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 is the surface-guided Lamb wave ( ≲ 0.01 Hz), which we observed propagating for four (+three antipodal) passages around the Earth over six days. Based on 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 (0.01–20 Hz), long-range (~10,000 km) 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. We highlight exceptional observations of the atmospheric waves.

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.

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.

We present an open-source Python package, lsforce, for performing single-force source inversions of long-period (tens to hundreds of seconds) seismic signals. Although the software is designed primarily for landslides, it can be used for any single-force seismic source. The package allows users to produce estimates of the three-component time series of forces exerted on the Earth by a landslide with postprocessing options to estimate the trajectory of its center of mass. Green’s functions for a user-selected 1D Earth model are obtained automatically from the Incorporated Research Institutions for Seismology Synthetics Engine webservice or can be computed for custom 1D Earth models using Computer Programs in Seismology. lsforce implements the two most commonly used source parameterizations: a fully flexible, high-resolution approach and a more stable but lower-resolution method of overlapping triangle sources. Regularization options include a blended zeroth-, first-, and second-order semiautomated Tikhonov regularization scheme, as well as additional optional constraints on start times, end times, and on the sum of forces. Uncertainty due to data selection can be assessed using either a leave-one-out approach or a modified jackknife technique that randomly excludes subsets of the data for multiple re-inversions. Numerous built-in plotting methods allow for easy quality control and assessment of results. In this article, we briefly outline the theory and methodology, describe our implementation, and demonstrate the usage of lsforce using the well-studied 28 June 2016 Lamplugh rock avalanche in Alaska. Despite the rapidly increasing prevalence of landslide single-force inversions in the landslide and seismology literature over the past decade, to our knowledge this is the first open-source code for performing such inversions.

Abstract. 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 the natural laboratory of 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 material near its summit. The May 2016 and June 2019 avalanches were particularly large and generated energetic seismic and infrasound signals which were recorded on 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 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 80 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 groundtruth combined with increased geophysical station coverage could yield significant gains in our understanding of these events.

In preparation for the next phase of the Source Physics Experiments, we acquired an active‐source seismic dataset along two transects totaling more than 30 km in length at Yucca Flat, Nevada, on the Nevada National Security Site. Yucca Flat is a sedimentary basin which has hosted more than 650 underground nuclear tests (UGTs). The survey source was a novel 13,000 kg modified industrial pile driver. This weight drop source proved to be broadband and repeatable, richer in low frequencies (1–3 Hz) than traditional vibrator sources and capable of producing peak particle velocities similar to those produced by a 50 kg explosive charge. In this study, we performed a joint inversion of P‐wave refraction travel times and Rayleigh‐wave phase‐velocity dispersion curves for the P‐ and S‐wave velocity structure of Yucca Flat. Phase‐velocity surface‐wave dispersion measurements were obtained via the refraction microtremor method on 1 km arrays, with 80% overlap. Our P‐wave velocity models verify and expand the current understanding of Yucca Flat’s subsurface geometry and bulk properties such as depth to Paleozoic basement and shallow alluvium velocity. Areas of disagreement between this study and the current geologic model of Yucca Flat (derived from borehole studies) generally correlate with areas of widely spaced borehole control points. This provides an opportunity to update the existing model, which is used for modeling groundwater flow and radionuclide transport. Scattering caused by UGT‐related high‐contrast velocity anomalies substantially reduced the number and frequency bandwidth of usable dispersion picks. The S‐wave velocity models presented in this study agree with existing basin‐wide studies of Yucca Flat, but are compromised by diminished surface‐wave coherence as a product of this scattering. As nuclear nonproliferation monitoring moves from teleseismic to regional or even local distances, such high‐frequency (>5  Hz) scattering could prove challenging when attempting to discriminate events in areas of previous testing.

Abstract. 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.

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