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This paper used the International Centre for Theoretical Physics (ICTP) Regional Climate Model, Version 3 (RegCM3) and rain gauge data selected from the Ghana Meteorological Agency (GMet) from 1990 to 2008 to investigate the extent and nature of variability in the annual rainfall and pattern of the raining seasons in Ghana. In the study, six meteorological stations selected from three rainfall distribution zones according to the divisions of the GMet were used to study the pattern of rainfall and its departure from the normal trend. The study also assessed the performance of the RegCM3 simulation with reference to the observed gauge data. Results confirmed the unimodal nature of the rainfall annual cycle over the northern belt and bi-modal rainfall nature over the middle and southern belts of Ghana. Negative departures of rainfall implying consistent downward trend were observed at all the stations. Our analysis showed that RegCM3 captured the average rainfall over Ghana but demonstrated an underestimation as compared to the observed gauge data. The model also had difficulty stimulating the departures accurately in direction and in magnitude in all the stations except for Accra where RegCM3 simulated the right direction of the departures.

We evaluate the capability of 21 models from the new state-of-the-art Coupled Model Intercomparison Project, Phase 6 (CMIP6) in the representation of present-day precipitation characteristics and extremes along with their statistics in simulating daily precipitation during the West African Monsoon (WAM) period (June–September). The study uses a set of standard extreme precipitation indices as defined by the Expert Team on Climate Change Detection and Indices constructed using CMIP6 models and observational datasets for comparison. Three observations; Global Precipitation Climatology Project (GPCP), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Tropical Applications of Meteorology using SATellite and ground-based observation (TAMSAT) datasets are used for the validation of the model simulations. The results show that observed datasets present nearly the same spatial pattern but discrepancies in the magnitude of rainfall characteristics. The models show substantial discrepancies in comparison with the observations and among themselves. A number of the models depict the pattern of rainfall intensity as observed but some models overestimate the pattern over the coastal parts (FGOALS-f3-L and GFDL-ESM4) and western part (FGOALS-f3-L) of West Africa. All model simulations explicitly show the pattern of wet days but with large discrepancies in their frequencies. On extreme rainfall, half of the models express more intense extremes in the 95th percentiles while the other half simulate less intense extremes. All the models overestimate the mean maximum wet spell length except FGOALS-f3-L. The spatial patterns of the mean maximum dry spell length show a good general agreement across the different models, and the observations except for four models that show an overestimation in the Sahara subregion. INM-CM4-8 and INM-CM5-0 display smaller discrepancies from their long-term average rainfall characteristics, in terms of extreme rainfall estimates than the other CMIP6 datasets. For the frequency of heavy rainfall, TaiESM1 and IPSL-CMGA-LR perform better when compared with observational datasets. MIROC6 and GFDL-ESM4 displayed the largest error in representing the frequency of heavy rainfall and 95th percentile extremes, and therefore, cannot be reliable. The study has assessed how rainfall extremes are captured in both observation and the models. Though there are some discrepancies, it gives room for improvement of the models in the next version of CMIP.