An Operational Technology for Assimilating Lagrangian Data Based on Dynamical Systems Techniques

Abstract

Much data in the ocean is Lagrangian in nature. Its full use in ocean prediction could advance significantly the Navy's ability to predict ocean conditions. The ultimate vision of this project has been the development of a data assimilation scheme that would afford a full naval predictive capacity in fixed ocean regions which can be comprehensively surveyed by Lagrangian measuring devices. This is based on the use of dynamical systems ideas that can generate strategies for deploying Lagrangian observational devices and their associated sensors. An effective Lagrangian data assimilation scheme coupled with an optimal deployment strategy can form the basis of an integrated prediction scheme for the ocean that can feed on both purely Lagrangian and mixed source data.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2008
Accession Number
ADA534142

Entities

People

  • Christopher K. R. T. Jones

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Assimilation
  • Bayesian Networks
  • Data Acquisition
  • Deployment
  • Equations
  • Filters
  • Flow
  • Flow Fields
  • Kalman Filters
  • Mathematics
  • Models
  • North Carolina
  • Observation
  • Particles
  • Sampling
  • Sequential Monte Carlo Methods
  • Three Dimensional

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Control Systems Engineering.
  • Oceanography.