Albert, S. A. | Search NASA

DOE OSTI2023

The AtmoSOFAR Channel: First Direct Observations of an Elevated Acoustic Duct

The Sound Fixing and Ranging (SOFAR) channel in the ocean allows for low frequency sound to travel thousands of kilometers, making it particularly useful for detecting underwater nuclear explosions. Suggestions that an elevated SOFAR-like channel should exist in the stratosphere date back over half a century and imply that sources within this region can be reliably sensed at vast distances. However, this theory has not been supported with evidence of direct observations from sound within this channel. Here we show that an infrasound sensor on a solar hot air balloon recorded the first infrasound detection of a ground truth airborne source while within this acoustic channel, which we refer to as the AtmoSOFAR channel. Our results support the existence of the AtmoSOFAR channel, demonstrate that acoustic signals can be recorded within it, and provide insight into the characteristics of recorded signals. Results also show a lack of detections on ground-based stations, highlighting the advantages of using balloon-borne infrasound sensors to detect impulsive sources at altitude.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Atmospheric Structure Prediction for Infrasound Propagation Modeling Using Deep Learning

Abstract Infrasound is generated by a variety of natural and anthropogenic sources. Infrasonic waves travel through the dynamic atmosphere, which can change on the order of minutes to hours. Infrasound propagation largely depends on the wind and temperature structure of the atmosphere. Numerical weather prediction models are available to provide atmospheric specifications, but uncertainties in these models exist and they are computationally expensive to run. Machine learning has proven useful in predicting tropospheric weather using Long Short‐Term Memory (LSTM) networks. An LSTM network is utilized to make atmospheric specification predictions up to ∼30 km for three different training and testing scenarios: (a) the model is trained and tested using only radiosonde data from the Albuquerque, NM, USA station, (b) the model is trained on radiosonde stations across the contiguous US, excluding the Albuquerque, NM, USA station, which was reserved for testing, and (c) the model is trained and tested on radiosonde stations across the contiguous US. Long Short‐Term Memory predictions are compared to a state‐of‐the‐art reanalysis model and show cases where the LSTM outperforms, performs equally as well, or underperforms in comparison to the state‐of‐the‐art. Regional and temporal trends in model performance across the US are also discussed. Results suggest that the LSTM model is a viable tool for predicting atmospheric specifications for infrasound propagation modeling.

54 ENVIRONMENTAL SCIENCES↗