2025-09-02 カリフォルニア大学サンタバーバラ校(UCSB)
Photo Credit:Elena Zhukova
There’s a cacophony of acoustic signals below the range of human hearing, many quite intense, that you can pick up with the right “ears.”
＜関連情報＞
- https://news.ucsb.edu/2025/022000/scientists-tune-surfs-hidden-signals
- https://academic.oup.com/gji/advance-article/doi/10.1093/gji/ggaf317/8236357
砕ける海波からの過渡的地震音響信号の同定：テンプレートマッチングと個別の波打ちイベントの位置特定 Identification of transient seismo-acoustic signals from crashing ocean waves: template matching and location of discrete surf events
Jeremy W Francoeur , Robin S Matoza , Hugo D Ortiz , Rodrigo De Negri
Geophysical Journal International Published:15 August 2025
DOI:https://doi.org/10.1093/gji/ggaf317
Summary
Crashing ocean waves, or surf, have previously been identified as persistent generators of coherent infrasound signals from 0.5 to 20 Hz. Here, we demonstrate that infrasonic and seismic (seismo-acoustic) signals from surf are composed of repetitive transient events which can be detected and characterized using template matching. Using data collected from a series of field experiments designed to study seismo-acoustic surf signals in Santa Barbara, California, we show that source regions of these events can be constrained primarily to just offshore of a local coastal headland using a reverse-time-migration implementation on a small spatial scale (<5 km2). Our data include one continuously running infrasound sensor (September 2022–July 2023) to examine temporal signal evolution, complemented by several short-duration campaigns involving various infrasound arrays, co-located seismometers, and video recordings. Throughout varied oceanographic and atmospheric conditions, we detect up to tens of thousands of independent surf repeaters per day over the course of a year. The amplitudes of detected infrasound signals are correlated with offshore significant wave height and local wind speed. We identify coincident arrivals of seismic and infrasound signals with similar spectral characteristics, suggesting a linked source mechanism locally producing both the seismic and acoustic transient signals. Source regions estimated from array- and network-based methods correspond to the surf zone as seen in video footage, and the directions of selected transient signals align with the location of a rocky reef shelf nearshore. This work showcases the ability to extract near-real-time information about the coastal sea state from seismic and acoustic signal features.
