Projection of Climate Extreme Indices Based on Representative Concentration Pathways (RCP) in Aceh Province

Abstract

Representative Concentration Pathways (RCP) scenarios are based on assumptions about the future development of radiative forcing. There are 4 RCP scenarios, but only 2 RCP scenarios are used in this study, RCP 4.5 and RCP 8.5. The aims are to identify characteristics and percentage changes in extreme climate indices in the future. CMIP5 model data such as CCSM4, IPSL-CM5A-LR, IPSL-CM5A-MR, IPSL-CM5B-LR and NorESM1-M were used. The model data was downscaled using a statistical method, and bias correction was based on observational data from five BMKG stations in Aceh Province for the historical period (2001-2005). Subsequently, the observation data and bias-corrected model data for extreme climate events were identified based on the Expert Team on Climate Change Detection and Indices (ETCCDI). The extreme climate indices utilized in this study are consecutive rainy days (CWD), consecutive dry days (CDD), total annual rainfall (Prcptot), monthly maximum temperature (TXx), and monthly minimum temperature (TNn). The results show that the CDD, Prcptot, TXx and TNn climate indices tend to increase in 2021 – 2100 periods. Meanwhile, the CWD decreased. Based on the historical period, all extreme climate indices increased significantly in 2021 - 2100 except TXx, which decreased in 2021 – 2040.