Geology topics
Publications and source records attributed to Matthew M. Haney.
We present corrections to the expressions for surface-wave Green’s tensors shown in a recent paper by Malkoti et al .
The eruption of the submarine Hunga Tonga-Hunga Haʻapai (Hunga Tonga) volcano on 15 January 2022, was one of the largest volcanic explosions recorded by modern geophysical instrumentation. The eruption was notable for the broad range of atmospheric wave phenomena it generated and for their unusual coupling with the oceans and solid Earth. The event was recorded worldwide across the Global Seismographic Network (GSN) by seismometers, microbarographs and infrasound sensors. The broad-band instrumentation in the GSN allows us to make high fidelity observations of spheroidal solid Earth normal modes from this event at frequencies near 3.7 and 4.4 mHz. Similar normal mode excitations were reported following the 1991 Pinatubo (Volcanic Explosivity Index of 6) eruption and were predicted, by theory, to arise from the excitation of mesosphere-scale acoustic modes of the atmosphere coupling with the solid Earth. Here, we compare observations for the Hunga Tonga and Pinatubo eruptions and find that both strongly excited the solid Earth normal mode 0 S 29 (3.72 mHz). However, the mean modal amplitude was roughly 11 times larger for the 2022 Hunga Tonga eruption. Estimates of attenuation ( Q ) for 0 S 29 across the GSN from temporal modal decay give Q = 332 ± 101, which is higher than estimates of Q for this mode using earthquake data ( Q = 186.9 ± 5). Two microbarographs located at regional distances (<1000 km) to the volcano provide direct observations of the fundamental acoustic mode of the atmosphere. These pressure oscillations, first observed approximately 40 min after the onset of the eruption, are in phase with the seismic Rayleigh wave excitation and are recorded only by microbarographs in proximity (<1500 km) to the eruption. We infer that excitation of fundamental atmospheric modes occurs within a limited area close to the site of the eruption, where they excite select solid Earth fundamental spheroidal modes of similar frequencies that are globally recorded and have a higher apparent Q due to the extended duration of atmospheric oscillations.
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.
We derive approximate expressions for the ellipticity (i.e. horizontal-to-vertical or vertical-to-horizontal ratio) of Rayleigh waves propagating in a layered medium. The approximation is based on the generalized energy equation for Rayleigh waves, which has been used previously to obtain perturbational results for ellipticity. For a medium with weakly heterogeneous layers, we obtain an approximation from the perturbational result by taking the background medium to be homogeneous. The generalized energy equation also requires an auxiliary function and we discuss how the various possible functions are related to the homogeneous Rayleigh-wave eigenfunction. The analysis reveals that, within the weak approximation, the product of ellipticity and squared phase velocity is linearly related to squared shear wave velocity in the subsurface. We show the accuracy of the approximation with a simple layer-over-half-space model and then demonstrate its utility in a linear inversion scheme for shear wave velocity.
Detection of the earliest stages of unrest is one of the most challenging and yet critically needed aspects of volcano monitoring. We investigate a sequence of five unusual long-period (LP) earthquakes that occurred in the days prior to the onset of a months-long volcano-tectonic (VT) earthquake swarm beneath Little Sitkin volcano in the Aleutian Islands during late 2012. The long-period earthquakes had two distinctive characteristics: their signals were dominated by a monochromatic spectral peak at approximately 0.57 Hz and they had impulsive P and S-wave arrivals on a seismometer located on Amchitka Island 80 km to the southeast of the volcano. In each case, the monochromatic earthquakes ended with a higher-frequency event after approximately 2 min of duration. We find evidence that the five monochromatic LP earthquakes resulted from the resonance of a tabular magma body at middle crustal depths (15 km) on the western side of Little Sitkin. Based on the resonant frequency and quality factor of the monochromatic LP earthquakes, we infer the magma body to have a lateral extent of 500 m and a thickness of 9 m. We interpret that a magmatic intrusion excited the monochromatic LP earthquakes and subsequently increased the stress beneath the volcano, leading to the onset of the shallow (<10 km depth) VT swarm five days later.
