Capturing the Acoustic Radiation Pattern of Strombolian Eruptions using Infrasound Sensors Aboard a Tethered Aerostat, Yasur Volcano, Vanuatu

Jolly, Arthur D.; Matoza, Robin S.; Fee, David; Kennedy, Ben; Iezzi, Alexandra M.; Fitzgerald, Rebecca H.; Austin, Allison; Johnson, Richard

doi:10.1002/2017gl074971

Cited by 41 publications

(69 citation statements)

References 38 publications

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“…Our study aims to determine if acoustic directionality is resolvable and explore the stability of both monopole and multipole source inversions of discrete explosions of Yasur volcano by sampling the wavefield in both the horizontal and vertical directions. Our deployment consists of a traditional deployment of infrasound sensors on the ground surface, as well as a sensor onboard a tethered aerostat that was fixed at various locations around the volcanic crater, capturing explosions from a variety of azimuths and inclinations (Jolly et al, ). We use finite‐difference time‐domain (FDTD) modeling to obtain the full 3‐D Green's functions for each propagation path from source to receiver.…”

Section: Introductionmentioning

confidence: 99%

“…Here we build upon these previous studies by using the inversion method of Kim et al () and including the multipole source. By accounting for topography to create the synthetic waveforms, we can examine how much of the observed directive radiation pattern (Jolly et al, ) is due to topography or source directivity (i.e., a dipole source mechanism), a problem evident in Kim et al () that has remained undetermined.…”

Section: Introductionmentioning

confidence: 99%

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Three‐Dimensional Acoustic Multipole Waveform Inversion at Yasur Volcano, Vanuatu

et al. 2019

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Acoustic waveform inversions can provide estimates of volume flow rate and erupted mass, enhancing the ability to estimate volcanic emissions. Previous studies have generally assumed a simple acoustic source (monopole); however, more complex and accurate source reconstructions are possible with a combination of equivalent sources (multipole). We deployed a high‐density acoustic network around Yasur volcano, Vanuatu, including acoustic sensors on a tethered aerostat that was moved every ∼15–60 min. Using this unique data set we invert for the acoustic multipole source mechanism using a grid search approach for 80 events to examine volume flow rates and dipole strengths. Our method utilizes finite‐difference time‐domain modeling to obtain the full 3‐D Green's functions that account for topography. Inversion results are compared using a monopole‐only, multipole (monopole and dipole), simulations that do not include topography, and those that use a subset of sensors. We find that the monopole source is a good approximation when topography is considered. However, initial compression amplitude is not fully captured by a monopole source so source directionality cannot be ruled out. The monopole solution is stable regardless of whether a monopole‐only or multipole inversion is performed. Inversions for the dipole components produce estimates consistent with observed source directionality, though these inversions are somewhat unstable given station configurations of typical deployments. Our results suggest that infrasound waveform inversion shows promise for realistic quantitative source estimates, but additional work is necessary to fully explore inversion stability, uncertainty, and robustness.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Three‐Dimensional Acoustic Multipole Waveform Inversion at Yasur Volcano, Vanuatu

et al. 2019

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“…The reclined S shape of N shows that spectral power is transferred away from the peak source frequency at 10-20 kHz ( N < 0) to higher frequencies at which N >0. Figures are reproduced from Reichman et al (2016) and Miller and Gee (2018) with permission. 2018; Watson et al, 2019), and source directivity (Jolly et al, 2017;Kim et al, 2012). Therefore, improved understanding of near-source distortions can lead to more accurate estimates of volcano-acoustic source characteristics.…”

