Local, Regional, and Remote Seismo-acoustic Observations of the April 2015 VEI 4 Eruption of Calbuco Volcano, Chile

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https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JB015182

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https://doi.org/10.1002/2017JB015182
 http://hdl.handle.net/11603/26627

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UMBC GESTAR II

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https://orcid.org/0000-0003-3189-9189

Date

2018-03-07

Type of Work

journal articles
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Citation of Original Publication

Matoza, R. S., Fee, D., Green, D. N.,Le Pichon, A., Vergoz, J., Haney, M. M.,et al. (2018). Local, regional, and remoteseismo-acoustic observations of theApril 2015 VEI 4 eruption of Calbucovolcano, Chile.Journal of GeophysicalResearch: Solid Earth,123, 3814–3827. https://doi.org/10.1002/2017JB015182.

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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract

The two major explosive phases of the 22–23 April 2015 eruption of Calbuco volcano, Chile,produced powerful seismicity and infrasound. The eruption was recorded on seismo-acoustic stations outto 1,540 km and onfive stations (IS02, IS08, IS09, IS27, and IS49) of the International Monitoring System (IMS)infrasound network at distances from 1,525 to 5,122 km. The remote IMS infrasound stations provide anaccurate explosion chronology consistent with the regional and local seismo-acoustic data and with previousstudies of lightning and plume observations. We use the IMS network to detect and locate the eruptionsignals using a brute-force, grid-search, cross-bearings approach. After incorporating azimuth deviationcorrections from stratospheric crosswinds using 3-D ray tracing, the estimated source location is 172 km fromtrue. This case study highlights the significant capability of the IMS infrasound network to provide automateddetection, characterization, and timing estimates of global explosive volcanic activity. Augmenting theIMS with regional seismo-acoustic networks will dramatically enhance volcanic signal detection, reducelatency, and improve discrimination capability.