In this study, the simulation results of temperature and precipitation adapted regional climate model(RegCM4) over South Korea were applied to the correction method developed by Hempel et al.(2013). Compared with other bias corrections, the correction method of Hempel et al.(2013) shows the highest correction level in extreme and mean climate of temperature and precipitation. Especially, the correction method preserved the variation tendency simulated by the model and the method, in terms of bias correction, shows superior results. After the bias correction, the results regarding systematically underestimated trend and error decreased and the spatial distributions seem to be similar. The extreme climate also decreased bias and errors in most indices. In particular, in the case of tropical night day, the model did not appropriately represent spatial distribution, but after modification it was similar to observation. However, the correction was overestimated in the extreme climate regarding upper percentile temperature such as TX5%, hot days and tropical nights. In the case of precipitation, bias and errors in daily and monthly precipitation, as well as the extreme climate decreased, spatial distributions appeared similar when compared with the observation. Frequency correction of precipitation such as non-precipitation days also shows great reliability. However, the correction was overestimated in the extreme climate about upper percentile precipitation such as PR5% and heavy rain days. In particular, it appears in summer and autumn more distinctively than spring and winter. However, after the correction the quantile root mean square errors, except the upper 5 percentile of the precipitation, were 0.74mm/day. As a result, the correction method of Hempel et al.(2013) is effective for the temperature and precipitation simulated by regional climate model over South Korea, and it is greatly reliable with regards to mean and extreme climate. If overestimated correction problems are resolved for the upper percentile of temperature and precipitation, it will yield a higher reliability with respect to the extreme climate.