Statistical and Stochastic Problems in Ocean Modeling and Prediction

Abstract

My project addresses statistical and stochastic problems in the following fields: Lagrangian data assimilation (1), Lagrangian prediction (2), development and validation of Lagrangian stochastic models (LSM) (3). The long range scientific objectives of this study comprise rigorous determining limits of predictability for Lagrangian motion in semi-enclosed seas, littoral zones, and straits on time scales of days and weeks, elaborating concrete prediction schemes, developing optimal Lagrangian data assimilation algorithms, and identification of multi particle stochastic models aimed at incorporating them to ocean circulation models (OCM).

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2007
Accession Number
ADA578327

Entities

People

  • L. I. Piterbarg

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Covariance
  • Data Fusion
  • Differential Equations
  • Equations
  • Error Analysis
  • Errors
  • Filtration
  • Mathematical Filters
  • Mixing
  • Oceans
  • Partial Differential Equations
  • Regions
  • Statistical Analysis
  • Statistics
  • Stratified Fluids

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers