Optimal Asset Distribution for Environmental Assessment and Forecasting Based on Observations, Adaptive Sampling, and Numerical Prediction.

摘要

The objective of this Multi-University Research Initiative (MURI) grant, subtitled, 'The Adaptive Sampling and Prediction System (ASAP)' was to learn how to deploy, direct, and utilize autonomous vehicles and other mobile sensing platforms most efficiently to sample the ocean, assimilate the data into numerical models in real or near-real time, and predict future conditions with minimal error. The scientific goal was to close the heat budget for a control volume surrounding a three-dimensional coastal upwelling center, and identify via the magnitude of the terms the relative importance of the surface fluxes, boundary layer processes, alongshore advection, and mesoscale interactions in determining the temperature changes within the box. The work resulted in seven publications in refereed journals authored or co-authored by the Pis, and the eighth is in advanced preparation.