The primary goal is to evaluate and discuss the validation of gridded precipitation and temperature data by means of three products (ANUSPLIN,SHERPAD,and Optimal Interpolation Method)at 05°×05° spatial resolution, using the daily data of precipitation and temperature from the network of 2419 national ground meteorological stations and 839 basic/reference meteorological stations from the National Meteorological Information Center (NMIC) of China in 2013 Results show that the accuracy of gridded precipitation and temperature data is higher, when the number of stations is greater. The correlation coefficient increases and the root mean square error (RMSE) decrease with increasing station density, which are different and change with seasons and months. The correlation coefficient and RMSE calculated from gridded precipitation in summer are better than those of the whole year,and the correlation coefficient calculated from gridded temperature in summer is worse than that of the whole year. The time series of evaluation indexes has greater uncertainty and larger fluctuation range for gridded precipitation than for gridded temperature. The comprehensive evaluation of the gridded precipitation data based on the climatic background filed by the Optimal Interpolation Method of NMIC and the elevation of the gridded temperature data by ANUSPLIN of NMIC are better than others.