Evaluation of long range acoustic model predictions using Monin-Obukhov similarity theory air temperature profiles

Refraction of sound in the atmosphere is largely governed by wind and air temperature. However, modeling sound propagation over long distances usually requires making a number of assumptions pertaining to the state of the atmosphere. In the near surface layer, Monin-Obukhov Similarity Theory (MOST) enables estimations of wind, air temperature, and humidity profiles with very little measurement input. This work examines how the assumption of MOST air temperature profile can affect acoustic model predictions over a range of 1 km. Over one years’ worth of air temperature profile, measurements over a water and marsh grass surface have been collected. Measurements were carried out by two arrays consisting of seven air temperature loggers spaced in 1 m intervals up to 7 m in elevation. Sound speed profiles based on both measured and modeled air temperature are implemented in a Crank-Nicholson Parabolic Equation (CNPE) solver. Predictions of sound pressure level made between each implementation of the CNPE model are compared over a wide range of weather conditions. [Work supported by Office of Naval Research Award N00014-22-1-2492.]