Above and below the waves: analysis of coordinated surface and subsurface autonomous vehicle data

Coastal nations along the edge of the Caribbean basin have long been plagued by a data deficit regarding tropical cyclone impacts. Over the last several decades, the annual frequency of these storms is increasing in this area, but the lack of nearshore storm behavior data collection and coverage persists. Despite efforts to gain better context, ocean-atmosphere interactions in coastal shelf and drop-off regions are still difficult to predict, especially during storm passage, due to a critical gap in water column information. Tropical cyclones can be subject to rapid changes in intensity immediately before landfall, therefore measuring data from the upper water column and air-sea interface immediately before, during, and after tropical cyclone passage could provide much-needed context behind coastal storm behavior. In November 2021, two autonomous vehicles that were already conducting individual missions collecting data near the U.S. Virgin Islands, Navy Slocum LBS-G Glider NG644 and Saildrone 1048 (SD-1048), were brought together over the shelf-break 16 km south of St. Thomas for a joint assignment that lasted 8 days. In a unique co-located sampling alliance, two different types of autonomous vehicles ran repeating, intersecting transects within a 10 km2 area. SD-1048 observed current velocities throughout the top 60 meters of the ocean’s mixed layer using an Acoustic Doppler Current Profiler (ADCP), while also taking atmospheric measurements such as air temperature, barometric pressure, and wind speed. Simultaneously, physical properties of approximately the same water column (temperature, salinity, and density) were measured by NG644, which would dive 9 times (2 profiles per dive) each mission day to approximately 500 meters before returning to the surface. The main focus of this research is the top 60 meters of the water column, where the two unmanned sampling platforms overlap. By coupling the profiles from individual glider dives with hourly-averaged profiles from the Saildrone, we could see the movement of different water masses within the surface mixed layer. It also allowed us to identify the ocean’s barrier layer, which separates the stratified surface layer from the thermocline and helps maintain the salinity and temperature of the water column. Initial analysis indicates a persistent west/northwest flowing current within the top 20 to 30 meters, as well as a positive correlation between greater current velocities and the depth of the freshwater layer (between 34 and 34.5 PSU). Our work also involved looking at the influence of the winds and tides on this surface barrier level movement. We further analyzed the much higher salinity layer that exists at 40 meters deep and below, as well as the thermal fluctuations occurring at the same depths. This is where different water masses are sliding past each other, and this paper aims to reveal more about the impact that water mass-induced shear has on the dynamics of the mixed layer and the air-sea interface. It is worth noting this joint effort was performed at the end of the Atlantic hurricane season and there weren’t any active tropical cyclones in the area, which allows this mission to serve as a control case. Our goal is to use the plotted data from two different types of autonomous vehicles to confirm the presence of previously identified water masses (from studies conducted on this same region). In doing this we will also examine the effects that atmospheric activity has on the upper water column in this region and reference historical trends to determine how this behavior could affect tropical cyclone intensity in the Caribbean. Using this research, we will also discuss the practicality and potential of using this type of compound autonomous vehicle mission in tropical cyclones and on a global scale.M.S.Includes bibliographical reference