Geology topics

Matthew M. Haney

Publications and source records attributed to Matthew M. Haney.

At least 55 records · Page 3Linked to original sources

USGS2020

Very‐long‐period (VLP) seismic artifacts during the 2018 caldera collapse at Kīlauea, Hawaii

Throughout the 2018 eruption of Kīlauea volcano (Hawai‘i), episodic collapses of a portion of the volcano’s summit caldera produced repeated M w "> M w 4.9–5.3 earthquakes. Each of these 62 events was characterized by a very‐long‐period (VLP) seismic signal ( ⁠ > 40    s "> > 40 s ⁠ ). Although collapses in the later stage of the eruption produced earthquakes with significant amplitude clipping on near‐summit broadband seismometers, the first 12 were accurately recorded. For these initial collapse events, we compare average VLP seismograms at six near‐summit locations to synthetic seismograms derived from displacements at collocated Global Positioning System stations. We show that the VLP seismic signal was generated by a radially outward and upward ramp function in displacement. We propose that at local distances the period of the VLP seismic signal is solely dependent on the duration of this ramp function and the instrument transfer function, that is, the seismic VLP is an artifact of the bandlimited instrument response and not representative of real ground motion. The displacement ramp function imposes a sinc‐function velocity amplitude spectrum that cannot be fully recovered through standard seismic instrument deconvolution. Any near‐summit VLP signals in instrument‐response‐corrected velocity or displacement seismograms from these collapse events are subject to severe band limitation. Similarly, the seismic amplitude response is not flat through the low‐frequency corner, for example, instrument‐response‐uncorrected seismograms scaled by instrument sensitivity are equally prone to band limitation. This observation is crucial when attempting to clarify the different contributions to the VLP source signature. Not accounting for this effect could lead to misunderstanding of the magmatic processes involved.

Hawaii↗

USGS2020

Bulk structure of the crust and upper mantle beneath Alaska from an approximate Rayleigh-wave dispersion formula

We introduce a method for estimating crustal thickness and bulk crustal and upper‐mantle shear‐wave velocities directly from high‐quality measurements of fundamental‐mode Rayleigh‐wave dispersion in the period range from 10 to 40 s. The method is based on an approximate Rayleigh‐wave dispersion formula and provides fast results with minimal model parameterization. We apply the method to Rayleigh‐wave phase maps in Alaska to reveal first‐order structure in a region that had not been systematically and densely instrumented prior to the Transportable Array (TA). To demonstrate the consistency of the results, we also apply the same method to existing Rayleigh‐wave phase maps derived from TA data in the conterminous United States, where crustal and upper mantle structures are better known. We contrast features observed in maps of crustal thickness and bulk shear‐wave velocity between the Cascadia and Alaska‐Aleutian subduction zones to highlight differences in the two regions. Our results show that, contrary to conventional wisdom, first‐order information on the location of major depth discontinuities (e.g., the Moho) can be extracted in a fast, straightforward manner from measurements of Rayleigh‐wave dispersion alone.

Seismological Research Letters↗

USGS2020

Seismic velocity variations associated with the 2018 lower East Rift Zone eruption of Kīlauea, Hawaiʻi

The 2018 lower East Rift Zone eruption of Kīlauea (Hawai‘i) marked a dramatic change in the volcano’s 35-year-long rift zone eruption. The collapse of the middle East Rift Zone vent Pu‘u ‘Ō‘ō was followed by one of the volcano’s most voluminous eruptions in 500 years. Over the course of this 3-month eruption, the draining of summit-stored magma led to near-daily collapses of a portion of the caldera and ultimately up to 500 m of summit subsidence. While deformation data indicated that the summit and middle East Rift Zone were inflating for the previous several years, why Pu‘u ‘Ō‘ō collapsed and what initiated down-rift dike propagation remains unclear. Using ambient noise seismic interferometry, we show that a Ml5.3 decollement earthquake beneath Kīlauea’s south flank in June 2017 induced a coseismic decrease of up to 0.30% in seismic velocity throughout the volcano. This velocity decrease may have been caused by dynamic stress–induced shallow crustal fracture, i.e., weakening to dilatant crack growth, and was greatest near Pu‘u ‘Ō‘ō. Additionally, we verify a pre-eruptive increase in seismic velocity, consistent with increasing pressurization in the volcano’s shallow summit magma reservoir. This velocity increase occurred coincident with the first in a series of lower-crustal earthquake swarms, 6 days before a 2-month period of rapid summit and middle East Rift Zone inflation. The increase in up-rift magma-static pressure, combined with the pre-existing weakness from the June 2017 earthquake, may have facilitated down-rift dike propagation and the devastating 2018 eruption.

Hawaii↗

USGS2020

Linking magma storage and ascent to eruption volume and composition at an arc caldera

Conceptual models of magma storage and transport under calderas favor a connected system of sills and dikes. These features are individually below the resolution of standard seismic tomography, but radial seismic anisotropy can reveal where they exist in aggregate. We model radial anisotropy at Okmok caldera, Alaska, to demonstrate the presence of a caldera-centered stacked sill complex and surrounding dike system. We show that ascending magma, inferred from seismicity, either intersects the sill complex, resulting in a larger volume eruption of evolved magma, or bypasses the overlying sill complex via dikes, resulting in a low-volume mafic eruption. Our results exemplify how the locations of magma storage and paths of transport impact eruption size and composition. As this type of crustal storage is likely common to many calderas, this analysis offers a potential new framework for volcano observatories to forecast the size of impending eruptions.

