Assessment of Historical and Future Mean and Extreme Precipitation Over Sub-Saharan Africa Using NEX-GDDP-CMIP6: Part I—Evaluation of Historical Simulation

This study assesses the performance of 28 NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6) models and their multi-model ensemble (MME) in simulating mean and extreme precipitation across sub-Saharan Africa from 1985 to 2014. The Multi-Source Weighted-Ensemble Precipitation (MSWEP) and Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) are used as reference datasets. Various statistical metrics such as the mean bias (MB), spatial correlation coefficients (SCCs), Taylor skill scores (TSS) and comprehensive ranking index (CRI) are employed to evaluate the performance of NEX-GDDP-CMIP6 models at both annual and seasonal scales. Results show that the NEX-GDDP-CMIP6 can reproduce the observed annual precipitation cycle in all the subregions, with the model spread within observational uncertainties. The MME also successfully reproduces the spatial distribution of mean precipitation, achieving SCCs and TSSs greater than 0.8 across all subregions. The biases in mean precipitation are consistent across different reference datasets. However, most of the NEX-GDDP-CMIP6 models show trends of mean precipitation opposite to observations. While the MME can generally reproduce the spatial distribution of extreme precipitation, its performance varies with the reference dataset, particularly for the number of rainy days (RR1) and maximum consecutive dry days (CDD). TSS values for extreme precipitation indices differ significantly by region, reference data and index, with the lowest values over South Central Africa and the highest over West Southern Africa. The CRI indicates that no single model consistently outperforms others across all subregions, even within the same region, when compared to both MSWEP and CHIRPS. These results may be helpful when using NEX-GDDP-CMIP6 models for future projections and impact assessment studies in sub-Saharan Africa.