Geology topics

John J. Lyons

Publications and source records attributed to John J. Lyons.

At least 37 records · Page 2Linked to original sources

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

Tracking secondary lahar flow paths and characterizing pulses and surges using infrasound array networks at Volcán de Fuego, Guatemala

Lahars are one of the greatest hazards at many volcanoes, including Volcán de Fuego (Guatemala). On 1 December 2018 at 8:00pm local Guatemala time (2:00:00 UTC), an hour-long lahar event was detected at Volcán de Fuego by two permanent seismo-acoustic stations along the Las Lajas channel on the southeast side. To establish the timing, duration, and speed of the lahar, infrasound array records were examined to identify both the source direction(s) and the correlated energy fluctuations at the two stations. Co-located seismic and acoustic signals were also examined, which indicated at least 5 distinct energy pulses within the lahar record. We infer that varying sediment load and/or changes in flow velocity is shown by clear fluctuations in the acoustic and seismic power recorded at one of the stations. This particular event studied with infrasound provides insight into how lahars occur around Volcán de Fuego.

Volcán de Fuego↗

USGS2021

High-speed lava flow infrasound from Kīlauea’s fissure 8 and its utility in monitoring effusion rate

The 2018 eruption of Kīlauea Volcano produced large and destructive lava flows from the fissure 8 (Ahu ‘aila ‘au) vent with flow velocities up to 17 m s −1 , highly variable effusion rates over both short (minutes) and long (hours) time scales, and a proximal channel or spillway that displayed flow features similar to open channel flow in river systems. Monitoring such dynamic vent and lava flow systems is a challenge. Our results demonstrate that infrasound, combined with ground-based observations and imagery from unoccupied aircraft systems (UAS), can be used to distinguish vent degassing activity from high-speed lava flow activity. We use spectral characteristics and the infrasound frequency index (FI) to distinguish spillway infrasound from vent infrasound. Comparing FI with flow speeds derived from UAS videos reveals that spillway infrasound only occurs when flow speeds were sufficiently high to cause a supercritical flow state and breaking waves (Froude values > 1.7), and we propose that the spillway signals are produced primarily through the interaction of the turbulent lava-free surface with the atmosphere. We show that FI can also provide a means to track bulk effusion rate. Our results indicate that infrasound offers a new way to characterize lava flow channel hydraulics and is a powerful tool for monitoring effusive eruptions when high-speed flows are possible.

Hawaii↗

USGS2021

Local explosion detection and infrasound localization by reverse time migration using 3-D finite-difference wave propagation

Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (<15 km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ∼20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.

Alaska↗

USGS2021

Volcanic seismicity beneath Chuginadak Island, Alaska (Cleveland and Tana volcanoes): Implications for magma dynamics and eruption forecasting

Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.

Alaska↗

USGS2020

Linking subsurface to surface using gas emission and melt inclusion data at Mount Cleveland volcano, Alaska

Mount Cleveland is one of Alaska's most active volcanoes, yet little is known about the magmatic system driving persistent and dynamic volcanic activity. Volcanic gas and melt inclusion (MI) data from 2016 were combined to investigate shallow magmatic processes. SO 2 emission rates were between 166 and 324 t/day and the H 2 O/SO 2 was 600 ± 53, whereas CO 2 and H 2 S were below detection. Olivine‐, clinopyroxene‐, and plagioclase‐hosted MIs have up to 3.8 wt.% H 2 O, 514 ppm CO 2 , and 2,320 ppm S. Equilibration depths, based on MI H 2 O contents, suggest that a magmatic column extended from 0.5 to 3.0 km (~10–60 MPa). We used MI data to empirically model open‐system H‐C‐S degassing from 0 to 12 km and found that a column of magma between 0.5 and 3 km could produce the measured gas H 2 O/SO 2 ratio. However, additional magma deeper than 3 km is required to sustain emissions over periods greater than days to weeks, if the observed vent dimension is a valid proxy for the conduit. Assuming an initial S content of 2,320 ppm, the total magma supply needed to sustain the annual SO 2 flux was 5 to 9.8 Mm 3 /yr, suggesting a maximum intrusive‐to‐extrusive ratio of 13:1. The model predicts degassing of <50 t/day CO 2 for July 2016, which corresponds to a maximum predicted CO 2 /SO 2 of 0.2. Ultimately, frequent recharge from deeper, less degassed magma is required to drive the continuous activity observed over multiple years. During periods of recharge we would expect lower H 2 O/SO 2 and measurable volcanic CO 2 .

