This study evaluates the ability of three Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) to simulate the characteristics of rainfall pattern during the West Africa Summer Monsoon from 1998 to 2008. The seasonal climatology, annual rainfall cycles, and wind fields of the RCMs output were assessed over three homogenous subregions and validated using precipitation data from eighty-one (81) ground observation stations and TRMM satellite data. Furthermore, the ability of the RCMs to simulate response to El Nino and La Nina events was assessed. Results show that two of the RCMs (RCA and REMO) simulated the main features of the rainfall climatology and associated dynamics over the three subregions (Guinea Coast, Savannah, and Sahel) of West Africa. The RCMs also capture the African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ) with little variations in position and intensity. Analysis shows significant biases in individual models depending on subregion and season under consideration which may be attributed to strong cyclonic circulation observed at 850 mb pressure level. In general, the study shows RCA and REMO fairly simulate West Africa rainfall adequately and can therefore be used for the assessment of West African Summer Monsoon and future climate projections.

The study presents observed changes in climate extremes using daily precipitation and temperature data over 24 stations, covering the three climatic zones (Guinea coast, Savannah and Sahel) of Nigeria for the period 1971–2013. The data were homogenized with Expert Team on Climate Change Detection Indices (ETCCDI) RHtests version 4 software. RClimDex version 1.0 software was used to calculate 17 of the ETCCDI recommended precipitation and temperature extreme indices. The spatio‐temporal variation in the observed trends was analysed over each of the climatic zone. Results show a significant increase in the frequencies of warm spell, warm days and nights and decreasing cold spell, cold days and nights over the three climatic zones. A significant increase in annual total precipitation was found in some stations across the Guinea coast and Sahel zones. Changes in consecutive dry days and consecutive wet days are non‐significant in most stations. Also, a significant increase in extremely wet days was observed in a few stations across the three climatic zones. The implication of the observed warming could, however, result in thermal discomfort of lives in areas with significant positive trends. This could also exert pressure on the economy's power sector, as energy demand for cooling will increase. The increase in total annual precipitation will potentially be favourable for hydropower generation and increase the availability of the potable water supply for both industrial and domestic uses in the country. However, the increase in consecutive dry days and the decrease in consecutive wet days are dangerous for agricultural practices and, hence, food security.

A 2-month (August–September) regime of the year 2007 West African monsoon (WAM) was simulated with 27 physics combinations using the Weather Research and Forecasting model at 20-km horizontal grid. The objective is to examine WAM sensitivity to parameterization of microphysical, convective, and boundary layer processes for long-term simulation. The model precipitation was evaluated against the TRMM, CMORPH, and GPCP satellite rainfall products. The surface temperature was compared against the ERA-Interim, NCEP, MERRA, and global surface air temperature, an ensemble of the three reanalysis datasets. Model skill score (MSS) computed from a synthesis of the normalized correlation coefficient, mean bias, and mean absolute error was used to rank the model performance. Results show the model adequately simulates the diurnal cycles of surface temperature than precipitation, as well as the westward propagation of intense precipitation associated with the African easterly waves. The new Grell-Freitas (nGF) cumulus parameterization scheme (CPS) outperforms its predecessor especially when combined with the Mellor-Yamada-Nakanishi-Niino 2.5 (MYNN) planetary boundary layer scheme. The new simplified Arakawa-Schubert (nSAS) and Tiedtke CPSs produced better simulation of precipitation and surface temperature, respectively. The simulation of observed peak of diurnal precipitation in nSAS and nGF highlights success made towards a more realistic representation of convective processes by the schemes. Goddard microphysics and MYNN performed better for both variables. Based on the MSS, some relatively good and poorly performing combinations for precipitation and surface temperature were identified. The optimal combinations are however not separated in a statistically significant way and, thus, could be used for long-term simulation of WAM.

Understanding the variability of rainfall is important for sustaining rain-dependent agriculture and driving the local economy of Nigeria. Paucity and inadequate rain gauge network across Nigeria has made satellite-based rainfall products (SRPs), which offer a complete spatial and consistent temporal coverage, a better alternative. However, the accuracy of these products must be ascertained before use in water resource developments and planning. In this study, the performances of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Precipitation estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Tropical Applications of Meteorology using SATellite data and ground-based observations (TAMSAT), were evaluated to investigate their ability to reproduce long term (1983–2013) observed rainfall characteristics derived from twenty-four (24) gauges in Nigeria. Results show that all products performed well in terms of capturing the observed annual cycle and spatial trends in all selected stations. Statistical evaluation of the SRPs performance show that CHIRPS agree more with observations in all climatic zones by reproducing the local rainfall characteristics. The performance of PERSIANN and TAMSAT, however, varies with season and across the climatic zones. Findings from this study highlight the benefits of using SRPs to augment or fill gaps in the distribution of local rainfall data, which is critical for water resources planning, agricultural development, and policy making.