 328(5985): 1517-1520

Rahmstorf S. 2007. A Semi-empirical approach to projecting future Sea-level rise. Science, 315(5810): 368-370

Syvitski J P M, Kettner A J, et al. 2009. Sinking deltas due to human activities. Nature Geoscience, 2(10): 681-686

Trisirisatayawong I, Naeije M, Simons W, et al. 2011. Sea level change in the Gulf of Thailand from GPS-corrected tide gauge data and multi-satellite altimetry. Global and Planetary Change, 76(3-4): 137-151

Volkov D L, Larncol G, Dorandeu J. 2007. Improving the quality of satellite altimetry data over continental shelves. Journal of Geo-physical Research, 112: C003765

Wang Guodong, Kang Jiancheng, Han Guoqi, et al. 2011. Analysis and prediction of sea-level-change multi-scale cycle for East China Sea. Advances in Earth Science, 26(6): 678-684

Zuo Juncheng, Yang Yiqiu, Zhang Jianli, et al. 2013. Prediction of China's submerged coastal areas by sea level rise due to cli-mate change. Journal of Ocean University of China, 12(3): 327-334

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