Alaska Volcano Research Articles

SPECIFICS OF LATE HOLOCENE SEDIMENTATION IN THE CHUKCHI SEA INFERRED FROM GRAIN SIZE AND MINERALOGICAL ANALYSES OF BOTTOM SEDIMENTS

The aim of this work is to elucidate the specifics of recent sedimentation in the Chukchi Sea, based on the study of the material composition of Late Holocene bottom sediments. Analytical methods included grain size and mineralogical analyses. The results of 210Pb and 137Cs dating were used. The sediments are clayey silt and silty clay containing sand admixture and single gravel grains and pebble. The content of coarse-grained material increases slightly in the upper parts of the studied sections. This is probably due to the greater contribution of ice rafting to the recent Chukchi Sea sedimentation as a result of climate warming. The ultrafine- and fine-grained (0.25–0.05 mm) sandy material is dominated by light-fraction minerals. Volcanic glass was discovered in the sediments sampled in the southern and central areas of the Chukchi Sea. It might have been transported from the volcanoes of Alaska, the Aleutian Islands, and the Kamchatka Peninsula through the Bering Strait by the Pacific currents directed from south to north. The sediments collected in the southern, central, and northern areas of the Chukchi Sea differ in grain size and mineral composition. This is probably due to their remoteness from the coastline and provenance areas and is also caused by different rates of sedimentation.

Scenario‐Based Volcano Slope Stability Hazard Analysis: Case Study of Augustine Volcano, Alaska

AbstractVolcanoes worldwide have undergone cyclic destruction of their edifices, generating catastrophic volcanic debris avalanches. Augustine Volcano in Alaska, USA, has a history of debris avalanches, causing cyclic destruction of the edifice and cascading hazards. These collapses, together with eruption‐related changes in the edifice structure, change the slope stability hazard of the volcano over time. This study aims to develop a current view of the slope stability hazard at Augustine Volcano by (a) characterizing collapse‐prone source areas on the edifice under various scenarios typical of dynamic volcanic environments and (b) identifying the controlling factors that underlie the slope stability hazard. Scenario‐based slope stability assessment was conducted using a quasi‐3D limit equilibrium method to test for the effect of various factors that drive or resist failure, including topography, shallow edifice structure, strength of edifice‐forming materials, pore fluid pressure distribution, and local and regional seismicity. Results show that in all scenarios assessed, the slopes of Augustine Volcano are stable with a factor of safety (FOS) greater than 1. The FOS, however, decreases with decreasing strength of edifice‐forming materials, pore fluid pressurization, and earthquake loading. The location of the relatively less stable slope, changes to the southwestern flank when accounting for subsurface heterogeneities derived from geophysical observations. Subsurface heterogeneity is thus a key underlying factor, along with steep topography, in controlling where collapse‐prone source areas occur, and it should be accounted for in volcanic slope stability hazard assessments.

Multiyear temporal variation of b-values at Alaskan volcanoes: The synergetic influence of stress and material heterogeneity

Changes in seismicity parameters is often utilized as a tool for forecasting eruptive activity at volcanoes worldwide. One of these parameters is the slope of the Gutenberg-Richter law, known as the b-value, whose temporal variation is studied here as an indicator of volcanic activity. Four Alaskan volcanoes (Makushin, Martin, Redoubt, Spurr) were selected in order to reconstruct the b-value variation over a multiyear period (≥ 25 years). The magnitude of completeness and the b-value were estimated using a sliding window for each earthquake catalog, while bootstrap uncertainties were estimated for each window. The size of the analysis window was selected by applying the Magnitude Bandwidth Criterion (MBC) that maximizes the number of windows with magnitude bandwidth larger than 2.0 in the complete part of the catalog. All four volcanoes exhibit decreasing b-values before unrest and eruptions, while maximum b-values exceed 1.0 only at Redoubt and Spurr. Previously published laboratory experiments on volcanic rock deformation and failure suggest that the decrease in b-value is a result of increased stress that may stem either from magma intrusions or from exsolution of volatiles. On the other hand, whether the b-value at each volcano will exceed 1.0 or not, is also determined by the degree of material heterogeneity.

