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A.D. Jolly

Publications and source records attributed to A.D. Jolly.

15 recordsLinked to original sources
USGS2025

A decade of precursory seismicity at Mauna Loa: 2013–2022

The 2022 eruption of Mauna Loa was preceded by nearly 10 years of seismic unrest. Using the earthquake catalog of the Hawaiian Volcano Observatory, we describe and explore many aspects of unrest between January 1, 2013, and the start of the eruption on November 28, 2022 (UTC). Earthquakes associated with unrest occurred above an inflating dike at shallow depths under and to the south of Moku‘āweoweo and in the cluster of seismicity to the west of Moku‘āweoweo associated with a buried rift zone. Earthquakes also occurred in a broad region at the base of the crust, likely associated with a zone of magma accumulation. Unrest is broken down into four phases of increasing intensity with time and into individual geographic regions. While activity occurring at shallow depths under the caldera often alternated with activity on the west flank in the first two phases of unrest, the third phase of unrest featured increased rates of earthquake activity in both areas acting concurrently. We also document a slow shift in seismicity across multiple years from the south of Moku‘āweoweo to an area under the caldera that likely represents a change in the location of the intrusion through time. Broadly speaking, unrest observed in advance of the 2022 eruption occurred in the same areas as the unrest preceding eruptions in 1975 and 1984. Furthermore, precursory unrest prior to eruptions in 1975, 1984 and 2022 lasted years and culminated in an intense phase of seismic activity lasting on the order of hours that represented the final dike propagation to the surface. Concurrent earthquake activity under Moku‘āweoweo and the west flank of Mauna Loa, paired with a shift in earthquakes under Moku‘āweoweo were the two most notable long-term precursors to an eruption; however, neither provided an actionable timeline of an impending eruption. The decade of precursory seismicity prior to the 2022 eruption is similar to long precursory phases prior to eruptions in 1975 and 1984 and underscores the challenges of informing on eruption hazards in a timely manner. By combining seismic activity with other geophysical fields such as geodesy and gravity, we present a conceptual model to aid in the interpretation of future unrest at Mauna Loa.

Hawaii↗
USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗
USGS2025

Local, regional, and distal recordings of seismic unrest at Tau Island volcano, American Samoa

A seismic swarm near Taʻū Island, a volcanic island in eastern American Samoa, occurred from July to October 2022. The earliest unrest was noted as felt shaking reports in late July, and instrumentation varied in the beginning of the sequence as the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory responded by installing temporary and then permanent seismometers to monitor the activity. This network variability made it difficult to characterize the earliest seismicity and contextualize the entire sequence to discriminate between an underlying tectonic or volcanic source. Here, we present results analyzing hydroacoustic detections from an International Monitoring System hydrophone array near Wake Island, 4500 km northwest of Taʻū Island volcano. Using least-squares beamforming analysis, we create a catalog of T-wave detections from the direction of Taʻū Island to track the earthquakes, some of which were located by the USGS National EarthquakeInformation Center. Both the rate and hydroacoustic pressures, which we interpret as a proxy for earthquake size, gradually increased from late July to August, peaking on August 19 (rate) and August 24 (size), before decreasing to background in late September. Minutes-long bursts of tremor were also contemporaneously recorded as local network data became avail-able on August 20. Tremor activity continued throughout the rest of August, peaking on August 25, before ending in earlySeptember. These tremor bursts were band-limited to ~ 1–5 Hz and recorded as S waves at a regional station on the island of Upolu in Samoa, 250 km to the west of Taʻū Island. Our results do not constrain the tremor locations, but comparisons of earthquake and tremor reduced displacements recorded locally and regionally suggest a deeper tremor source. We interpret the increase in earthquake size and rate, together with the occurrence, characteristics, and relative depth of the tremor to be the result of magmatic activity beneath Taʻū Island volcano.

American Samoa, Taʻū Island↗
USGS2024

Dynamics and detection of pulsed tremor at Whakaari (White Island), Aotearoa New Zealand

Volcanic tremor is a crucial indicator for assessing the state and hazard potential of volcanic systems. At Whakaari (White Island volcano, Aotearoa New Zealand), a pulsed tremor signal emerged after a hydrothermal explosion in August 2012. The tremor accompanied the extrusion of a lava dome, before gradually disappearing prior to the onset of renewed hydrothermal activity in January 2013. We interpret this seismic signal to represent discrete gas transfers from a magmatic intrusion toward a permeable cap—possibly a hydrothermal seal—in the upper layers of Whakaari's hydrothermal system. Such tremor may thus be associated with heightened potential for hazardous explosive activity but is difficult to detect using conventional seismic monitoring parameters. To highlight the emergence of subtle periodic signals, we experiment with Lomb-Scargle periodograms (LS). LS detect the tremor 5 days before it becomes visible in seismograms, thus facilitating the recognition of such elusive seismic patterns.

