Thread: IRIS Webinar: Ambient Noise Interferometry as a Real-Time Volcanic Eruption Forecasting Tool

Started: 2022-04-05 09:14:37
Last activity: 2022-04-05 09:14:37
Topics: Webinars
Please register for our next IRIS Webinar on Thursday, April 14th at 2PM Eastern

Title: Somewhere Over the Rainbow: Ambient Noise Interferometry as a Real-Time Volcanic Eruption Forecasting Tool

Presenter: Dr. Ninfa Bennington, Research Geophysicist, U.S. Geological Survey, Hawaiian Volcano Observatory

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In ambient noise interferometry (ANI), ubiquitous ambient noise signals are capitalized on to probe the subsurface of the Earth for temporal changes in seismic velocity. Previous studies have applied ANI to seismic data recorded at active volcanic systems and have identified volcanic activity such as pre-eruption inflation, eruption onset, and co-eruptive deformation. For this reason, ANI has become a methodology of great interest to volcano observatories worldwide. However, retrospective ANI studies have the advantage of knowing when a particular volcanic event was observed (e.g. onset of an eruption), allowing the investigators to mine that time window of seismic data for changes in seismic velocity that occurred contemporaneously.

Previous ANI studies have shown that seasonal variations in the hydrologic cycle cause observable changes in seismic velocity. The amount of annual rainfall, snowpack, and/or snow melt, as well as the exact timing of these events, causes changes in both the amplitude and timing of seasonal velocity changes observed from year-to-year. Thus, in regions of volcanic activity, a grand challenge to using ANI as a forecasting tool lies in determining whether observed changes in a real-time environment are driven by volcanic activity or due solely to other sources (i.e., hydrologic or meteorologic events). Volcanic activity will always occur contemporaneous with seasonal events (e.g. annual rainfall, snowpack, or snow melt). For this reason, ANI determined seismic velocity changes will reflect the confluence of variations in the hydrologic cycle, meteorologic events (if they are occurring), and volcanic activity (if it is occurring). In this study, we develop and test a new forecasting tool, in real-time, at Kilauea volcano, Hawaii. Specifically, we focus on the 2020 and ongoing Kilauea eruptions. Using empirical orthogonal function analysis, we identify when ANI determined changes in seismic velocity at Kīlauea have moved outside of a seasonal trend and are indicative of volcanic activity.

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Justin Sweet, PhD
Portable Project Associate
IRIS/PASSCAL Instrument Center

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