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

Abstract

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. The 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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2012
Accession Number
ADA590800

Entities

People

  • Steven R. Ramp

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Autonomous Vehicles
  • Bays
  • Boundaries
  • Boundary Layer
  • Climate Change
  • Continental Shelves
  • Delphi Method
  • Environmental Assessment
  • Heat Energy
  • Heat Flux
  • Observation
  • Oceans
  • Sampling
  • Three Dimensional
  • Underwater Acoustics
  • Vehicles

Fields of Study

  • Environmental science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Coastal Oceanography
  • Research Science/Academic Research

Technology Areas

  • Autonomy