On Stochastic Stability of Regional Ocean Models to Finite-Amplitude Perturbations of Initial Conditions

Abstract

We consider error propagation near an unstable equilibrium state (classified as an unstable focus) for spatially uncorrelated and correlated finite-amplitude initial perturbations using short- (up to several weeks) and intermediate (up to two months) range forecast ensembles produced by a barotropic regional ocean model. An ensemble of initial perturbations is generated by the Latin Hypercube design strategy, and its optimal size is estimated through the Kullback - Liebler distance (the relative entropy). Although the ocean model is simple, the prediction error (PE) demonstrates non-trivial behavior similar to that existing in 3D ocean circulation models. In particular, in the limit of zero horizontal viscosity, the PE at first decays with time for all scales due to dissipation caused by nonlinear bottom friction, and then grows faster than [quasi]-exponentially. Statistics of a prediction time scale [the irreversible predictability time (IPT)] quickly depart from Gaussian (the linear predictability regime) and becomes Weibullian (the non-linear predictability regime) as amplitude of initial perturbations grows. A transition from linear to non-linear predictability is clearly detected by the specific behavior of IPT variance. A new analytical formula for the model predictability horizon is introduced and applied to estimate the limit of predictability for the ocean model.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA478877

Entities

People

  • Leonid M. Ivanov
  • Peter Cheng Chu

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Amplitude
  • Computational Science
  • Data Mining
  • Data Science
  • Distribution Functions
  • Information Science
  • Intensity
  • Monte Carlo Method
  • Ocean Currents
  • Oceanography
  • Probability
  • Probability Density Functions
  • Sampling
  • Statistical Analysis
  • Statistics
  • Three Dimensional
  • Topography

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers