Statistical Problems in Ocean Modeling and Prediction

Abstract

My project addresses statistical and stochastic problems in the following fields: Lagrangian prediction and Lagrangian data assimilation (1), estimating transport and mixing parameters from tracer observations (2), and ocean model validation (3). The long range scientific goals of this study comprise determining limits of predictability for Lagrangian motion in semi-enclosed seas and littoral zones on time scales of days and weeks, estimating mixing and transport parameters in the upper ocean to improve performance of numerical models , and constructing statistical tests for model validation based on realistic confidence intervals for estimated mean fields and appropriate quantitative misfit measures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2002
Accession Number
ADA627096

Entities

People

  • L. I. Piterbarg

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Assimilation
  • Computational Fluid Dynamics
  • Computational Science
  • Data Science
  • Equations
  • Fluid Mechanics
  • Information Science
  • Kalman Filters
  • Littoral Zones
  • Mathematical Filters
  • Observation
  • Simulations
  • Statistical Analysis
  • Statistical Inference
  • Statistical Tests
  • Transport Ships

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Regression Analysis.