Coastal And Ocean Data Assimilation

Abstract

The long range scientific goal of this proposal is to produce optimal estimates of both the Lagrangian and Eulerian state space of the ocean, its marginal seas, and coastal zones in order to document, understand, and predict average conditions and variability. This is being accomplished through the use of data assimilation methods for ocean circulation models and Bayesian-based filtering techniques for Lagrangian prediction.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2008
Accession Number
ADA533825

Entities

People

  • Arthur J. Mariano
  • Toshio M. Chin

Organizations

  • Rosenstiel School of Marine, Atmospheric, and Earth Science

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Arabian Sea
  • Assimilation
  • Atmospheric Sciences
  • Boundaries
  • Dynamics
  • Filters
  • Filtration
  • Gulf Stream
  • High Resolution
  • Ocean Currents
  • Oceanography
  • Oceans
  • Particles
  • Physical Oceanography
  • Sequential Monte Carlo Methods
  • Signal Processing

Fields of Study

  • Environmental science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • Space