Modelling weather prediction errors
Modélisation des erreurs de prévision météorologique
Résumé
This dissertation describes several approaches to error modelling. In part 1, the principles of error modelling are introduced for data assimilation and ensemble prediction applications. Part 2 summarizes my work on background error modelling, which has been applied to global operational variational assimilation, and in an academic Kalman Filter setting. Part 3 discusses how error models can be validated, which can be done in terms of error covariances, meteorological objects, or ensemble prediction. An outlook on these issues is given as a conclusion.
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