Collaborative Research: Comparison between In-situ and Polarimetric Radar Hail Observations in Convective Storms

美国的天气雷达系统利用偏振观测，雷达波束以垂直和水平方向发射，以估计降水粒子的形状。 该奖项将利用现有的偏振雷达数据和风暴穿透飞机（SPA）的观测结果，以改善雷达数据对冰雹属性的估计。 冰雹是一种公共安全和经济危害，改进的冰雹雷达信息可以为业务预报员提供额外的工具来提供早期预警。 多名学生将在该项目下接受培训，科学界使用的软件将得到增强。研究团队计划重新审视与研究飞机和偏振雷达同时进行的冰雹观测，以深入了解冰雹的形状，方向，大小和浓度如何影响雷达特征。 南达科他州矿业与技术学院在1987年至2003年期间在NSF的支持下运营了一架T-28风暴穿透飞机。 在此期间，该飞机参与了18个项目，其中许多项目包括使用冰雹光谱仪和云探测器测量冰雹。 这些行动通常在双极化雷达的近距离内进行，包括CSU-CHILL和NCAR SPOL雷达。 在这个项目中，现有的这些数据的分析将通过增加新的航班和飞行时间，包括来自云和降水探测器（2D-C，HVPS）的数据，以及来自记录冰雹击中飞机挡风玻璃的声音的麦克风的独特数据源来增强。 主要任务包括：1）处理来自光谱仪探测器的水凝物图像，包括使用离散偶极子和T矩阵软件计算偏振雷达特征，2）分析雷达数据以确定雷达扫过遭遇冰雹的风暴体的时间并提取偏振参数，以及3）合成数据，其目的是比较导致计算的和观察的雷达特征信号的更好或更差一致性的条件的特性，和评价冰雹的物理特性，其中每一个计算的偏振参数是最敏感的。由地球科学理事会和高级网络基础设施办公室合作资助，以支持AI/地球科学中的ML和开放科学活动。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准。

The system of operational weather radars in the United States makes use of polarimetric observations, where radar beams are sent out in vertical and horizontal configurations to retrieve an estimate of the shapes of precipitation particles. This award will make use of existing polarimetric radar data and observations from a Storm Penetrating Aircraft (SPA) to improve estimates of the properties of hail from radar data. Hail is a public safety and economic hazard, and improved radar information about hail could provide operational forecasters with an additional tool to provide early warnings. Multiple students will be trained under this project and software used by the scientific community will be enhanced.The research team plans to revisit existing observations of hail that were made concurrently with a research aircraft and polarimetric radars to provide insight into how hail shapes, orientation, sizes, and concentrations influence radar signatures. The South Dakota School of Mines and Technology operated a T-28 storm penetrating aircraft under NSF support from 1987-2003. During that time, the aircraft was involved in 18 projects, many of which included measurements of hail using a hail spectrometer and cloud probes. These campaigns were often conducted within a close distance of a dual-polarimetric radar, including the CSU-CHILL and NCAR SPOL radars. In this project, existing analyses of these data will be augmented by the addition of new flights and flight periods, the inclusion of data from cloud and precipitation probes (2D-C, HVPS), and a unique source of data from a microphone that recorded the sound of hail hitting the aircraft windshield. The main tasks include: 1) Processing hydrometeor images from spectrometer probes, including the calculation of polarimetric radar signatures using discrete dipole and T-matrix software, 2) Analyzing radar data to identify the time the radar swept through the storm volume with the hail encounter and extraction of polarimetric parameters, and 3) Synthesis of the data, with objectives of comparing characteristics of conditions leading to better or worse agreement of computed and observed radar signatures, and evaluation of hail physical characteristics to which each computed polarimetric parameter is most sensitive.This project is co-funded by a collaboration between the Directorate for Geosciences and Office of Advanced Cyberinfrastructure to support AI/ML and open science activities in the geosciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.