This paper investigates the performance of 10 Regional Climate Models (RCMs) hindcasts from the Coordinated Regional Climate Downscaling Experiments (CORDEX) over Central Africa, covering the period 1998–2008 and performed over a common model grid spacing 0.44° ( ∼50 km). Multiple observational data sets are used to evaluate model performances over four targeted subregions. Throughout the work, a measure of observational uncertainty is made and we discuss whether or not the models are found within or outside the range of observational uncertainty. Results indicate that RCMs generally capture rainfall and temperature basic features, though important biases exist and vary for models and seasons. Dry (wet) biases are common features over the Congo basin (northern and southern part of the domain). In terms of precipitation and temperature in both seasonal and annual scale, most RCMs along with their ensemble mean generally fall in the range of observational uncertainty. Furthermore, most RCMs show a good spread of grid points where the added value of RCMs is found although the added value in temperature is not as great as with precipitation. UC‐WRF is among models adding less value on ERAINT and this could explain why whatever the time scale of variability, UC‐WRF outputs are generally out from the observational uncertainty. The multimodel ensemble mean is generally found within observational range when most models are there as well. This highlights the fact that the ensemble mean, built from the equal treatment of RCMs, does not generally outperform individual RCMs realization as it is reported in several previous studies.

Although climate models are important for making projections of future climate, little attention has been devoted to model simulation of the complex climate of Central Africa (CA). This study investigates rainfall biases through processes in three versions of the Met Office Unified Model over CA with both coupled and atmosphere-only formulations for each version. The study shows that the models depict a wet (dry) bias over the eastern (coastal western) CA in the September-November season with the wet (dry) bias stronger in coupled (atmosphere-only) models. Here, we explore potential regional to large-scale

We evaluate and compare the simulation of the main features (low-level westerlies (LLWs) and the Congo basin (CB) cell) of low-level circulation in Central Equatorial Africa (CEA) with eight climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and the corresponding eight previous models from CMIP5. Results reveal that, although the main characteristics of the two features are reasonably well depicted by the models, they bear some biases. The strength of LLWs is generally overestimated in CMIP5 models. The overestimation is attributed to both divergent and rotational components of the total wind with the rotational component contributing the most in the overestimation. In CMIP6 models, thanks to a better performance in the simulation of both divergent and rotational circulation, LLWs are slightly less strong compared to the CMIP5 models. The improvement in the simulated divergent component is associated with a better representation of the near-surface pressure and/or temperature difference between the Central Africa landmass and the coastal Atlantic Ocean. Regarding the rotational circulation, and especially for HadGEM3-GC31-LL and BCC-CSM2-MR, a simulated higher 850 hPa pressure is associated with less pronounced negative vorticity and a better representation of the rotational circulation. Most CMIP5 models also overestimate the CB cell intensity and width in association with the simulated strength of LLWs. However, in CMIP6 models, the strength of key cell characteristics (intensity and width) are reduced compared to CMIP5 models. This depicts an improvement in the representation of the cell in CMIP6 models and this is associated with the improvement in the simulated LLWs.