Alaska↗

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↗

USGS2020

Evolving infrasound detections from Bogoslof volcano, Alaska: Insights from atmospheric propagation modeling

Bogoslof volcano, a back-arc volcano in Alaska’s Aleutian arc, began an eruptive sequence in mid-December 2016 that ended in late August 2017, with 70 individual eruptive episodes. Because there were no local seismic or infrasound stations on the island, the Alaska Volcano Observatory (AVO) relied on distant geophysical networks and remote sensing techniques to assess activity during the eruption. AVO maintains six infrasound arrays to monitor activity along the Aleutian arc: Adak, the Island of Four Mountains, Okmok, Akutan, Sand Point, and Dillingham. Eruption detection at infrasound arrays is subject to local as well as mesoscale meteorological conditions that vary greatly over both short and long timescales. Infrasound detections from the array nearest to Bogoslof (Okmok), with a latency of about 3 min, played a crucial role in monitoring activity during the eruption. Despite the relative proximity of the Okmok array to Bogoslof (60 km), infrasound detections were not uniformly observed with only about two-thirds of the events successfully detected. The farthest array at Dillingham (816 km) detected approximately half of the explosive events, with all other arrays detecting less than half of the events. We compare observations with infrasound propagation model predictions, using both normal mode and parabolic equation forward models, to interpret the variation in detections of the 70 explosive events across the AVO infrasound network. The forward models utilize the newly created, publicly available AVO-G2S atmospheric reconstruction using numerical weather predictions data for the lower atmosphere, coupled with upper atmosphere empirical models of wind speeds and temperature. We find that long-range detections (> 100 km) of Bogoslof events are largely aligned with seasonal variability in favorable propagation conditions, while regional detections (< 100 km) are less consistent with propagation modeling. Understanding the output of numerical models in comparison to past observations will facilitate their use in future operational settings for AVO and other observatories.

Alaska↗

USGS2020

Did ice-charging generate volcanic lightning during the 2016–2017 eruption of Bogoslof volcano, Alaska?

The 2016–2017 shallow submarine eruption of Bogoslof volcano in Alaska injected plumes of ash and seawater to maximum heights of ~ 12 km. More than 4550 volcanic lightning strokes were detected by the World Wide Lightning Location Network (WWLLN) and Vaisala’s Global Lightning Dataset (GLD360) over 9 months. Lightning assisted monitoring efforts by confirming ash-producing explosions in near-real time, but only 32 out of the 70 explosive events produced detectable lightning. What led to electrical activity within some of the volcanic plumes, but not others? And why did the lightning intensity wax and wane over the lifetime of individual explosions? We address these questions using multiparametric observations from ground-based lightning sensors, satellite imagery, photographs, acoustic signals, and 1D plume modeling. Detailed time-series of monitoring data show that the plumes did not produce detectable lightning until they rose higher than the atmospheric freezing level (approximated by − 20 °C temperatures). For example, on 28 May 2017 (event 40), the delayed onset of lightning coincides with modeled ice formation in upper levels of the plume. Model results suggest that microphysical conditions inside the plume rivaled those of severe thunderstorms, with liquid water contents > 5 g m −3 and vigorous updrafts > 40 m s −1 in the mixed-phase region where liquid water and ice coexist. Based on these findings, we infer that ‘thunderstorm-style’ collisional ice-charging catalyzed the volcanic lightning. However, charge mechanisms likely operated on a continuum, with silicate collisions dominating electrification in the near-vent region, and ice charging taking over in the upper-level plumes. A key implication of this study is that lightning during the Bogoslof eruption provided a reliable indicator of sustained, ash-rich plumes (and associated hazards) above the atmospheric freezing level.

