Predictability of Particle Trajectories in the Ocean

Abstract

LONG TERM GOALS. The long term goal of this grant is to determine optimal employment and Lagrangian data assimilation strategies for drifting buoys, in order to enhance prediction of particle motion in the ocean with potential applications to ecological, search and rescue, and the floating mine problems. OBJECTIVES. The specific scientific objective of the work done has been to determine the effectiveness of using insitu Lagrangian measurements and data assimilation techniques in improving the prediction of particle trajectories. This has been done initially in the context of an ocean model (MICOM) and then using real oceanic drifter data representing both small scale (the Adriatic Sea) and large scale (tropical Pacific Ocean) motion. APPROACH. The work is based primarily on simple probabilistic particle models and data assimilation strategies. It also involves the use of OGCMs and processing of oceanic data.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1999
Accession Number
ADA636468

Entities

People

  • Annalisa Griffa
  • Arthur J. Mariano
  • Tamay M. Özgökmen

Organizations

  • Rosenstiel School of Marine, Atmospheric, and Earth Science

Tags

DTIC Thesaurus Topics

  • Adriatic Sea
  • Assimilation
  • Atmospheric Sciences
  • Data Analysis
  • Data Sets
  • Errors
  • Flow
  • Flow Fields
  • Kalman Filtering
  • Kalman Filters
  • Mediterranean Sea
  • Oceanography
  • Oceans
  • Pacific Ocean
  • Particle Trajectories
  • Particles
  • Trajectories

Fields of Study

  • Environmental science

Readers

  • Acoustical Oceanography.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers