Abstract: In the context of intensifying global warming, accurate projections of climate changes in the coming period is essential． The 15 global climate models (GCMs) in the newly released coupled model intercomparison project 6 (CMIP6) are used to quantify uncertainty in temperature and precipitation estimates in the Qinghai-Xizang Plateau under the next four shared socioeconomic pathways and typical concentration pathway combination scenarios． The CMIP6 model output data is bias-corrected using the DT method． The magnitude of the uncertainty before and after DT is compared, the potential of bias correction in reducing uncertainty in temperature and precipitation estimates was discussed． The correction results of the DT method are found closer to measured values． In the long run, model uncertainty dominates, while contribution of scenario uncertainty and internal variability is relatively low． DT method is effective to reduce uncertainty in precipitation prediction, reducing the model uncertainty by 80%; this has little effect on the size of scenario uncertainty but affects the relative contribution of uncertainty． It is concluded that DT method for deviation correction reduces uncertainty in estimation, with important implications for the impact of climate change on water cycles in alpine regions．