Whakaari (White Island)↗
USGS2024

Time varying crustal anisotropy at Whakaari/White Island volcano

Whakaari/White Island has been the most active New Zealand volcano in the 21st century, producing small phreatic and phreatomagmatic eruptions, which are hard to predict. The most recent eruption occurred in 2019, tragically claiming the lives of 22 individuals and causing numerous injuries. We employed shear-wave splitting analyses to investigate variations in anisotropy during quiescence, unrest, and an eruption between 2018 and 2020. We examined spatial and temporal variations in 7972 shear-wave splitting measurements and derived 1402 V p /IV s ratio measurements. Comparing shear-wave splitting parameters from similar earthquake paths across different times indicates that the observed temporal changes are unlikely to result from variations in earthquake paths through media with spatial variability. Instead, these changes may stem from variations in anisotropy over time, likely caused by changes in crack alignment due to stress or varying fluid content.

Whakaari/White Island volcano↗
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↗
USGS2023

Identification of seismo-volcanic regimes at Whakaari/White Island (New Zealand) via systematic tuning of an unsupervised classifier

We present an algorithm based on Self-Organizing Maps (SOM) and k-means clustering to recognize patterns in a continuous 12.5-year tremor time series recorded at Whakaari/White Island volcano, New Zealand (hereafter referred to as Whakaari). The approach is extendable to a variety of volcanic settings through systematic tuning of the classifier. Hyperparameters are evaluated by statistical means, yielding a combination of “ideal” SOM parameters for the given data set. Extending from this, we applied a Kernel Density Estimation approach to automatically detect changes within the observed seismicity. We categorize the Whakaari seismic time series into regimes representing distinct volcano-seismic states during recent unrest episodes at Whakaari (2012/2013, 2016, and 2019). There is a clear separation in classification results between background regimes and those representing elevated levels of unrest. Onset of unrest is detected by the classifier 6 weeks before the August 2012 eruption, and ca. 3.5 months before the December 2019 eruption, respectively. Regime changes are corroborated by changes in commonly monitored tremor proxies as well as with reported volcanic activity. The regimes are hypothesized to represent diverse mechanisms including: system pressurization and depressurization, degassing, and elevated surface activity. Labeling these regimes improves visualization of the 2012/2013 and 2019 unrest and eruptive episodes. The pre-eruptive 2016 unrest showed a contrasting shape and nature of seismic regimes, suggesting differing onset and driving processes. The 2016 episode is proposed to result from rapid destabilization of the shallow hydrothermal system, while rising magmatic gases from new injections of magma better explain the 2012/2013 and 2019 episodes.

Whakaari, White Island↗
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

Evidence for near-source nonlinear propagation of volcano infrasound from Strombolian explosions at Yasur Volcano, Vanuatu

Volcanic eruption source parameters may be estimated from acoustic pressure recordings dominant at infrasonic frequencies (< 20 Hz), yet uncertainties may be high due in part to poorly understood propagation dynamics. Linear acoustic propagation of volcano infrasound is commonly assumed, but nonlinear processes such as wave steepening may distort waveforms and obscure the sourcing process in recorded waveforms. Here we use a previously developed frequency-domain nonlinearity indicator to quantify spectral changes due to nonlinear propagation primarily in 80 signals from explosions at Yasur Volcano, Vanuatu. We find evidence for &#x2264; "> ≤ ≤ 10 −3 dB/m spectral energy transfer in the band 3–9 Hz for signals with amplitude on the order of several hundred Pa at 200–400 m range. The clarity of the nonlinear spectral signature increases with waveform amplitude, suggesting stronger nonlinear changes for greater source pressures. We observe similar results in application to synthetics generated through finite-difference wavefield simulations of nonlinear propagation, although limitations of the model complicate direct comparison to the observations. Our results provide quantitative evidence for nonlinear propagation that confirms previous interpretations made on the basis of qualitative observations of asymmetric waveforms.

Bulletin of Volcanology↗
USGS2022

Synthetic evaluation of infrasonic multipole waveform inversion

Acoustic source inversions estimate the mass flow rate of volcanic explosions or yield of chemical explosions and provide insight into potential source directionality. However, the limitations of applying these methods to complex sources and their ability to resolve a stable solution have not been investigated in detail. We perform synthetic infrasound waveform inversions that use 3-D Green’s functions for a variety of idealized and realistic deployment scenarios using both a flat plane and Yasur volcano, Vanuatu as examples. We investigate the ability of various scenarios to retrieve the input source functions and relative amplitudes for monopole and multipole (monopole and dipole) inversions. Infrasound waveform inversions appear to be a robust method to quantify mass flow rates from simple sources (monopole) using deployments of infrasound sensors placed around a source, but care should be taken when analyzing and interpreting results from more complex acoustic sources (multipole) that have significant directional components. In the examples we consider the solution is stable for monopole inversions with a signal-to-noise ratio greater than five and the dipole component is small. For most scenarios investigated, the vertical dipole component of the multipole explosion source is poorly constrained and can impact the ability to recover the other source term components. Because multipole inversions are ill-posed for many deployments, a low residual does not necessarily mean the proper source vector has been recovered. Synthetic studies can help investigate the limitations and place bounds on information that may be missing using monopole and multipole inversions for potentially directional sources.

Journal of Geophysical Research-Solid Earth↗
USGS2022

High-rate very-long-period seismicity at Yasur volcano, Vanuatu: source mechanism and decoupling from surficial explosions and infrasound

Yasur volcano, Vanuatu is a continuously active open-vent basaltic-andesite stratocone with persistent and long-lived eruptive activity. We present results from a seismo-acoustic field experiment at Yasur, providing locally dense broad-band seismic and infrasonic network coverage from 2016 July 27 to August 3. We corroborate our seismo-acoustic observations with coincident video data from cameras deployed at the crater and on an unoccupied aircraft system (UAS). The waveforms contain a profusion of signals reflecting Yasur’s rapidly occurring and persistent explosive activity. The typical infrasonic signature of Yasur explosions is a classic short-duration and often asymmetric explosion waveform characterized by a sharp compressive onset and wideband frequency content. The dominant seismic signals are numerous repetitive very-long-period (VLP) signals with periods of ∼2–10 s. The VLP seismic events are ‘high-rate’, reoccurring near-continuously throughout the data set with short interevent times (∼20–60 s). We observe variability in the synchronization of seismic VLP and acoustic sources. Explosion events clearly delineated by infrasonic waveforms are underlain by seismic VLPs. However, strong seismic VLPs also occur with only a weak infrasonic expression. Multiplet analysis of the seismic VLPs reveals a systematic progression in the seismo-acoustic source decoupling. The same dominant seismic VLP multiplet occurs with and without surficial explosions and infrasound, and these transitions occur over a timescale of a few days during our field campaign. We subsequently employ template matching, stacking, and full-waveform inversion to image the source mechanism of the dominant VLP multiplet. Inversion of the dominant VLP multiplet stack points to a composite source consisting of either a dual-crack (plus forces) or pipe-crack (plus forces) mechanism. The derived mechanisms correspond to a point-source directly beneath the summit vents with centroid depths in the range ∼900–1000 m below topography. All mechanisms suggest a northeast trending crack dipping relatively shallowly to the northwest and indicate a VLP source centroid and mechanism controlled by a stable structural geologic feature beneath Yasur. We interpret the results in the framework of gas slug ascent through the conduit responsible for Yasur explosions. The VLP mechanism and timing with infrasound (when present) are explained by a shallow-buffered top-down model in which slug ascent is relatively aseismic until reaching the base of a shallow section. Slug disruption in this shallow zone triggers a pressure disturbance that propagates downward and couples at the conduit base (VLP centroid). If the shallow section is open, an explosion propagates to the surface, producing infrasound. In the case of (the same multiplet) VLPs occurring without surficial explosions and weak or no infrasound, the decoupling of the dominant VLPs at ∼900–1000 m depth from surficial explosions and infrasound strongly indicates buffering of the terminal slug ascent. This buffering could be achieved by a variety of conditions at or directly beneath the vents, such as a high-viscosity layer of crystal-rich magma, a debris cap from backfill, a foam layer, or a combination of these. The dominant VLP at Yasur captured by our experiment has a source depth and mechanism separated from surface processes and is stable over time.

