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<p>This study investigates magnetic field anomalies as precursors to the Mw7.7 Myanmar earthquake (March 28, 2025) using Swarm satellite data. We analyzed vector magnetic field (X, Y, Z) measurements over the Dobrovolsky region during the 10 days preceding the earthquake, applying cubic-spline filtering to identify residual anomalies. Our results revealed Y-component anomalies in 22 of 85 half-orbits, detectable up to 8 days before the event. Magnitude estimates were obtained using four empirical equations based on anomaly parameters such as duration, amplitude (“energy”), timing, and satellite–epicenter distance. Among these, the distance-based relation provided the most accurate estimate (M ≈ 7.2), showing reasonable agreement with the observed magnitude (M = 7.7). Interestingly, anomaly energy values consistently clustered within a narrow range (570–577), which may represent a characteristic signature of earthquake-related anomalies. These findings suggest that satellite-based magnetic anomalies could contribute to short-term earthquake forecasting systems, although further validation with larger datasets is needed to assess the robustness and general applicability of the approach.</p>

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Detection of pre-seismic magnetic field anomalies using Swarm satellite data: a case study of the 2025 Mw7.7 Myanmar earthquake

  • 期刊论文

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  • 发表日期：

    2025年10月22日

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  • Homayoon Alimoradi,
  • Habib Rahimi,
  • Angelo De Santis

摘要

This study investigates magnetic field anomalies as precursors to the Mw7.7 Myanmar earthquake (March 28, 2025) using Swarm satellite data. We analyzed vector magnetic field (X, Y, Z) measurements over the Dobrovolsky region during the 10 days preceding the earthquake, applying cubic-spline filtering to identify residual anomalies. Our results revealed Y-component anomalies in 22 of 85 half-orbits, detectable up to 8 days before the event. Magnitude estimates were obtained using four empirical equations based on anomaly parameters such as duration, amplitude (“energy”), timing, and satellite–epicenter distance. Among these, the distance-based relation provided the most accurate estimate (M ≈ 7.2), showing reasonable agreement with the observed magnitude (M = 7.7). Interestingly, anomaly energy values consistently clustered within a narrow range (570–577), which may represent a characteristic signature of earthquake-related anomalies. These findings suggest that satellite-based magnetic anomalies could contribute to short-term earthquake forecasting systems, although further validation with larger datasets is needed to assess the robustness and general applicability of the approach.