Geology topics

Robin S. Matoza

Publications and source records attributed to Robin S. Matoza.

At least 19 recordsLinked to original sources

USGS2025

Infrasonic directivity of monopole, dipole, and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local ( ⁠< 5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source ( ⁠< 5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Geophysical Journal International↗

USGS2023

UAS-Based Observations of Infrasound Directionality at Stromboli Volcano, Italy

Infrasound (low frequency sound waves) can be used to monitor and characterize volcanic eruptions. However, infrasound sensors are usually placed on the ground, thus providing a limited sampling of the acoustic radiation pattern that can bias source size estimates. We present observations of explosive eruptions from a novel uncrewed aircraft system (UAS)-based infrasound sensor platform that was strategically hovered near the active vents of Stromboli volcano, Italy. We captured eruption infrasound from short-duration explosions and jetting events. While potential vertical directionality was inconclusive for the short-duration explosion, we find that jetting events exhibit vertical sound directionality that was observed with a UAS close to vertical. This directionality would not have been observed using only traditional deployments of ground-based infrasound sensors, but is consistent with jet noise theory. This proof-of-concept study provides unique information that can improve our ability to characterize and quantify the directionality of volcanic eruptions and their associated hazards.

Stromboli Volcano↗

USGS2022

Earth’s upper crust seismically excited by infrasound from the 2022 Hunga Tonga–Hunga Ha’apai eruption, Tonga

Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near‐surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high‐amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic‐to‐seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients ( ⁠ S V / A ">

Seismological Research Letters↗

USGS2022

Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon

Laterally directed explosive eruptions are responsible for multiple fatalities over the past decade and are an increasingly important volcanology problem. To understand the energy dynamics for these events, we collected field-scale explosion data from nine acoustic sensors surrounding a tiltable cannon as part of an exploratory experimental design. For each cannon discharge, the blast direction was varied systematically at 0°, 12°, and 24° from vertical, capturing acoustic wavefield directivity related to the tilt angle. While each event was similar in energy discharge potential, the resulting acoustic signal features were variable event-to-event, producing non-repetitious waveforms and spectra. Systematic features were observed in a subset of individual events for vertical and lateral discharges. For vertical discharges, the acoustic energy had a uniform radiation pattern. The lateral discharges showed an asymmetric radiation pattern with higher frequencies in the direction of the blast and depletion of those frequencies behind the cannon. Results suggest that, in natural volcanic systems, near-field blast directionality may be elucidated from acoustic sensors in absence of visual data, with implications for volcano monitoring and hazard assessment.

Earth, Planets and Space↗

USGS2022

Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano

Real-time monitoring is crucial to assess hazards and mitigate risks of sustained volcanic eruptions that last hours to months or more. Sustained eruptions have been shown to produce a low frequency (infrasonic) form of jet noise. We analyze the lava fountaining at fissure 8 during the 2018 Lower East Rift Zone eruption of Kīlauea volcano, Hawaii, and connect changes in fountain properties with recorded infrasound signals from an array about 500 m from the fountain using jet noise scaling laws and visual imagery. Video footage from the eruption reveals a change in lava fountain dynamics from a tall, distinct fountain at the beginning of June to a low fountain with a turbulent, out-pouring lava pond surrounded by a tephra cone by mid-June. During mid-June, the sound pressure level reaches a maximum, and peak frequency drops. We develop a model that uses jet noise scaling relationships to estimate changes in volcanic jet diameter and jet velocity from infrasound sound pressure levels and peak frequencies. The results of this model indicate a decrease in velocity in mid-June which coincides with the decrease in fountain height. Furthermore, the model results suggest an increase in jet diameter, which can be explained by the larger width of the fountain that resembles a turbulent lava pond compared to the distinct fountain at the beginning of June. The agreement between the infrasound-derived and visually observed changes in fountain dynamics suggests that jet noise scaling relationships can be used to monitor lava fountain dynamics using infrasound recordings.