Inflation of Okmok Volcano During 2008–2020 From PS Analyses and Source Inversion With Finite Element Models

AbstractOkmok volcano, located on northeastern Umnak Island along the eastern end of the Aleutian island arc, is one of the most active volcanoes in Alaska, producing multiple eruptions in the past century. The most recent eruption, which occurred during July–August of 2008, was the most explosive since the early nineteenth century. In the years following the 2008 eruption, Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) observations indicate that Okmok has inflated at a variable rate of 40–195 mm/yr. In this study, we investigate the post‐eruptive deformation of Okmok (2008–2020) using InSAR and GNSS. L‐band ALOS‐2, C‐band Sentinel‐1/Envisat and X‐band TerraSAR‐X data are analyzed with Persistent Scatterer (PS) InSAR method. The deformation time series calculated from InSAR and GNSS are assimilated into finite element models using the Ensemble Kalman Filter to track the evolution of the magma system through time. The results indicate that the InSAR‐derived deformation history can be well explained by a spatially stable magmatic source located in the central caldera, at about 3 km beneath the sea level, which is also believed to be the same source that produced the 1997 and 2008 eruptions. Magma accumulation in the reservoir is about from 2008 to 2020, which is about 160% and about 60% of the total reservoir volume changes during the 1997 and the 2008 eruptions, respectively.

An Alaskan volcano, climate change, and the history of ancient Rome

In the first century BCE, political instability set the Roman Republic on edge. Researchers have found evidence of an eruption that may have catalyzed the republic’s end.

An Alaskan volcano, climate change, and the history of ancient Rome

An Alaskan volcano, climate change, and the history of ancient Rome

Extreme climate after massive eruption of Alaska’s Okmok volcano in 43 BCE and effects on the late Roman Republic and Ptolemaic Kingdom

The assassination of Julius Caesar in 44 BCE triggered a power struggle that ultimately ended the Roman Republic and, eventually, the Ptolemaic Kingdom, leading to the rise of the Roman Empire. Climate proxies and written documents indicate that this struggle occurred during a period of unusually inclement weather, famine, and disease in the Mediterranean region; historians have previously speculated that a large volcanic eruption of unknown origin was the most likely cause. Here we show using well-dated volcanic fallout records in six Arctic ice cores that one of the largest volcanic eruptions of the past 2,500 y occurred in early 43 BCE, with distinct geochemistry of tephra deposited during the event identifying the Okmok volcano in Alaska as the source. Climate proxy records show that 43 and 42 BCE were among the coldest years of recent millennia in the Northern Hemisphere at the start of one of the coldest decades. Earth system modeling suggests that radiative forcing from this massive, high-latitude eruption led to pronounced changes in hydroclimate, including seasonal temperatures in specific Mediterranean regions as much as 7 °C below normal during the 2 y period following the eruption and unusually wet conditions. While it is difficult to establish direct causal linkages to thinly documented historical events, the wet and very cold conditions from this massive eruption on the opposite side of Earth probably resulted in crop failures, famine, and disease, exacerbating social unrest and contributing to political realignments throughout the Mediterranean region at this critical juncture of Western civilization.

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.

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.

Goals and Development of the Alaska Volcano Observatory Seismic Network and Application to Forecasting and Detecting Volcanic Eruptions

AbstractThe 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.

Overview, chronology, and impacts of the 2016–2017 eruption of Bogoslof volcano, Alaska

