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Multi-Channel Singular Spectrum Analysis on Geocenter Motion and Its Precise Prediction.

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  • 1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China.

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Summary

Geocenter motion (GCM) analysis reveals significant seasonal patterns and long-term trends. A novel method combining multi-channel singular spectrum analysis (MSSA) with linear and ARMA models accurately predicts future GCM parameters.

Keywords:
autoregressive moving averagegeocenter motionmulti-channel singular spectrum analysisprediction

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Area of Science:

  • Earth System Science
  • Geophysics
  • Satellite Geodesy

Background:

  • Geocenter motion (GCM) reflects Earth's mass redistribution and interactions between solid Earth and surface loading.
  • Understanding GCM is crucial for monitoring Earth system dynamics.

Purpose of the Study:

  • To analyze geocenter motion (GCM) data using advanced time series analysis.
  • To extract periodic components and long-term trends in GCM.
  • To develop a predictive model for real-time GCM parameter estimation.

Main Methods:

  • Multi-channel singular spectrum analysis (MSSA) applied to satellite laser ranging data (1993-2017).
  • Identification of seasonal (annual, semi-annual, etc.) and long-period terms.
  • Integration of MSSA with linear models (LM) and autoregressive moving average (ARMA) for prediction.

Main Results:

  • GCM exhibits dominant annual, semi-annual, quasi-0.6-year, and quasi-1.5-year seasonal variations in X, Y, and Z directions.
  • Significant long-period term of 6.09 years identified.
  • Non-linear trends of 0.05, 0.04, and -0.10 mm/yr observed in the three directions.
  • Predicted GCM parameters with root mean squared errors (RMSE) of 1.53 mm (X), 1.08 mm (Y), and 3.46 mm (Z) for a 2-year forecast.

Conclusions:

  • The study successfully identified key periodicities and trends in geocenter motion.
  • The combined MSSA-LM-ARMA model provides accurate predictions of GCM parameters.
  • This predictive capability is valuable for real-time monitoring of Earth system mass changes.