A preliminary application of artificial intelligence on the detection and nowcasting of hail weather

Based on three-dimensional mosaic reflectivity data from ten S-band Doppler radars in Guangdong Province, an artificial intelligence (AI) algorithm for automatic hail detection and nowcasting is developed using the machine learning technology. The training dataset used to develop the algorithm includes vertical and horizontal slice data of the mosaic radar reflectivity, in which the slice data of hail clouds are taken as positive samples, and other data are used as negative samples. The Bayes classifier method is used during the training process of machine learning to establish the capability of AI on recognizing the characteristics of the hail cloud. The data during the period of 2008-2013 and 2015-2016 are taken as training sets, while the observed data during the 12 hail weather processes in 2014 are used to validate the capability of AI. The result of comparative validation is encouraging, and the AI method is 9% higher than the traditional Conceptual Model method on identifying the hit rate. The current study preliminarily shows the strong capability of AI on identifying the nonlinear strong weather processes.