Analysis of the variation characteristics of the sea level in Zhoushan and the adjacent East China Sea from 1993 to 2021

doi:10.3969/j.issn.1001-909X.2025.01.007

Abstract

Abstract:

Based on the satellite altimeter data from January 1993 to December 2021, the least squares method and the ensemble empirical mode decomposition (EEMD) were used to analyze the long-term changes of the sea level in Zhoushan and the adjacent East China Sea and its influencing factors. The study found that the sea level in the study area was generally on an upward trend, and the upward trend was more obvious in the coastal waters on the east side of the Zhoushan Islands. The average linear rate was 0.36±0.10 cm/a, and the upward trend had been somewhat mitigated since 2018. The sea level in the study area showed obvious seasonal differences. Its linear rate was the largest in autumn (0.37±0.12 cm/a), followed by in winter, and slightly smaller in spring and summer (approximately 0.34±0.10 cm/a). The nonlinear change trend over the past 30 years showed that the upward rates in summer and autumn had almost remained unchanged, the upward rate in winter had shown a slowdown trend, and the upward trend in spring had been accelerating. There was a trend of increasing annual amplitude of the sea level in the study area. The long-term changes of the sea level were closely related to the seawater thermal expansion effect caused by temperature and the water increase-decrease effect caused by changes in wind stress.

Key words: sea level change, Zhoushan sea areas, East China Sea, the ensemble empirical model decomposition, linear trend, nonlinear trend

CLC Number:

P731.23

JIN Jie, CHEN Yujie, YAO Yongheng, ZHANG Siyuan, HU Zhentao, DING Mengrong, JIA Bin. Analysis of the variation characteristics of the sea level in Zhoushan and the adjacent East China Sea from 1993 to 2021[J]. Journal of Marine Sciences, 2025, 43(1): 69-78.

Figures/Tables 14

Fig.1 Map of study area

Fig.2 The spatial variation of the multi-year average sea level in Zhoushan and its adjacent sea areas during 1993-2021

Fig.3 The spatial variation of the multi-year average sea level in each season during 1993-2021

Fig.4 The spatial distribution of the linear rising rate of the sea level in the study area during 1993-2021

Fig.5 The spatial distribution of the average linear rising rate of the sea level in each season during 1993-2021

Fig.6 The linear change trend of the sea level in the study area during 1993-2021 (The dots represent the annual or seasonal mean sea level and the dashed lines represent the linear fitting results.)

Fig.7 The spatial distribution of nonlinear variation of annual mean sea level in the study area during 1993-2021

Fig.8 The spatial distribution of nonlinear variation of mean sea level in spring in the study area during 1993-2021

Fig.9 The spatial distribution of nonlinear variation of mean sea level in autumn in the study area during 1993-2021

Fig.10 Nonlinear trends (a) and its annual change rate (b) of sea level during 1993-2021

Fig.11 The spatial distribution of climatological annual-mean sea surface temperature (a) and its linear variation (b) during 1993-2021

Fig.12 Time series of the first(a) and second principal component (b) for the empirical orthogonal decomposition of sea surface temperature during 1993-2021

Fig.13 The spatial distribution of multi-year average sea surface wind (a) and its linear variation (b) during 1993-2021

Fig.14 Time series of the first (a) and second principal component (b) for the empirical orthogonal decomposition of sea surface wind during 1993-2021

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