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Based on the statistics of normal and abnormal frequencies of the monitoring status and data quality of ground temperature, pressure, temperature, humidity, wind and precipitation from newtype automatic meteorological stations, the correlation analysis between observation data and equipment status information is conducted, and the accuracy rate and error rate are calculated in this paper. The results show that there is a good consistency between observational data and communication status, equipment selftest status and sensors, with normalaccuracy rate exceeding 96%, while the consistency between observational data and the collector, communication interface, counter, AD and motherboard temperature, etc., is poor, with abnormalaccuracy rate less than 3%. The operational status information of domestic newtype AWSs is utilized for the quality judgment of observation elements for the first time. Although there are still certain problems in application needing improvement, this study is of significance for improving the data quality control methods and promoting the authenticity and availability of AWS’s data.