Japan Geoscience Union Meeting 2025

Presentation information

[E] Poster

S (Solid Earth Sciences ) » S-SS Seismology

[S-SS07] Environmental Seismology: from deep earth to surface process

Sun. May 25, 2025 5:15 PM - 7:15 PM Poster Hall (Exhibition Hall 7&8, Makuhari Messe)

convener:Ling Bai(Institute of Tibetan Plateau Research, Chinese Academy of Sciences), Kiwamu Nishida(Earthquake Research Institute, University of Tokyo), Yifei Cui(Tsinghua University), Yuzo Ishikawa(Shizuoka university)

5:15 PM - 7:15 PM

[SSS07-P02] A global search for long-lasting long-period monochromatic signals

*Tomoya Takano1, Piero Poli2 (1.National Research Institute for Earth Science and Disaster Resilience, 2.Università di Padova)

Keywords:monochromatic seismic signal, surface wave, array analysis

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.