Multi-Station ULF Geomagnetic Analysis for Enhanced Earthquake Precursor Identification
DOI:
Abstract
Western Java’s ongoing seismic hazard highlights the need for understanding earthquake precursor mechanisms. Recent studies have increasingly focused on ultra-low-frequency (ULF) signals that may carry information related to pre-seismic phases. However, a key difficulty persists: isolating faint, localized lithospheric signals from the stronger ionospheric activity. Most previous investigations in Western Java have relied on single-sensor measurements, a limitation that complicates the detection of true anomalies. This study addresses this limitation by examining daily ULF variations before the 2023 Banten earthquake sequence (M5.4 and M5.1), using a multi-point setup to distinguish lithospheric signals from stronger background ionospheric noise. Continuous three-component geomagnetic data from two primary stations near the epicenter, Serang (SRG) and Sukabumi (SKB), and a distant reference station (TRD) in East Kalimantan were analyzed. The Z/G spectral density ratio was calculated in the 0.01–0.09 Hz range, using only data from quiet nighttime intervals (15:00–21:00 UTC) and magnetic storm-free days (Dst > -50 nT). The results identified and filtered false positive anomalies by correlating them with signals at the TRD reference station. Two distinct, validated pre-seismic anomalies were identified, concentrated in the 0.04–0.08 Hz band: a multi-station anomaly at H-20 (at SRG and SKB) and a localized, broadband anomaly at H-15 (at SRG). Both emissions were absent at TRD, confirming their lithospheric origin. These results highlight the importance of a multi-station approach for reliably identifying lithospheric ULF anomalies. However, this study is limited to a specific event sequence. Future investigations should focus on integrating broader sensor networks and ionospheric models across multiple seismic events to validate these findings globally and enhance false positive rejection methods.
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