Alaska↗

USGS2020

Infrasound generated by the 2016-2017 shallow submarine eruption of Bogoslof volcano, Alaska

The 2016–2017 shallow submarine eruption of Bogoslof volcano produced numerous infrasound signals over 9 months that were recorded on six Alaska Volcano Observatory (AVO) arrays at ranges of 59 to over 800 km from the volcano. The lack of geophysical monitoring near Bogoslof and the repeated production of volcanic clouds to flight levels made monitoring by remote infrasound critical during the eruption; for the first time, AVO relied extensively on automated infrasound detections from regional arrays to dispatch timely notifications of the ongoing activity. Most of the 70 eruptive events were detected on at least one array, but no array detected all of the events mainly because atmospheric conditions were highly variable during the eruption. Acoustic propagation modeling helps explain some of the variation in array detections but also highlights limitations in regional propagation models. To our knowledge, this is the first example of well-recorded infrasound from an explosive eruption occurring in shallow seawater, providing extensive insights into eruption dynamics in this unique environment. The dominance of low-frequency infrasound (0.1–1 Hz) is attributed to eruptions occurring beneath tens of meters of seawater. Higher-frequency infrasound signals were mostly limited to eruptions where the vent was isolated from major interaction with seawater or in several cases where a lava dome grew above sea level.

Alaska↗

USGS2020

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

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.

Alaska↗

USGS2020

Constraints on eruption processes and event masses for the 2016–2017 eruption of Bogoslof volcano, Alaska, through evaluation of IASI satellite SO2 masses and complementary datasets

Bogoslof volcano, Alaska, experienced at least 70 explosive eruptions between 12 December 2016 and 31 August 2017. Due to its remote location and limited local monitoring network, this eruption was monitored and characterized primarily using remote geophysical and satellite techniques. SO 2 emissions from Bogoslof were persistently detected by the Infrared Atmospheric Sounding Interferometer (IASI) satellite sensors. Of Bogoslof’s 70 explosive events, 50% produced measurable SO 2 masses ranging from 0.1 to 21.5 kt, with a median and standard deviation of 0.7 ± 4.0 kt SO 2 , respectively. Here, we compare IASI-derived SO 2 masses from Bogoslof events to complementary geophysical datasets to provide insights into eruption source processes, namely the degree of seawater scrubbing of water-soluble SO 2 and variations in magma flux. Correlations with the number of lightning strokes and infrasound energy are expected to indicate magma-flux as a controlling process, while correlations with infrasound frequency index are expected to indicate variations in vent-water content as a controlling factor. These comparisons suggest that the measured SO 2 masses are primarily a function of eruption magnitude (degassed magma mass) and that scrubbing of SO 2 emissions by vent seawater may have exerted a minor effect on the observed SO 2 masses. SO 2 masses were combined with petrologic constraints on melt inclusion and matrix glass S concentrations to calculate degassed magma masses and volumes. The cumulative SO 2 -derived degassed magma mass and estimated volume (dense-rock equivalent) for the full Bogoslof eruption were found to be 2.8 × 10 10 kg and 9.3 × 10 6 m 3 , respectively. When individual event masses are compared against event masses calculated using an empirical plume-height method, a strong correlation is found ( R 2 = 0.83), with better than order-of-magnitude agreement in most cases. These estimates of eruption masses provide useful information on the magnitude, behavior, and associated hazards of the 2016–2017 eruption, and potentially future unrest at Bogoslof volcano.

Alaska↗

USGS2020

Characteristics of thunder and electromagnetic pulses from volcanic lightning at Bogoslof volcano, Alaska

We combine global detections of volcanic lightning with acoustic and hydroacoustic data to investigate novel indications of plume electrification in ground-based, geophysical data streams during the 2016–2017 eruption of Bogoslof volcano, Alaska. Such signals offer additional ways to diagnose the occurrence of volcanic lightning and confirm whether eruptive activity is producing significant amounts of ash. We discuss three signatures of lightning activity: volcanic thunder, electromagnetic pulses arising from lightning-induced voltages in cabling, and hydroacoustic signals associated with volcanic lightning. Observations of these phenomena provide additional insights into volcanic lightning activity and reveal several periods of electrical activity that were not otherwise detected during the Bogoslof eruption.

Alaska↗

USGS2020

Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions

The Alaska Volcano Observatory (AVO) seismic network has been in operation since 1988 and during this time has grown from 29 to 217 seismic stations providing real-time monitoring of 32 active volcanoes in Alaska, as well as useful data for regional earthquake monitoring. Since 1988, AVO has detected 59 volcanic eruptions at Aleutian arc volcanoes, and 31 of these have been captured by local seismic instrumentation. As part of this monitoring effort, AVO has cataloged more than 120,000 earthquake hypocenters and magnitudes associated with volcanic processes throughout the arc. This high rate of volcanic activity provides an excellent opportunity to study seismicity associated with magmatic and eruptive processes and develop and refine analytical techniques to track volcanic seismicity and warn of hazardous eruptions. The network is currently undergoing an extensive upgrade, replacing aging short-period analog seismometers with digital broadband instruments. These are expected to improve AVO’s seismic capability and further facilitate other geophysical instrumentation such as continuous Global Positioning System receivers, infrasound sensors, and web cams.

