The Effect of Stochastic Noise on Predictability

Abstract

Our long-term goal is to improve the accuracy of numerical prediction models of weather and climate. We shall concentrate on sources of prediction error involving interactions between physical phenomena having different timescales. We examine how inadequate representation of rapidly-varying (i.e., stochastic) atmospheric effects in General Circulation Models (GCMs) can systematically affect prediction on a variety of scales, and how errors arising from this inadequacy may be ameliorated. Concurrently, we develop useful, efficient and accurate methods of accounting for these systematic effects of stochastic forcing, and also provide methods for estimating the spread of ensemble predictions taking into account multiplicative stochastic effects.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 2000
Accession Number
ADA610242

Entities

People

  • Cecile Penland
  • Matthew Newman
  • Prashant Sardeshmukh

Organizations

  • National Oceanic and Atmospheric Administration

Tags

DTIC Thesaurus Topics

  • Applied Mathematics
  • Climate Change
  • Computational Science
  • Electronic Mail
  • Equations
  • Errors
  • Fluid Dynamics
  • Fokker Planck Equations
  • Information Operations
  • Linear Systems
  • Mathematics
  • Noise
  • Numerical Analysis
  • Rossby Waves
  • Simulations
  • Weather Forecasting
  • White Noise

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Theoretical Analysis.