Abstract
Understanding climate science is essential for effective policy development, adaptation, mitigation, and risk management. Given the inherent limitations in climate models, this study evaluates the performance of CORDEX Africa regional climate models to simulate precipitation and temperatures over the Melka-Wakena catchment. To accomplish this, the performance evaluation utilizes techniques such as multi-metric weighted ranking to select top-1 (best individual model), specific multi-model ensembles (top-N ensemble), multi-model ensemble, and average hybrid (top-N ensemble with MME) approaches at various temporal scales. Also, Taylor diagrams and empirical cumulative distribution functions are other useful elements for model comparison visualization. This study finds that, top-3 ensemble (for temporal scale tasmin, monthly pr), top-7 ensemble (monthly and seasonal tasmax), average hybrid (top-1 with MME (daily pr and tasmax), HadGEM2ES_RACMO22T for seasonal and yearly pr), and HadGEM2ES_RCA4 for yearly tasmax) are preferable, with weighted scores of 0.29, 0.44, 0.22, 0.20, 0.35, 0.40, 0.39, 0.33, 0.45, 0.25, and 0.33, respectively. In short, RCA4 and RACMO22T efficiently mimic air temperatures and precipitation in the Melka-Wakena catchment. While ensemble approaches are generally more resilient and possible, single-best-performing model approaches can be quite effective for long-term periods. Finally, these studies have an important implication for improving climate change assessment, adaptation, and mitigation measures.