Evaluating the performance of selected CMIP6 GCMs for simulations of historical temperature over Ethiopia
Year: 2026
Type: article
Abstract: This study evaluates the performance of seven Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and their Ensemble mean in reproducing historical maximum (Tmax) and minimum (Tmin) temperatures across five agro-ecological zones (AEZs) of Ethiopia during 1995–2014. The assessment covers daily to annual time scales using observational and GCM datasets. Model performance was evaluated using Percent Bias (PBIAS), Root Mean Square Error (RMSE), and correlation coefficient (r), while the Comprehensive Rating Index (CRI) was applied for ranking. Results show substantial spatial and temporal variability in model performance. For Tmax, the Ensemble mean and EC-Earth3-veg performed best at the daily scale, while EC-Earth3-veg, MPI-ESM1-2-LR and BCC-CSM2-MR excelled at the monthly scale across most AEZs. Seasonally, top-performing models included Ensemble mean, MPI-ESM1-2-LR and MRI-ESM2-0 during Bega (October-January), EC-Earth3-veg, CNRM-CM6-1 and Ensemble mean during Belg (February-May) and CNRM-CM6-1 and MPI-ESM1-2-LR during Kiremt (June-September). For Tmin, CNRM-CM6-1, BCC-CSM2-MR and Ensemble mean ranked highest at both daily and monthly scales in most AEZs. At the annual scale, MRI-ESM2-0, Ensemble mean, MPI-ESM1-2-LR and CNRM-CM6-1 excel for Tmax, while EC-Earth3-veg, BCC-CSM2-MR and Ensemble mean lead for Tmin across most AEZs. MIROC6 consistently exhibited the weakest performance for both Tmax and Tmin across most AEZs and time periods. Thus, the Ensemble mean of all evaluated models does not consistently rank among the top three performers across all AEZs and time scales. The identified best-performing CMIP6 models provide valuable tools for assessing climate change impacts and developing region-and time-specific adaptation strategies in Ethiopia. Given the variability in GCM performance across AEZs and time scales, national or large-scale studies would benefit from using the Ensemble mean derived from the best-performing models. This study provides crucial insights into the strengths and weaknesses of different GCMs, supporting evidence-based decision-making and enhancing efforts to build climate resilience and adaptation strategies in the region.
Authors: Alehegn Belay Tagele, Temesgen Gashaw Tarkegn, Pieter R. van Oel, Ram Lakhan Ray, Gebrekidan Worku Tefera, Sintayehu Fetene Demessie, Alemayehu Abate Shawul, Othoo Calvince Ouko, Daniel Berhanu, Amare Haileslassie, Abeyou W. Worqlul, Amare Bantider, Yihun T. Dile, Abebe D. Chukalla, Tazebew Abera Tadesse, Enyew Adgo
Institutions: Bahir Dar University, Prairie View A&M University, Wageningen University & Research, Haramaya University, Kotebe University of Education, Madda Walabu University, The Co-operative University of Kenya, Water and Land Resource Centre, Addis Ababa University, International Water Management Institute, International Center for Agricultural Research in the Dry Areas, Texas A&M University, IHE Delft Institute for Water Education
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W7128049630