Statistical and Stochastic Problems in Ocean Modeling and Prediction

Abstract

My project addresses statistical and stochastic problems in the following fields: Lagrangian prediction (1), Lagrangian data assimilation (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, 2006
Accession Number
ADA613672

Entities

People

  • L. I. Piterbarg

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Computational Science
  • Data Sets
  • Differential Equations
  • Dispersions
  • Error Analysis
  • Errors
  • Estimators
  • High Resolution
  • Mathematical Filters
  • Models
  • Oceans
  • Partial Differential Equations
  • Statistical Analysis
  • Stratified Fluids
  • Turbulence

Readers

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