The characteristics of the main components of the water cycle over Equatorial Central Africa (ECA) were analysed using the 32-year period, spanning from 1968 to 2000, of the National Centers for Environmental Prediction-National Censearch (NCEP-) reanalysis project database. A special emphasis was given to identifying the causes of annual and interannual variability of water vapor flux and precipitation recycling. The results suggest that the first maximum of moisture convergence, during the rainy season MAM, comes from upper level moisture flux, related to the north component of the African Easterly Jet (AEJ-N). The second, and greatest, maximum in SON is found to be a consequence of low level moisture advection from the Atlantic Ocean. AEJ-N also drive the seasonal spatial pattern of moisture flux. The interannual variability of moisture flux is contributed mainly by the low level moisture advected from the Atlantic Ocean, underlying its crucial role for the regional climate. Studying the recycling ratio in ECA as a whole shows a low annual cycle whereas subregional scale analysis reveals high amplitude of the seasonal variation. Seasonal variability of the spatial gradient of precipitation recycling is regulated by both moisture flux direction and strength. The annual cycles of recycling ratio in the North and the South of ECA are regulated by both moisture transport and evapotranspiration.

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With the recurrence of extreme weather events in Central Africa, it becomes imperative to provide high-resolution forecasts for better decision-making by the Early warning systems. This study assesses the performance of the Weather Research and Forecasting (WRF) model to simulate heavy rainfall that affected the city of Douala in Cameroon during 19–21 August 2020. The WRF model is configured with two domains with horizontal resolutions of 15 and 5[Formula: see text]km, 33 vertical levels using eight cumulus parameterization schemes (CPSs). The WRF model performance is assessed by investigating the agreement between simulations and observations. Categorical and deterministic statistics are used, which include the probability of detection (POD), the success ratio (SR), the equitable threat score (ETS), the pattern correlation coefficient (PCC), the root mean square error (RMSE), the mean absolute error (MAE), and the BIAS. K-index is finally used to assess the capacity of the WRF model to predict the instability of the atmosphere in Douala during the above-mentioned period. It is found that (1) The POD, SR and ETS decrease when the threshold increases, showing the difficulty of the WRF model to predict and locate heavy rainfall events; (2) There are important differences in the rainfall area simulated by the eight CPSs; (3) The BIAS is negative for the eight CPSs, implying that all of the CPSs tested underestimate the rainfall over the study area; (4) Some of the CPSs have good agreement with observations, especially the new modifed Tiedtke and the Betts–Miller–Janjic schemes; (5) The K-index, an atmospheric instability index, is well predicted by the eight CPSs tested in this work. Overall, the WRF model exhibits a strong ability for rainfall simulation in the study area. The results point out that heavy rainfall events in tropical areas are very sensitive to CPSs and study domain. Therefore, sensitivity tests studies should be multiplied in order to identify most suitable CPSs for a given area.

The propagation of radio electric waves emitted from ground-based meteorological instruments is determined through stratification of the atmosphere. In super-refractive cases characterized by strong temperature inversions or strong vertical moisture gradients, the radar beam can be deflected towards the ground (trapping). This phenomenon often results in spurious returned echoes and misinterpretation of radar images such as erroneous precipitation, wind, and temperature detection. In this study, a 5-year Central and West Africa (CWA) climatology of the frequency of super-refractive and trapping-layer base height has been produced using refractivity computations from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses at a 40-km horizontal resolution and 60 levels in the vertical direction. The aim of this climatology is to improve the understanding on how frequent such anomalous propagations conditions are, which is a prerequisite for fully benefiting from radar data information for the multiple purposes of model validation, precipitation analysis, and data assimilation. First, the main climatological features are summarized for the whole CWA: Sahara and inlands seldom experience super-refraction, whereas coastal areas are strongly affected, especially in regions where the temperature inversion and the trade winds are intense lying near the surface. Over land, seasonal averages of super-refraction frequencies reach 80% (40%) over moist areas year-round but remain below 40% (15%) in most other regions. Seasonal statistics exhibit a pronounced diurnal cycle of super-refraction occurrences, with averaged frequencies peaking at 60% in summer late afternoon over the areas located on the Atlantic Ocean border but inlands region are less affected with super-refractive cases by midday.

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