![]() In the current contribution, we propose a deep learning approach trained on a large set of simulated wavefields generated using PE simulations and realistic atmospheric winds to predict infrasound ground-level amplitudes up to 1000 km from a ground-based source. ![]() This introduces significant uncertainties in the predicted TL. Therefore, many studies rely on analytical regression-based heuristic TL equations that neglect complex vertical wind variations and the range-dependent variation in the atmospheric properties. However, the computational cost inherent in full-waveform modelling tools, such as Parabolic Equation (PE) codes, often prevents the exploration of a large parameter space, i.e., variations in wind models, source frequency, and source location, when deriving reliable estimates of source or atmospheric properties – in particular for real-time and near-real-time applications. ![]() Such predictions enable the reliable assessment of infrasound source characteristics such as ground pressure levels associated with earthquakes, man-made or volcanic explosion properties, and ocean-generated microbarom wavefields. Modelling the spatial distribution of infrasound attenuation (or transmission loss, TL) is key to understanding and interpreting microbarometer data and observations. Listening in on the atmospheres of Venus and Saturn's moon Titan just became a lot more promising as well. It shows that, we can likely put sound recorders on aircraft such as drones (both low and close to the ground, and high in the sky), getting useful results in the process. This is a big deal, because no one knew it was possible to pick up faint sounds amid the rushing wind caused by the birds' flight. The birds flew far and wide across the ocean, recording both nearby and distant sound along the way. (2021) solved this problem by putting sound recorders on wandering albatrosses. There's some places we can't reach though, like just above the surface of the ocean. ![]() Only in the last few years have we begun to explore the sounds in this vast region, and typically we use tethered or free floating balloons to do so. Scientists typically record these sounds using instruments that sit on the ground, despite the fact that there is an ocean of air lying above them. If these sounds are deep enough, they can travel a long way. Many things make sound on Earth and other planets. The comparison shows a statistical agreement for 85% of the time between the modeled and observed soundscapes. The reconstructed soundscapes are compared with microbarom recordings by microbarometer arrays and the INFRA‐EAR, a miniature sensor deployed as a biologger near the Crozet Islands. This is a significant improvement to previous approaches, which accounted for the normalized loudest source region only. The method reconstructs omnidirectional soundscapes in absolute numbers. In this study, a method for the reconstruction of the microbarom source field is introduced. Insights in the ambient noise field improve natural hazards monitoring and the verification of the Comprehensive Nuclear‐Test‐Ban Treaty. Under noisy conditions, microbaroms can mask infrasonic signals of interest, such as infrasound from volcanoes or explosions. The microbarom signals can be divided into a direct signal, only detectable close by the source, and a propagating signal, which travels over large distances. They have a characteristic and continuous signature within the infrasound spectrum and are often classified as ambient noise. ![]() Microbaroms are omnipresent sources of low‐frequency, inaudible sound, that is, infrasound. ![]()
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