Alaska↗

USGS2020

Uncertainty in detection of volcanic activity using infrasound arrays: Examples from Mt. Etna, Italy

The injection of gas and pyroclastic material from volcanic vents into the atmosphere is a prolific source of acoustic waves. Infrasound arrays offer efficient, cost-effective, and near real-time solutions to track the rate and intensity of surface activity at volcanoes. Here, we present a simple framework for the analysis of acoustic array data, based on least-squares beamforming, that allows to evaluate the direction and speed of propagation of acoustic waves between source and array. The algorithms include a new and computationally efficient approach for quantitative assessment of the uncertainty on array measurements based on error propagation theory. We apply the algorithms to new data collected by two 6-element infrasound arrays deployed at Mt. Etna during the period July–August 2019. Our results demonstrate that the use of two infrasound arrays allowed detecting and tracking acoustic sources from multiple craters and active vents associated with degassing and ash-rich explosions, vigorous and frequent Strombolian activity, opening of new eruptive fractures and emplacement of lava flows. Finally, we discuss the potential use of metrics based on infrasound array analyses to inform eruption monitoring operations and early warning at volcanoes characterized by episodic intensification of activity.

Mt. Etna↗

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↗

USGS2020

Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano

The 2018 eruption of Kīlauea volcano, Hawaiʻi, resulted in a major collapse of the summit caldera along with an effusive eruption in the lower East Rift Zone. The caldera collapse comprised 62 highly similar collapse cycles of strong ground deformation and earthquake swarms that ended with a magnitude 5 collapse event and one partial cycle that did not end with a collapse event. We analyzed geodetic and seismic data to better understand how the caldera collapse progressed over 3 months of activity, focusing on the cyclical activity. We identified 3 main phases of collapse: initial ring-fault activation and small explosions (Phase 1), an eastward shift in activity and freeing of the central piston (Phase 2), and a recoupling of the piston to the reservoir followed by relatively steady behavior until the eruption’s end (Phase 3). Additionally, we observed geodetic evidence of tangential motion from the localization of the main ring fault (Phase 2) and the formation of a major peripheral ring fault on the eastern side of the collapse caldera during Phase 3. Both geodetic and seismic parameters suggest that the collapse may have had an eastward-component of motion after the ring fault system had formed. The cyclical seismic and geodetic parameters show no obvious signs that the collapse was coming to an end, with the only notable change being a significant increase in the ratio of cyclical displacement to co-collapse displacement observed during the last complete cycle on GNSS stations outside the caldera region.

Hawaii↗

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

Perturbational and nonperturbational inversion of Love-wave velocities

We describe a set of MATLAB codes to forward model and invert Love-wave phase or group velocities. The forward modeling is based on a finite-element method in the frequency-wavenumber domain, and we obtain the different modes with an eigenvector-eigenvalue solver. We examine the issue of parasitic modes that arises for modeling Love waves, in contrast to the Rayleigh wave case, and how to discern parasitic from physical modes. Once the matrix eigenvector-eigenvalue problem has been solved for Love waves, we show a straightforward technique to obtain sensitivity kernels for S-wave velocity and density. In practice, the sensitivity of Love waves to density is relatively small and inversions only aim to estimate the S-wave velocity. Two types of inversion accompany the forward-modeling codes: One is a perturbational scheme for updating an initial model, and the other is a nonperturbational method that is well-suited for defining a good initial model. The codes are able to implement an optimal nonuniform layering designed for Love waves, invert combinations of phase and group velocity measurements of any mode, and seamlessly handle the transition from guided to leaky modes below the cutoff frequency. Two software examples demonstrate use of the codes at near-surface and crustal scales.

Geophysics↗

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↗

USGS2019

Catalog of earthquake parameters and description of seismograph and infrasound stations at Alaskan volcanoes—January 1, 2013, through December 31, 2017

Between January 1, 2013, and December 31, 2017, the Alaska Volcano Observatory (AVO) located a total of 28,172 earthquakes at volcanoes in Alaska. The annual totals are 3,840, 5,819, 5,297, 6,151, and 7,065 earthquakes for the years 2013 through 2017, respectively. This represents an average of 5,634 earthquakes per year, which is comparable to the yearly number of earthquakes AVO located in the previous decade when AVO monitored a similar number of volcanoes. During the reporting period, there was significant seismic activity at 20 of the 34 volcanoes monitored by a seismograph network (Akutan Peak, Aniakchak Crater, Augustine, Mount Cerberus, Mount Cleveland, Fourpeaked Mountain, Mount Gareloi, Great Sitkin, Ilimana, Kanaga, Korovin, Makushin, Mount Martin, Okmok Caldera, Pavlof, Shishaldin, Mount Spurr, Tanaga, Ugashik-Peulik, and Mount Veniaminof) and two volcanoes without a monitoring network (Mount Recheshnoi and Bogoslof Island). Instrumentation highlights for this period include the establishment of a new subnetwork on Mount Cleveland, an accelerated transition from analog to digital telemetry at most subnetworks, and an increased number of broadband and infrasound sensors throughout the AVO network. The operational highlight was the return of seismic monitoring at Korovin and Ugashik-Peulik Volcanoes following network repairs. This catalog includes hypocenters, magnitudes, and statistics of the earthquakes located in 2013–17, along with the associated station parameters, and velocity models.

Alaska↗