In this article, we evaluate the predictions of the French cloud-resolving model AROME using a set of high-resolution (5 km) simulations that focus on the well documented African Monsoon Multidisciplinary Analysis (AMMA) period of 23–28 July 2006 over a large domain (0–22°N, 15°W–20°E). The model skill is assessed against independent Global Positioning System observations of precipitable water and in terms of quantitative precipitation forecasts. As the rain-gauge network is sparse over West Africa, the simulated precipitation fields were compared with data from satellite-based precipitation products (TRMM-3B42). We show that initial and boundary conditions significantly improve the AROME forecasts when the large-scale forcing model (ARPEGE) assimilates surface-sensitive observations from microwave remote-sensing sensors over land surface.
The daily mean AROME precipitation shows a spatial distribution in good agreement with the satellite precipitation estimates. The intertropical convergence zone is correctly reproduced in terms of shape and location but its intensity is broadly overestimated by about 25%. The AROME model is shown to be able to reproduce all regimes, from light rain to the biggest Mesoscale Convective Systems (MCSs). The observations made at the Niamey AMMA supersite allow a detailed evaluation. Near the Niamey AMMA supersite, we show that AROME is able to represent most of the key features of the West African monsoon from the diurnal to synoptic scales. The life cycle of two successive sequences of MCSs associated with an African easterly wave and a deep monsoon burst are well captured by AROME.
Finally, a tracking approach based on the 1 h accumulated precipitation is applied to both Global Satellite Mapping of Precipitation (GSMaP) satellite estimates and to AROME and ARPEGE forecasts, allowing a good characterization of each MCS and statistics. Contrary to ARPEGE, the AROME MCSs trajectories and lifetimes, and the diurnal cycles of their initiation and dissipation, are in agreement with the GSMaP tracking and previous MCS statistics.
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