The Use of Observed Data for the Initial Value Problem in Numerical Weather Prediction.

Abstract

The problem of combining observed and predicted values of meteorological variables, all with error, to obtain current weather conditions is considered. Statistical interpolation is in common use for this problem. Properties of isotropic spatial covariance functions are developed. The performance of several families of covariance functions in fitting published data is investigated. The second order autoregressive covariance function is identified as having suitable theoretical and excellent approximation properties. Sensitivity of the errors in statistical interpolation to misspecification of the statistical parameters is explored, showing that the process is quite stable to such perturbations.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1987
Accession Number
ADA181744

Entities

People

  • Edward Barker
  • James Goerss
  • Richard Franke

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Bessel Functions
  • Covariance
  • Data Science
  • Equations
  • Grids
  • Information Science
  • Mathematics
  • Military Research
  • Probability
  • Probability Density Functions
  • Research Facilities
  • Standards
  • Statistical Analysis
  • Statistics
  • Two Dimensional
  • United States
  • Weather Forecasting

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Computational Modeling and Simulation