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.

To investigate the impact of radial velocity assimilation in the clear-air region on forecasting, this paper conducted cycle assimilation experiments for short-duration convection and heavy rainfall forecasting using the latest classified raw radar data from the Meteorological Observation Centre of China Meteorological Administration. These experiments involve the assimilation of radial velocity in the clear-air region, alongside the assimilation of radar reflectivity factor and radial velocity in the precipitation region. The results show that as the cycle assimilation progresses, radial velocity in the clear-air region gradually influences the interior of the convective system, adjusting the thermal and dynamic conditions within the convection. This adjustment improves the coordination between various physical quantities, thereby improving the forecast skill of short-duration convection. Furthermore, the radial velocity in the clear-air region gradually affects the physical quantities in the precipitation region through the cycle of assimilation, thereby improving precipitation forecast skills. The study discloses that reasonable assimilation of radial velocity in the clear-air region can play an important role in pre-convection and precipitation forecasts.