Renewal of Multi-Scale Model-Driven Sampling with Autonomous Systems at a National Littoral Laboratory: Turbulence Characterization with an AUV.

摘要

The overall goal of this research is to utilize turbulence measurements obtained from small Autonomous Underwater Vehicle (AUV) based sensors to improve mixing parameterizations in the data-assimilative modeling components of the LEO coastal prediction network applied to coastal upwelling. The rational for this research is that the lack of observations of vertical mixing rates imposes a severe limitation on our understanding of mixing processes in coastal waters, as well as on the development of models for them. A necessary step toward understanding these mechanisms is to directly observe spatial and temporal variations in turbulent mixing in and near upwelling events.