Use of Polarimetric Radar Measurements to Initialize Moisture Fields in Cloud/Mesoscale Numerical Weather Prediction Models: The Severe Hailstorm

9311911 STRAKA研究任务对短期天气预报的进步至关重要，是改进模式初始化和数据同化。重要的第一步是开发通过遥感确定风暴中云水流星类型的方法。首席调查员将使用先进天气研究雷达提供的各种信息来确定对流风暴中的水流星分布。利用这些信息，首席研究人员将首次尝试在云/中尺度数值天气预报模式中初始化水汽场。具体目标包括：(1)改进和测试一个用于从反射率、双波长、偏振和多普勒雷达测量中推断降水水气象类型和降水量的算法；(2)利用雷达测量的降水信息，结合速度/热力学/微物理反演和动态初始化方案，对云/中尺度数值预报模式进行初始化；(3)利用观测和反演的风、热力、云和降水信息测试数值模式对初始化的敏感性；(4)利用雷达分析提供的信息，检验关于冰雹形成和增长的流行理论。***

9311911 Straka Research tasks that are crucial for advancements in short term weather forecasting are improvements in model initialization and assimilation of data. An important first step is to develop methods for determining cloud hydrometeor types within storms through remote sensing. The Principal Investigators will use a variety of information from advanced weather research radars to determine hydrometeor distribution within convective storms. Using this information, the Principal Investigators will make a first attempt to initialize moisture fields in a cloud/mesoscale numerical weather prediction model. Specific objectives include: (1) Refine and test an algorithm designed to deduce precipitating hydrometeor types and amounts from reflectivity, dual-wavelength, polarimetric and Doppler radar measurements; (2) Use precipitation information from radar measurements with combined velocity/thermodynamic/microphysical retrieval and dynamic initialization schemes to initialize cloud/mesoscale numerical prediction model; (3) Test the sensitivity of numerical model to initialization with observed and retrieved wind, thermodynamic, cloud and precipitation information; (4) examine popular theories on the formation and growth of hail using information from radar analyses. ***