Analyzing the spatiotemporal distribution of Climate Extreme Indices under CMIP6 Climate Model over the Upper Blue Nile Basin, Northwestern Ethiopia

Climate change is anticipated to increase the frequency and severity of extreme occurrences worldwide. The study was aimed to analyzing climate extreme indices using the Coupled Model Inter-comparison Project Phase six (CMIP6) model under socioeconomic pathways (SSPs) over the Upper Blue Nile Basin, Ethiopia. Observed and projected CMIP6 precipitation and temperature data were analyzed under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. For this study, power transformation and distribution mapping bias correction methods were applied. This study utilized Sen's slope and Mann-Kendall (MK) trend test to assess the trends in extreme temperature and rainfall indices. The study also used 15 rainfall and temperature extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). The result indicated that INM-CM5-0 and INM-CM4-8 models performed best for precipitation and temperature, respectively. Extreme temperature indices revealed that there was a significant decreasing trend in the frequency of cool days (TX10p) and cool nights (TN10p) at (p < 0.05 and p < 0.01) significance level, respectively. The finding also shows there was a positive significant (p < 0.001) increasing trend in warm days (TX90p) and warm nights (TN90p). Additionally, rainfall indices showed there was a significant (p < 0.001) increasing trend in heavy (R10) and very heavy precipitation (R20 and R25) in the study area. Hence, the communities should practice efficient water management practices to adapting the projected increase in heavy and very heavy precipitation events and shift towards more climate-resilient crop varieties.