The 2020 Global Operational NWP Data Assimilation System at Météo-France
Berre, Loïk ; Bénichou, Hervé ; Chambon, Philippe ; Girardot, Nicole ; Guidard, Vincent ; Loo, Cécile ; Mahfouf, Jean-François ; Moll, Patrick ; Payan, Christophe ; Raspaud, Dominique
The main features of the 2020 version of global Numerical Weather Prediction (NWP) model Action de Recherche Petite Echelle Grande Echelle (ARPEGE) ARPEGE run operationally at Météo-France are described. This spectral model, developed in collaboration with the Integrated Forecasting System (IFS) of ECMWF, has a tilted and rotated horizontal grid that allows to reach a resolution of 5 km over Europe. The initial conditions are provided by an incremental 4D-Var data assimilation system with a 6-hour time window. Two inner-loops are performed respectively at 100 and 40 km. A comprehensive set of observations is assimilated with a dominance of satellite data representing 90% of them. However in terms of information content, conventional observations reach a fractional value of 20%. A 50-member ensemble data assimilation system based on low resolution 4D-Var is used to estimate daily background error covariances. The most recent improvements on this system regarding model resolutions, ensemble size and observation usage, that took place between mid-2019 and mid-2020, are presented with a selection of evaluations in terms of analysis and forecast skill scores.</p>
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