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author:

Li, Y. (Li, Y..) [1] | Guo, J. (Guo, J..) [2] | Sun, Y. (Sun, Y..) [3] | Zhou, J. (Zhou, J..) [4] | Sun, H. (Sun, H..) [5]

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Scopus

Abstract:

Regional relative sea level changes are most relevant for coastal communities and remain challenging to understand. China’s adjacent seas are among the world’s most vulnerable regions to sea level rise. This paper investigates the sea level budgets in China’s adjacent seas over the past 20 years. We use multiple time-varying gravity field data and steric data to assess the uncertainties of some components in the sea level budget and the contributions of mass loss from ice sheets, glaciers, and terrestrial water storage changes to regional relative sea level changes were estimated using sea level fingerprints. The sea level budget results based on ensemble mean data show that the root mean square errors of the budget residuals in the Bohai Sea, Yellow Sea, East China Sea, South China Sea, and Northwest Pacific are 40±3 mm, 52±4 mm, 36±2 mm, 23±2 mm, and 11±1 mm, respectively. A single dataset fails to close the long-term sea level trends for all regions within a 65% confidence interval. We discussed the impacts of each component on the budget residuals and identified steric data and the ocean dynamics model as the main reasons for the excessive residuals. The de-aliasing product of the GRACE satellite, AOD1B model, is primarily responsible for the strong interannual signals in the residuals of the sea level budget in the Bohai Sea, Yellow Sea, and East China Sea. © The Author(s) 2025.

Keyword:

GRACE Regional sea level budget Sea level fingerprints Steric

Community:

  • [ 1 ] [Li Y.]State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
  • [ 2 ] [Li Y.]College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China
  • [ 3 ] [Li Y.]University of Chinese Academy of Sciences, Beijing, China
  • [ 4 ] [Guo J.]College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China
  • [ 5 ] [Sun Y.]Key Lab of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou, China
  • [ 6 ] [Zhou J.]State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
  • [ 7 ] [Zhou J.]University of Chinese Academy of Sciences, Beijing, China
  • [ 8 ] [Sun H.]State Key Laboratory of Precision Geodesy, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
  • [ 9 ] [Sun H.]University of Chinese Academy of Sciences, Beijing, China

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Source :

Scientific Reports

ISSN: 2045-2322

Year: 2025

Issue: 1

Volume: 15

3 . 8 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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