Evaluation of CMIP6 Global Climate Models for Rainfall Simulation Across Agro-Ecological Zones of Ethiopia

Abstract

Rainfall is one of the most critical climatic variables for investigating the impacts of climate change. Global Climate Models (GCMs) are widely used tools for examining changes in the climate system and projecting future climate scenarios. This study evaluated the performance of Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models in simulating rainfall climatology over Ethiopia. Eight CMIP6 GCMs were assessed at daily, monthly, and annual timescales across five Agro-Ecological Zones (AEZs) of Ethiopia for the period 1995–2014, using station observations as reference data. Model performance was evaluated using Root Mean Square Error (RMSE), Percent Bias (PBIAS), and Pearson’s correlation coefficient (r). Each model was ranked using the Comprehensive Rating Index (CRI). The results showed that model performance varied considerably for daily to annual rainfall totals across the AEZs, with both overestimation and underestimation observed. For daily rainfall, EC-Earth3-Veg performed best in tropical, subtropical, and temperate AEZs; MRI-ESM2-0 performed best in the desert AEZ; and MPI-ESM1-2-LR performed best in the alpine AEZ. BCC-CSM2-MR performed well across tropical, subtropical, temperate, and alpine AEZs, while MRI-ESM2-0 performed better in desert AEZs. For annual rainfall, MRI-ESM2-0 was superior in desert and tropical AEZs, BCC-CSM2-MR performed best in temperate and alpine AEZs, and EC-Earth3-Veg performed best in the subtropical AEZ. EC-Earth3 was the least effective at reproducing mean monthly rainfall. Overall, the models’ performance was inconsistent across timescales and regions. Given the spatial and temporal variability in CMIP6 GCM performance, it is recommended that models be thoroughly evaluated and bias-corrected for specific locations and intended applications, particularly regarding their ability to simulate Ethiopia’s diverse rainfall regimes.