Geophysical Journal International↗
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↗
USGS2016

Seismo-acoustic evidence for an avalanche driven phreatic eruption through a beheaded hydrothermal system: An example from the 2012 Tongariro eruption

The 6 August 2012 Te Maari eruption comprises a complex eruption sequence including multiple eruption pulses, a debris avalanche that propagated ~ 2 km from the vent, and the formation of a 500 m long, arcuate chasm, located ~ 300 m from the main eruption vent. The eruption included 6 distinct impulses that were coherent across a local infrasound network marking the eruption onset at 11:52:18 (all times UTC). An eruption energy release of ~ 3 × 1012 J was calculated using a body wave equation for radiated seismic energy. A similar calculation based on the infrasound record, shows that ~ 90% of the acoustic energy was released from three impulses at onset times 11:52:20 (~ 20% of total eruption energy), 11:52:27 (~ 50%), and 11:52:31 (~ 20%). These energy impulses may coincide with eyewitness accounts describing an initial eastward directed blast, followed by a westward directed blast, and a final vertical blast. Pre-eruption seismic activity includes numerous small unlocatable micro-earthquakes that began at 11:46:50. Two larger high frequency earthquakes were recorded at 11:49:06 and 11:49:21 followed directly by a third earthquake at 11:50:17. The first event was located within the scarp based on an arrival time location from good first P arrival times and probably represents the onset of the debris avalanche. The third event was a tornillo, characterised by a 0.8 Hz single frequency resonance, and has a resonator attenuation factor of Q ~ 40, consistent with a bubbly fluid filled resonator. This contrasts with a similar tornillo event occurring 2.5 weeks earlier having Q ~ 250–1000, consistent with a dusty gas charged resonator. We surmise from pre-eruption seismicity, and the observed attenuation change, that the debris avalanche resulted from the influx of fluids into the hydrothermal system, causing destabilisation and failure. The beheaded hydrothermal system may have then caused depressurisation frothing of the remaining gas charged system leading to the onset of explosive activity.

Journal of Volcanology and Geothermal Research↗
USGS2007

Three-dimensional P-wave velocity structure derived from local earthquakes at the Katmai group of volcanoes, Alaska

The three-dimensional P-wave velocity structure beneath the Katmai group of volcanoes is determined by inversion of more than 10,000 rays from over 1000 earthquakes recorded on a local 18 station short-period network between September 1996 and May 2001. The inversion is well constrained from sea level to about 6 km below sea level and encompasses all of the Katmai volcanoes; Martin, Mageik, Trident, Griggs, Novarupta, Snowy, and Katmai caldera. The inversion reduced the average RMS travel-time error from 0.22 s for locations from the standard one-dimensional model to 0.13 s for the best three-dimensional model. The final model, from the 6th inversion step, reveals a prominent low velocity zone (3.6–5.0 km/s) centered at Katmai Pass and extending from Mageik to Trident volcanoes. The anomaly has values about 20–25% slower than velocities outboard of the region (5.0–6.5 km/s). Moderately low velocities (4.5–6.0 km/s) are observed along the volcanic axis between Martin and Katmai Caldera. Griggs volcano, located about 10 km behind (northwest of) the volcanic axis, has unremarkable velocities (5.0–5.7 km/s) compared to non-volcanic regions. The highest velocities are observed between Snowy and Griggs volcanoes (5.5–6.5 km/s). Relocated hypocenters for the best 3-D model are shifted significantly relative to the standard model with clusters of seismicity at Martin volcano shifting systematically deeper by about 1 km to depths of 0 to 4 km below sea level. Hypocenters for the Katmai Caldera are more tightly clustered, relocating beneath the 1912 scarp walls. The relocated hypocenters allow us to compare spatial frequency-size distributions ( b -values) using one-dimensional and three-dimensional models. We find that the distribution of b is significantly changed for Martin volcano, which was characterized by variable values (0.8 < b < 2.0) with standard locations and more uniform values (0.8 < b < 1.2) after relocation. Other seismic clusters at Mageik (1.2 < b < 2.2), Trident (0.5 < b < 1.5) and Katmai Caldera (0.8 < b < 1.8) had stable b -values indicating the robustness of the observations. The strong high b -value region at Mageik volcano is mainly associated with an earthquake swarm in October, 1996 that possibly indicates a shallow intrusion or influx of gas. The new velocity and spatial b -value results, in conjunction with prior gravity (Bouguer anomalies up to − 40 mgal) and interferometry (several cm uplift) data, provide strong evidence in favor of partially molten rock at shallow depths beneath the Mageik–Katmai–Novarupta region. Moderately low velocities beneath Martin and Katmai suggest that old, mostly solidified intrusions exist beneath these volcanoes. Higher relative velocities beneath the Griggs and Snowy vents suggest that no magma is resident in the shallow crust beneath these volcanoes.

Journal of Volcanology and Geothermal Research↗