Abstract: Based on the daily data from 54 meteorological stations in Northern and Southern Regions of the Qinling Mountains between 1960 and 2011, with the help of FAO Penman-Monteith formula, the potential evapotranspiration and humid index were calculated. By using the Spline interpolation method, climate trend rate, correlation analysis and other methods, we analyzed the distribution of temporal and spatial variation characteristics of temperature, precipitation, potential evapotranspiration and humid index as well as the meteorological elements which influenced evapotranspiration and humid index. The results are given as follows: 1) The average annual temperature of the northern and southern regions increased gradually from north to south, 1993 was the turning point of temperature, and cooling trend in southern area before 1993 was more obvious. Since 1994, the temperature of most stations increased significantly (P <0.01), and there was no significant difference among four regions. 2) The annual precipitation decreased from south to north. Precipitation showed a downward trend before 1995, and the northern region was more obvious. While precipitation increased since 1995, including more than 70% stations. The northern part was becoming dry while the southern slope was becoming wet, and there was no significant change in other parts. 3)The potential evapotranspiration decreased from eastern part to western part. All the sub regions showed consistent downward trend (P<0.05). Southern slope was more obvious than northern slope, but there was no significant turning point. 4)The humid index decreased from south to north. The northern region was becoming warmer and drier, while southern region was becoming cooler and wetter. At the seasonal scale, four sub regions showed the same tendency, that humid index of most stations in spring and autumn showed a decreasing trend while in summer and winter showed an increasing trend. 5) Sunshine hours, average temperature, maximum temperature and evapotranspiration correlated negatively with humid index significantly ( P < 0.01). But minimum temperature and wind speed had no significant relationship with humid index. The increase of precipitation and relative humid can improve humid index.