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The fidelity of 28 CMIP5 models and their multimodel mean (MMM) in simulating the historical climate of Africa is assessed in this study. For the historical period of 1975–2005, the spatial distribution of the seasonal precipitation is simulated with pattern correlation coefficients (PCCs) of 0.91, 0.95, 0.94, and 0.95 for March–May (MAM), June–August (JJA), September–November (SON), and December–February (DJF) seasons, respectively, when compared with the CRU data. For the surface temperature, the PCCs are 0.96, 0.98, 0.83, and 0.97, respectively, for the four seasons mentioned in the preceding. The root mean square error (RMSE) for the precipitation are 0.86, 0.77, 0.97, and 1.05 mm day−1 for the MAM, JJA, SON, and DJF seasons, respectively, whereas for the temperature, the respective values are 1.64, 1.28, 1.68, and 1.87°C. The study also assesses the performance of the models over four sub‐regions of Africa, viz. North, South, East, and West Africa. The observational trends show large spatial heterogeneity in warming for each season. The MMM does not show the strong warming over Africa and simulate generally a weak warming over most of the region. The MMM fails to capture the sign and magnitude of the observed precipitation trends.

In this study we evaluate the reliability of the Regional Climate Model (RegCM4.6) by performing several sensitivity tests at 50 km horizontal resolution using 10 convection schemes or combination of convection schemes. Emphasis on model output is made for the September-October-November 2017-2019 seasonal period.Part of the Central African region, five sub-regions, was identified. The simulated temperatures are compared to the daily climatology of near-surface temperature of the European Centre for Medium-Range Weather Forecasts Reanalysis fifthgeneration and the National Center for Environmental Prediction datasets, while the simulated precipitations are compared to the precipitation of the Global Precipitation Climatology Project and Climate Hazards Group Infrared Precipitation with Stations datasets. In most analyses, the Grell scheme with Arakawa-Schubert closure assumption tends to have the best index of agreement but its spatial distribution shows underestimation of rainfall. Generally, the Emanuel convection scheme is more suitable to represent rainfall and temperature over Central Africa. Compared to our previous study (Komkoua Mbienda et al., International Journal of Climatology, 2017, 37, 328-342), the present study shows that we have to pay attention to the choice of convective scheme when using any version of RegCM4 released for climate study over Central Africa. This choice is strictly related to the RegCM version released, the study years and the season. It is important to note, however, that the results presented are a preliminary study of the response to the selected convection schemes. The analysis uses a limited sample of climate model simulation (three model years for each convection scheme). Follow-up work, featuring longer duration climate simulations and a full assessment of statistical significance, is therefore required to confirm the robustness of the analysis presented.

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Interannual variability of the precipitation over West Africa Sahel is analyzed based on 32 years (1979-2010) from monthly and daily database of the Global Precipitation Climatology Project (GPCP). In this region, we found that there is a link between the West Africa Monsoon (WAM) and the daily means of the precipitation in the summer, unseasonal rains can occur in the transition seasons and even in the heart of the dry season. Rainfall is the most important element for agro-pastoral activities in this region. The 850-hPa wind and wind divergence structure show a maximum convection over Mountain region (Fouta-Djalon and Mont-Cameroon) which corresponds to the high precipitation and OLR observed in these regions. The trend and empirical orthogonal function (EOF) of the precipitation are presented, including the mid-July variability of the precipitation. The dominant EOF of GPCP precipitation accounts for around 25.3% of the variance with slightly large amplitude in the north while relatively small in the equatorial band respectively. The second and third EOF which accounts for 20.5% and 14%, describes a longitudinal contrast with a zonal gradient.