Remote Measurements of Volcanic Plume Electrification Using a Sparse Network Technique
Abstract
Ash from explosive volcanic eruptions can severely affect our environment by disrupting airline flights and marine traffic, reducing air quality, and impacting downwind communities. Understanding the signals produced during eruptions can help mitigate these hazards by giving early warning of the eruption onset and improving the forecasts of ash dispersal. An emerging tool in this approach is detecting the electrification of volcanic ash clouds. Volcanic lightning is a relatively new field of research, with recent field campaigns focusing on how to link electrification to eruption dynamics such as mass flux, water content, and microphysical processes (e.g., volcanic hail formation). However, many volcanoes are remote and lack local monitoring equipment, making fine-scale electrical measurements challenging. Here, we present a new technique to detect volcanic electrification that requires only two wideband radio-frequency sensors located within approximately 1,000 km of the volcano. The technique consists of calculating the expected time delay of the signal between the two sensors, and from the volcano under observation. With this time delay, a cross-correlation can be applied to determine signals that possibly originated from the volcano. The sensors used in this study are from the Earth Networks Total Lightning Network (ENTLN), which are wideband electric field sensors in the range of 5 - 500 kHz. We demonstrate the technique using the eruption of Bogoslof volcano in Alaska on June 10th, 2017. We also investigate the likelihood and origin of false positives. Initial results indicate that this technique can detect many electrical discharges that were filtered out by the ENTLN operational algorithm (due to the limited number of sensors in the region) and/or undetected by other global lightning detection networks. An important implication is that this technique could reduce the latency of volcano alerts indicating that significant ash emissions have begun and could increase the number of detected discharges available to characterize the eruption dynamics in near-real time. We suggest this technique could be operationalized into an eruption alert system, which would be especially useful for volcanoes that are not currently instrumented.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.V43B..08L
- Keywords:
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- 3304 Atmospheric electricity;
- ATMOSPHERIC PROCESSESDE: 8419 Volcano monitoring;
- VOLCANOLOGYDE: 8428 Explosive volcanism;
- VOLCANOLOGYDE: 8488 Volcanic hazards and risks;
- VOLCANOLOGY