Statistical Prediction of Ocean Circulation and Trajectories

Abstract

Our goals are to develop efficient means for statistically forecasting ocean currents and Lagrangian trajectories. Objectives are to formulate and test methods for predicting flows and trajectories that represent evolution of uncertainty and feedback of the uncertain component upon the mean. Such statistical predictions can be obtained via ensemble forecasts, but these are computationally expensive and suffer from statistical noise due to finite ensemble size. We seek statistical forecast methods that avoid these difficulties, guided by statistical mechanical theory and numerical investigation of quasi-geostrophic (qg) flow statistics. Anticipating application to more realistic flows, we have sought to extend statistical mechanics beyond qg to the case of finite-amplitude topography.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2001
Accession Number
ADA625413

Entities

People

  • Greg Holloway
  • William Merryfield

Organizations

  • Institute of Ocean Sciences

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Data Science
  • Equations
  • Flow
  • Fluid Dynamics
  • Information Science
  • Mechanics
  • Mixing
  • Ocean Currents
  • Oceans
  • Personal Information Managers
  • Sea Ice
  • Statistical Mechanics
  • Statistics
  • Test Methods
  • Topography
  • Trajectories
  • Uncertainty

Fields of Study

  • Mathematics
  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Atmospheric Science/Meteorology
  • Computational Modeling and Simulation