A posteriori diagnostics of the impact of observations on the AROME‐France convective‐scale data assimilation system

AROME-France is an operational convective-scale numerical weather prediction system which uses a 3D-Var assimilation scheme in order to determine its initial conditions. In addition to conventional and satellite observations, regional high-resolution observations are assimilated, such as screen-level observations, total zenith delays from ground-based GPS stations and radar measurements (radial winds and reflectivities). The impact of the various observation types on AROME-France analyses is assessed using an a posteriori diagnostic, the reduction of the estimation error variance. This diagnostic, estimated using a randomization technique, allows one to investigate observation impact depending on the control variable field, model levels, date, analysis time, and spatial scales considered. This highlights the importance of screen-level observations (2 m temperature and relative humidity, 10 m wind) for the lowest layers, of aircraft measurements for temperature and wind field analyses and of radar observations for wind and specific humidity in middle and high troposphere. Only the last mentioned observations appear to be informative regarding the horizontal length-scale below 200 km, while all observations are mostly informative for length-scales above 200 km. The results from two diagnostics, namely the variance reduction and the Degrees of Freedom for Signal (DFS), are compared and found to be largely similar. The variance reduction appears to be an interesting diagnostic to improve the understanding of how observations are used.

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