The 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc, began in December 2016 and included 70 explosive events and at least two episodes of subaerial dome building. Because the volcano had no local monitoring stations during the eruption, a combination of distant seismic stations, regional infrasound sensors, lightning detection, a variety of satellite data and observer reports, and a field visit in 2018, were used to recreate the events that occurred during the nine-month eruption. Following precursory seismicity that started in September 2016, the eruption began in December 2016 with a series of explosive events that persisted through mid-March 2017. After a 6-week hiatus, activity resumed on May 17 and lasted through the end of August 2017 and consisted of additional explosions and two short-lived subaerial lava domes that formed in June and August. For most of the eruption, Bogoslof’s vent was submerged in shallow seawater, though during several of the longer events a subaerial edifice grew, and the vent migrated above sea level resulting in more ash-rich volcanic clouds. Eruptive products, geophysical signals, and eruptive style are all broadly consistent with vulcanian activity where slow magma ascent led to repetitive dome or plug formation, overpressurization in the upper conduit, and sudden release during short-lived explosions. Infiltration of seawater may have prohibited large domes from forming especially in the first half of the eruption when explosions were closely spaced in time. The largest four explosions in the sequence occurred after inter-event times of 10 days or more. Three events produced ashfall on nearby communities and mariners east and south of Bogoslof and the eruption resulted in dozens of flight cancelations and flight diversions around the volcano and its ash clouds.

Hindcasting Magma Reservoir Stability Preceding the 2008 Eruption of Okmok, Alaska

AbstractVolcanic eruptions pose a significant and sometimes unpredictable hazard, especially at systems that display little to no precursory signals. For example, the 2008 eruption of Okmok volcano in Alaska notably lacked observable short‐term precursors despite years of low‐level unrest. This unpredictability highlights that direct monitoring alone is not always enough to reliably forecast eruptions. In this study, we use the Ensemble Kalman Filter (EnKF) to produce a successful hindcast of the Okmok magma system in the lead up to its 2008 eruption. By assimilating geodetic observations of ground deformation, finite element models track the evolving stress state of the magma system and evaluate its stability using mechanical failure criteria. The hindcast successfully indicates an increased eruption likelihood due to tensile failure weeks in advance of the 2008 eruption. The effectiveness of this hindcast illustrates that EnKF‐based forecasting methods may provide critical information on eruption probability in systems lacking obvious precursors.

Absolute tree-ring dates for the Late Bronze Age eruptions of Aniakchak and Thera in light of a proposed revision of ice-core chronologies

Abstract

Causes of volcanic unrest at Mt. Spurr in 2004\u20132005 inferred from repeated tomography

Mt. Spurr is the largest active volcano in Alaska of high explosive potential. The most recent activity, including two recent magmatic eruptions in 1953 and 1992, has occurred via the flanking Crater Peak. From 2004 to 2006, strong seismicity, gas flux, and heating were observed in the summit area, which had remained inactive for more than 5 Ka. To understand the cause of this reactivation, we performed repeated tomography inversions that clearly imaged the magma reservoir beneath Mt. Spurr and showed temporal changes in its shape and intensity. During the two years preceding the unrest, we observed ascension of the upper limit of the reservoir-related anomaly from a depth of 5 to 3 km below the surface, accompanied by strong seismicity. During the following years, the shape of the anomaly remained unchanged, but its intensity weakened. These observations may indicate the release of fluids from the ductile reservoir and fast upward ascent through the brittle cover that caused intensive seismicity and gas flux during the unrest from 2004 to 2006. The origin of this zone will possibly cause a resumption of explosive eruptions in the summit area of Mt. Spurr.

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 over 60 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). 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, event-specific ash-cloud dispersion modeling, interagency coordination, and development and distribution of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, AVO called emergency response partners 15 minutes, and issued written notices 30 minutes, 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 Volcano Observatory Alert and Forecasting Timeliness: 1989–2017

