A globally applicable framework for earthquake precursor identification using gravity gradient tensor anomalies from satellite gravimetry

Abstract

Earthquakes remain one of the most unpredictable natural disasters, yet forecasting such events is critical for mitigating their devastating impact. In this study, we introduce a novel framework for earthquake forecasting by analyzing satellite remote sensing data. Specifically, we use Gravity Gradient Tensor (GGT) anomalies derived from the GRACE satellite mission as a prospective pre-seismic precursor. Unlike traditional forecasting methods that are often limited to point-specific epicentral data or complex machine learning ‘black-box’ models, our proposed framework offers the distinct advantage of physical interpretability and continuous global scalability. Our work directly addresses a key debate in the literature by demonstrating the statistical significance of these anomalies, thereby moving beyond previous isolated case studies. Our proposed method is physically interpretable and operates on a continuous, global scale.

By analyzing historical GRACE data from 2002 to 2016, we developed a unique threshold-based methodology to extract GGT anomalies across five distinct tectonic regions: Japan, Sumatra, Chile, China, and the India–Nepal belt. The framework employs robust statistical filtering to minimize noise and relies on a regionalized approach to establish a dynamic, data-driven threshold. Our results demonstrate high predictive accuracy, with a regional performance of up to 96% true positives in a highly seismic region and as low as 0% false positives. Our method achieves an average true prediction rate of 91% and an average false alarm rate of 13% across all regions. Quantitative comparisons confirm that our model provides superior reliability and significantly lower false alarm rates compared to conventional machine learning classifiers. This research confirms the potential of GGT anomalies as a valuable precursor and establishes a scalable, data-driven framework for global earthquake forecasting, highlighting a new frontier for satellite geodesy applications in solid Earth science.