Tuning of Observation Error Parameters in a Variational Data Assimilation

Tuesday, April 30, 2002 - 10:30am - 11:15am
Keller 3-180
Gerald Desroziers (NRM/GMAP)
Joint work with B .Chapnik (*), F. Rabier (*), and O. Talagrand (**)

Data assimilation schemes implemented in most of the National Weather Prediction systems basically rely on linear estimation theory, or an extension of this theory. In such an approach, each observation is given a weight proportional to the inverse of its specified error variance. We present a method based on diagnostics of observations-minus-analysis differences that aims at performing a tuning of observation error parameters from a single batch of observations. This method is intended to be implemented in a variational assimilation scheme. The relationship of this procedure with the maximum-likelihood principle is also shown.

(*) Meteo-France, CNRM, Toulouse, France
(**) Ecole Normale Superieure, LMD, Paris, Fr