Climate change in Africa: guide to global model and ensemble selection for regions 

Abstract

There are numerous general circulation models (GCMs) in the current Coupled Model Intercomparison Project (CMIP6) developed to simulate past climate and project future climate. With the available climate scenarios and climate variables, there are tens of thousands of possible simulations for future climate. However, due to cost and resource implications, researchers are often required to select specific models. Additionally, there is a need for downscaling climate products to regional levels so as to inform applicable climate change adaptation and natural resource management. In this study, I selected 23 models from the CMIP6 and analyzed their projections for 19 bioclimatic variables under the shared socio-economic pathway 2 "middle of the road" (SSP2-4.5) in the future period 2041-2060. I used hierarchical cluster analysis to classify the GCMs into five clusters according to the similarity in projections. I visualized and presented projected changes in the mean annual temperature and mean annual precipitation according to these clusters. I further visualized the models associated with the climate variables using principal component analysis. Finally, a model selection guide for “best”, “middle” and “worst” case scenario was presented to guide regional model selection for suitable purposes. The models selected had varying projections of the magnitude of change for mean annual temperature and mean annual precipitation however they all maintained the same direction of change. The models that projected the "best" case scenario for Africa in SSP2-4.5 in the period 2041-2060 were INM-CM5-0 and INM-CM4-8 whereas the hot and dry also the "worst" case scenario was projected by UKESM1-0-LL and HadGEM3-GC31-LL. Generally, the regions projected to have the hottest and driest climate were the Mediterranean, West-southern Africa and the Arabian peninsula. On the other hand, Central and Western Africa were projected to have comparably cool and wet climates.

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