Evaluation and Selection of the CMIP6 Climate Model over Ethiopia

Abstract

Model simulation accuracy is essential for understanding climate change and its socioeconomic effects. Twenty global climate models that were a part of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were assessed in this study. The main goal was to assess and determine which models performed best in capturing rainfall patterns over Ethiopia between 1981 and 2014. The Correlation Coefficient (CC), Root Mean Square Error (RMSE), and PBIAS were used to evaluate the performance of CMIP6-GCM. The findings showed that the majority of CMIP6 models mostly reproduced the features of the ENACTS climatology pattern for total rainfall. Furthermore, rainfall over the study area was underestimated in six out of twenty CMIP6 models. The models that overestimate rainfall the most are MRI-ESM2-0, INM-CM4-8, and CESM2_WACCM, whereas the models that underestimate rainfall the most are CNRM-ESM2-1, ACCESS-CM2, and MPI-ESM1-2-LR. Every model has a correlation coefficient that falls between 0.6 and 0.99. The top six models with greater correlation coefficient (CC) values and higher performance out of 20 are the MPI-ESM1-2-LR (0.99), BCC-CSM2-MR (0.98), MIROC-ES2L (0.96), NorESM2-MM (0.96), and EC_Earth3_CC (0.96). All models, except IITM-ESM and MRI-ESM2-0, have root mean square errors below 5mm, strong correlation with ENACTS values, PBIAS range -3.94-4.3, and RMSE and PBIAS values near optimal 0. The significance of determining the optimal performance models for extreme rainfall events over the study area, both now and in the future, is underscored by these findings.