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SUMMARY Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local ($<$5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source ($<$5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications. 

SUMMARY Powerful infrasound (acoustic waves $$\lt $$20 Hz) can be produced by explosive volcanic eruptions. The long-range propagation capability, over hundreds to thousands of kilometers, of atmospheric infrasound motivates the development of regional or even global scale volcano-infrasound monitoring systems. Infrasound propagation paths are subject to spatiotemporal atmospheric dynamics, which lead to deviations in the direction-of-arrival (back-azimuth) observed at sensor arrays and contribute to source location uncertainty. Here, we further investigate the utility of empirical climatologies combined with 3-D ray tracing for providing first-order estimates of infrasound propagation paths and back-azimuth deviation corrections. The intended application is in scenarios requiring rapid or pre-computed infrasound propagation calculations, such as for a volcano-infrasound monitoring system. Empirical climatologies are global observationally based function fitting models of the atmosphere, representing robust predictors of the bulk diurnal to seasonal atmospheric variability. Infrasound propagation characteristics have previously been shown to have strong seasonal and diurnal components. At the International Monitoring System infrasound station IS22, New Caledonia, quasi-continuous multiyear infrasound array detections show oscillating azimuthal variations for arrivals from volcanoes in Vanuatu, including Yasur ($$\sim$$400 km range), Ambrym ($$\sim$$670 km range) and Lopevi ($$\sim$$650 km range). We perform 3-D ray tracing to model infrasound propagation from the Ambrym and Yasur volcano locations to IS22 every six hours (00:00, 06:00, 12:00 and 18:00 UTC) for every day of 2004 and 2019 for Ambrym and Yasur, respectively and evaluate the results as compared to the multiyear observations. We assess a variety of models and parametrizations, including both empirical climatologies and hybrid descriptions; range-independent and range-dependent atmospheric discretizations; and unperturbed and perturbed range-independent empirical climatologies. The hybrid atmospheric descriptions are composed of fifth generation reanalysis descriptions (ERA 5) from the European Centre for Medium-Range Weather Forecasts below $$\sim$$80 km altitude combined with empirical climatologies above. We propose and employ simple parametric perturbations to the empirical climatologies, which are designed to enhance the stratospheric duct and compensate for missing gravity wave perturbations not included in the climatologies, and thereby better match observations. We build year-long back-azimuth deviation interpolations from the simulations and compare them with three different multiyear array detection data sets from IS22 covering from 2003 up to 2022. Through a systematic comparison, we find that the range-independent empirical climatologies can capture bulk azimuth deviation variability and could thus be useful for rapid infrasound propagation calculation scenarios, particularly during favourable sustained propagation ducting conditions. We show that the hybrid models better describe infrasound propagation during periods of weak stratospheric ducting and during transient atmospheric changes such as stratospheric wind reversals. Overall, our results support the notion that climatologies, if perturbed to compensate for missing gravity wave structure, can improve rapid low-latency and pre-computed infrasound source discrimination and location procedures. 

Abstract The 2018 eruption of Sierra Negra volcano, Galápagos, Ecuador has provided new insights into the mechanisms of caldera resurgence, subsidence, and fissuring at basaltic shield volcanoes. Here, we integrate local (∼0.4 km) seismo‐acoustic records and regional (∼85 km) infrasound array data to present new observations of the 2018 Sierra Negra eruption with improved time and spatial resolutions. These observations include: air‐to‐ground coupling ∼2 hr before the time of the eruption onset, migration of the infrasound tremor from 22:54 June 26 to 12:31 June 27 UT (all times in UT), and persistent infrasound detections during the weeks between 5 July and 18 August from an area that does not coincide with the previously documented eruptive fissures. We interpret air‐to‐ground coupling as infrasound tremor generated in the nearby fissures before the main eruptive phase started, although ambiguity remains in interpreting a single seismic‐infrasonic sensor pair. The progressive location change of the infrasound tremor agrees with the migration of the eruption down the north flank of Sierra Negra at a rate of ∼0.15 ± 0.04 m/s. The weeks‐long persistent detections coincide with a region that has thermal anomalies, co‐eruptive deformation, lava fields, and geological features that could be interpreted as multiple lava tube skylights. Our observations and interpretations provide constraints on the mechanisms underlying fissure formation and magma emplacement at Sierra Negra. 

