Uncertainty and Reliability Analysis of CMIP5 Climate Projections in South Korea Using REA Method

Weighting criteria methods achieved popularity in the quantification of uncertainty in the first decade of 21st century. In this study, Reliability Ensemble Averaging (REA) method is used to provide a quantitative estimate of uncertainty range and reliability of future climate projections over Han river basin in Korea simulated by 18 GCMs under CMIP5 Project. The root mean square error (RMSE) was used to measure uncertainty range. The result indicates that historical simulations project 43% decrease in precipitation while future scenarios simulations of GCMs projects a moderate increase in mean annual temperature and precipitation. The future projections showed a reduction in uncertainty range of about 150% as compared to simple ensemble average approach. The results suggest the viability of REA method by incorporating the model performance and model convergence criteria.