Surficial mass wasting events are a hazard worldwide. Seismic and acoustic signals from these often remote processes, combined with other geophysical observations, can provide key information for monitoring and rapid response efforts and enhance our understanding of event dynamics. Here, we present seismoacoustic data and analyses for two very large ice–rock avalanches occurring on Iliamna Volcano, Alaska (USA), on 22 May 2016 and 21 June 2019. Iliamna is a glacier-mantled stratovolcano located in the Cook Inlet, ∼200 km from Anchorage, Alaska. The volcano experiences massive, quasi-annual slope failures due to glacial instabilities and hydrothermal alteration of volcanic rocks near its summit. The May 2016 and June 2019 avalanches were particularly large and generated energetic seismic and infrasound signals which were recorded at numerous stations at ranges from ∼9 to over 600 km. Both avalanches initiated in the same location near the head of Iliamna's east-facing Red Glacier, and their ∼8 km long runout shapes are nearly identical. This repeatability – which is rare for large and rapid mass movements – provides an excellent opportunity for comparison and validation of seismoacoustic source characteristics. For both events, we invert long-period (15–80 s) seismic signals to obtain a force-time representation of the source. We model the avalanche as a sliding block which exerts a spatially static point force on the Earth. We use this force-time function to derive constraints on avalanche acceleration, velocity, and directionality, which are compatible with satellite imagery and observed terrain features. Our inversion results suggest that the avalanches reached speeds exceeding 70 m s−1, consistent with numerical modeling from previous Iliamna studies. We lack sufficient local infrasound data to test an acoustic source model for these processes. However, the acoustic data suggest that infrasound from these avalanches is produced after the mass movement regime transitions from cohesive block-type failure to granular and turbulent flow – little to no infrasound is generated by the initial failure. At Iliamna, synthesis of advanced numerical flow models and more detailed ground observations combined with increased geophysical station coverage could yield significant gains in our understanding of these events.
Infrasound data are routinely used to detect and locate volcanic and other explosions, using both arrays and single sensor networks. However, at local distances (<15 km) topography often complicates acoustic propagation, resulting in inaccurate acoustic travel times leading to biased source locations when assuming straight-line propagation. Here we present a new method, termed Reverse Time Migration-Finite-Difference Time Domain (RTM-FDTD), that integrates numerical modeling into the standard RTM back-projection process. Travel time information is computed across the entire potential source grid via FDTD modeling to incorporate the effects of topography. The waveforms are then back-projected and stacked at each grid point, with the stack maximum corresponding to the likely source. We apply our method to three volcanoes with different network configurations, source-receiver distances, and topography. At Yasur Volcano, Vanuatu, RTM-FDTD locates explosions within ∼20 m of the source and differentiates between multiple vents. RTM-FDTD produces a more accurate location for the two Yasur subcraters than standard RTM and doubles the number of detected events. At Sakurajima Volcano, Japan, RTM-FDTD locates the source within 50 m of the active vent despite notable topographic blocking. The RTM-FDTD location is similar to that from the Time Reversal Mirror method, but is more computationally efficient. Lastly, at Shishaldin Volcano, Alaska, RTM and RTM-FDTD both produce realistic source locations (<50 m) for ground-coupled airwaves recorded on a four-station seismic network. We show that RTM is an effective method to detect and locate infrasonic sources across a variety of scenarios, and by integrating numerical modeling, RTM-FDTD produces more accurate source locations and increases the detection capability.
In this study, we use ambient noise interferometry to determine temporal changes in seismic velocity at Okmok volcano, Alaska, during the inter-eruptive period between the 1997 and 2008 eruptions. Specifically, we examine seismic velocity changes between 2005 and 2007. We further calculate seismic velocity changes in the frequency and depth domains. Examination of depth-constrained changes in seismic velocity allow us to distinguish between volcanic and non-volcanic processes occurring at Okmok. We show evidence that the presence of overlying lava flows may result in long term increases in the seismic velocity of the subsurface. Using the software package Coulomb 3.3, complementary theoretical volumetric strain modeling of volcanic deformation at Okmok is also carried out. These strain models are interpreted in tandem with our depth-constrained changes in seismic velocity. This joint analysis technique allows us to determine the location of the volcanic deformation at Okmok during the 1997-2008 inter-eruptive period. The location technique that we develop requires the use of only three seismic stations or station pairs in order to locate the center of volcanic deformation. Thus, this technique is a potentially valuable tool for monitoring the location of active magma storage at sparsely instrumented volcanoes worldwide.
