Abstract
AbstractThis data assimilation study exploits infrasound from explosions to probe an atmospheric wind component from the ground up to stratospheric altitudes. Planned explosions of old ammunition in Finland generate transient infrasound waves that travel through the atmosphere. These waves are partially reflected back towards the ground from stratospheric levels, and are detected at a receiver station located in northern Norway at 178 km almost due north from the explosion site. The difference between the true horizontal direction towards the source and the backazimuth direction (the horizontal direction of arrival) of the incoming infrasound wavefronts, in combination with the pulse propagation time, are exploited to provide an estimate of the average cross‐wind component in the penetrated atmosphere. We perform offline assimilation experiments with an ensemble Kalman filter and these observations, using the ERA5 ensemble reanalysis atmospheric product as background (prior) for the wind at different vertical levels. We demonstrate that information from both sources can be combined to obtain analysis (posterior) estimates of cross‐winds at different vertical levels of the atmospheric slice between the explosion site and the recording station. The assimilation makes greatest impact at the 12–60 km levels, with some changes with respect to the prior of the order of 0.1–1.0 m·s−1, which is a magnitude larger than the typical standard deviation of the ERA5 background. The reduction of background variance in the higher levels often reached 2–5%. This is the first published study demonstrating techniques to implement assimilation of infrasound data into atmospheric models. It paves the way for further exploration in the use of infrasound observations – especially natural and continuous sources – to probe the middle atmospheric dynamics and to assimilate these data into atmospheric model products.
Highlights
Despite much recent attention to extratropical stratospheric dynamics and their connection to the troposphere, the amount of observational data in the stratosphere available to numerical weather prediction centres remains limited
We demonstrate that information from both sources can be combined to obtain analysis estimates of cross-winds at different vertical levels of the atmospheric slice between the explosion site and the recording station
Probabilistic infrasound propagation has been studied by Smets et al (2015), where measured infrasound wavefront parameters for one year of infrasound explosions were compared to ray-tracing simulations using the ensemble atmospheric wind and temperature fields of the ECMWF ensemble data assimilation system of perturbed analyses (Buizza et al, 1999)
Summary
Despite much recent attention to extratropical stratospheric dynamics and their connection to the troposphere, the amount of observational data in the stratosphere available to numerical weather prediction centres remains limited. Infrasound waves are acoustic waves at frequencies below the human hearing limit (typically around 20 Hz) These waves can be generated by natural sources, such as volcanoes, earthquakes and ocean swell, and by human sources, such as mining and explosions (e.g., Le Pichon et al, 2018). Infrasound waves may travel from sources on the surface of the Earth, reach a maximum altitude where they are partly or fully reflected or refracted, and reach back to the surface to be detected by a receiver They probe a slab of the atmosphere in a tomographic fashion since the time it takes for these waves to complete their path is affected by the characteristics of the atmosphere they pass through: in particular, the wind velocity and temperature, and attenuation-related properties like density and relative humidity. Probabilistic infrasound propagation has been studied by Smets et al (2015), where measured infrasound wavefront parameters for one year of infrasound explosions were compared to ray-tracing simulations using the ensemble atmospheric wind and temperature fields of the ECMWF ensemble data assimilation system of perturbed analyses (Buizza et al, 1999)
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