Abstract/Summary

Reliable and accurate weather forecasts have the potential to improve living conditions in densely populated southern West Africa (SWA), in particularly those of rainfall and its extremes. A limited availability of observations has long impeded a rigorous evaluation of current state‐of‐the‐art forecast models. The field campaign of the Dynamics‐Aerosol‐Chemistry‐Cloud Interactions in West Africa (DACCIWA) project in June‐July 2016 has created an unprecedentedly dense set of measurements from surface stations and radiosondes. Here we present results from a comprehensive evaluation of both numerical model forecasts and satellite products using these data on a regional and local level. Results reveal a substantial observational uncertainty showing considerable underestimations in satellite estimates of rainfall and low‐cloud cover with little correlation at the local scale. Models have a dry bias of 0.1–1.9 mmday−1 in rainfall and too low column relative humidity. They tend to underestimate low clouds, leading to excess surface solar radiation of 43 Wm−2. Remarkably, most models show some skill in representing regional modulations of rainfall related to synoptic‐scale disturbances, while local variations in rainfall and cloudiness are hardly captured. Slightly better results are found with respect to temperature and for the post‐onset rather than for the pre‐onset period. Delicate local features such as the Maritime Inflow phenomenon are also rather poorly represented, leading to too cool, dry and cloudy conditions at the coast. Differences between forecast days 1 and 2 are relatively small and hardly systematic, suggesting a relatively quick error saturation. Using explicit convection leads to more realistic spatial variability in rainfall, but otherwise no marked improvement. Future work should aim at improving the subtle balance between the diurnal cycles of low clouds, surface radiation, the boundary layer and convection. Further efforts are also needed to improve the observational system beyond field campaign periods.