Multi-model ensemble of CMIP6 projections for past and future climate change on mean precipitation and temperature

High-resolution climatic Projections are increasingly essential for informed decision-making and efficient adaptation and mitigation planning, especially in climatically sensitive regions such as the Baro River sub-basin in Ethiopia. This study applied station observation data with systematic bias correction utilizing quantile mapping. Historical and future climate trends were analyzed using multi-model ensembles from high-resolution Coupled Model Intercomparison Project phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). The non-parametric Mann–Kendall test and Sen’s Slope estimator were used to detect trends in the 21st century. Historical records (1986–2014) reveal a distinct seasonal rainfall pattern, with peak rainfall occurring in July and August. Projections for the late 21st century (2081–2100) suggest significant increases in mean monthly rainfall by 20.6% (159.1 mm/month) under SSP2-4.5 and by 46.7% (193.5 mm/month) under SSP5-8.5 compared to the historical baseline (132.0 mm/month). Station-level analysis reveals pronounced spatial variability, with substantial increases in rainfall at Lare (+ 129.99%) and Gambella (+ 103.09%) under SSP5-8.5, while other stations show slight increases or even negative trends. Mean annual temperatures are projected to rise by up to 7.16% (reaching 23.69 °C) under SSP2-4.5 and by 18.83% (up to 26.27 °C) under SSP5-8.5, with anomalies reaching as high as 6 °C by the end of the century. Probability density function analysis indicates a shift toward greater variability and more extreme events, mostly under SSP5-8.5. Rainfall distributions exhibit increasing bimodality, while temperature distributions demonstrate widening, indicating a higher likelihood of extreme drought and extreme hot and wet years. These findings emphasize how vulnerable the Baro River Sub-Basin is to hydro-climatic extremes and highlight the urgent need for emissions mitigation and developing strong, tailored adaptation strategies for the area.