Numerical modeling of infrasonic emissions from clear-air turbulence

Turbulence is a significant contributor to weather-related aviation incidents, with profound economic and safety implications. Clear-air turbulence (CAT) refers to turbulence occurring in the atmosphere, typically near the tropopause, without the observable convective cloud features. CAT is particularly hazardous as it remains invisible to pilots and many onboard instruments. With its occurrence expected to increase due to anthropogenic climate change, improved CAT detection is essential.

This study examines the infrasonic signature of CAT as a means for remote detection. Turbulence is a well-established source of sound, and infrasound has proven effective in detecting a range of geophysical events as the long-wavelength acoustic information can travel long distances with minimal attenuation. Using the Weather Research and Forecasting (WRF) model and observed meteorological data, high-resolution simulations were performed to reproduce representative case studies of CAT, including a documented event over Trout Peak in Wyoming, USA. These simulations provide the inputs for the acoustic model, with the dominant acoustic sources arising from turbulence and vorticity.

Acoustic pressure was computed at various far-field observation locations for two subdomains, one containing the CAT region and another representing the background flow with only minor fluctuations, to isolate the acoustic contributions from CAT specifically. The acoustic propagation is assumed to occur in a static and homogeneous medium, neglecting the effects of refraction and convection. Results reveal a significant increase in acoustic power associated with the CAT, with distinct and directionally dependent spectral peaks. These findings support the feasibility of using infrasound as a tool for real-time remote CAT detection.