Abstract:In order to improve the monitoring and early warning capabilities for autumn hail, based on the dual-polarization radar and FY-4A satellite data, this paper analyzed a rare autumn severe hail process that occurred in Hunan Province in November 2023, and discussed its early warning characteristics. The findings are as follows: (1) The severe hail process was produced by supercell hailstorms. In the hail stage, the bottom of the strong echo center with horizontal reflectivity factor ZH ≥65 dBz was close to the ground, the correlation coefficient (CC) was lower than 0.9, the specific differential phase (KDP) was a cavity, and the differential reflectivity factor (ZDR) was -3-0 dB. These corresponded to the condition for the fall of large hailstone with diameter ≥ 5 cm, and matched with the observation. The rise and fall of the ZDR column can characterize the strengthening and weakening of updraft, and the ZDR with CC can identify three body scatter signature (TBSS) and side lobe characteristics. (2) The area of strong echo and the height of centroid were good indicators for different development stages of supercell. Combined with monitoring, the lead time of early warning of hail can be improved by more than 12 min. During this severe hail process, the length of TBSS caused by the supercell reached 73 km which is rarely seen. The emergence of TBSS and the divergence of the storm top showed a significant weakening trend, which was 17 min more earlier than the occurrence time of hail. (3) Hail and thunderstorm gale appeared in areas with large gradients of hail cloud blackbody brightness temperature (TBB), cloud top temperature (CTT), cloud top height (CTH), and cloud top pressure (CTP). TBB≤-58℃, CTT≤-56℃, CTH≥13 km, CTP≤180 hPa and the continuous increase of TBB≤-52℃ area can be used as monitoring and early warning indicators of the characteristic parameters of autumn hail cloud by FY-4A satellite. (4) The TBB maximum lapse rate can provide at least 11 min of advance warning for impending hail. The brightness temperature difference of 13.3 μm and 10.8 μm channel is the most sensitive to the development and weakening of hail clouds. The brightness temperature difference of 6.5 μm and 10.8 μm channels is more sensitive to the related conditions before and after the hail passes through the hit area than other brightness temperature differences among the single-station convection monitoring indicators.