Seismological Research Letters↗

USGS2019

Seismo-acoustic evidence for vent drying during shallow submarine eruptions at Bogoslof volcano, Alaska

Characterizing the state of the volcanic vent is key for interpreting observational datasets and accurately assessing volcanic hazards. This is particularly true for remote, complex eruptions such as the 2016–2017 Bogoslof volcano, Alaska eruption sequence. Bogoslof’s eruptions in this period were either shallow submarine or subaerial, or some combination of both. Our results demonstrate how low-frequency sound waves (infrasound), integrated with seismic and satellite data, can provide unique insight into shallow vent processes, otherwise not available. We use simple metrics, such as the infrasound frequency index (FI), event duration, and acoustic-seismic amplitude ratio, to look at changes in the elastic energy radiation and infer changes in seawater access to the vent. Satellite imagery before and after selected eruptions is used to ground-truth inferences on vent conditions. High FI and gradual increases in infrasound frequency content at Bogoslof correspond with transitions from submarine to subaerial vent conditions and a diminished or absent role of water, likely resulting in a drying out of the vent region. Event durations generally correlate with high FI and the range of FI values for each event, suggesting long duration events were more effective at drying out the vent region. A trend from low to high acoustic-seismic amplitude ratios for some long duration events also suggests an increase in acoustic efficiency as the vent dried out. We demonstrate that infrasound can serve as a robust indicator of seawater involvement for Bogoslof and other shallow submarine eruptions that may not be inferable from other datasets, particularly in near-real-time.

Alaska↗

USGS2019

Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska

The 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc, began in December 2016 and included 70 explosive events and at least two episodes of subaerial dome building. Because the volcano had no local monitoring stations during the eruption, a combination of distant seismic stations, regional infrasound sensors, lightning detection, a variety of satellite data and observer reports, and a field visit in 2018, were used to recreate the events that occurred during the nine-month eruption. Following precursory seismicity that started in September 2016, the eruption began in December 2016 with a series of explosive events that persisted through mid-March 2017. After a 6-week hiatus, activity resumed on May 17 and lasted through the end of August 2017 and consisted of additional explosions and two short-lived subaerial lava domes that formed in June and August. For most of the eruption, Bogoslof’s vent was submerged in shallow seawater, though during several of the longer events a subaerial edifice grew, and the vent migrated above sea level resulting in more ash-rich volcanic clouds. Eruptive products, geophysical signals, and eruptive style are all broadly consistent with vulcanian activity where slow magma ascent led to repetitive dome or plug formation, overpressurization in the upper conduit, and sudden release during short-lived explosions. Infiltration of seawater may have prohibited large domes from forming especially in the first half of the eruption when explosions were closely spaced in time. The largest four explosions in the sequence occurred after inter-event times of 10 days or more. Three events produced ashfall on nearby communities and mariners east and south of Bogoslof and the eruption resulted in dozens of flight cancelations and flight diversions around the volcano and its ash clouds.

Alaska↗

USGS2019

Infrasound from giant bubbles during explosive submarine eruptions

Shallow submarine volcanoes pose unique scientific and monitoring challenges. The interaction between water and magma can create violent explosions just below the surface, but the inaccessibility of submerged volcanoes means they are typically not instrumented. This both increases the risk to marine and aviation traffic and leaves the underlying eruption physics poorly understood. Here we use low-frequency sound in the atmosphere (infrasound) to examine the source mechanics of shallow submarine explosions from Bogoslof volcano, Alaska. We show that the infrasound originates from the oscillation and rupture of magmatic gas bubbles that initially formed from submerged vents, but that grew and burst above sea level. We model the low-frequency signals as overpressurized gas bubbles that grow near the water–air interface, which require bubble radii of 50–220 m. Bubbles of this size and larger have been described in explosive subaqueous eruptions for more than a century, but we present a unique geophysical record of this phenomenon. We propose that the dominant role of seawater during the effusion of gas-rich magma into shallow water is to repeatedly produce a gas-tight seal near the vent. This resealing mechanism leads to sequences of violent explosions and the release of large, bubble-forming volumes of gas—activity we describe as hydrovulcanian.

Alaska↗