High-Resolution Projections of Future Climate and Extremes over South Korea Using Statistically Downscaled CMIP6 Ensembles

Climate change is expected to alter climate conditions and increase the frequency and intensity of climate extremes, with implications for hydrological systems. Reliable high-resolution future climate datasets are needed to support regional assessments of hydrological change. However, developing such datasets remains challenging because generating high-resolution projections from large CMIP6 ensembles can be computationally demanding, limiting the number of GCMs included. This study develops statistically downscaled 1/16° future climate datasets for South Korea using 16 CMIP6 GCMs under the SSP2-4.5 and SSP5-8.5 scenarios. We use the Hybrid Delta (HD) statistical downscaling method with long-term observation-based high-resolution datasets as a reference. The HD method integrates projected changes in climate distributions with observed temporal structures and spatial characteristics, preserving historical variability while representing future changes in mean conditions and extremes. Temperature projections indicate persistent warming, with uniform summer warming and greater winter warming over the northwestern region under the high-emission scenario. Precipitation shows greater spatial and seasonal heterogeneity than temperature, while 20-year return period extreme precipitation is projected to intensify. These results indicate substantial future changes in climate conditions and extremes that may influence hydrological responses and water-related risks. The dataset provides spatially detailed, temporally consistent climate forcing for hydrological modeling and water resources assessment.