Modeling and Forecasting Ocean Acoustic Conditions

Abstract

Modeling acoustic conditions in an oceanic environment is a multiple-step process. The environmental conditions (features) in the area first must be measured or estimated; relevant features include seabed geometry, seabed composition, and four-dimensionally (4D) variable sound-speed and density variations related to evolving or wave motions. Often the dynamical wave modeling depends on first obtaining correct seabed and mean stratification conditions (for example, nonlinear internal wave modeling). Next, this information must be included in sound propagation modeling. A selection of the many methods and tools available for these tasks are described, with a focus on modeling sounds of 20 to 1000 Hz propagating through water-column features that are time-dependent and variable in three dimensions (i.e., 4D variable). An example of a 3D parabolic equation acoustic calculation shows how variability caused by evolving internal tidal waves affects sound propagation. Different propagation and scattering regimes are discussed, including the theoretically delineated weak scattering and strong scattering regimes, as well as the empirically examined regime found in nonlinear internal waves. The histories and the current state of our oceanographic knowledge (the input to acoustic modeling) and of our ability to effectively model complex acoustic conditions are discussed. Example acoustic simulation applications are also discussed; these are ocean acoustic tomography, coherence prediction, and signal-to-noise ratio prediction. Types of ocean models and acoustic models and how they are interfaced are also examined. These include deterministic, statistical analytic feature models.

The Importance of Remote Forcing for Regional Modeling of Internal Waves

“…Deterministic representation allows exact interpretation of ocean measurements at short space and time scales to the extent that internal waves are treated as signal instead of noise. Applications include acoustic propagation (Duda, 2017) and process experiments to quantify the interactions that produce the continuum spectrum. On the other hand, since internal waves are a primary driver of ocean turbulence, statistical representation in models allows reproduction of ocean physical and ecosystem dynamics (MacKinnon et al, 2017).…”