17:15 〜 19:15
[SSS07-P02] 長時間継続する長周期単色微動の探索
キーワード：単色微動、表面波、アレイ解析
Continuous seismic data analysis reveals signals associated with physical processes within the Earth or on its surface. At periods longer than 25 s, back-propagation of surface waves recorded by global seismic networks has identified previously unrecognized seismic events that are absent from traditional earthquake catalogs. Previous studies discovered unidentified events, most of which occur in polar regions.
However, global surface wave-based methods have limited ability to detect long-lasting and monochromatic signals generated by volcanic, environmental, and oceanic processes due to their narrow frequency bands, long duration, and unclear onset. Characterizing such monochromatic signals may provide valuable insights into volcanic activity, ocean waves, and glacier dynamics.
In this study, we apply a coherence-based approach to characterize long-period monochromatic seismic signals. We compute temporal coherence, averaged across all station pairs within a regional seismic array in Japan from 2003 to 2022. Our analysis identifies several periods with coherent, long-lasting monochromatic signals. We examine both known and previously unreported signals originating from the Gulf of Guinea, Vanuatu, the Fukutoku-Okanoba submarine volcano, and the Canadian Arctic Islands. Using inter-station arrival times derived from cross-correlations between global seismic stations, we estimate source locations of these signals. Additionally, we apply the matched-filtering method to identify repeating events. Our findings establish a foundation for systematically detecting and characterizing volcanic and environmental signals, which are increasing due to ongoing climate change.
However, global surface wave-based methods have limited ability to detect long-lasting and monochromatic signals generated by volcanic, environmental, and oceanic processes due to their narrow frequency bands, long duration, and unclear onset. Characterizing such monochromatic signals may provide valuable insights into volcanic activity, ocean waves, and glacier dynamics.
In this study, we apply a coherence-based approach to characterize long-period monochromatic seismic signals. We compute temporal coherence, averaged across all station pairs within a regional seismic array in Japan from 2003 to 2022. Our analysis identifies several periods with coherent, long-lasting monochromatic signals. We examine both known and previously unreported signals originating from the Gulf of Guinea, Vanuatu, the Fukutoku-Okanoba submarine volcano, and the Canadian Arctic Islands. Using inter-station arrival times derived from cross-correlations between global seismic stations, we estimate source locations of these signals. Additionally, we apply the matched-filtering method to identify repeating events. Our findings establish a foundation for systematically detecting and characterizing volcanic and environmental signals, which are increasing due to ongoing climate change.