In this study, we investigated spatial and temporal changes in precipitation over the Coordinated Regional Climate Downscaling Experiment (CORDEX) East Asia domain, for present (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) and future (2031-2050) periods using the Regional Climate Model version 4 (RegCM4). Future meteorology produced by the Hadley Center Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) following global climate change scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5) was used as meteorological boundary conditions for the RegCM4. Six subregions (South Korea, North China, South China, Japan, Mongolia, and India) in the CORDEX East Asia domain were considered for analysis. The RegCM4 simulated spatial distributions of precipitation over East Asia with a correlation coefficient of 0.7 against Climate Research Unit data. The simulation skills of its temporal variability varied based on geographical regions and seasons, showing relatively poorer performance (underestimation in rainfall amount) in summer than in winter, in general. The future climate simulations by the RegCM4 presented that the East Asian continental regions will be warmer and more humid, leading to increased precipitation amounts, especially in the summer. The summer precipitation amount was projected to increase by about 5%, on average, over the East Asian domain, 5À15% in most subregions, and even higher (44% and 24%) in the South Korean region for the RCP 4.5 and 8.5 scenarios, respectively. It was also expected that heavy rainfall (> 50 mm/d) events may occur more frequently in the future possibly owing to meteorological changes that are favorable to convective heavy precipitation.

In this paper, the prediction skills of five ensemble methods for temperature and precipitation are discussed by considering 20 yr of simulation results (from 1989 to 2008) for four regional climate models (RCMs) driven by NCEP-Department of Energy and ECMWF Interim Re-Analysis (ERA-Interim) boundary conditions. The simulation domain is the Coordinated Regional Downscaling Experiment (CORDEX) for East Asia, and the number of grid points is 197 3 233 with a 50-km horizontal resolution. Three new performance-based ensemble averaging (PEA) methods are developed in this study using 1) bias, root-mean-square errors (RMSEs) and absolute correlation (PEA_BRC), RMSE and absolute correlation (PEA_RAC), and RMSE and original correlation (PEA_ROC). The other two ensemble methods are equal-weighted averaging (EWA) and multivariate linear regression (Mul_Reg). To derive the weighting coefficients and cross validate the prediction skills of the five ensemble methods, the authors considered 15-yr and 5-yr data, respectively, from the 20-yr simulation data. Among the five ensemble methods, the Mul_Reg (EWA) method shows the best (worst) skill during the training period. The PEA_RAC and PEA_ROC methods show skills that are similar to those of Mul_Reg during the training period. However, the skills and stabilities of Mul_Reg were drastically reduced when this method was applied to the prediction period. But, the skills and stabilities of PEA_RAC were only slightly reduced in this case. As a result, PEA_RAC shows the best skill, irrespective of the seasons and variables, during the prediction period. This result confirms that the new ensemble method developed in this study, PEA_RAC, can be used for the prediction of regional climate.

[1] The impact of boundary conditions (BCs) on simulations of precipitation characteristics using the Regional Climate Model version 4 (RegCM4) driven by two BCs (ERA-Interim: ERA, NCEP/DOE 2: R2) was investigated using 18 years (1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) of simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) East Asia region. The RegCM4 adequately simulated spatial distribution of precipitation over the East Asia region and its temporal variations, irrespective of the BC used. It overestimated precipitation over the central region of the model domain except for India and South Korea and underestimated precipitation over equatorial ocean regions. The RegCM4's simulation skills were better in winter than in summer regardless of the BC, which can be related to the low spatial resolution (50 km) of the model, but detailed simulations of precipitation are significantly impacted by the BCs, although the impact varies with geographical location and season. Driven by ERA, the RegCM4 reproduces more precipitation in the central inland region of the model's domain and less precipitation in the southern coastal areas than when driven by R2. The differences occur because RegCM4 driven by ERA simulated the lower troposphere as being warmer and more humid and the upper troposphere as being cooler than that by R2. The transport of moisture into the central region of the model domain is also enhanced when the RegCM4 is driven by ERA. Although the RegCM4 accurately simulated the seasonal variations in precipitation, it failed to capture diurnal variations over South Korea, particularly when driven by R2, and overestimated and underestimated light precipitation (<25 mm/day) and heavy precipitation (> 50 mm/day), respectively.

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere-Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor's skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54 o C/+1.92 o C for RCP2.6, +1.68 o C/+2.91 o C for RCP4.5, +1.17 o C/+3.11 o C for RCP6.0, and +1.75 o C/+4.73 o C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.

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