Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data

Abstract Infrasound (low‐frequency acoustic waves) has proven useful to detect and characterize subaerial volcanic activity, but understanding the infrasonic source during sustained eruptions is still an area of active research. Preliminary comparison between acoustic eruption spectra and the jet no...

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Autores principales:	J. E. Gestrich, D. Fee, R. S. Matoza, J. J. Lyons, M. C. Ruiz
Formato:	article
Lenguaje:	EN
Publicado:	American Geophysical Union (AGU) 2021
Materias:	jet noise infrasound volcano turbulence acoustic monitoring Astronomy QB1-991 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/a5c48d17a35843109b9aea31d071e77c
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spelling	oai:doaj.org-article:a5c48d17a35843109b9aea31d071e77c2021-11-23T21:03:08ZFitting Jet Noise Similarity Spectra to Volcano Infrasound Data2333-508410.1029/2021EA001894https://doaj.org/article/a5c48d17a35843109b9aea31d071e77c2021-11-01T00:00:00Zhttps://doi.org/10.1029/2021EA001894https://doaj.org/toc/2333-5084Abstract Infrasound (low‐frequency acoustic waves) has proven useful to detect and characterize subaerial volcanic activity, but understanding the infrasonic source during sustained eruptions is still an area of active research. Preliminary comparison between acoustic eruption spectra and the jet noise similarity spectra suggests that volcanoes can produce an infrasonic form of jet noise from turbulence. The jet noise similarity spectra, empirically derived from audible laboratory jets, consist of two noise sources: large‐scale turbulence (LST) and fine‐scale turbulence (FST). We fit the similarity spectra quantitatively to eruptions of Mount St. Helens in 2005, Tungurahua in 2006, and Kīlauea in 2018 using nonlinear least squares fitting. By fitting over a wide infrasonic frequency band (0.05–10 Hz) and restricting the peak frequency above 0.15 Hz, we observe a better fit during times of eruption versus non‐eruptive background noise. Fitting smaller overlapping frequency bands highlights changes in the fit of LST and FST spectra, which aligns with observed changes in eruption dynamics. Our results indicate that future quantitative spectral fitting of eruption data will help identify changes in eruption source parameters such as velocity, jet diameter, and ash content which are critical for effective hazard monitoring and response.J. E. GestrichD. FeeR. S. MatozaJ. J. LyonsM. C. RuizAmerican Geophysical Union (AGU)articlejet noiseinfrasoundvolcanoturbulenceacousticmonitoringAstronomyQB1-991GeologyQE1-996.5ENEarth and Space Science, Vol 8, Iss 11, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	jet noise infrasound volcano turbulence acoustic monitoring Astronomy QB1-991 Geology QE1-996.5
spellingShingle	jet noise infrasound volcano turbulence acoustic monitoring Astronomy QB1-991 Geology QE1-996.5 J. E. Gestrich D. Fee R. S. Matoza J. J. Lyons M. C. Ruiz Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
description	Abstract Infrasound (low‐frequency acoustic waves) has proven useful to detect and characterize subaerial volcanic activity, but understanding the infrasonic source during sustained eruptions is still an area of active research. Preliminary comparison between acoustic eruption spectra and the jet noise similarity spectra suggests that volcanoes can produce an infrasonic form of jet noise from turbulence. The jet noise similarity spectra, empirically derived from audible laboratory jets, consist of two noise sources: large‐scale turbulence (LST) and fine‐scale turbulence (FST). We fit the similarity spectra quantitatively to eruptions of Mount St. Helens in 2005, Tungurahua in 2006, and Kīlauea in 2018 using nonlinear least squares fitting. By fitting over a wide infrasonic frequency band (0.05–10 Hz) and restricting the peak frequency above 0.15 Hz, we observe a better fit during times of eruption versus non‐eruptive background noise. Fitting smaller overlapping frequency bands highlights changes in the fit of LST and FST spectra, which aligns with observed changes in eruption dynamics. Our results indicate that future quantitative spectral fitting of eruption data will help identify changes in eruption source parameters such as velocity, jet diameter, and ash content which are critical for effective hazard monitoring and response.
format	article
author	J. E. Gestrich D. Fee R. S. Matoza J. J. Lyons M. C. Ruiz
author_facet	J. E. Gestrich D. Fee R. S. Matoza J. J. Lyons M. C. Ruiz
author_sort	J. E. Gestrich
title	Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
title_short	Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
title_full	Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
title_fullStr	Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
title_full_unstemmed	Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data
title_sort	fitting jet noise similarity spectra to volcano infrasound data
publisher	American Geophysical Union (AGU)
publishDate	2021
url	https://doaj.org/article/a5c48d17a35843109b9aea31d071e77c
work_keys_str_mv	AT jegestrich fittingjetnoisesimilarityspectratovolcanoinfrasounddata AT dfee fittingjetnoisesimilarityspectratovolcanoinfrasounddata AT rsmatoza fittingjetnoisesimilarityspectratovolcanoinfrasounddata AT jjlyons fittingjetnoisesimilarityspectratovolcanoinfrasounddata AT mcruiz fittingjetnoisesimilarityspectratovolcanoinfrasounddata
_version_	1718416113105108992

Fitting Jet Noise Similarity Spectra to Volcano Infrasound Data

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