Statistical and Stochastic Problems in Ocean Modeling and Prediction, Stage II

Abstract

My project addresses statistical and stochastic problems in the following fields: Lagrangian prediction (1), Lagrangian data assimilation (2), and ocean model validation (3). The long range scientific objectives of this study comprise rigorous determining limits of predictability for the 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 constructing and testing discrepancy measures (metrics) for comparison of modeled and observed time series of oceanic parameters to improve performance of numerical models.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2002
Accession Number
ADA626590

Entities

People

  • L. I. Piterbarg

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Concrete
  • Data Analysis
  • Data Sets
  • Differential Equations
  • Equations
  • Errors
  • Kalman Filters
  • Littoral Zones
  • Materials
  • Mathematical Filters
  • Oceans
  • Partial Differential Equations
  • Statistical Analysis
  • Statistical Inference
  • Validation

Readers

  • Computational Modeling and Simulation
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design