Vers une meilleure représentation de la distribution et de la variabilité de lʹozone atmosphérique par lʹassimilation des données satellitaires

Data assimilation plays an important role in the analysis of atmospheric data, in particular for numerical weather prediction and the detection of climate variations. In the field of atmospheric chemistry, assimilation techniques have been recently developed to study the distribution of tracer species, with emphasis on the ozone content. The present work reports on assimilation experiments of vertical ozone profiles from the GOME instrument performed with MOCAGE, a chemical-transport model and a 3D-FGAT variational technique. It is shown that this technique is very well adapted for ozone assimilation and can be extended to various sensors or other trace species. To cite this article: S. Massart et al., C. R. Geoscience 337 (2005).