AUV-based turbulence characterization for coastal predictive networks

In the context of a coastal network, microstructure data are obtained from a small REMUS AUV integrated with a comprehensive suite of turbulence sensors. Instrumentation includes two shear probes, an ultra-fast thermistor, two CTDs, upward and downward looking ADCPs, and an ADV-O. This data acquisition enables estimates of dissipation rate, temperature microstructure, vertical shear of finescale horizontal velocity, and stratification; and consequently mixing parameters such as Richardson number, eddy viscosity, and eddy diffusivity.

In the LEO network, these estimates are utilized to characterize subgrid scale processes in the SCRUM model, and compare turbulence closure approaches. During July 1999, a field experiment was conducted in the LEO-15 region off New Jersey, to examine mixing processes associated with wind-driven upwelling. Using model-based adaptive sampling, the AUV was deployed along trajectories through components of the local emerging upwelling circulation, including the upstream coastal “pipe”, the downstream coastal “pipe”, and the detached offshore “jet”. For the final model prediction cycle, the data derived eddy viscosity in the upstream pipe was utilized as the inshore maximum value for SCRUM.

In the FRONT network, efforts are focused on the mid-shelf front offshore of Long Island Sound, which occurs often in SST and chlorophyll. The turbulence estimates are utilized to verify mixing fidelity in the coastal version of the MITgcm model being adapted for this study. During May 1999, a pilot field experiment was conducted in the region of maximum near-surface salinity gradient, and a spring microstructure transit was obtained. Subsequently, more extensive studies of the fall and spring front will be done when the network is full operation beginning in Fall 2000.

These inner and mid-shelf results are compared with previous estimates from the Cape Cod Bay gyre obtained in the LOOPS network. For example, a comparison of data distribution on a Froude number vs. Buoyancy Reynolds number diagram can be useful in distinguishing three dimensional turbulence from other coastal mixing processes such as internal waves.