The Alaska Volcano Observatory (AVO) monitors volcanoes in Alaska and issues notifications and warnings of volcanic unrest and eruption. We evaluate the timeliness and accuracy of eruption forecasts for 53 eruptions at 20 volcanoes, beginning with Mount Redoubt’s 1989–1990 eruption. Successful forecasts are defined as those where AVO issued a formal warning before eruption onset. These warning notifications are now part of AVO’s Aviation Color Code and Volcanic Alert Level. This analysis considers only the start of an eruption, although many eruptions have multiple phases of activity. For the 21 eruptions at volcanoes with functioning local seismic networks, AVO has high forecasting success at volcanoes with: >15 yr repose intervals and magmatic eruptions (4 out of 4, 100%); or larger eruptions (Volcanic Explosivity Index (VEI) 3 or greater; 6 out of 10, 60%). AVO successfully forecast all four monitored, longer-repose period, VEI 3+ eruptions: Redoubt 1989-1990 and 2009, Spurr 1992, and Augustine 2005–2006. For volcanoes with functioning seismic monitoring networks, success rates are lower for: volcanoes with shorter repose periods (3 out of 16, 19%); more mafic compositions (3 out of 18, 17%); or smaller eruption size (VEI 2 or less, 1 out of 11, 9%). These eruptions (Okmok, Pavlof, Veniaminof, and Shishaldin) often lack detectable precursory signals. For 32 eruptions at volcanoes without functioning local seismic networks, the forecasting success rate is much lower (2, 6%; Kasatochi 2008 and Shishaldin 2014). For remote volcanoes where the main hazard is to aviation, rapid detection is a goal in the absence of in situ monitoring. Eruption detection has improved in recent years, shown by a decrease in the time between eruption onset and notification. Even limited seismic monitoring can detect precursory activity at volcanoes with certain characteristics (intermediate composition, longer repose times, larger eruptions), but difficulty persists in detecting subtle precursory activity at frequently active volcanoes with more mafic compositions. This suggests that volcano-specific characteristics should be considered when designing monitoring programs and evaluating forecasting success. More proximally-located sensors and data types are likely needed to forecast eruptive activity at frequently-active, more mafic volcanoes that generally produce smaller eruptions.

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.

Computer aided detection of transient inflation events at Alaskan volcanoes using GPS measurements from 2005–2015

Analysis of transient deformation events in time series data observed via networks of continuous Global Positioning System (GPS) ground stations provide insight into the magmatic and tectonic processes that drive volcanic activity. Typical analyses of spatial positions originating from each station require careful tuning of algorithmic parameters and selection of time and spatial regions of interest to observe possible transient events. This iterative, manual process is tedious when attempting to make new discoveries and does not easily scale with the number of stations. Addressing this challenge, we introduce a novel approach based on a computer-aided discovery system that facilitates the discovery of such potential transient events. The advantages of this approach are demonstrated by actual detections of transient deformation events at volcanoes selected from the Alaska Volcano Observatory database using data recorded by GPS stations from the Plate Boundary Observatory network. Our technique successfully reproduces the analysis of a transient signal detected in the first half of 2008 at Akutan volcano and is also directly applicable to 3 additional volcanoes in Alaska, with the new detection of 2 previously unnoticed inflation events: in early 2011 at Westdahl and in early 2013 at Shishaldin. This study also discusses the benefits of our computer-aided discovery approach for volcanology in general. Advantages include the rapid analysis on multi-scale resolutions of transient deformation events at a large number of sites of interest and the capability to enhance reusability and reproducibility in volcano studies.

Sustainable Surface Deformation Related with 2006 Augustine Volcano Eruption in Alaska Measured Using GPS and InSAR Techniques

Augustine volcano, located along the Aleutian Arc, is one of the most active volcanoes in Alaska and nearby islands, with seven eruptions occurring between 1812 and 2006. This study monitored the surface displacement before and after the most recent 2006 eruption. For analysis, we conducted a time-series analysis on data observed at the permanent GPS(Global Positioning System) observation stations in Augustine Island between 2005 and 2011. According to the surface displacement analysis results based on GPS data, the movement of the surface inflation at the average speed of 2.3 cm/year three months prior to the eruption has been clearly observed, with the post-eruption surface deflation at the speed of 1.6 cm/year. To compare surface displacements measurement by GPS observation, ENVISAT(Environmental satellite) radar satellite data were collected between 2003 and 2010 and processed the SBAS(Small Baseline Subset) method, one of the time-series analysis techniques using multiple InSAR(Interferometric Synthetic Aperture Radar) data sets. This result represents 0.97 correlation value between GPS and InSAR time-series surface displacements. This research has been completed precise surface deformation using GPS and time-series InSAR methods for a detection of precursor symptom on Augustine volcano.

Seismic Envelope‐Based Detection and Location of Ground‐Coupled Airwaves from Volcanoes in Alaska

Abstract 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.