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To facilitate infrasound propagation studies, we present AVO-G2S, an open-source, Ground-to-Space model which provides temperature and wind specifications from the surface to an altitude of 225 km. This model provides a means of smoothly characterizing atmospheric conditions using multiple numerical weather prediction forecast and reanalysis products, along with upper-atmospheric empirical models. Regional atmospheric reconstructions only require a limited domain and can utilize high-resolution numerical weather prediction forecasts typically provided on a projected grid. The use of a projected grid allows for faster spectral transform libraries to be employed. The AVO-G2S software can also provide global reconstructions that rely on global numerical weather prediction products and spherical harmonic decompositions. AVO-G2S is inspired by a global Ground-to-Space model developed by the Naval Research Laboratory, and relies on their empirical descriptions of upper-atmospheric conditions. Alaska Volcano Observatory has implemented this model for near-real-time infrasound monitoring of volcanic eruptions and historical research projects.

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.

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 (

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. SO2 emissions from Bogoslof were persistently detected by the Infrared Atmospheric Sounding Interferometer (IASI) satellite sensors. Of Bogoslof’s 70 explosive events, 50% produced measurable SO2 masses ranging from 0.1 to 21.5 kt, with a median and standard deviation of 0.7 ± 4.0 kt SO2, respectively. Here, we compare IASI-derived SO2 masses from Bogoslof events to complementary geophysical datasets to provide insights into eruption source processes, namely the degree of seawater scrubbing of water-soluble SO2 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 SO2 masses are primarily a function of eruption magnitude (degassed magma mass) and that scrubbing of SO2 emissions by vent seawater may have exerted a minor effect on the observed SO2 masses. SO2 masses were combined with petrologic constraints on melt inclusion and matrix glass S concentrations to calculate degassed magma masses and volumes. The cumulative SO2-derived degassed magma mass and estimated volume (dense-rock equivalent) for the full Bogoslof eruption were found to be 2.8 × 1010 kg and 9.3 × 106 m3, respectively. When individual event masses are compared against event masses calculated using an empirical plume-height method, a strong correlation is found (R2 = 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., SCOPUS: ar.j, info:eu-repo/semantics/published

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.

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.

During explosive eruptions, airborne particles collide and stick together, accelerating the fallout of volcanic ash and climate-forcing aerosols. This aggregation process remains a major source of uncertainty both in ash dispersal forecasting and interpretation of eruptions from the geological record. Here we illuminate the mechanisms and timescales of particle aggregation from a well-characterized ‘wet' eruption. The 2009 eruption of Redoubt Volcano, Alaska, incorporated water from the surface (in this case, a glacier), which is a common occurrence during explosive volcanism worldwide. Observations from C-band weather radar, fall deposits and numerical modelling demonstrate that hail-forming processes in the eruption plume triggered aggregation of ∼95% of the fine ash and stripped much of the erupted mass out of the atmosphere within 30 min. Based on these findings, we propose a mechanism of hail-like ash aggregation that contributes to the anomalously rapid fallout of fine ash and occurrence of concentrically layered aggregates in volcanic deposits., The behaviour of airborne fine ash during explosive volcanic eruptions is poorly understood. Here, the authors study hail formation during an eruption, proposing a mechanism of particle aggregation that leads to the fallout of fine ash and the occurrence of concentrically layered aggregates in volcanic deposits