Geology topics

Matthew M. Haney

Publications and source records attributed to Matthew M. Haney.

At least 73 records · Page 4Linked to original sources

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↗

USGS2018

Volcanic thunder from explosive eruptions at Bogoslof volcano, Alaska

Lightning often occurs during ash-producing eruptive activity, and its detection is now being used in volcano monitoring for rapid alerts. We report on infrasonic and sonic recordings of the related, but previously undocumented, phenomenon of volcanic thunder. We observe volcanic thunder during the waning stages of two explosive eruptions at Bogoslof volcano, Alaska, on a microphone array located 60 km away. Thunder signals arrive from a different direction than coeruptive infrasound generated at the vent following an eruption on 10 June 2017, consistent with locations from lightning networks. For the 8 March 2017 eruption, arrival times and amplitudes of high-frequency thunder signals correlate well with the timing and strength of lightning detections. In both cases, the thunder is associated with lightning that continues after significant eruptive activity has ended. Infrasonic and sonic observations of volcanic thunder offer a new avenue for studying electrification processes in volcanic plumes.

Alaska↗

USGS2017

Seismic equivalents of volcanic jet scaling laws and multipoles in acoustics

We establish analogies between equivalent source theory in seismology (moment-tensor and single-force sources) and acoustics (monopoles, dipoles and quadrupoles) in the context of volcanic eruption signals. Although infrasound (acoustic waves < 20 Hz) from volcanic eruptions may be more complex than a simple monopole, dipole or quadrupole assumption, these elementary acoustic sources are a logical place to begin exploring relations with seismic sources. By considering the radiated power of a harmonic force source at the surface of an elastic half-space, we show that a volcanic jet or plume modelled as a seismic force has similar scaling with respect to eruption parameters (e.g. exit velocity and vent area) as an acoustic dipole. We support this by demonstrating, from first principles, a fundamental relationship that ties together explosion, torque and force sources in seismology and highlights the underlying dipole nature of seismic forces. This forges a connection between the multipole expansion of equivalent sources in acoustics and the use of forces and moments as equivalent sources in seismology. We further show that volcanic infrasound monopole and quadrupole sources exhibit scalings similar to seismicity radiated by volume injection and moment sources, respectively. We describe a scaling theory for seismic tremor during volcanic eruptions that agrees with observations showing a linear relation between radiated power of tremor and eruption rate. Volcanic tremor over the first 17 hr of the 2016 eruption at Pavlof Volcano, Alaska, obeyed the linear relation. Subsequent tremor during the main phase of the eruption did not obey the linear relation and demonstrates that volcanic eruption tremor can exhibit other scalings even during the same eruption.

Geophysical Journal International↗

USGS2017

The 2014 eruptions of Pavlof Volcano, Alaska

Pavlof Volcano is one of the most frequently active volcanoes in the Aleutian Island arc, having erupted more than 40 times since observations were first recorded in the early 1800s . The volcano is located on the Alaska Peninsula (lat 55.4173° N, long 161.8937° W), near Izembek National Wildlife Refuge. The towns and villages closest to the volcano are Cold Bay, Nelson Lagoon, Sand Point, and King Cove, which are all within 90 kilometers (km) of the volcano (fig. 1). Pavlof is a symmetrically shaped stratocone that is 2,518 meters (m) high, and has about 2,300 m of relief. The volcano supports a cover of glacial ice and perennial snow roughly 2 to 4 cubic kilometers (km 3 ) in volume, which is mantled by variable amounts of tephra fall, rockfall debris, and pyroclastic-flow deposits produced during historical eruptions. Typical Pavlof eruptions are characterized by moderate amounts of ash emission, lava fountaining, spatter-fed lava flows, explosions, and the accumulation of unstable mounds of spatter on the upper flanks of the volcano. The accumulation and subsequent collapse of spatter piles on the upper flanks of the volcano creates hot granular avalanches, which erode and melt snow and ice, and thereby generate watery debris-flow and hyperconcentrated-flow lahars. Seismic instruments were first installed on Pavlof Volcano in the early 1970s, and since then eruptive episodes have been better characterized and specific processes have been documented with greater certainty. The application of remote sensing techniques, including the use of infrasound data, has also aided the study of more recent eruptions. Although Pavlof Volcano is located in a remote part of Alaska, it is visible from Cold Bay, Sand Point, and Nelson Lagoon, making distal observations of eruptive activity possible, weather permitting. A busy air-travel corridor that is utilized by a numerous transcontinental and regional air carriers passes near Pavlof Volcano. The frequency of air travel across the region results in a relatively large number of airborne observations of eruptive activity. During the 2014 Pavlof eruptions, the Alaska Volcano Observatory received observations and photographs from pilots and local observers, which aided evaluation of the eruptive activity and the areas affected by eruptive products. This report outlines the chronology of events associated with the 2014 eruptive activity at Pavlof Volcano, provides documentation of the style and character of the eruptive episodes, and reports briefly on the eruptive products and impacts. The principal observations are described and portrayed on maps and photographs, and the 2014 eruptive activity is compared to historical eruptions.

