Abstract:Based on the hourly temperature data derived from 48 708 surface automatic weather stations in China, the CLDAS-V2.0 temperature data in October 2017, January 2018, April 2018 and July 2018 (resolution:0.062 5°) were analyzed by using the evaluation indexes such as mean deviation (Bias), correlation coefficient, root mean square error (RMSE) and mean absolute error (MAE).This paper studied the correlation and deviation distribution characteristics between CLDAS and station temperature in spring, summer, autumn and winter in eight zones of China.Results show that:(1) CLDAS temperature reflects the interannual variation of temperature in China, and the average correlation coefficients of non-independence test, independence test and station temperature are 0.995 and 0.991 respectively.The correlation coefficient is the highest in Northeast China and the lowest in Southwest China.(2) The Bias of CLDAS and station temperature is -0.011℃, RMSE and MAE of non-independence test are 1.275℃ and 1.645℃, and RMSE and MAE of independence test are 0.867℃ and 1.089℃, respectively.In general, CLDAS has small temperature error and high reliability.(3) The deviation in spring and autumn is less than that in summer and winter.The deviation in Northeast, North China, Jianghuai and South China is smaller than that in Northwest and Southwest China.In 84.6% stations, the cold deviation or warm deviation is within 1℃, and the spatial distribution of cold and warm deviation is uniform.(4) The maximum temperature of CLDAS has cold deviation, the minimum temperature has warm deviation, and the maximum deviation of maximum temperature in summer is -0.59℃.(5) The diurnal variation of mean deviation of CLDAS is -0.23-0.07℃, colder in the daytime and warmer in the night.The diurnal variation of mean deviation of CLDAS is significant in summer, and the diurnal range of deviation is 0.26℃.The maximum diurnal variation of summer mean deviation in the eight zones of China is 1.06℃, and the variation ranges in autumn, winter and spring are similar.The diurnal variation of mean deviation is the largest in Southwest China and the smallest in Jianghuai.