Abstract
AbstractReliable and accurate weather forecasts, particularly those of rainfall and its extremes, have the potential to improve living conditions in densely populated southern West Africa (SWA). The 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 in rainfall and too low column relative humidity. They tend to underestimate low clouds, leading to excess surface solar radiation of 43 . 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.
Highlights
Many developing countries in the Tropics are strongly affected by variations in rainfall, temperature, wind and cloudiness, and have low resilience against weather extremes (e.g., Webster, 2013)
Söhne et al (2008) compared one month of forecasts using a regional model with 32 km grid spacing with satellite-derived brightness temperatures and found too many/too thick low clouds over southern West Africa (SWA), too low surface temperatures, a too shallow planetary boundary layer (PBL), reduced convective available potential energy (CAPE) and reduced deep convection in agreement with the negative feedback found in the sensitivity study by Kniffka et al (2019)
UK Met Office (UKMO) forecasts were provided in near-real time from the operational global numerical weather prediction (NWP) version of the Unified Model (Cullen and Davies, 1991; Wood et al, 2014), which is suitable for atmospheric prediction on a wide range of temporal and spatial scales (Brown et al, 2012)
Summary
Many developing countries in the Tropics are strongly affected by variations in rainfall, temperature, wind and cloudiness, and have low resilience against weather extremes (e.g., Webster, 2013). Söhne et al (2008) compared one month of forecasts using a regional model with 32 km grid spacing with satellite-derived brightness temperatures and found too many/too thick low clouds over SWA (between 5 and 10◦N), too low surface temperatures, a too shallow PBL, reduced convective available potential energy (CAPE) and reduced deep convection in agreement with the negative feedback found in the sensitivity study by Kniffka et al (2019) Their model showed overall sharper meridional gradients, a too fast monsoon flow, too little vertical mixing, limiting speed reduction and drying.
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