How Do Tides Affect Underwater Acoustic Propagation? A Collaborative Approach to Improve Internal Wave Modeling at Basin to Global Scales

Accurate prediction of underwater sound speed and acoustic propagation is dependent on realistic representation of the ocean state and its underlying dynamics within ocean models. Stratified, high-resolution global ocean models that include tidal forcing better capture the ocean state by introducing internal tides that generate higher frequency (supertidal) internal waves. Through the disciplines of internal wave modeling, acoustics, and machine learning, we examined how internal wave energy moves through numerical simulations, how this energy alters the ocean state and sound speed, and how machine learning could aid the modeling of these impacts. The project used global, basin-scale, and idealized HYbrid Coordinate Ocean Model (HYCOM) simulations as well as regional Massachusetts Institute of Technology general circulation model (MITgcm) simulations to examine how tidal inclusion affects sea surface height variability, the propagation and dissipation of internal wave energy, and the sensitivity of internal wave modeling to vertical and horizontal grid spacing. Sound speed, acoustic parameters, and modeled acoustic propagation were compared between simulations with and without tidal forcing, and deep learning algorithms were used to examine how a tidally forced ocean state could be generated while reducing computational costs.