Hawaii↗

USGS2022

Spatial analysis of globally detected volcanic lightning from the June 2019 eruption of Raikoke volcano, Kuril Islands

The 21–22 June 2019 eruption of Raikoke volcano, Russia, provided an opportunity to explore how spatial trends in volcanic lightning locations provide insights into pulsatory eruption dynamics. Using satellite-derived plume heights, we examine the development of lightning detected by Vaisala’s Global Lightning Dataset (GLD360) from eleven, closely spaced eruptive pulses. Results from one-dimensional plume modeling show that the eruptive pulses with maximum heights 9–16.5 km above sea level were capable of producing ice in the upper troposphere, which contributed variably to electrification and volcanic lightning. A key finding is that lightning locations not only followed the main dispersal direction of these ash plumes, but also tracked a lower-level cloud derived from pyroclastic density currents. We show a positive relationship between umbrella cloud expansion and the area over which lightning occurs (the ‘lightning footprint’). These observations suggest useful metrics to characterize ongoing eruptive activity in near real-time.

Kuril Islands, Raikoke volcano↗

USGS2022

Infrasound single-channel noise reduction: Application to detection and localization of explosive volcanism in Alaska using backprojection and array processing

Infrasound sensors are deployed in a variety of spatial configurations and scales for geophysical monitoring, including networks of single sensors and networks of multisensor infrasound arrays. Infrasound signal detection strategies exploiting these data commonly make use of intersensor correlation and coherence (array processing, multichannel correlation); network-based tracking of signal features (e.g. reverse time migration); or a combination of these such as backazimuth cross-bearings for multiple arrays. Single-sensor trace-based denoising techniques offer significant potential to improve all of these various infrasound data processing strategies, but have not previously been investigated in detail. Single-sensor denoising represents a pre-processing step that could reduce the effects of ambient infrasound and wind noise in infrasound signal association and location workflows. We systematically investigate the utility of a range of single-sensor denoising methods for infrasound data processing, including noise gating, non-negative matrix factorization, and data-adaptive Wiener filtering. For the data testbed, we use the relatively dense regional infrasound network in Alaska, which records a high rate of volcanic eruptions with signals varying in power, duration, and waveform and spectral character. We primarily use data from the 2016–2017 Bogoslof volcanic eruption, which included multiple explosions, and synthetics. The Bogoslof volcanic sequence provides an opportunity to investigate regional infrasound detection, association, and location for a set of real sources with varying source spectra subject to anisotropic atmospheric propagation and varying noise levels (both incoherent wind noise and coherent ambient infrasound, primarily microbaroms). We illustrate the advantages and disadvantages of the different denoising methods in categories such as event detection, waveform distortion, the need for manual data labelling, and computational cost. For all approaches, denoising generally performs better for signals with higher signal-to-noise ratios and with less spectral and temporal overlap between signals and noise. Microbaroms are the most globally pervasive and repetitive coherent ambient infrasound noise source, with such noise often referred to as clutter or interference. We find that denoising offers significant potential for microbarom clutter reduction. Single-channel denoising of microbaroms prior to standard array processing enhances both the quantity and bandwidth of detectable volcanic events. We find that reduction of incoherent wind noise is more challenging using the denoising methods we investigate; thus, station hardware (wind noise reduction systems) and site selection remain critical and cannot be replaced by currently available digital denoising methodologies. Overall, we find that adding single-channel denoising as a component in the processing workflow can benefit a variety of infrasound signal detection, association, and location schemes. The denoising methods can also isolate the noise itself, with utility in statistically characterizing ambient infrasound noise.

Alaska↗

USGS2022

Trends in volcano seismology: 2010 to 2020 and beyond

Volcano seismology has been fundamental to our current understanding of crustal magma migration and eruption. The increasing availability of portable seismic networks with the creative use of seismic sources and ambient noise has led to a better understanding of the volcanic structure of many volcanoes and is producing increasingly detailed images of the volcanic subsurface. The past decade (2010-2020) has seen advances in our understanding of seismic sources under and surrounding volcanoes through precise locations, and through analysis of source mechanisms from seismic signals that are more varied and smaller in magnitude, reaching beyond traditional techniques. In tandem with continued research on fundamental physics-based understanding of volcano-seismic sources, new advances in computational analyses including machine learning methods will push our understanding of volcanic processes into the future. Incorporation of multidisciplinary geophysical observations (especially infrasound) has become commonplace, and our understanding of infrasound propagation and sources will feed back into our ability to monitor ongoing eruptions and surficial mass movements. Open-source codes will permit widespread evaluation and adoption of new methodologies for volcano-seismic analysis and inversion. Combined with quantitative and conceptual source models using improved structural constraints, these new methodologies will better characterize the range of volcano-seismic signal evolution scenarios and hold promise for creating better short-term forecasts. Finally, permanent instrumentation is available on an expanding range of volcanoes, and open data policies are increasingly making these data available to the scientific community in near real time.

