Optimal estimation in meteorology (presentation, 2001)
June 2001
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
- estimation theory
- Using a background
- Optimal Interpolation
- Structure functions
- Using a model: the Kalman Filter
- Principle of a 3D-Var or Optimal Interpolation scheme
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