The realtime data of Automatic Meteorological Station (AWS) is of great significance to meteorological warning, decisionmaking service, and forecast verification. Developing the quality control of realtime data is necessary to ensure the rationality and accuracy of realtime data of AWS’s. The data quality of national AWS’s from the Atmospheric observing System Operation and Monitoring platform (ASOM) in 2013 is statistically analyzed,〖JP2〗 and the variation regularities and internal consistency of meteorological elements when special weather happens are studied on the basis of historical data of AWS’s, 〖JP〗and then criterions for judging highhumidity and sudden weather change events are proposed to improve the data quality control algorithm of AWS’s. The application results of the new algorithms indicate that the improved data quality control algorithms can reduce the misjudgment rate effectively and achieve good control effect.