Section: Introductionmentioning

confidence: 99%

Investigating Spectral Distortion of Local Volcano Infrasound by Nonlinear Propagation at Sakurajima Volcano, Japan

et al. 2020

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Sound waves generated by erupting volcanoes can be used to infer important source dynamics, yet acoustic source‐time functions may be distorted during propagation, even at local recording distances ( <15 km). The resulting uncertainty in source estimates can be reduced by improving constraints on propagation effects. We aim to quantify potential distortions caused by wave steepening during nonlinear propagation, with the aim of improving the accuracy of volcano‐acoustic source predictions. We hypothesize that wave steepening causes spectral energy transfer away from the dominant source frequency. To test this, we apply a previously developed single‐point, frequency domain, quadspectral density‐based nonlinearity indicator to 30 acoustic signals from Vulcanian explosion events at Sakurajima Volcano, Japan, in an 8‐day data set collected by five infrasound stations in 2013 with 2.3‐ to 6.2‐km range. We model these results with a 2‐D axisymmetric finite‐difference method that includes rigid topography, wind, and nonlinear propagation. Simulation results with flat ground indicate that wave steepening causes up to ∼2 dB (1% of source level) of cumulative upward spectral energy transfer for Sakurajima amplitudes. Correction for nonlinear propagation may therefore provide a valuable second‐order improvement in accuracy for source parameter estimates. However, simulations with wind and topography introduce variations in the indicator spectra on order of a few decibels. Nonrandom phase relationships generated during propagation or at the source may be misinterpreted as nonlinear spectral energy transfer. The nonlinearity indicator is therefore best suited to small source‐receiver distances (e.g., <2 km) and volcanoes with simple sources (e.g., gas‐rich strombolian explosions) and topography.

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“…where ρ is the density of the ground, c is the seismic medium velocity, S is the site response, U is the seismic amplitude, and A is the wave propagation attenuation that can be determined from A = e (−πƒr/cQ) . Estimating seismic energies, values of ρ = 2120 kg/m 3 and a homogeneous p-wave estimate of c = 2200 m/s (Jolly et al 2017b) were used for Whakaari. Due to possible directional variations among the network array (topography, source directionality of the radiation pattern, site effects, etc.)…”

Section: Determining Eruption Pulse Characteristics Using the Volcanimentioning

confidence: 99%

Geophysical examination of the 27 April 2016 Whakaari/White Island, New Zealand, eruption and its implications for vent physiognomies and eruptive dynamics

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et al. 2019

Earth Planets Space

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At approximately 09:36 UTC on 27 April 2016, a phreatic eruption occurred on Whakaari Island (White Island) producing an eruption sequence that contained multiple eruptive pulses determined to have occurred over the first 30 min, with a continuing tremor signal lasting ~ 2 h after the pulsing sequence. To investigate the eruption dynamics, we used a combination of cross-correlation and coherence methods with acoustic data. To estimate locations for the eruptive pulses, seismic data were collected and eruption vent locations were inferred through the use of an amplitude source location method. We also investigated volcanic acoustic-seismic ratios for comparing inferred initiation depths of each pulse. Initial results show vent locations for the eruptive pulses were found to have possibly come from two separate locations only ~ 50 m apart. These results compare favorably with acoustic lag time analysis. After error analysis, eruption sources are shown to conceivably come from a single vent, and differences in vent locations may not be constrained. Both vent location scenarios show that the eruption pulses gradually increase in strength with time, and that pulses 1, 3, 4, and 5 possibly came from a deeper source than pulses 2 and 6. We show herein that the characteristics and locations of volcanic eruptions can be better understood through joint analysis combining data from several data sources.

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Capturing the Acoustic Radiation Pattern of Strombolian Eruptions using Infrasound Sensors Aboard a Tethered Aerostat, Yasur Volcano, Vanuatu

Cited by 41 publications

References 38 publications

Three‐Dimensional Acoustic Multipole Waveform Inversion at Yasur Volcano, Vanuatu

Three‐Dimensional Acoustic Multipole Waveform Inversion at Yasur Volcano, Vanuatu

Investigating Spectral Distortion of Local Volcano Infrasound by Nonlinear Propagation at Sakurajima Volcano, Japan

Geophysical examination of the 27 April 2016 Whakaari/White Island, New Zealand, eruption and its implications for vent physiognomies and eruptive dynamics

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