Towards a 2DEnVar surface data assimilation approach within the convective scale numerical weather prediction model AROME-France - Centre national de recherches météorologiques
Article Dans Une Revue Quarterly Journal of the Royal Meteorological Society Année : 2024

Towards a 2DEnVar surface data assimilation approach within the convective scale numerical weather prediction model AROME-France

Résumé

Surface data assimilation (DA) plays a key role in the initialisation of soil variables in coupled surface-atmosphere numerical weather prediction (NWP) models. Météo-France, as many other NWP centres, uses an operational surface DA method based on an optimal interpolation (OI), implemented more than 30 years ago. The current surface DA system implemented at Météo-France in the operational limited-area AROME-France model operates in two steps. First, a two-dimensional OI method analyses the diagnostic screen-level parameters, which are then used to initialise the prognostic soil variables according to a onedimensional OI method. This article presents the implementation and the results of a new two-dimensional ensemble-based variational (2DEnVar) system, Marimbordes et al. in OI.

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Dates et versions

hal-04747897 , version 1 (22-10-2024)

Identifiants

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Sophie Marimbordes, Camille Birman, Etienne Arbogast, Nadia Fourrié, Jean‐françois Mahfouf. Towards a 2DEnVar surface data assimilation approach within the convective scale numerical weather prediction model AROME-France. Quarterly Journal of the Royal Meteorological Society, 2024, ⟨10.1002/qj.4867⟩. ⟨hal-04747897⟩
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