This paper introduces a quality control (QC) program for the real-time hourly land surface temperature observation developed by the Central Weather Bureau in Taiwan. There are three strategies involved. The first strategy is a range check scheme that inspects whether the observation falls inside the climatological limits of the station to screen out the obvious outliers. Limits are adjusted according to the station’s elevation. The second strategy is a spatial check scheme that scrutinizes whether the observation falls inside the derived confidence interval, according to the data from the reference stations and the correlations among the stations, to judge the reliability of the data. The scheme is specialized, as it employs the theorems of unbiased and minimum error estimators to determine the weights. The performance evaluation results show that the new method is in theory superior to the spatial regression test (You et al.). The third strategy is a temporal check scheme that examines whether the temperature difference of two successive observations exceeds the temperature variation threshold for judging the rationality of the data. Different thresholds are applied for the data observed in different times under different rainfall conditions. Procedurally, the observation must pass the range check first and then go through the spatial or the temporal check. The temporal check is applied only when the spatial check is unavailable. Post-examinations of the data from 2014 show that the QC program is able to filter out most of the significant errors.