Statistical bias correction of regional climate model simulations for climate change projection in the Jemma sub-basin, upper Blue Nile Basin of Ethiopia

Abstract

This study evaluates bias correction methods and develops future climate scenarios using the output of a better bias correctiontechnique at the Jemma sub-basin. The performance of different bias correction techniques was evaluated using several statisticalmetrics. The bias correction methods performance under climate condition different from the current climate was also evaluatedusing the differential split sample testing (DSST) and reveals that the distribution mapping technique is valid under climatecondition different from the current climate. All bias correction methods were effective in adjusting mean monthly and annualRCM simulations of rainfall and temperature to the observed rainfall and temperature values. However, distribution mappingmethod was better in capturing the 90th percentile of observed rainfall and temperature and wet day probability of observedrainfall than other methods. As a result, we use the future (2021–2100) simulation of RCMs which are bias corrected usingdistribution mapping technique. The output of bias-adjusted RCMs unfolds a decline of rainfall, a persistent increase of temperature and an increase of extremes of rainfall and temperature in the future climate under emission scenarios of RepresentativeConcentration Pathways 4.5, 8.5 and 2.6 (RCP4.5, RCP8.5 and RCP2.6). Thus, climate adaptation strategies that can provideoptimal benefits under different climate scenarios should be developed to reduce the impact of future climate change.