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Abstract 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. 

A high‐sensitivity pressure sensor was deployed as part of the Mars Interior Exploration using Seismic Investigations, Geodesy and Heat Transport lander on Elysium Planitia in November 2018. We use pressure records from 1 October to 31 December 2019 (Sol 301–389) for frequencies between 0.1 and 0.5 Hz to infer relative sound‐speed changes in the Martian atmosphere using the autocorrelation infrasound interferometry method. We find that relative sound‐speed changes are up to ±15%, follow a similar pattern to Martian‐daily variations of atmospheric temperature and horizontal wind velocity, and are similar to those inferred from in‐situ observations and Martian climatology. The relative sound‐speed changes and horizontal wind speed variations are synchronous, while temperature peaks ∼1.88 hr after these time series. The strong and continuous emergence of coherent phases in the autocorrelation codas suggests the presence of continuous infrasound on Mars.

 

Seismic and infrasound multistation ambient‐noise interferometry has been widely used to infer ground and atmospheric properties, and single‐station and autocorrelation seismic interferometry has also shown potential for characterizing Earth structure at multiple scales. We extend autocorrelation seismic interferometry to ambient atmospheric infrasound recordings that contain persistent local noise from waterfalls and rivers. Across a range of geographic settings, we retrieve relative sound‐speed changes that exhibit clear diurnal oscillations consistent with temperature and wind variations. We estimate ambient air temperatures from variations in relative sound speeds. The frequency band from 1 to 2 Hz appears most suitable to retrieve weather parameters as nearby waterfalls and rivers may act as continuous and vigorous sources of infrasound that help achieve convergence of coherent phases in the autocorrelation codas. This frequency band is also appropriate for local sound‐speed variations because it has infrasound with wavelengths of ∼170–340 m, corresponding to a typical atmospheric boundary layer height. After applying array analysis to autocorrelation functions derived from a three‐element infrasound array, we find that autocorrelation codas are composed of waves reflected off nearby topographic features, such as caldera walls. Lastly, we demonstrate that autocorrelation infrasound interferometry offers the potential to study the atmosphere over at least several months and with a fine time resolution.