To increase the efficiency in artificial hail suppression operation, a storm autoclassification technology is developed based on the storm tracking and recognition algorithm using the new generation Doppler weather radar data in this study. The characteristic indices of storm structure are firstly automatically extracted by using the radar and sounding data and the SCIT algorithm. And then according to the intensities, the storms are classified into weak thunderstorm, singlecell storm, multicell storm and severe storm by adopting the automatic classification technology of decision tree model. Finally, the early warnings on the downstream direction of the storm or working parameters near the operating location are automatically performed according to properties of the storm such as storm intensity, height, location and GIS information. From the analysis of 182 hail cases during the 31 hail weather processes over Chongqing, Dalian of Liaoning and Sanmenxia of Henan from 2006 to 2014, the storm autoclassification technology developed in current study can significantly increase (decrease) the hit (false alarm) rate of storm tracking and recognition. The hit rate can reach 100%, and the false alarm rate is only 11.4%. The result suggests that this storm autoclassification technology can enhance the automation of artificial hail prevention and contribute to the decision making for the operation of artificial hail suppression.