To understand the dynamics and health of marine ecosystems such as lagoons and coral reefs as well as to understand the impact of human activities on these systems, it is imperative to predict the residence times of water masses and connectivity between ocean domains. In the present work, we consider the pristine lagoons and coral reefs of the Red Sea as an example of such sensitive ecosystems, with a large number of marine species, many of which are unique to the region. To study the residence times and connectivity patterns, we make use of recent advances in dynamic three-dimensional Lagrangian analyses using partial differential equations. Specifically, we extend and apply our novel efficient flow map composition scheme to predict the time needed for any particular water parcel to leave the domain of interest (i.e., a lagoon) as well as the time for any particular water parcel to enter that domain. These spatiotemporal residence time fields along with four-dimensional Lagrangian metrics such as finite time Lyapunov exponent (FTLE) fields provide a quantitative description of the Lagrangian pathways and connectivity patterns of lagoons in the Red Sea.

Covering the vast majority of our planet, the ocean is still largely unmapped and unexplored. Various imaging techniques researched and developed over the past decades, ranging from echo-sounders on ships to LIDAR systems in the air, have only systematically mapped a small fraction of the seafloor at medium resolution. This, in turn, has spurred recent ambitious efforts to map the remaining ocean at high resolution. New approaches are needed since existing systems are neither cost nor time effective. One such approach consists of a sparse aperture mapping technique using autonomous surface vehicles to allow for efficient imaging of wide areas of the ocean floor. Central to the operation of this approach is the need for robust, accurate, and efficient inference methods that effectively provide reliable estimates of the seafloor profile from the measured data. In this work, we utilize such a stochastic prediction and Bayesian inversion and demonstrate results on benchmark problems. We first outline efficient schemes for deterministic and stochastic acoustic modeling using the parabolic wave equation and the optimally-reduced Dynamically Orthogonal equations and showcase results on stochastic test cases. We then present our Bayesian inversion schemes and its results for rigorous nonlinear assimilation and joint bathymetry-ocean physics-acoustics inversion.

With the increasing availability of high-resolution comprehensive spatio-temporal ocean models and observation systems, ocean data visualization has become ubiquitous. This is due to the major impact of ocean products on disaster management, shipping, fisheries, autonomy, coastal operations, and scientific studies. Yet, there are several challenges for effective communication of data through visualization techniques. Specifically, ocean data is multivariate (e.g. temperature, salinity, velocity, etc.), is available for multiple depths and multiple time instants, and contains uncertainties, all of which leads to large, multi-dimensional datasets. Thus, it is necessary to have an interactive multiscale multivariate visualization tool that can assist scientists, engineers, policy makers, and the public in making insights from big data produced by ocean predictions and observations. In this work, we present a 3D (spatial) + 1 (temporal) multi-resolution multivariate visualization tool that produces interactive, dynamic, fast and portable ocean maps.

The North Equatorial Current (NEC) transports water westward around numerous islands and over submarine ridges in the western Pacific. As the currents flow over and around this topography, the central question is: how are momentum and energy in the incident flow transferred to finer scales? At the south point of Peleliu Island, Palau, a combination of strong NEC currents and tides flow over a steep, submarine ridge. Energy cascades suddenly from the NEC via the 1 km scale lee waves and wake eddies to turbulence. These submesoscale wake eddies are observed every tidal cycle, and also in model simulations. As the flow in each eddy recirculates and encounters the incident flow again, the associated front contains interleaving temperature (T) structures with 1–10 m horizontal extent. Turbulent dissipation (ε) exceeds 10^-5 W kg^-1 along this tilted and strongly sheared front. A train of such submesoscale eddies can be seen at least 50 km downstream. Internal lee waves with 1 km wavelengths are also observed over the submarine ridge. The mean form drag exerted by the waves (i.e., upward transport of eastward momentum) of about 1 Pa is sufficient to substantially reduce the westward NEC, if not for other forcing, and is greater than the turbulent bottom drag of about 0.1 Pa. The effect on the incident flow of the form drag from only one submarine ridge may be similar to the bottom drag along the entire coastline of Palau. The observed ε is also consistent with local dissipation of lee wave energy. The circulation, including lee waves and wake eddies, was simulated by a data-driven primitive equation ocean model. The model estimates of the form drags exerted by pressure drops across the submarine ridge and due to wake eddies were found to be about 10 times higher than the lee wave and turbulent bottom drags. The ridge form drag was correlated to both the tidal flow and winds while the submesoscale wake eddy drag was mainly tidal.

Using a combination of models and observations, the US Office of Naval Research Flow Encountering Abrupt Topography (FLEAT) initiative examines how island chains and submerged ridges affect open ocean current systems, from the hundreds of kilometer scale of large current features to the millimeter scale of turbulence. FLEAT focuses on the western Pacific, mainly on equatorial currents that encounter steep topography near the island nation of Palau. Wake eddies and lee waves as small as 1 km were observed to form as these currents flowed around or over the steep topography. The direction and vertical structure of the incident flow varied over tidal, inertial, seasonal, and interannual timescales, with implications for downstream flow. Models incorporated tides and had grids with resolutions of hundreds of meters to enable predictions of flow transformations as waters encountered and passed around Palau’s islands. In addition to making scientific advances, FLEAT had a positive impact on the local Palauan community by bringing new technology to explore local waters, expanding the country’s scientific infrastructure, maintaining collaborations with Palauan partners, and conducting outreach activities aimed at elementary and high school students, US embassy personnel, and Palauan government officials.