Over the last four decades the use of numerical flow models in oceanography has vastly increased. Models are run operationally for regional locations, ocean basins, and the entire earth. In addition, specialized research models targeting specific processes and areas are routinely produced. These models are often coupled with biological and chemical models for research into biological-physical and biogeochemical-physical interactions. The role of some models is to create conditions close to reality, in a deterministic sense, whereas others have the role of imitating mean behavior or fluctuation behavior. The role of yet another family of models is to alter conditions from reality to study the ramifications, examples being interdisciplinary climate models [1-3]. All of these models provide full access to time- evolving three-dimensional fields (4-D fields) for process studies, or for predictive purposes. There is strong motivation for using these models for ocean acoustic studies. Suitably formulated models can include the important flow and water-mass features of the ocean, with the important features covering a wide dynamic range. Each feature has its own acoustic propagation or scattering signature, with some signatures having an interfering effect on underwater acoustic activities. The signature can be in the temporal domain, the spatial domain, or both. An important part of ocean acoustics research at this time is identifying which processes are dominant at specific times and places, and models are well suited to this. Significant acoustic effects of water-column and seafloor features occur in concert. However, they have traditionally been studied individually, sometimes in idealized or very simple form. Despite the isolation of the processes, many of these studies have been very successful. Examples are the analysis of the Pekeris waveguide [4], adiabatic mode propagation in a smoothly varying waveguide [5], and propagation through idealized internal waves [6-8]. The state of our knowledge now demands that the full complexity be analyzed, as can be done using the ocean models. Initial efforts that have coupled four-dimensional ocean fields with 2D acoustics modeling include data assimilation and uncertainty studies [9, 10], end-to-end computations [11], real-time at-sea predictions [12] and coupled adaptive sampling [13]. In the present work, a specific focus is on 3D acoustic effects coupled to 4D ocean predictions. We have thus motivated the use of oceanographic flow models as a straightforward approach for objective and comprehensive study of sound propagation in realistic environments, which we refer to as coupled ocean/acoustics modeling. The alternative of investigating the overall effects of simultaneously occurring feature types by constructing idealized process models with multiple features (straight line internal waves in two-layer fluid over a uniformly sloped bottom and one eddy, for example) is likely to lack objectivity or completeness. In fact, such feature models are mainly utilized to initialize ocean models or describe/assimilate specific features [14]. Coupled ocean/acoustics modeling can have high value, under the condition that the synthesized environments are sufficiently inclusive, representative, and accurate. This is a nontrivial condition; many challenges remain for flow models in terms of boundary conditions and data assimilation, resolution of near-boundary effects and mixing effects, and three-dimensional nonlinear gravity waves with hydrostatic pressure. Note that making acoustic propagation predictions, without analysis of the behavior or the mechanisms at work, is a byproduct of coupled ocean-acoustic modeling. Coupled ocean/acoustics modeling is becoming more common. Nevertheless, the approach is relatively recent and the best research path to take at this time deserves discussion. In this paper we discuss the potential of this method, and inform the discussion with some example computations from recent work in the Mid Atlantic Bight.