Recognition of Organizational Morphology of Mesoscale Convective Systems Using Himawari-8 Observations

The onset, evolution, and propagation processes of convective cells can be reflected by the organizational morphology of mesoscale convective systems (MCSs), which are key factors in determining the potential for heavy precipitation. This paper proposed a method for objectively classifying and segmenting MCSs using geosynchronous satellite observations. Validation of the product relative to the classification in radar composite reflectivity imagery indicates that the algorithm offers skill for discriminating between convective and stratiform areas and matched 65% of convective area identifications in radar imagery with a false alarm rate of 39% and an accuracy of 94%. A quantitative evaluation of the similarity between the structures of 50 MCSs randomly obtained from satellite and radar observations shows that the similarity was as high as 60%. For further testing, the organizational modes of the MCS that caused the heavy precipitation in Northwest China on August 21, 2016 (hereinafter known as the "0821" rainstorm) were identified. It was found that the MCS, accompanied by the "0821" rainstorm, successively exhibited modes of the isolated cell, squall line with parallel stratiform (PS) rain, and non-linear system during its life cycle. Among them, the PS mode might have played a key role in causing this flooding. These findings are in line with previous studies.