GPM资料在分析“彩虹”台风降水垂直结构中的应用

GPM Data Application in Analysis of Vertical Structure of Typhoon‘Mujigae'Precipitation

全球降水测量计划GPM(Global Precipitation Measurement)是新一代全球卫星降水产品,其核心观测平台搭载的微波扫描辐射仪增加的高频通道可以探测小雨和雪,双频降水雷达将Ku波段和Ka波段数据结合,可获取更多云与降水粒子信息。为探测台风降水的云雨结构,利用GPM的1C-GMI产品和2A-DPR产品,分析了2015年10月初的1522号台风"彩虹"的降水分布、垂直结构、雨顶高度、层云和对流云降水的结构,并与地基雷达的观测进行对比。结果表明:双频雷达的Ku波段擅长探测降水和零度层亮带,Ka波段探测云顶小粒子的效果更佳。台风在成熟阶段近地面降水率集中在20mm/h以下,部分在20~60mm/h,最大值达到88.68mm/h;雨顶高度集中在5~10km,最大高度超过15km。层云降水的面积在台风中所占比例达到63.4%,但单位面积平均降水率比对流降水低37%。双频降雨雷达DPR((Dual-frequency Precipitation Radar)和地基S波段雷达探测"彩虹"台风的结果十分相近,证明了DPR数据质量的可靠性。

The Global Precipitation Measurement（GPM）mission is designed to provide the next generation of global satellite precipitation products.The GPM Microwave Imager（GMI）carried on the Core Observatory adds high-frequency channels which can detect light rain and snow.The Dual-Frequency Precipitation Radar（DPR）combining the data of Ku-band and Ka-band helps to obtain more information of cloud and precipitation particles.To detect the cloud and precipitation structure in the typhoon,lots of information from both bands such as precipitation distribution,vertical structure,rain top height and structure of stratus cloud and convective cloud of typhoon ‘Mujigae＇occurring in early October 2015 are analyzed,using1 C-GMI and 2 A-DPR products of GPM.The results show that the Ku-band of DPR is better at detecting precipitation and bright band.However,Ka-band has better effects on detecting small particles of the cloud top.The near-surface precipitation rate centers upon values below 20 mm/hr and partly focuses on 20-60 mm/h.The maximum value of near-surface precipitation rate is 88.68 mm/hr.The rain top height centers on values between 5 km and 10 km,and the maximum value exceeds 15 km.The proportion of stratus cloud precipitation in the typhoon reaches 63.4%,but its average rainfall rate per unit area is lower than convective cloud precipitation by 37%.The detecting results of DPR and ground-based SA-band radar are very close which proves the reliability of DPR data.