DOI: 10.3390/rs18152574 ISSN: 2072-4292

Spatial Correspondence Between Seismic b-Value Stress Localization and Pre-Earthquake GNSS-TEC Anomalies in Southern California and Northern Baja California

Karan Nayak, Roberto Colonna

Identifying reliable earthquake precursors remains a major challenge in geophysics. Among the most widely investigated candidates are seismicity-based indicators, such as the Gutenberg–Richter b-value, and ionospheric disturbances expressed through Total Electron Content (TEC) anomalies. However, these observables are commonly investigated independently, and their quantitative spatial relationship remains poorly constrained. This study investigates the spatio-temporal evolution of b-values and GNSS-derived TEC anomalies preceding the 2019 Ridgecrest (Mw 7.1) and 2010 Baja California (Mw 7.2) earthquakes. Temporal analyses reveal progressive reductions in b-values prior to both earthquakes, while spatial mapping identifies localized low-b regions with thresholds of b≤0.88 for Ridgecrest and b≤0.83 for Baja California. Independent TEC analyses reveal negative ionospheric anomalies of approximately 2.34 TECU and 4.27 TECU, occurring 9–10 days and ~2 days before the respective mainshocks under geomagnetically quiet conditions. A multi-scale centroid-based spatial validation framework, incorporating both global and local low-b centroids together with Monte Carlo randomization tests, demonstrates that the dominant low-b regions consistently exhibit the closest spatial correspondence with the TEC depletion. The observed centroid separations occupied only a limited fraction of the theoretical earthquake preparation zone, with normalized distances of 0.33 and 0.24 for the global centroids, decreasing to 0.32 and 0.17, respectively, for the dominant local low-b regions. Overall, the results support a stress-conditioned lithosphere–atmosphere–ionosphere coupling framework and demonstrate that integrating long-term seismic stress evolution with GNSS-derived ionospheric observations provides an objective multi-parameter framework for investigating the spatial organization of earthquake preparation processes.

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