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Listening to the Atmosphere: Using Infrasound Observations to Infer Atmospheric Conditions.

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Title: Listening to the Atmosphere: Using Infrasound Observations to Infer Atmospheric Conditions.
Authors: Amezcua, Javier1 (AUTHOR) j.amezcua@reading.ac.uk, Averbuch, Gil2 (AUTHOR), Näsholm, Sven Peter3,4 (AUTHOR), Arrowsmith, Stephen5 (AUTHOR)
Source: Journal of Geophysical Research. Atmospheres. 3/16/2026, Vol. 131 Issue 5, p1-23. 23p.
Subject Terms: *Mesosphere, *Weather forecasting, *Weather, *Stratosphere, Infrasonic waves, Data assimilation, Inverse problems, Sensor arrays
Geographic Terms: Oklahoma
Abstract: The stratosphere and mesosphere are important regions for the prediction of weather at the Earth's surface for medium‐ and long‐range forecasts. The availability of observations in these layers is lower than that of the troposphere, especially for the dynamics. While seeking new observational sources is important, there are existing infrasound data sets that provide indirect observations of these layers to be exploited. Infrasound waves generated at the Earth's surface travel horizontally and vertically through the atmosphere, and can be detected by sensor arrays at ranges of hundreds or thousands of kilometers. These waves are affected by the atmospheric conditions they encounter during propagation, and the integrated contributions can be observed in the recorded observations. Inverse problem techniques can be readily used to extract information from these integrated observations and provide valuable data related to the atmospheric conditions. We exploit observations from controlled ammunition explosions in Oklahoma, which generate waves traveling to 30–50 km altitude before being refracted back to the surface and detected 256 km from the explosion site. As model background we use the 10‐member European Reanalysis product, valid 1 hr before the explosions. We use the Modulated Ensemble Transform Kalman Filter to combine these two sources of information and obtain updated atmospheric profiles. The assimilated observations bring the atmospheric profiles closer to those obtained by solely interpolating the reanalysis product to the time of the explosions. The most benefited altitudes are those close to the refraction heights of the infrasound waves, 35–55 km. Plain Language Summary: Observations of stratospheric and mesospheric variables are rare, particularly of winds. There are, however, indirect and underutilized observations which can help constrain variables in these levels. Detonations at the Earth's surface generate infrasound waves which travel horizontally and vertically through the atmosphere. As they travel, they are affected by winds and temperature. The integrated effect is contained in observations taken when these waves are detected at specialized sensor stations. In this work, we use data assimilation techniques to extract information of the atmospheric variables from integrated observations. We take advantage of a unique data set of infrasound recorded from a set of controlled explosions in Oklahoma. Key Points: There are sensor arrays around the world constantly measuring infrasound waves, providing unique long‐term data sets of opportunityWe use indirect observations to update middle atmospheric variables (temperature and winds) which are otherwise sparsely observedThis is the first work performing data assimilation with a full ray‐tracing routine as observation operator and applied to recorded data [ABSTRACT FROM AUTHOR]
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Abstract:The stratosphere and mesosphere are important regions for the prediction of weather at the Earth's surface for medium‐ and long‐range forecasts. The availability of observations in these layers is lower than that of the troposphere, especially for the dynamics. While seeking new observational sources is important, there are existing infrasound data sets that provide indirect observations of these layers to be exploited. Infrasound waves generated at the Earth's surface travel horizontally and vertically through the atmosphere, and can be detected by sensor arrays at ranges of hundreds or thousands of kilometers. These waves are affected by the atmospheric conditions they encounter during propagation, and the integrated contributions can be observed in the recorded observations. Inverse problem techniques can be readily used to extract information from these integrated observations and provide valuable data related to the atmospheric conditions. We exploit observations from controlled ammunition explosions in Oklahoma, which generate waves traveling to 30–50 km altitude before being refracted back to the surface and detected 256 km from the explosion site. As model background we use the 10‐member European Reanalysis product, valid 1 hr before the explosions. We use the Modulated Ensemble Transform Kalman Filter to combine these two sources of information and obtain updated atmospheric profiles. The assimilated observations bring the atmospheric profiles closer to those obtained by solely interpolating the reanalysis product to the time of the explosions. The most benefited altitudes are those close to the refraction heights of the infrasound waves, 35–55 km. Plain Language Summary: Observations of stratospheric and mesospheric variables are rare, particularly of winds. There are, however, indirect and underutilized observations which can help constrain variables in these levels. Detonations at the Earth's surface generate infrasound waves which travel horizontally and vertically through the atmosphere. As they travel, they are affected by winds and temperature. The integrated effect is contained in observations taken when these waves are detected at specialized sensor stations. In this work, we use data assimilation techniques to extract information of the atmospheric variables from integrated observations. We take advantage of a unique data set of infrasound recorded from a set of controlled explosions in Oklahoma. Key Points: There are sensor arrays around the world constantly measuring infrasound waves, providing unique long‐term data sets of opportunityWe use indirect observations to update middle atmospheric variables (temperature and winds) which are otherwise sparsely observedThis is the first work performing data assimilation with a full ray‐tracing routine as observation operator and applied to recorded data [ABSTRACT FROM AUTHOR]
ISSN:2169897X
DOI:10.1029/2025JD044841