The Genale Dawa River Basin (GDRB) in southeastern Ethiopia is highly vulnerable to climate variability. However, limited research has examined how well the latest CMIP6 climate models simulate key climate variables in this complex, data-scarce region. This study evaluates 12 CMIP6 Global Climate Models (GCMs) in reproducing historical precipitation, maximum temperature (Tmax), and minimum temperature (Tmin) over the GDRB for 1985-2014, and projects future changes for 2021-2050 and 2051-2080 under SSP2-4.5 and SSP5-8.5 scenarios. Observational data from ENACTS and 60 ground-based stations were used to validate model outputs, which were resampled to 0.05° × 0.05° resolution and bias-corrected using quantile mapping. Model performance was evaluated using Mean Bias Error (MBE), Root Mean Square Error (RMSE), Pearson correlation, and Taylor Skill Score (TSS). The multi-model ensemble (MME) outperformed individual GCMs, achieving TSS values of 0.80 for precipitation, 0.98 for Tmax, and 0.99 for Tmin. Among individual models, CNRM-CM6-1 performed best for precipitation, GFDL-CM4 and NorESM2-MM for Tmax, and FGOALS-g3 and MRI-ESM2-0 for Tmin. Most models reproduced observed spatial and temporal patterns well but showed a systematic cold bias in Tmin, while Tmax was more accurately simulated. Under the SSP5-8.5 mid-century scenario, Tmax and Tmin are projected to increase by about 1.8 °C, and precipitation by 11.1% (5.4 mm). These findings demonstrate the value of ensemble-based projections and robust model evaluation for improving climate risk assessment and adaptation planning in the GDRB.
Fetene Muluken Chanie (Thu,) studied this question.