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Optimal estimation in meteorology (presentation, 2001)
Article published on June 2001
last modification on 21 June 2007

OPTIMAL ESTIMATION IN METEOROLOGY was presented by Gérald Desroziers during the ALATNET seminar on Data Assimilation, June 11-22, 2001.

  • Introduction
    • estimation theory
      • observations are not perfect,
      • the estimate will also be approximate,
      • the estimate must be an optimal combination of observations,
      • it is better to overdetermine the problem,
      • a model can be used to give a preliminary estimate,
      • model are never perfect,
      • the estimate should fit observations within their errors.
    • 1st approach: minimisation of the estimation error variance
    • 2nd approach: Weighted Least Squares
    • 3rd approach: Maximum-likelihood
  • Using a background
  • Optimal Interpolation
  • Structure functions
  • Using a model: the Kalman Filter
    • Principle of a 3D-Var or Optimal Interpolation scheme