Bulletin of Volcanology↗

USGS2022

Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga

The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. Here, we highlight exceptional observations of the atmospheric waves.

Hunga volcano↗

USGS2021

Fitting jet noise similarity spectra to volcano infrasound data

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.

Earth and Space Science↗

USGS2021

Reconstructing the dynamics of the highly similar May 2016 and June 2019 Iliamna Volcano, Alaska ice–rock avalanches from seismoacoustic data

Surficial mass wasting events are a hazard worldwide. Seismic and acoustic signals from these often remote processes, combined with other geophysical observations, can provide key information for monitoring and rapid response efforts and enhance our understanding of event dynamics. Here, we present seismoacoustic data and analyses for two very large ice–rock avalanches occurring on Iliamna Volcano, Alaska (USA), on 22 May 2016 and 21 June 2019. Iliamna is a glacier-mantled stratovolcano located in the Cook Inlet, ∼200 km from Anchorage, Alaska. The volcano experiences massive, quasi-annual slope failures due to glacial instabilities and hydrothermal alteration of volcanic rocks near its summit. The May 2016 and June 2019 avalanches were particularly large and generated energetic seismic and infrasound signals which were recorded at numerous stations at ranges from ∼9 to over 600 km. Both avalanches initiated in the same location near the head of Iliamna's east-facing Red Glacier, and their ∼8 km long runout shapes are nearly identical. This repeatability – which is rare for large and rapid mass movements – provides an excellent opportunity for comparison and validation of seismoacoustic source characteristics. For both events, we invert long-period (15–80 s) seismic signals to obtain a force-time representation of the source. We model the avalanche as a sliding block which exerts a spatially static point force on the Earth. We use this force-time function to derive constraints on avalanche acceleration, velocity, and directionality, which are compatible with satellite imagery and observed terrain features. Our inversion results suggest that the avalanches reached speeds exceeding 70 m s−1, consistent with numerical modeling from previous Iliamna studies. We lack sufficient local infrasound data to test an acoustic source model for these processes. However, the acoustic data suggest that infrasound from these avalanches is produced after the mass movement regime transitions from cohesive block-type failure to granular and turbulent flow – little to no infrasound is generated by the initial failure. At Iliamna, synthesis of advanced numerical flow models and more detailed ground observations combined with increased geophysical station coverage could yield significant gains in our understanding of these events.

Alaska↗

USGS2021

Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands

Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 106 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.

Hokkaido, Sakhalin Oblast↗

USGS2021

Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea

Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn - and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO 2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO 2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn -eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.

Bismark volcanic arc, New Britain Island, Ulawun v↗

USGS2020

Remote detection and location of explosive volcanism in Alaska with the EarthScope Transportable Array

The current deployment of the EarthScope Transportable Array (TA) in Alaska affords an unprecedented opportunity to study explosive volcanic eruptions using a relatively dense regional seismoacoustic network. Infrasound monitoring has demonstrated utility for the remote (>250 km range) detection and characterization of volcanic explosions, but previous studies have used relatively sparse regional or global networks. Seventy explosive events from the locally unmonitored Bogoslof volcano (2016–2017) provide a unique validation data set to examine the ability of the TA and other regional networks to detect and locate remote explosive volcanic eruptions in Alaska. With a simple envelope-based reverse time migration (RTM) technique, we are able to detect and locate more than 72% of the 61 Bogoslof infrasound events detected by the Alaska Volcano Observatory. Notably, RTM using only sparse regional infrasound arrays produces results similar to when incorporating the extensive single-sensor TA network, likely due to favorable signal-to-noise ratios, seasonal propagation conditions, and source-receiver geometries. Our implementation also detects and locates explosive eruptions from Cleveland volcano, Alaska, and Bezymianny volcano, Kamchatka, as well as infrasound from nonvolcanic events such as earthquakes. We characterize the success of the RTM algorithm and associated parameter choices using receiver operating characteristic curves, event detection rates, and location accuracy. Our methods are useful for explosive volcanic and nonvolcanic event detection and localization using real-time data and for scanning continuous waveform data archives.

