Seismic equivalents of volcanic jet scaling laws and multipoles in acoustics

Haney, Matthew M.; Matoza, Robin S.; Fee, David; Aldridge, David F.

doi:10.1093/gji/ggx554

Cited by 29 publications

(28 citation statements)

References 51 publications

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“…We plot a power-law fit of the data as a dashed black line and a weak correlation (R 2 = 0.43) is observed. The exponent of the power law is 1.4, close to values previously determined by McNutt (1994) and Haney et al (2017). Events following the first 10 listed in Fig.…”

Section: Mcnutt Et Al (2010) Discuss Low D R Eruptions Fromsupporting

confidence: 89%

“…A power-law fit of the form D R~H b , where H indicates plume height, yields an exponent for the fit of 1.4-close to the exponent of 1.8 obtained by McNutt (1994) when considering several worldwide eruptions. Haney et al (2017) also found an exponent for the power-law fit of 1.7 during the waxing phase (Fee et al 2017) of the 2016 eruption of Pavlof. However, the correlation observed in Fig.…”

Section: Resultsmentioning

confidence: 83%

“…For example, McNutt et al (2013) use a station 14 km from the volcano to compute reduced displacement for the 2009 Redoubt eruption. Haney et al (2017) calculated D R for the 2016 Pavlof eruption by taking the median over a local network of 5 stations located between 8 and 13 km from the summit. When possible, taking the median or average over a group of stations reduces the impact of individual site effects at a particular station on the value of D R , similar to how a summary earthquake magnitude is averaged over several individual channel magnitudes.…”

Section: Methodsmentioning

confidence: 99%

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Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

et al. 2020

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We analyze seismic tremor recorded during eruptive activity over the course of the 2016-2017 eruption of Bogoslof volcano, Alaska. Only regional recordings of the tremor wavefield exist for Bogoslof, making it a challenge to place the recordings in context with other eruptions that are normally captured by local seismic data. We apply a technique of time-frequency polarization analysis to three-component seismic data to reveal the wavefield composition of Bogoslof eruption tremor. We find that at regional distances, the tremor is dominated by P-waves in the band from 1.5 to 10 Hz. Using this information, along with an enriched Bogoslof earthquake catalog, we obtain estimates of average reduced displacement (D R) for eruption tremor during 25 of the 70 Bogoslof events. D R reaches as high as approximately 40 cm 2 for two of the major events, similar to other VEI~3 eruptions in Alaska. Overall, average reduced displacement displays a weak correlation to plume height during the first half of the 9-month-long eruption sequence, with a few notable exceptions. The two events with the highest D R values also generated measurable eruption tremor at very-long-periods (VLP) between 0.05 and 0.15 Hz.

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Section: Mcnutt Et Al (2010) Discuss Low D R Eruptions Fromsupporting

confidence: 89%

Section: Resultsmentioning

confidence: 83%

Section: Methodsmentioning

confidence: 99%

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Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

et al. 2020

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“…Higherorder equivalent sources (dipoles and quadrupoles) can be mathematically constructed from combinations of monopoles (Lighthill, 1962;Morse and Ingard, 1968;Lighthill, 1978, Pierce, 1989. The relationship between acoustic and seismic equivalent sources was recently investigated by Haney et al (2018).…”

Section: Source Theorymentioning

confidence: 99%

“…Thus, it was not possible to observe any directivity in the radiation pattern of the rock fall event that may have been present. For example, it is possible that a piston-like push of air away from the nose of a directed mass movement may be better modeled by an acoustic dipole, which is equivalent to a force acting on the air (e.g., Russell et al, 1999;Haney et al, 2018). A common example of a dipole source in audible acoustics is a loudspeaker set in a flat panel (e.g., Russell et al, 1999).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Seismic and acoustic signatures of surficial mass movements at volcanoes

Allstadt

Matoza

Lockhart

et al. 2018

Journal of Volcanology and Geothermal Research

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Surficial mass movements, such as debris avalanches, rock falls, lahars, pyroclastic flows, and outburst floods, are a dominant hazard at many volcanoes worldwide. Understanding these processes, cataloging their spatio-temporal occurrence, and detecting, tracking, and characterizing these events would advance the science of volcano monitoring and help mitigate hazards. Seismic and acoustic methods show promise for achieving these objectives: many surficial mass movements generate observable seismic and acoustic signals, and many volcanoes are already monitored. Significant progress has been made toward understanding, modeling, and extracting quantitative information from seismic and infrasonic signals generated by surficial mass movements. However, much work remains. In this paper, we review the state of the art of the topic, covering a range of scales and event types from individual rock falls to sector collapses. We consider a full variety of volcanic settings, from submarine to subaerial, shield volcano to stratovolcano. Finally, we discuss future directions toward operational seismoacoustic monitoring of surficial mass movements at volcanoes.

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Rapid characterization of large volcanic eruptions: measuring the impulse of the Hunga Tonga explosion from teleseismic waves

Poli

Shapiro

2022

Preprint

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Most of the largest volcanic activity in the world occurs in remote places as deep oceans or poorly monitored oceanic islands. Thus, our capacity of monitoring volcanoes is limited to remote sensing and global geophysical observations. However, the rapid estimation of volcanic eruption parameters is needed for scientific understanding of the eruptive process and rapid hazard estimation. We present a method to rapidly identify large volcanic explosions, based on analysis of seismic data. With this methodology, we promptly detect the January 15, 2022 Hunga Tonga eruption. We then analyze the seismic waves generate by the volcanic explosion and estimate important first-order parameters of the eruption. We further relate the parameters with the volcanic explosivity index (VEI). Our estimate of VEI˜6, indicate how the Hunga Tonga eruption is among the largest volcanic activity ever recorded with modern geophysical instrumentation, and can provide new insights about the physics of large volcanoes.

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Seismic equivalents of volcanic jet scaling laws and multipoles in acoustics

Cited by 29 publications

References 51 publications

Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

Seismic and acoustic signatures of surficial mass movements at volcanoes

Rapid characterization of large volcanic eruptions: measuring the impulse of the Hunga Tonga explosion from teleseismic waves

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Seismic equivalents of volcanic jet scaling laws and multipoles in acoustics

Cited by 29 publications

References 51 publications

Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

Co-eruptive tremor from Bogoslof volcano: seismic wavefield composition at regional distances

Seismic and acoustic signatures of surficial mass movements at volcanoes

Rapid characterization of large volcanic eruptions: measuring the impulse of the Hunga Tonga&nbsp;explosion from teleseismic waves

Contact Info

Product

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Rapid characterization of large volcanic eruptions: measuring the impulse of the Hunga Tonga explosion from teleseismic waves