Abstract: The hourly meteorological data from the automatic weather stations (AWS) is very vital to meteorological disaster warning, decision-making service and forecast and so on. Based on the hourly temperature data from the AWS, the daily maximum/minimum air temperature in four times (02:00, 08:00, 14:00, 20:00 Beijing time) from the national weather stations, the questionable and wrong hourly air temperature data were analyzed, and a quality control procedure of hourly air temperature data was developed for the temperature of AWS in China. The quality control procedure could be used for the regional and national AWS. It had been evaluated by the hourly air temperature data about 27000 weather stations from 2006 to 2010 in China. The results show that the accurate rates, questionable rates and wrong rates of hourly air temperature in the regional AWS are 99.431%, 2.24‰ and 3.45‰, and the corresponding rates in the national AWS are 99.82 %, 1.27 ‰ and 0.49 ‰, respectively. Both questionable rates are similar, while there is a magnitude difference for both wrong rates. According to the analysis of quality control of long time series air temperature data, it suggests that the design of the procedure is reasonable, and it could check the questionable data and wrong data. Thus, it could be used in the meteorological operation.

Key words:  Hourly air temperature data, Quality control, Regional automatic weather station (AWS), National automatic weather station (AWS)