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This research focuses on the estimation of extreme precipitation quantiles using climate change scenario data from the 6th Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC). The study involved the analysis of precipitation data from 23 global climate models (GCMs), with a final selection of 10 models that best represented the characteristics of extreme precipitation in South Korea, based on statistical measures against observed rainfall data. Particularly, precipitation data from 71 observation points within the Chungju-Dam basin, a region of hydrological significance and susceptibility to extreme weather events, were collected for analyzing climate change impacts. Furthermore, the study conducted the regional frequency analysis (index-flood method) to estimate rainfall quantiles, employing the Generalized Extreme Value (GEV) distribution and L-moment method for parameter estimation. The analysis resulted in the development of a multi-model ensemble (MME) incorporating the 10 selected GCMs and 4 Shared Socioeconomic Pathways (SSP) scenarios. This approach facilitated a comprehensive understanding of potential future climate changes, considering emission trajectories and socio-economic changes. Additionally, the study quantitatively evaluated the impact of climate change and associated uncertainties in the region, which is essential for devising adaptation and mitigation strategies in response to climate change conditions, particularly in areas susceptible to extreme weather events. This research provides valuable insights into the understanding of climate-induced extreme weather events and offers guidance for policymakers and environmental planners in preparing for the impacts of global climate change.
Kim et al. (Sat,) studied this question.