Abstract: In order to analyze the grain production situation in the study area and its response to climate change, the meteorological and agricultural data were used to analyze the climate change in recent 60 years and its effect on agricultural climate resources, sown area and per unit area yield with the linear trend, cumulative anomaly and mutation method, and a multiple linear regression equation was developed to predict the future changes in grain yield for guiding scientific farming and better serving the agricultural ecosystem. The results are as follows: ① Over the past 60 years, an obvious warming-wetting trend occurred in the study area. The temperature and precipitation increase rates were 0.2℃·（10a）^-1(P<0.01) and 4.5 mm·（10a）^-1(P< 0.05) respectively, but the sunshine duration decreased with a decrease rate of 21.1 h·（10a）^-1. The temperature mutation occurred in 1996, but there were no obvious mutations in precipitation and sunshine duration; ②With climate warming, the duration of cumulative temperature ≥10 ℃ increased by 19d, but that of negative one shortened by 8 d; ③ In addition to the negative cumulative temperature, the grain yield was positively correlated with air temperature, sunshine duration, cumulative temperature ≥10 ℃, sown area, per unit area yield and applying quantity of chemical fertilizer; ④ The multiple regression model revealed that 7 independent variable factors could be used to explain the 99.7% grain yield variation without considering other factors. Climate change is conducive to expanding grain sown area and increasing per unit area yield to a certain extent.