冰雹云卫星早期识别与自动预警

利用陕西、山东、贵州和新疆等地近十年日间降雹记录和对应的极轨卫星数据，采用卫星云微物理反演技术，定量分析冰雹云微物理特征，比较不同地区间差异，并利用FY-4A静止卫星定量分析一次冰雹过程云微物理特征演变，探讨冰雹云卫星识别预警应用潜力。结果表明:（1）陕西、山东等地冰雹云微物理特征具有一致性，卫星早期识别指标为:晶化温度（T_g）较冷，均值为?33°C；全部冰晶化时T_g对应的云粒子有效半径r_e（表征为r_eg）未饱和（<40 μm），均值36.9 μm，且r_eg 越小冰雹云越强；云顶呈现r_e随高度减小带。（2）各地冰雹云早期识别指标在数值上存在一定差异，实际应用时应针对各地进行相应调整。（3）在静止卫星上，冰雹云微物理特征与极轨卫星相一致，将早期识别指标应用于FY-4A静止卫星，跟踪云团发展演变，实现自动预警。（4）经过4次降雹过程中应用，FY-4A卫星自动预警与实况吻合22次，漏报2次，自动预警平均提前约2小时。FY-4A卫星自动预警对及时有效组织实施人工防雹作业具有重要现实意义。

Early Identification and Automatic Warning of Hail Clouds by Satellite

Meteorological satellites have provided useful information for improving weather forecasting, environmental monitoring, and short-term climate prediction. In the field of the weather forecast, satellites provide a powerful means for the forecast of typhoons, rainstorms, hail, sandstorms, and other severe weather conditions. In this study, the microstructure of hail clouds was analyzed by satellite observation data based on nearly a decade of hail event records of Shaanxi, Shandong, Guizhou, and Xinjiang. The comparison between the hail cloud and deep convective precipitation cloud characteristics retrieved by polar orbit satellites showed different cloud properties such as cloud top temperature/effective radius and cloud glaciation temperatures. Based on distinct cloud properties between hail clouds and convective clouds, this work summarized the characteristics and further applied them to the FY-4A geostationary satellite, which captures the hail cycle, which occurred on August 16, 2019, in the Shandong area. Results showed that the satellite has the potential to capture a hail cloud during its developing stage and use it as an application of early warning. The hail cloud shows the following characteristics: (1) There are considerable differences in the cloud’s physical characteristics between hail clouds and deep convective precipitation clouds. Microphysical characteristics of hail clouds observed by satellites are shown in three aspects: Glaciation temperature（T_g）is cooler with an average value of ?33°C. The hail cloud reaches the glaciation temperature with a smaller effective radius (<40 μm) with an average of 36.9 μm when the clouds are fully glaciated. It also shows that the smaller the r_eg (effective radius corresponding to glaciation temperature), the stronger the hail cloud. Additionally, hail cloud tops often have a reduction zone of r_e with increasing height. (2) All the studied areas have consistent cloud properties such as a lower T_g, smaller r_eg, and a decreased r_e compared to those of adjacent convective clouds. However, it still showed regional variabilities that indicate the need to establish different indicators for identifying hail clouds for early warning purposes. (3) The case study of the FY-4A geostationary satellite shows that the geostationary satellite can track the evolution of hail clouds. By tracking the hail cloud, the geostationary satellite has a response consistent with that of the polar orbit satellite, providing a method for monitoring and early warning service of hail weather. The geostationary satellite can be used to track the development and evolution of the cloud cluster at any time when the satellite detects a strong hail signal because of the high time resolution. Combining the satellite’s early warning with radar observation, the location of hail occurrence can be determined precisely. (4) Combining the indicators summarized by polar orbit satellites with the FY-4A to track the hail cloud evolution. Four hail storms that occurred in Shaanxi and Shandong were applied for early warnings. Ground observations reported 24 hail events in the two regions, of which the satellite successfully warned 22 times in advance and missed two times. The average early warning time is about two hours before the hail disaster. All of these suggest that the automatic warning of hail by the FY-4A satellite has important practical significance for timely and effective organization and implementation of operational hail mitigation.