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Infrasound (low frequency sound waves) can be used to monitor and characterize volcanic eruptions. However, infrasound sensors are usually placed on the ground, thus providing a limited sampling of the acoustic radiation pattern that can bias source size estimates. We present observations of explosive eruptions from a novel uncrewed aircraft system (UAS)‐based infrasound sensor platform that was strategically hovered near the active vents of Stromboli volcano, Italy. We captured eruption infrasound from short‐duration explosions and jetting events. While potential vertical directionality was inconclusive for the short‐duration explosion, we find that jetting events exhibit vertical sound directionality that was observed with a UAS close to vertical. This directionality would not have been observed using only traditional deployments of ground‐based infrasound sensors, but is consistent with jet noise theory. This proof‐of‐concept study provides unique information that can improve our ability to characterize and quantify the directionality of volcanic eruptions and their associated hazards. Plain Language Summary: Low frequency sound (infrasound) is emitted from volcanic eruptions and can be used to detect and characterize the event. However, sensors that record infrasound are often placed on the ground, so the data only sample a small fraction of the sound that is radiated in all directions. We present observations of explosive events at Stromboli volcano, Italy, using infrasound sensors tethered to an uncrewed aircraft system (UAS) that was strategically hovered near the eruptions. By having a sensor high above the ground, we find that some explosive eruptions radiate more sound vertically than horizontally. This phenomenon cannot be observed by ground‐based sensors alone. This proof‐of‐concept study provides unique information on infrasound and explosion dynamics using a platform that successfully extends data collection capabilities to previously unreachable locations near active volcanoes and other explosive sources. Key Points: We present unique uncrewed aircraft system (UAS)‐based infrasound observations of explosive eruptionsVertical infrasound directionality from volcanic jetting was observed even after accounting for the effects of topographyThis successful proof‐of‐concept study presents a novel UAS‐based sensor platform suitable for future volcano infrasound deployments [ABSTRACT FROM AUTHOR]

Over the past two decades (2000–2020), volcano infrasound (acoustic waves with frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of academic research to a useful monitoring tool. As a result, infrasound is routinely used by volcano observatories around the world to detect, locate, and characterize volcanic activity. It is particularly useful in confirming subaerial activity and monitoring remote eruptions, and it has shown promise in forecasting paroxysmal activity at open-vent systems. Fundamental research on volcano infrasound is providing substantial new insights on eruption dynamics and volcanic processes and will continue to do so over the next decade. The increased availability of infrasound sensors will expand observations of varied eruption styles, and the associated increase in data volume will make machine learning workflows more feasible. More sophisticated modeling will be applied to examine infrasound source and propagation effects from local to global distances, leading to improved infrasound-derived estimates of eruption properties. Future work will use infrasound to detect, locate, and characterize moving flows, such as pyroclastic density currents, lahars, rockfalls, lava flows, and avalanches. Infrasound observations will be further integrated with other data streams, such as seismic, ground- and satellite-based thermal and visual imagery, geodetic, lightning, and gas data. The volcano infrasound community should continue efforts to make data and codes accessible and to improve diversity, equity, and inclusion in the field. In summary, the next decade of volcano infrasound research will continue to advance our understanding of complex volcano processes through increased data availability, sensor technologies, enhanced modeling capabilities, and novel data analysis methods that will improve hazard detection and mitigation. [ABSTRACT FROM AUTHOR]

Volcanic eruption source parameters may be estimated from acoustic pressure recordings dominant at infrasonic frequencies (< 20 Hz), yet uncertainties may be high due in part to poorly understood propagation dynamics. Linear acoustic propagation of volcano infrasound is commonly assumed, but nonlinear processes such as wave steepening may distort waveforms and obscure the sourcing process in recorded waveforms. Here we use a previously developed frequency-domain nonlinearity indicator to quantify spectral changes due to nonlinear propagation primarily in 80 signals from explosions at Yasur Volcano, Vanuatu. We find evidence for ≤ 10−3 dB/m spectral energy transfer in the band 3–9 Hz for signals with amplitude on the order of several hundred Pa at 200–400 m range. The clarity of the nonlinear spectral signature increases with waveform amplitude, suggesting stronger nonlinear changes for greater source pressures. We observe similar results in application to synthetics generated through finite-difference wavefield simulations of nonlinear propagation, although limitations of the model complicate direct comparison to the observations. Our results provide quantitative evidence for nonlinear propagation that confirms previous interpretations made on the basis of qualitative observations of asymmetric waveforms. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We combine global detections of volcanic lightning with acoustic and hydroacoustic data to investigate novel indications of plume electrification in ground-based, geophysical data streams during the 2016–2017 eruption of Bogoslof volcano, Alaska. Such signals offer additional ways to diagnose the occurrence of volcanic lightning and confirm whether eruptive activity is producing significant amounts of ash. We discuss three signatures of lightning activity: volcanic thunder, electromagnetic pulses arising from lightning-induced voltages in cabling, and hydroacoustic signals associated with volcanic lightning. Observations of these phenomena provide additional insights into volcanic lightning activity and reveal several periods of electrical activity that were not otherwise detected during the Bogoslof eruption. [ABSTRACT FROM AUTHOR]

Abstract 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. Highlights • Infrasound is important for monitoring in Alaska where volcanoes are both remote and numerous. • AVO-G2S is an updated ground-to-space atmospheric model tailored to the needs of the Alaska Volcano Observatory. • The long-range propagation of infrasound can be adequately modeled using AVO-G2S. • We analyze recent eruptions in Alaska and compare predicted propagation with detections. [ABSTRACT FROM AUTHOR]