Alaska↗

USGS2018

Infrasound signal detection and back azimuth estimation using ground-coupled airwaves on a seismo-acoustic sensor pair

We present a new infrasonic signal detection and back azimuth determination technique that requires just one microphone and one three-component seismometer. Ground-coupled airwaves (GCAs) occur when an incident atmospheric acoustic wave impinges on the ground surface and is partially transmitted as a seismic wave. GCAs are commonly detected hundreds of kilometers away on seismic networks and are observed to have retrograde particle motion. Horizontally propagating acoustic waves and GCAs have previously been observed on collocated infrasound and seismic sensor pairs as coherent with a 90° phase difference. If the sensors are spatially separated, an additional propagation-induced phase shift is present. The additional phase shift depends on the direction from which the acoustic wave arrives, as each back azimuth has a different apparent distance between the sensors. We use the additional phase shift, the coherence, and the characteristic particle motion on the three-component seismometer to determine GCA arrivals and their unique back azimuth. We test this technique with synthetic seismo-acoustic data generated by a coupled Earth-atmosphere 3-D finite difference code, as well as three seismo-acoustic data sets from Mount St. Helens, Mount Cleveland, and Mount Pagan volcanoes. Results from our technique compare favorably with traditional infrasound array processing and provide robust GCA detection and back azimuth determination. Assuming adequate station spacing and sampling, our technique provides a new and robust method to detect infrasonic signals and determine their back azimuth, and may be of practical benefit where resources are limited and large sensor networks or arrays are not feasible.

JGR Solid Earth↗

USGS2018

Local, regional, and remote seismo-acoustic observations of the April 2015 VEI 4 eruption of Calbuco volcano, Chile

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 out to 1,540 km and on 5 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 an accurate explosion chronology consistent with the regional and local seismo-acoustic data, and with previous studies of lightning and plume observations. We use the IMS network to detect and locate the eruption signals using a brute-force, grid search, cross-bearings approach. After incorporating azimuth deviation corrections from stratospheric cross-winds using 3D ray-tracing, the estimated source location is 172 km from true. This case study highlights the significant capability of the IMS infrasound network to provide automated detection, characterization, and timing estimates of global explosive volcanic activity. Augmenting the IMS with regional seismo-acoustic networks will dramatically enhance volcanic signal detection, reduce latency, and improve discrimination capability.

Calbuco volcano↗

USGS2017

Volcanic tremor and plume height hysteresis from Pavlof Volcano, Alaska

The March 2016 eruption of Pavlof Volcano, Alaska produced ash plumes that canceled over 100 flights in North America. The eruption produced strong tremor recorded by seismic and remote low-frequency acoustic (infrasound) stations, including the EarthScope Transportable Array. The relationship between the tremor amplitudes and plume height changes considerably between the waxing and waning portions of the eruption. Similar hysteresis has been observed between seismic river noise and discharge during storms, suggesting flow and erosional processes in both rivers and volcanoes can produce irreversible structural changes detectable in geophysical data. We propose that the time-varying relationship at Pavlof arose from changes in the tremor source related to volcanic vent erosion. This relationship may improve estimates of volcanic emissions and characterization of eruption size and intensity.

Alaska↗

USGS2016

Seismic envelope-based detection and location of ground-coupled airwaves from volcanoes in Alaska

Volcanic explosions and other infrasonic sources frequently produce acoustic waves that are recorded by seismometers. Here we explore multiple techniques to detect, locate, and characterize ground‐coupled airwaves (GCA) on volcano seismic networks in Alaska. GCA waveforms are typically incoherent between stations, thus we use envelope‐based techniques in our analyses. For distant sources and planar waves, we use f ‐ k beamforming to estimate back azimuth and trace velocity parameters. For spherical waves originating within the network, we use two related time difference of arrival (TDOA) methods to detect and localize the source. We investigate a modified envelope function to enhance the signal‐to‐noise ratio and emphasize both high energies and energy contrasts within a spectrogram. We apply these methods to recent eruptions from Cleveland, Veniaminof, and Pavlof Volcanoes, Alaska. Array processing of GCA from Cleveland Volcano on 4 May 2013 produces robust detection and wave characterization. Our modified envelopes substantially improve the short‐term average/long‐term average ratios, enhancing explosion detection. We detect GCA within both the Veniaminof and Pavlof networks from the 2007 and 2013–2014 activity, indicating repeated volcanic explosions. Event clustering and forward modeling suggests that high‐resolution localization is possible for GCA on typical volcano seismic networks. These results indicate that GCA can be used to help detect, locate, characterize, and monitor volcanic eruptions, particularly in difficult‐to‐monitor regions. We have implemented these GCA detection algorithms into our operational volcano‐monitoring algorithms at the Alaska Volcano Observatory.

Alaska↗