A simple prediction algorithm for the Lagrangian motion in two-dimensional turbulent flows

Leonid I. Piterbarg, Tamay M Ozgokmen

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

A new algorithm is suggested for prediction of a Lagrangian particle position in a stochastic flow, given observations of other particles. The algorithm is based on linearization of the motion equations and appears to be efficient for an initial tight cluster and small prediction time. A theoretical error analysis is given for the Brownian flow and a stochastic flow with memory. The asymptotic formulas are compared with simulation results to establish their applicability limits. Monte Carlo simulations are carried out to compare the new algorithm with two others: the center-of-mass prediction and a Kalman filter-type method. The algorithm is also tested on real data in the tropical Pacific.

Original languageEnglish (US)
Pages (from-to)116-148
Number of pages33
JournalSIAM Journal on Applied Mathematics
Volume63
Issue number1
DOIs
StatePublished - Aug 2002

Fingerprint

Turbulent Flow
Turbulent flow
Stochastic Flow
Motion
Prediction
Barycentre
Linearization
Asymptotic Formula
Error Analysis
Kalman filters
Kalman Filter
Error analysis
Equations of motion
Theoretical Analysis
Monte Carlo Simulation
Data storage equipment
Simulation

Keywords

  • Lagrangian motion
  • Oceanographic applications
  • Prediction
  • Stochastic flow
  • Stochastic simulations

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

Cite this

A simple prediction algorithm for the Lagrangian motion in two-dimensional turbulent flows. / Piterbarg, Leonid I.; Ozgokmen, Tamay M.

In: SIAM Journal on Applied Mathematics, Vol. 63, No. 1, 08.2002, p. 116-148.

Research output: Contribution to journalArticle

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