Coherence-Based Characterization of a Long-Period Monochromatic Seismic Signal

Abstract

Continuous seismic data analysis identifies signals related to physical processes within the Earth or on its surface. Characterizing seismic signals yields insights into source processes and Earth's structural features. Global seismic network analysis of long-period (25–100 s) surface waves has detected seismic events not identified through high-frequency body wave analysis. However, detecting long-lasting monochromatic signals with narrow spectral peaks, which carry valuable information about geological and environmental processes, remains challenging on a global scale. We developed a coherence-based approach to characterize long-period monochromatic signals on a global scale. In addition to signals originating from the Gulf of Guinea, Vanuatu islands, and a submarine volcano, we observed a previously unidentified signal originating from the Canadian Arctic, likely associated with glacier dynamics. Our approach explores long-period monochromatic seismic signals in continuous seismic data, providing a foundation for future studies to characterize the physical processes generating these signals on Earth's surface.