Recognition of hail and rainstorm based on the radar reflectivity image features

Abstract

Based on radar reflectivity image features, an automatic recognition method is proposed to identify the hail and rainstorm. We extract the image features of hail echo areas and rainstorm echo areas from radar reflectivity images. By analyzing both the differences in single feature between hail and rainstorm and the classified complementarity among different features, we determine the effective image features, including the intensity and texture features, to identify the hail and rainstorm. The hail and rainstorm objective recognition model can be established through the data mining of the extracted sample features and sounding data by using the Rough Set Theory. Through the test and identification of the 362 test samples, the hit ratio of hail reaches 93.29% and the hit ratio of rainstorm reaches 89.07%. The false alarm ratios of hail and rainstorms can be also at a low level. Compared with those from the PUP system, the experimental results from the present system show that it has a good effect to identify and classify hail and rainstorm by using the radar reflectivity image features.