Alaska↗

USGS2017

Reducing risk where tectonic plates collide—U.S. Geological Survey subduction zone science plan

The U.S. Geological Survey (USGS) serves the Nation by providing reliable scientific information and tools to build resilience in communities exposed to subduction zone earthquakes, tsunamis, landslides, and volcanic eruptions. Improving the application of USGS science to successfully reduce risk from these events relies on whole community efforts, with continuing partnerships among scientists and stakeholders, including researchers from universities, other government labs and private industry, land-use planners, engineers, policy-makers, emergency managers and responders, business owners, insurance providers, the media, and the general public. Motivated by recent technological advances and increased awareness of our growing vulnerability to subduction-zone hazards, the USGS is uniquely positioned to take a major step forward in the science it conducts and products it provides, building on its tradition of using long-term monitoring and research to develop effective products for hazard mitigation. This science plan provides a blueprint both for prioritizing USGS science activities and for delineating USGS interests and potential participation in subduction zone science supported by its partners. The activities in this plan address many USGS stakeholder needs: High-fidelity tools and user-tailored information that facilitate increasingly more targeted, neighborhood-scale decisions to mitigate risks more cost-effectively and ensure post-event operability. Such tools may include maps, tables, and simulated earthquake ground-motion records conveying shaking intensity and frequency. These facilitate the prioritization of retrofitting of vulnerable infrastructure; Information to guide local land-use and response planning to minimize development in likely hazardous zones (for example, databases, maps, and scenario documents to guide evacuation route planning in communities near volcanoes, along coastlines vulnerable to tsunamis, and built on landslide-prone terrain); New tools to assess the potential for cascading hazards, such as landslides, tsunamis, coastal changes, and flooding caused by earthquakes or volcanic eruptions; Geospatial models of permanent, widespread land- and sea-level changes that may occur in the immediate aftermath of great ( M ≥8.0) subduction zone earthquakes; Strong partnerships between scientists and public safety providers for effective decision making during periods of elevated hazard and risk; Accurate forecasts of far-reaching hazards (for example, ash clouds, tsunamis) to avert catastrophes and unnecessary disruptions in air and sea transportation; Aftershock forecasts to guide decisions about when and where to re-enter, repair, or rebuild buildings and infrastructure, for all types of subduction zone earthquakes.

Circular↗

USGS2017

Volcanic tremor and plume height hysteresis from Pavlof Volcano, Alaska

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

Alaska↗

USGS2017

Perturbational and nonperturbational inversion of Rayleigh-wave velocities

The inversion of Rayleigh-wave dispersion curves is a classic geophysical inverse problem. We have developed a set of MATLAB codes that performs forward modeling and inversion of Rayleigh-wave phase or group velocity measurements. We describe two different methods of inversion: a perturbational method based on finite elements and a nonperturbational method based on the recently developed Dix-type relation for Rayleigh waves. In practice, the nonperturbational method can be used to provide a good starting model that can be iteratively improved with the perturbational method. Although the perturbational method is well-known, we solve the forward problem using an eigenvalue/eigenvector solver instead of the conventional approach of root finding. Features of the codes include the ability to handle any mix of phase or group velocity measurements, combinations of modes of any order, the presence of a surface water layer, computation of partial derivatives due to changes in material properties and layer boundaries, and the implementation of an automatic grid of layers that is optimally suited for the depth sensitivity of Rayleigh waves.

Geophysics↗

USGS2016

Volcano deformation source parameters estimated from InSAR: Sensitivities to uncertainties in seismic tomography

The eruption cycle of a volcano is controlled in part by the upward migration of magma. The characteristics of the magma flux produce a deformation signature at the Earth's surface. Inverse analyses use geodetic data to estimate strategic controlling parameters that describe the position and pressurization of a magma chamber at depth. The specific distribution of material properties controls how observed surface deformation translates to source parameter estimates. Seismic tomography models describe the spatial distributions of material properties that are necessary for accurate models of volcano deformation. This study investigates how uncertainties in seismic tomography models propagate into variations in the estimates of volcano deformation source parameters inverted from geodetic data. We conduct finite element model-based nonlinear inverse analyses of interferometric synthetic aperture radar (InSAR) data for Okmok volcano, Alaska, as an example. We then analyze the estimated parameters and their uncertainties to characterize the magma chamber. Analyses are performed separately for models simulating a pressurized chamber embedded in a homogeneous domain as well as for a domain having a heterogeneous distribution of material properties according to seismic tomography. The estimated depth of the source is sensitive to the distribution of material properties. The estimated depths for the homogeneous and heterogeneous domains are 2666 ± 42 and 3527 ± 56 m below mean sea level, respectively (99% confidence). A Monte Carlo analysis indicates that uncertainties of the seismic tomography cannot account for this discrepancy at the 99% confidence level. Accounting for the spatial distribution of elastic properties according to seismic tomography significantly improves the fit of the deformation model predictions and significantly influences estimates for parameters that describe the location of a pressurized magma chamber.

Journal of Geophysical Research B: Solid Earth↗

USGS2016

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

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

Alaska↗

USGS2016

Erratum to Surface‐wave green’s tensors in the near field

Haney and Nakahara (2014) derived expressions for surface‐wave Green’s tensors that included near‐field behavior. Building on the result for a force source, Haney and Nakahara (2014) further derived expressions for a general point moment tensor source using the exact Green’s tensors. However, it has come to our attention that, although the Green’s tensors were correct, the resulting expressions for a general point moment tensor source were missing some terms. In this erratum, we provide updated expressions with these missing terms. The inclusion of the missing terms changes the example given in Haney and Nakahara (2014).

Bulletin of the Seismological Society of America↗