Geology topics

Matthew M. Haney

Publications and source records attributed to Matthew M. Haney.

At least 55 records · Page 3Linked to original sources

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↗

USGS2019

Hydroacoustic, seismic, and bathymetric observations of the 2014 submarine eruption at Ahyi Seamount, Mariana Arc

Ahyi seamount, a shallow submarine volcano in the Northern Mariana Islands, began erupting on April 23, 2014. Hydroacoustic eruption signals were observed on the regional Mariana seismic network and on distant hydrophones, and NOAA scuba divers working in the area soon after the eruption began heard and felt underwater explosion sounds. The NOAA crew observed yellow orange bubble mats along the shore of neighboring Farallon de Pájaros island, but no other surface manifestations of the eruption were reported by the crew or observed in satellite data. Here, we detail the eruption chronology and its morphologic impacts through analysis of seismic and hydroacoustic recordings and repeat bathymetric mapping. Throughout the 2-week-long eruption, Ahyi produced several thousand short, impulsive hydroacoustic signals that we interpret as underwater explosions as well as tremor near the beginning and end of the sequence. The initial tremor, which occurred for 2 hours, is interpreted as small phreatomagmatic explosions. This tremor was followed by a 90 min pause before the characteristic impulsive signals began. Occasional tremor (lasting up to a few minutes) during the last 1.5 days of the eruption is interpreted as more sustained eruptive activity. Bathymetric changes show that a new crater, about 150 m deep, formed near the former summit and a large landslide chute formed on the southeastern flank. Comparing to other geophysically-detected submarine eruptions, we find that the signals from the 2014 Ahyi eruption were more similar to those from other shallow or at surface submarine eruptions than those at deep (>500 m) eruptions.

Geochemistry, Geophysics, Geosystems↗

USGS2019

A unified catalog of earthquake hypocenters and magnitudes at volcanoes in Alaska—1989 to 2018

The Alaska Volcano Observatory (AVO) has maintained an earthquake catalog since 1989 that now contains over 120,000 hypocenters and magnitudes that occurred near Alaskan volcanoes. Since 1989 the seismic instrumentation and data acquisition and processing techniques have undergone numerous changes as computer systems and seismic processing software have advanced and evolved. In this report we recalculate earthquake hypocenters and magnitudes in a consistent manner between October 1989 and January 2018. The new hypocenters and magnitudes are archived at the AVO within an AQMS database and in the compressed UNIX tar file that accompanies this publication.

Alaska↗

USGS2019

Application of an updated atmospheric model to explore volcano infrasound propagation and detection in Alaska

Winds and temperature gradients greatly affect the long-range propagation of infrasound . The spatio-temporal variability of these parameters must therefore be accurately characterized to correctly interpret recorded infrasound at long distances, specifically to differentiate between source and propagation effects. Here we present the first results of an open source reanalysis model, termed Alaska Volcano Observatory Ground-to-Space (AVO-G2S), constructed to accurately characterize the atmosphere and model long-range infrasound propagation from volcanic eruptions in Alaska. We select a number of case studies to examine recent eruptions of Alaskan volcanoes whose ash emissions posed a threat to air traffic, including the two most recent eruptions of Pavlof Volcano and two typical explosions from Cleveland Volcano. Strong tropospheric ducting and low noise at the station during the 21 July 2015 explosion of Cleveland Volcano led to an automated detection of the explosion at an infrasound array 992 km away, whereas low signal-to-noise ratio for the 6 November 2014 Cleveland Volcano explosion helps explain the non-detection in real-time of a predicted strong stratospheric arrival. For the November 2014 Pavlof eruption, discrepancies between local seismic data and a distal infrasound array 460 km away cannot be solely explained by changes in atmospheric conditions, though some features of the complex propagation predictions follow the trends in long-range infrasound signals. The most recent eruption of Pavlof Volcano in March 2016 shows minimal changes in propagation conditions throughout the eruption and therefore indicates that the signals detected at long-range primarily reflect source processes. These results show how detailed examination of the acoustic propagation conditions provides insight into detection capability and eruption dynamics. Future work will implement AVO-G2S and high-resolution long-range infrasound propagation modeling in real-time for Alaskan volcanoes of interest.

