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

Authors: Steven R Ramp; SOLITON OCEAN SERVICES INC CARMEL VALLEY CA

Abstract:

The long-term goal of this research is to enhance our understanding of coastal oceanography by means of applying simple dynamical theories to high-quality observations obtained in the field. The objective of this Multi-University Research Initiative (MURI) grant, subtitled The Adaptive Sampling and Prediction System (ASAP), is 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. Our scientific goal is 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 mobile assets for this project included 10 gliders, 3 propeller-driven vehicles, a research aircraft, and several support ships. Given these resources and the objectives above, a control volume was selected for the 2006 experiment. The box, approximately 40 x 20 km, enclosed the upwelling center that was of central scientific interest. Six gliders were deployed along racetracks within the box and 4 were deployed as rockers oscillating back-and-forth along the boundaries, one on each end and two covering the offshore side. Using a combination of autonomous and human-activated control, the gliders were coordinated as a group to optimize the sampling coverage of the control volume in response to the ever-changing current conditions. A pair of bottom-mounted acoustic Doppler current profilers (ADCPs) was also deployed along the southern boundary of the box to sample and report the internal wave environment in real time via a Seaweb underwater network.

Limitations:

APPROVED FOR PUBLIC RELEASE