Improvement of the forecast of convective activity from the AROME‐France system

Abstract

AROME‐France is a convective‐scale numerical weather prediction system which has been running operationally at Météo‐France since the end of 2008. In order to determine its initial conditions, it uses a 3D‐Var assimilation scheme at the same resolution as the model in a continuous data assimilation cycle. In addition to conventional and satellite observations used in global data assimilation systems, dedicated observations for the mesoscale such as surface observations and radar measurements (radial winds and reflectivities) are assimilated. A major update of this system occurred in April 2015 with, among several improvements, (i) an increase of both horizontal and vertical resolutions (1.3 km and 90 vertical levels versus 2.5 km and 60 levels), and (ii) the reduction of the period of the data assimilation cycle from 3 to 1 h (as a result of the model spin‐up reduction and the tuning of the background‐error covariances). This study presents the preparatory work to these modifications and explores the main impact expected on convective activity forecasts. (i) appears to result in more realistic convective cells and better rainfall and wind gust scores and (ii) allows assimilation of more observations with information at the mesoscale which provides more accurate initial conditions and hence better subsequent rainfall forecasts. The benefits of using both (i) and (ii) in a pre‐operational configuration are shown using objective precipitation scores and illustrated by a case‐study.