Abstract: The detection of large-area average changes of meteorological data is always hampered because of the different record series of long-term in-situ measurements, which can often cause the spatial sampling errors. Fortunately, more and more scientists explore that the grid-based dataset can reduce the spatial sampling error through given interpolation method. Substantial progress has been made in the last two decades in quantitatively documenting analysis of different meteorological factors. Ground water vapor pressure is an important meteorological factor that can control some physiological, ecological and water balance process in ecosystem. In this article, using the quality controlled observational monthly and yearly mean ground water vapor pressure data series over China Mainland, through the ANUSPLIN software developed by the Australian National University based on the thin-plate smooth spline method, the datasets of yearly and monthly grid-based ground water vapor pressure are established over China in recent 55 years from the 1951 to 2005. Cross-validation tests show that this gauge-based analysis has high quantitative quality, which annual interpolation error is typically less than 0.3 hPa except from 1951 to 1953 and monthly error has periodic variation with biggest in summer and smallest in winter. In spring and autumn its monthly error value is between the others. The research results include: (1) The relationship between measured and its corresponding grid cell indicates that they are a good linear correlation passing the 0.01-level confidence check. The grid value can represent the pattern of the measured one. (2) Using the 30-year normal from the 1971 to 2000, annual and seasonal variation based on the grid dataset suggests that average annual change shows increasing trend over the 55 years with its linear trend 0.52 hPa per 100-year. The increasing trend in western China is more obvious than that in eastern China. For the seasonal scales, the summer trend is the most dramatic, which is estimated linear trend 0.98 hPa per 100-year over the whole China. While the spring's is lowest which is 0.42 hPa per 100-year. Considering the temperature rising in recent 50 years, 3.15% of water vapor will be increased when temperature warms up 1 degree over China, which is lower than the globe average value. There are two reasons for it, one is the stronger warming trend in China than in the world the other maybe arises from drought enhancement in China. This developed datasets are helpful to explore the spatial and temporal distributions of the ground water vapor pressure. It can be used in a wide range of applications, including weather/climate monitoring, climate analysis, numerical model verifications, ecological assessment, and hydrological studies.