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author:

Yu, Hongjuan (Yu, Hongjuan.) [1] | Zhang, Yong (Zhang, Yong.) [2] | Sun, Yu (Sun, Yu.) [3] | Sośnica, Krzysztof (Sośnica, Krzysztof.) [4] | Shen, Yi (Shen, Yi.) [5]

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Abstract:

Understanding the geophysical drivers of seasonal geocentre motion (GCM) variations remains challenging due to the complexity of Earth system interactions, limited data on individual mass redistribution components and model uncertainties. This study presents a comprehensive investigation of seasonal GCM signals from April 2002 to January 2024 using the Fingerprint Approach (FPA), which enables direct quantification of contributions from distinct Earth system components. Additionally, Multichannel Singular Spectrum Analysis (MSSA) is applied to quantify the influence of terrestrial water storage (TWS), atmosphere (ATM) and ocean (OCN) variability on seasonal GCM fluctuations. Correlation and lag analyses are employed to explore their temporal relationships and underlying geophysical linkages. The results reveal that TWS, ATM and OCN jointly explain 97.9 per cent, 98.1 per cent and 90.8 per cent of the seasonal variance in the X, Y and Z components of GCM, respectively. TWS exerts as the dominant contributor in the Y (66.4 per cent) and Z (67.9 per cent) components, while ATM and OCN each contribute less than 49 per cent to all components. Further analysis indicates that ATM, OCN and TWS exhibit varying lag relationships with GCM in the X and Z components, while TWS demonstrates a notably stronger correlation with GCM in the Y component. Importantly, an approximately 120-d periodic signal identified in GCM is, for the first time, linked to global precipitation variability, providing a novel geophysical interpretation. These findings enhance our understanding of climate-driven geophysical mass redistribution and offer new insights into the processes governing seasonal GCM variations. ©C The Author(s) 2025.

Keyword:

Digital storage Geodesy Geodetic satellites Gravitation Precipitation (meteorology) Spectrum analysis Time series analysis Uncertainty analysis

Community:

  • [ 1 ] [Yu, Hongjuan]School of Geomatics, Liaoning Technical University, Fuxin; 123000, China
  • [ 2 ] [Zhang, Yong]School of Geomatics, Liaoning Technical University, Fuxin; 123000, China
  • [ 3 ] [Sun, Yu]Key Lab of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Wulongjiang North Road, Fujian, Fuzhou; 350108, China
  • [ 4 ] [Sośnica, Krzysztof]Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, Grunwaldzka 53, Wroclaw; PL-50-357, Poland
  • [ 5 ] [Shen, Yi]School of Geographic Sciences, Xinyang Normal University, Xinyang; 464000, China

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Source :

Geophysical Journal International

ISSN: 0956-540X

Year: 2025

Issue: 1

Volume: 243

2 . 8 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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