Analysis of Fingerprint-Derived Geocenter Motion Time Series Using Multichannel Singular Spectrum Analysis

Summary Understanding the geophysical drivers of seasonal geocenter 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 in 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-day 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.