To address the insufficient applicability of the original hail size discrimination algorithm (HSDA) in China, a modified HSDA applicable to S-band and C-band dual-polarization radars in China is proposed in this study. Utilizing 760 ground hail reports and dual-polarization radar observations in China from 2021 to April 2026, this study statistically analyzes the polarimetric characteristics of different hail sizes at various height layers, based on which the membership functions are optimized. The findings are as follows. (1) Differences in hail polarimetric characteristics observed by different radar wavelengths are identified, which are attributed to the combined effects of hail melting, resonance scattering, and attenuation correction residual errors. In lower height layers, the differential reflectivity (Z_DR) of S-band radars increases as the horizontal reflectivity factor (Z_H) decreases, while essentially negligible correlation between the two is observed for C-band radars. (2) The modified HSDA at S-band expands the identified areas of small and large hails while reducing the area of giant hail. The classification accuracy of the modified HSDA for S-band radars at 1.5° elevation exceeds 80%, representing an 8% increase compared to the original HSDA. Although the HSDA was originally developed only for S-band, adapting the membership functions to C-band characteristics enables the classification accuracy to exceed 81% at 1.5° elevation, demonstrating the algorithm’s robust adaptability to different radar wavelengths. (3) Analysis of the severe hail event in Beijing on 13 May 2025 reveals that the modified HSDA effectively reveals the evolution of hail sizes and the growth process of large hail within the storm. Furthermore, deepening of the Z_DR and K_DP columns can provide a lead time of 18–30 min prior to the descent of giant hail to the ground.

A spring rainstorm which was underestimated by subjective quantitative precipitation forecast struck southern North China on 21 April 2018. The mesoscale and large scale dynamic processes of the backdoor cold front and associated mesoscale convective system (MCS) were studied using high spatial and temporal resolution observations, the fifth generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis and high-resolution numerical simulations. Results showed that the rainstorm was produced by the backdoor cold front. The backdoor cold front consisted of two sections, and the western one was oriented along the south-north direction while the eastern one was oriented along the east-west direction. Cold air was concentrated below 1.5 km. With the strengthening of northeasterly or easterly winds behind the front, the front moved southward, the height of cold air dam on the east side of Taihang mountain increased, and the front intensified. The rainstorm was brought by the MCS, which occurred in the horizontal wind convergence region ahead of warm air climbing along the backdoor front. The formation and maintenance of MCS occurred near the backdoor front accompanied by frontogenesis. The enhancement of the northeasterly winds behind the front resulted in rapid southward movement of the front and higher cold air dam, while the MCS was enhanced and the convective center also moved southward. The ascending motion favorable for MCS formation was mainly contributed by the resultant force of vertical pressure gradient force and buoyancy. Diagnostic analysis showed that the large value center of the resultant force was ahead of the warm and moist air climbing along the front, corresponding to the region of large horizontal equivalent potential temperature gradient. These results explain the southward movement of the convective center and the development of MCS. This work reveals the key mesoscale dynamic processes of the MCS and backdoor cold front in spring rainstorm in North China, and sheds light on the improvement of related numerical model physical processes and forecasting techniques in the future.