Abstract: A statistical downscaling model（SDSM）was applied to develop the quantitative statistical relationships between the predictands and the predictors based on the mean daily, maximum and minimum temperature data observed by 7 meteorological stations in the Qinling Mountains during the period of 1961-2011. The gradual linear regression method was used in the study, the optimal predictors in NCEP atmospheric circulation were selected, the applicability of air temperature change in the Qinling Mountains in the future was analyzed, and the change trends of air temperature in three periods of 2011-2040, 2041-2070 and 2071-2099 were predicted. The results showed that the air temperature results simulated with SDSM for the situation in the Qinling Mountains were significantly good. The increase of air temperature in the study area in the future would be remarkable, its difference, however, would be quite different from different time scales. The temporal change of three predictands was similar at monthly and seasonal scales. At monthly scale, the temperature increase would be the highest in August but the lowest in December. At seasonal scale, the temperature increase would be in an order of winter < spring < autumn < summer. Spatially, the increase of temperature in 2011-2040 would be higher in the northern slope of the Qinling Mountains than that in the southern slope.

Key words: air temperature, change trend, downscaling, SDSM, future scenario, Qinling Mountains