Abstract Popocatépetl is a highly active stratovolcano in central Mexico with recurrent activity of Vulcanian-type explosions and frequent degassing. The proximity of Popocatépetl volcano to Mexico City, one of the most populated cities in the world, demands continuous monitoring to achieve an adequate volcano risk assessment. We present an overview of the first high-dynamic-range and high-broadband (0.01–200 Hz; 400 Hz sampling rate) seismoacoustic network (PoPiNet), which we operated around Popocatépetl volcano from August 2021 to May 2022. Here, we show preliminary results of the explosions recorded in September 2021. We deployed five seismoacoustic stations within 4–25 km horizontal distance (range) from the vent. We identify infrasonic waveforms associated with tremor and explosions, with pressures ranging from 16 to 134 Pa and dominant frequencies between 0.2 and 5.0 Hz. The frequency content of the recorded signals at the closest stations to the volcano spans the sub-bass (20–60 Hz) and bass (60–250 Hz) ranges. The associated seismic signals of moderate explosions exhibit air-to-ground coupled waves with maximum coherence values at frequencies up to 5 and 25 Hz for the farthest and closest stations to the volcano, respectively. Conversely, we observe infrasound signal amplitudes from relatively small explosions reaching maximum pressures of 10 Pa that do not couple into the ground, even at the closest stations. These infrasound signals are associated with type-I long-period events as reported in previous investigations. The waveform consistency suggests repetitive and nondestructive sources beneath the volcano. 

Abstract Seismicity at restless volcanoes commonly features a variety of signal types reflecting both volcanotectonic and fluid-driven source processes. However, traditional catalogs of seismicity are often incomplete, especially concerning events with emergent onsets such as those driven by the dynamics of magmatic and hydrothermal fluids. The detection of all discrete events and continuous seismic tremors, regardless of the underlying source processes, would therefore improve the ability of monitoring agencies to forecast eruptions and mitigate their associated hazards. We present a workflow for generalized detection of seismic events based on the network covariance matrix (Seydoux et al., 2016). Our contributions enable the method to simultaneously detect continuous and short-duration (<∼10 s) events, provide information about the frequency content of the signals, and to refine the initial detection times by an order of magnitude (from window lengths of 75 to 7.5 s). We test the workflow on a 15-month record of seismicity with 23 stations at Mammoth Mountain, California (July 2012–October 2013) and detect 62% of long-period events and 94% of volcanotectonic events in the existing Northern California Earthquake Data Center catalog. In addition, ∼3000 events are not included in the catalog, and thousands of tremor signals are found. The method is suitable for near-real-time analysis of continuous waveforms and can provide a valuable supplement to existing algorithms to improve the completeness of catalogs used for monitoring volcanoes. 

Abstract We present a revision and update to the high‐precision relocated seismicity catalog presented by Matoza et al. (2021,https://doi.org/10.1029/2020ea001253) for the Island of Hawai'i from 1986 to 2018. The starting catalog of hypocenters (input data), on which the study by Matoza et al. (2021,https://doi.org/10.1029/2020ea001253) was based, contained an inconsistent depth datum for events before and after 00:00 UT, 29 December 2017. Here we present a recomputed version of the catalog using a consistent reference depth. We corrected the starting catalog to a common depth datum (all events now use the model depth reference datum) and re‐ran the entire workflow as described in the paper by Matoza et al. (2021,https://doi.org/10.1029/2020ea001253). This included pairing, cross‐correlating, and relocating all seismic events again based on the updated starting catalog. We consider 347,446 events representing 32 years of seismicity on and around the island from 1986 to 2018. We now successfully relocate 299,966 (86%) events using ∼2.53 billion differential times (PandS) from ∼194 million similar‐event pairs, derived from cross‐correlations between ∼887 million event pairs total, a significant increase from our original analysis. The resolution of fine‐scale seismicity features is improved and the median depth of shallow events (<5 km) under Kaluapele (Kīlauea summit caldera) in 2018 is shifted 926 m deeper as a result of the change. The interpretations and other major conclusions in the paper by Matoza et al. (2021,https://doi.org/10.1029/2020ea001253) are unchanged. 

