Collaborative Research: Using Polarimetric Radar Observations, Cloud Modeling, and In Situ Aircraft Measurements for Large Hail Detection and Warning of Impending Hail

合作研究：利用偏振雷达观测、云建模和现场飞机测量来检测大冰雹并预警即将发生的冰雹

• 批准号: 2344259
• 负责人: Alexander Ryzhkov
• 金额: $ 29.84万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-15 至 2027-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2344259&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; Polarimetric; Radar

Hail is one of the most dangerous and destructive manifestations of severe weather, resulting in an annual average of more than $10 billion USD in insured property losses around the world. In addition to the strong hail impact on personal and business property, the agricultural and renewable energy sectors also suffer. Advanced polarimetric weather radars are the best instruments to remotely detect hail in the clouds, estimate its size, and produce timely warnings of impending hail if guided by the physical cloud models that predict hail growth and its fallout on the surface. However, existing methodologies for quantifying and forecasting large hail have serious limitations which will be mitigated as a result of the project. This project will capitalize on the unique observations of hail from the armored T-28 research aircraft that penetrated hail-bearing storms during multiple field campaigns in the past. Combining direct hail measurements within the cloud aloft and at the surface with cloud modeling describing its evolution on the way to the ground and the collocated polarimetric radar observations within the full depth of the storm will help to better understand the microphysical processes of hail generation and develop more advanced methodologies for its quantification and prediction / nowcasting.The technical approach will involve utilization of the documented measurements of sizes, number concentrations, and shapes of hailstones aloft to initialize the cloud model. The model involves spectral bin microphysics describing the evolution of hailstones including the change of hail size and kinetic energy with height within the storm as they fall to the surface. The output of the cloud model will be converted into the vertical profiles of polarimetric radar variables which will be compared to the associated measured profiles. This will allow to retrieve size distribution of hail above the melting layer using vertical profiles of radar variables associated with melting hail within the melting layer and beneath and will serve as an observational reference for cloud models’ evaluation and optimization. Novel polarimetric radar predictors in deep convective updrafts signifying large or giant hail at the surface will be identified and explored across a wide range of thermodynamic and climatological regimes and height of the surface relative to sea level using polarimetric radar data collected by the operational WSR-88D radars in a multitude of particularly devastating hailstorms.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.

冰雹是恶劣天气最危险和最具破坏性的表现形式之一，每年平均在全球造成超过100亿美元的保险财产损失。除了对个人和商业财产的强烈影响外，农业和可再生能源部门也受到影响。先进的偏振天气雷达是远程探测云中冰雹的最佳工具，估计其大小，并在预测冰雹生长及其在地面上的沉降物的物理云模型的指导下及时发出即将来临的冰雹警报。然而，现有的大冰雹量化和预报方法有严重的局限性，该项目将减轻这些局限性。该项目将利用装甲T-28研究飞机对冰雹的独特观测，这些飞机在过去的多次实地活动中穿透了冰雹风暴。将高空云内和地面的直接冰雹测量与描述其在到达地面的过程中演变的云模型以及在风暴整个深度内的配置偏振雷达观测相结合，将有助于更好地了解冰雹生成的微物理过程，并开发更先进的方法来量化和预测冰雹。该技术方法将涉及利用高空冰雹的大小、数量密度和形状的记录测量结果来初始化云模型。该模式包括描述冰雹演变的谱箱微物理学，包括冰雹大小和动能随风暴内高度的变化，因为它们落在表面。 云模型的输出将被转换成极化雷达变量的垂直分布，并将其与相关的测量分布进行比较。这将允许使用与融化层内和下面的融化冰雹相关的雷达变量的垂直廓线来检索融化层上方的冰雹的大小分布，并将作为云模式的评估和优化的观测参考。 使用WSR业务收集的偏振雷达数据，将在大范围的热力学和气候学状况以及相对于海平面的地表高度中识别和探索深对流上升气流中的新型偏振雷达预报器，该上升气流表示地表的大或巨型冰雹。该奖项反映了NSF的法定使命，并被认为是值得支持的，使用基金会的知识价值和更广泛的影响审查标准进行评估。