Cleveland and Tana are remote volcanoes located in the central Aleutian volcanic arc on the eastern end of the Islands of Four Mountains (IFM). The persistently active Mount Cleveland volcano, on the western side of Chuginadak Island, is surrounded by several closely spaced Quaternary volcanic centers including Carlisle, Herbert, Kagamil, Tana, and Uliaga, and numerous small satellite vents on Chiginadak between Cleveland and Tana. The Alaska Volcano Observatory (AVO) installed two permanent broadband seismometers on Chuginadak Island in 2014, and we operated a temporary broadband network focused on the western side of the island in 2015–2016. Collectively, these stations provided the first seismic observations of this frequently active volcano and the surrounding Holocene-aged volcanic vents. During the study period (July 2014–January 2019), eruptive activity at Cleveland was characterized by small explosions separated by periods of lava effusion that formed small domes in the volcano's summit crater. We characterize seismicity beneath Chuginadak Island through automated analysis of event waveform frequency content, development of a one-dimensional P-wave velocity model, calculation of earthquake hypocenters, magnitudes, focal mechanisms, and identification of earthquake families. This analysis reveals the full range of seismic event types expected in a highly active volcanic environment and includes Volcano-Tectonic (VT) earthquakes, Long-Period (LP) events, and explosion signals. LP events appear to cluster at shallow depth beneath the active crater of Mount Cleveland and almost all of the explosions occur without identifiable short-term (hours to days) seismic precursors. VT earthquakes beneath Mount Cleveland occur at depths of 2 to 8 km below sea level (BSL) and range in magnitude from −0.2 to 1.8. VT focal mechanisms have horizontal P-axes that align with the regional axis of maximum stress. These observations, and a relatively slow one-dimensional seismic velocity model, are consistent with a shallow body of magma that is fed through a deeper conduit system. The time-history of VT earthquakes and shallow LP events suggest their occurrence may track the transfer of magma and fluids from the mid-crust to the shallow portions of the conduit system and may provide a means to anticipate future explosions and periods of dome growth. VT hypocenters also extend ~7 km northeast of Cleveland's summit at depths of 5 to 10 km BSL, under a group of Holocene-aged vents between Mount Cleveland and Tana. These earthquakes have vertically-oriented P-axes and a greater percentage occur in families. These observations, combined with observations of vent orientation and morphology and gas flux, suggest the area between Cleveland and Tana represents a zone of complicated volcano-tectonic interaction, similar to calderas elsewhere in the Aleutian arc. The presence of a larger volcanic system in the eastern IFM could influence magmatism and account for the multiple closely spaced volcanic centers in this region.
The Mariana Islands region hosts interesting geological features as well as abundant biodiversity. The subduction zone and back-arc spreading center have led to active volcanism that can have impacts on local islanders, aircraft flying in the region, and military activities. We deployed a small aperture hydrophone array from June 2017 to June 2018 in the Marianas back-arc to better characterize submarine volcanic activity in the region. In addition, we recorded other activity, including calls from historically understudied Bryde’s whales and T-phases from earthquakes. Here, we describe and discuss preliminary results from the array.
Seismic waves are commonly used to monitor unrest before, during, and after volcanic eruptions. The source of seismic tremor during a sustained explosive volcanic eruption is not well understood. Recent observations of the 2016 eruption of Pavlof Volcano, Alaska, revealed a change in the relationship (hysteresis) between ash plume height and seismic amplitude over time. Based on similarities in physical processes and observed seismic tremor in rivers, we explore two key sources of seismic energy in the volcanic conduit: (1) forces exerted by particle impacts and (2) dynamic pressure changes by the turbulent flow. We develop a physical model calculating the seismic power spectral density (PSD), where forces on the conduit wall are convolved with the Green's function for Rayleigh waves. Using reasonable eruption parameters, the model is able to reproduce the frequency spectrum from the Pavlof eruption, although the modeled amplitudes are generally lower. We test the relative importance of different eruption parameters, including grain size, velocity, and conduit dimensions. We find that turbulence generally dominates over particle impacts. However, to reach the PSD amplitude during the Pavlof eruption, large grain sizes are required, as they have the greatest relative influence on the modeled amplitude. The hysteresis between plume height and seismic amplitude can then potentially be explained by grain size changes. The PSD shape is mostly determined by the Rayleigh-wave quality factor Q, and substantial variations in seismic amplitude can be modeled assuming a constant mass eruption rate.
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.
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.
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.
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.
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.
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.
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.