Gaps remain in the comprehension of mechanisms triggering convection in central Africa. The effect of mid‐level dry entrainment to preclude deep convection is well established (Holloway & Neelin, 2009). Entrainment of environmental dry air reduces cloud droplet number concentration (Guo et al., 2015) and inhibits deep convection. In the early stage of the convection process, boundary layer turbulence generates shallow clouds that can be diluted by mixing with environmental dry air through entrainment. This prevents deep cloud formation and in turn delays the transition to deep convection (Khairoutdinov & Randall, 2006). Henceforth, the location of dry subtropical deserts over southern Africa and North Africa and associated equatorward mid‐level dry air advection by shallow meridional circulation (Longandjo et al., submitted) impede the triggering or reduce the strength of regional convection over central Africa. Pivotal work in the future should focus on better understanding of the characteristics of rainfall‐producing systems.
2.4 CLIMATE MODELING
There is an increasing number of recent studies using regional and global models to assess climate over central Africa (e.g., Aloysius et al.; 2016; Creese and Washington 2016, 2018; Dosio et al., 2019; Fotso‐Kamga et al., 2019; Haesnler et al., 2013; Sonkoué et al., 2018; Taguela et al., 2020; Tamoffo et al., 2019; Tchotchou and Mkankam, 2010; Vondou and Haensler 2017; Washington et al., 2013). Using CMIP5 global models, Aloysius et al. (2016) reveal that skills of simulated temperature is better than those of rainfall. There is an important discrepancy in the climatology of rainfall appearing in the seasonality, spatial patterns, and magnitude of precipitation. Tamoffo et al. (2020) highlight the importance of monitoring moisture variables and strength of low‐level flow that transports moisture toward the central African region. The findings of a large ensemble of climate models convey dissimilarity but possible outlines for the rainfall change are owing to the contrasts of climatology features across models. In their investigation, Creese and Washington (2016) demonstrated that simulated precipitation depends on the penetration of the moisture in the Congo Basin, where CMIP5 models strongly disagree. They also call for reinforcement of observations for a better description of the processes interacting and also required to represent convection explicitly in models in the Congo Basin.
Taguela et al. (2020) show that models involved in the CORDEX‐Africa project are able to capture basic features of temperature and precipitation despite the persistence of local biases. In contrast to what is obtained in other African regions, the model ensemble mean does not always depict better results than individual simulation. This interesting fact highlights the reliability of model output, as already mentioned by Washington et al. (2013). Vondou and Haensler (2017) show that increasing model resolution is not always the way to proceed for the enhancement of climate simulation over central Africa, consistent with analysis of Wu et al. (2019). It was pointed out that model formulation mostly impacts precipitation production rather than refinement of resolution. However it is important to note that the amplitude of the diurnal cycle of precipitation is influenced by spatial resolution of the model. For the improvement of the regional model RCA4 to mimic precipitation over the Congo Basin, Tamoffo et al. (2019) use an ensemble of experiments based on moisture transport and regional circulation analysis. Henceforth, they raise the question of the credence of models over central Africa and highlight the fact that much effort should be given to the improvement of boundary layer representation and land‐atmosphere coupling. Another big problem models encounter in central Africa is representation of land–sea contrast. Vondou and Haensler (2017), using regional climate REMO, show that the model tends to overestimate rainfall over the ocean while simulating less precipitation over the Congo Basin in accordance with recent results of Fotso‐Kamga et al. (2019), when they analyzed COSMO model output. Misunderstanding of the central African climate engine can lead to poor mimicking of key regional processes, discrepancies in simulated precipitation, and in turn important unreliable information in the guidelines for the future climate (Cook & Vizy, 2019; Creese et al., 2019; Tamoffo et al., 2020).
2.5 CONCLUSION
The climate system in central Africa suffers from a lack of attention compared to other regions in Africa. A simplistic view of the annual rainfall regime over the region was adopted and associated with the north–south migration of the ITCZ, which suggests collocation of maximum temperature, low pressure, high cloudiness, and rainfall. This results from conjectures that were later found to be incorrect for the region. The wealth of regional studies over West Africa, East Africa, and southern Africa contributed to advances in the understanding of several mean climate features over the continent, which later on have shown importance for the climate regime over central Africa. In the effort to improve comprehension of the functioning of the central African climate, attempts to parallel other region concepts may be avoided as some climate features have shown differences in their interactions with the climate in central Africa and other regions (Cook, 2015). This may also prevent from misinformation, as was the case for the ITCZ concept.
A progressively clearer picture of the seasonal cycle over central Africa is emerging. Recent findings highlight lower‐level subsidence underneath areas of deep convection, which is mainly controlled by the mid‐tropospheric dynamics. This mid‐tropospheric dynamic is modulated by the mid‐level jets and shallow meridional cells over northern and southern central Africa, which are associated with heat lows over northern and southern Africa. Another progress is the contribution of Walker‐like circulation, with the lower‐level Congo Basin Cell controlling the location of maximum rainfall over eastern central Africa and the upper level Zonal Asymmetric Pattern. This suggests myriad feedbacks to shape the annual rainfall regime over central Africa. What controls lower‐level subsidence over central Africa and how these climate features contribute to the dynamic of mesoscale convective systems is unclear and merits further attention.
Central Africa borders on West Africa, East Africa, and southern Africa, which all have climate systems that benefit from a wealth of region‐specific studies. This fragmented approach contributed to the poor understanding of the central African climate. An integrated approach is required to provide an improvement in the understanding of central Africa’s climate as the region is influenced by features as Saharan heat low, Angola low, mid‐tropospheric easterly jets, and shallow meridional circulation driven by these lows. Lack of this integrated assessment in past studies (Hart et al., 2019) suggests that exploration of the manner in which the central, eastern, northern, and southern African climate systems are linked is crucial, thereby breaking the rigid regional view of the continent’s climate system. Climate models generally suffer from poor performance over central Africa compared to other regions in the continent. Indisputably, lack of knowledge on mechanisms driving central African climate significantly hampered efforts for model evaluation and exacerbates the issue of model deficiencies. However, the credibility of model projection relies on the plausibility of mechanisms driving changes. This underlines the need, while improving understanding of regional climate,