Alaska↗

USGS2019

Seismic and acoustic signatures of surficial mass movements at volcanoes

Surficial mass movements, such as debris avalanches, rock falls, lahars, pyroclastic flows, and outburst floods, are a dominant hazard at many volcanoes worldwide. Understanding these processes, cataloging their spatio-temporal occurrence, and detecting, tracking, and characterizing these events would advance the science of volcano monitoring and help mitigate hazards. Seismic and acoustic methods show promise for achieving these objectives: many surficial mass movements generate observable seismic and acoustic signals, and many volcanoes are already monitored. Significant progress has been made toward understanding, modeling, and extracting quantitative information from seismic and infrasonic signals generated by surficial mass movements. However, much work remains. In this paper, we review the state of the art of the topic, covering a range of scales and event types from individual rock falls to sector collapses. We consider a full variety of volcanic settings, from submarine to subaerial, shield volcano to stratovolcano. Finally, we discuss future directions toward operational seismo-acoustic monitoring of surficial mass movements at volcanoes.

Journal of Volcanology and Geothermal Research↗

USGS2018

Inferring magma dynamics at Veniaminof volcano via application of ambient noise

Ambient noise interferometry has become an increasingly popular tool for monitoring active volcanoes. We apply this method to investigate seven past eruptive periods at Veniaminof volcano, Alaska. Two of the largest eruptions studied show seismic velocity changes associated with preeruptive , coeruptive, and posteruptive volcanic processes. We develop and implement new analysis techniques to determine how seismic velocity changes at Veniaminof are distributed with depth. Spatiotemporal examination of these seismic velocity changes reveals evidence for the distribution of magma storage and the timescale at which magmatic fluids intrude into and reside within these storage regions in the months preceding eruption. We conduct the depth analysis using data recorded on a single seismometer. The same analysis could be applied to any volcano monitored by at least one seismometer in order to detect magmatic activity indicative of impending eruption, specifically the intrusion and migration of magmatic fluids into the volcanic system.

Alaska↗

USGS2018

Short-term forecasting and detection of explosions during the 2016–2017 eruption of Bogoslof volcano, Alaska

We describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explosive events. Because the volcano has no local monitoring stations, we used distant stations on the nearest volcanoes, Okmok (54 km) and Makushin (72 km), combined with regional infrasound sensors and lightning detection from the Worldwide Lightning Location Network (WWLLN). Pre-eruptive seismicity was detected for 12 events during the first half of the eruption; for all other events co-eruptive signals allowed for detection only. Monitoring of activity used a combination of scheduled checks combined with automated alarms. Alarms triggered on real-time data included real-time seismic amplitude measurement (RSAM); infrasound from several arrays, the closest being on Okmok; and lightning strokes detected from WWLLN within a 20-km radius of the volcano. During periods of unrest, a multidisciplinary response team of four people fulfilled specific roles to evaluate geophysical and remote-sensing data, run event-specific ash-cloud dispersion models, ensure interagency coordination, and develop and distribute of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, Alaska Volcano Observatory (AVO) called emergency response partners 15 min, and issued written notices 30 min, after event onset (mean times). Factors that affect timeliness of written warnings include event size and number of data streams available; bigger events and more data both decrease uncertainty and allow for faster warnings. In remote areas where airborne ash is the primary hazard, the approach used at Bogoslof is an effective strategy for hazard mitigation.

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

Using earthquakes, T waves, and infrasound to investigate the eruption of Bogoslof Volcano, Alaska

The 2016‐2017 eruption of Bogoslof volcano, a submarine stratovolcano in the Bering Sea, produced 70 discrete explosive eruptions over 8 months. With no local monitoring data, activity was seismically recorded on nearby islands 50‐100 km away, limiting the detection and resolution of seismic observations. We construct a matched filter catalog of 3199 events from 49 earthquake families, many of which occurred with hydroacoustic T waves of varying strength. We then use a 2D finite difference model to show that hydroacoustic amplitudes should decrease with increased source depth beneath the edifice and leverage each family's seismically recorded T wave amplitude as a proxy for source depth, which we compare to regional infrasound data. This unique combination of using P and S waves to detect events, T waves as a proxy for depth, and infrasound for precise timing of emissions allows us to interpret the dynamics and evolution of the Bogoslof eruption.

Alaska↗

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↗