Abstract: QM and QDM methods are used to correct simulated temperature and precipitation over China from a set of regional climate model (RegCM4) projection simulations in which the RegCM4 is driven by five different general circulation models. Extreme climate indices are derived separately based on both original-simulation and bias-corrected results, and a comparative analysis is conducted. Both the individual simulations and ensemble RCM (ensR) show higher simulation skill scores in the temperature indices compared to those in the precipitation indices in which the annual maximummax daily maximum temperature (TXx) is the best and the annual maximum consecutive dry days (CDD) is the worst. Biases can be effectively reduced using both the QM and QDM methods for all the five simulations and ensR. After bias corrections, the spatial correlations between the simulations and observations are certainly increased. No significant differences exist in the correction effects of the two methods. For future changes under RCP4.5, the QM modifies the originally projected change magnitudes and spatial patterns of changes, whereas the QDM effectively preserves the climate change signals in the extreme indices. Changes in the national average show that all the indices except the CDD will continuously increase, and the results corrected through the QDM are closer to the original future projection simulations. Therefore, employing the QDM to correct climate change simulations is recommended.