Added value of very high resolution climate simulations over South Korea using WRF modeling system

This study investigates the added value of very high resolution in long-term climate simulations over South Korea using the Weather Research and Forecasting (WRF) model. A one-way double-nested modeling system consisting of a mother domain (20-km resolution) and nested domain (5-km resolution) is customized for simulating the distinct climatological patterns in Korea, where the region-specific climate is largely influenced by the area’s complex geographical features. The ERA-Interim reanalysis data are used for the initial and boundary conditions, and the simulation spans the period from December 1, 1985 to December 31, 2005 (20-year analysis period with 1-month spin-up). Simulations from both the mother and the nested domain show reasonable performance in capturing the general characteristics of summer temperature and precipitation in terms of temporally and spatially averaged quantities. However, the added value from the nested domain with its higher resolution is apparently found in the reproduction of the intensity and frequency of extreme events and in the physical realism related to the partitioning of convective and large-scale precipitation. The nested domain not only better resolves the sharp gradients of temperature variation over short distances but also substantially reduces the systematic cold bias seen in temperature extremes produced by the mother domain. Furthermore, the nested domain is better able to simulate the upper tail of precipitation distributions and thus of extreme events. The higher resolution also improves the simulation of partitioning between convective and large-scale precipitation, leading to a plausible relationship between extreme precipitation and temperature and showing good agreement with in situ observation. Given the different behaviors of convective and large-scale precipitation in response to temperature changes, their realistic partitioning in the model has important potential for enhancing the reliability of precipitation projection under global warming.