Background‐error covariances for a convective‐scale data‐assimilation system: AROME–France 3D‐Var

Abstract

Abstract AROME–France is a convective‐scale numerical weather prediction system running operationally at Météo‐France since the end of 2008. It uses a 3D‐Var assimilation scheme to determine its initial conditions. Climatological background‐error covariances of such a system are calculated using differences between forecasts from an AROME ensemble assimilation. These statistics are compared with the lower‐resolution ALADIN–France system ones: they provide 3D‐Var analysis increments that are more intense and more localized, in accordance with the actual AROME model resolution. AROME ensemble‐assimilation (ENS_DA) covariances have also been compared with covariances calculated with an AROME ensemble of forecasts run in spin‐up mode (ENS_SU). On the one hand, ENS_SU appears to be a reasonable approximation of ENS_DA compared with ALADIN–France covariances, by representing a large part of the small‐scale variance increase. On the other hand, ENS_DA allows for a fully cycled development of small‐scale forecast perturbations, which leads to a further enhancement of small‐scale covariances. This aspect is shown to be beneficial in terms of assimilation diagnostics and forecast performance and in a case study. Copyright © 2011 Royal Meteorological Society