Abstract We present the transverse coherence minimization method (TCM)—an approach to estimate the back-azimuth of infrasound signals that are recorded on an infrasound microphone and a colocated three-component seismometer. Accurate back-azimuth information is important for a variety of monitoring efforts, but it is currently only available for infrasound arrays and for seismoacoustic sensor pairs separated by 10 s of meters. Our TCM method allows for the analysis of colocated sensor pairs, sensors located within a few meters of each other, which may extend the capabilities of existing seismoacoustic networks and supplement operating infrasound arrays. This approach minimizes the coherence of the transverse component of seismic displacement with the infrasound wave to estimate the infrasound back-azimuth. After developing an analytical model, we investigate seismoacoustic signals from the August 2012 Humming Roadrunner experiment and the 26 May 2021 eruption of Great Sitkin Volcano, Alaska, U.S.A., at the ranges of 6.5–185 km from the source. We discuss back-azimuth estimates and potential sources of deviation (1°–15°), such as local terrain effects or deviation from common analytical models. This practical method complements existing seismoacoustic tools and may be suitable for routine application to signals of interest. 

Abstract Since the 1919 foundation of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI), the fields of volcano seismology and acoustics have seen dramatic advances in instrumentation and techniques, and have undergone paradigm shifts in the understanding of volcanic seismo-acoustic source processes and internal volcanic structure. Some early twentieth-century volcanological studies gave equal emphasis to barograph (infrasound and acoustic-gravity wave) and seismograph observations, but volcano seismology rapidly outpaced volcano acoustics and became the standard geophysical volcano-monitoring tool. Permanent seismic networks were established on volcanoes (for example) in Japan, the Philippines, Russia, and Hawai‘i by the 1950s, and in Alaska by the 1970s. Large eruptions with societal consequences generally catalyzed the implementation of new seismic instrumentation and led to operationalization of research methodologies. Seismic data now form the backbone of most local ground-based volcano monitoring networks worldwide and play a critical role in understanding how volcanoes work. The computer revolution enabled increasingly sophisticated data processing and source modeling, and facilitated the transition to continuous digital waveform recording by about the 1990s. In the 1970s and 1980s, quantitative models emerged for long-period (LP) event and tremor sources in fluid-driven cracks and conduits. Beginning in the 1970s, early models for volcano-tectonic (VT) earthquake swarms invoking crack tip stresses expanded to involve stress transfer into the wall rocks of pressurized dikes. The first deployments of broadband seismic instrumentation and infrasound sensors on volcanoes in the 1990s led to discoveries of new signals and phenomena. Rapid advances in infrasound technology; signal processing, analysis, and inversion; and atmospheric propagation modeling have now established the role of regional (15–250 km) and remote (> 250 km) ground-based acoustic systems in volcano monitoring. Long-term records of volcano-seismic unrest through full eruptive cycles are providing insight into magma transport and eruption processes and increasingly sophisticated forecasts. Laboratory and numerical experiments are elucidating seismo-acoustic source processes in volcanic fluid systems, and are observationally constrained by increasingly dense geophysical field deployments taking advantage of low-power, compact broadband, and nodal technologies. In recent years, the fields of volcano geodesy, seismology, and acoustics (both atmospheric infrasound and ocean hydroacoustics) are increasingly merging. Despite vast progress over the past century, major questions remain regarding source processes, patterns of volcano-seismic unrest, internal volcanic structure, and the relationship between seismic unrest and volcanic processes. 

Abstract Volcano infrasound data contain a wealth of information about eruptive patterns, for which machine learning (ML) is an emerging analysis tool. Although global catalogs of labeled infrasound events exist, the application of supervised ML to local (<15 km) volcano infrasound signals has been limited by a lack of robust labeled datasets. Here, we automatically generate a labeled dataset of >7500 explosions recorded by a five-station infrasound network at the highly active Yasur Volcano, Vanuatu. Explosions are located via backprojection and associated with one of Yasur’s two summit subcraters. We then apply a supervised ML approach to classify the subcrater of origin. When trained and tested on data from the same station, our chosen algorithm is >95% accurate; when training and testing on different stations, accuracy drops to about 75%. The choice of waveform features provided to the algorithm strongly influences classification performance.