PREEVENTS Track 2: Collaborative Research: Improving High-Impact Hail Event Forecasts by Linking Hail Environments and Modeled Hailstorm Processes

预防轨道 2：协作研究：通过将冰雹环境与冰雹过程模型联系起来改进高影响冰雹事件预报

• 批准号: 1855054
• 负责人: John Allen
• 金额: $ 24.81万
• 依托单位: Central Michigan University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855054&HistoricalAwards=false
• 关键词: PREEVENTS; Track; Collaborative; Research; Improving

The United States suffers billions of dollars in insured losses each year from damaging hail storms and the societal and economic costs of such storms have been increasing. Over 10 million properties in the U.S. were damaged by hail in 2017 alone. Recent examples of catastrophic hailstorms include a $2.3 billion loss hail event impacting Denver in 2017, a $1.4 billion loss hail event in San Antonio in April 2016 that included 4.5+ inch hailstones, and a 2012 hailstorm in Amarillo, TX that produced 2-m drifts of hail that washed out roads and brought traffic to a standstill. Unfortunately, none of these events were anticipated ahead of time. This proposal will identify what type of environments produce such high impact hail events, and how the physical processes that produce hail are affected by environmental processes. The improved understanding of hail growth will be incorporated into a hail forecasting system within national weather prediction models to improve hail forecasts, which is in line with NSF's mission to advance national health, prosperity and welfare and to secure the national defense. With improved short-term ( 1 h) hail forecasts, immediate threats could be avoided, such as recommending that attendees at outdoor stadiums or events take shelter. Improved intermediate-term forecasts (1-3 days) could result in recommended action that required more time-intensive planning, such as moving aircraft under shelter, notifying insurance adjusters, and working with county-level emergency managers to have contingency plans in place for public outdoor events. Knowledge of the expected type of event, such as giant hail or lots of small hail (or "blizzard" hail), in addition to merely hail size, would allow forecasters to better prepare the public: for example, a forecasted "blizzard" hail event might require a city to ready its plowing equipment and advise the public to avoid low-lying areas that could potentially flood. Additionally, knowledge of which environments are connected to which hail events types is a necessary step for developing hail forecasts on longer time scales, of subseasonal to seasonal scale and beyond. This proposal will also support a graduate student receiving a Ph.D. degree, two graduate students receiving M.S. degrees, and three undergraduate students.In order to advance predictability and reduce the increasingly significant impact of hail on society, this proposal will accomplish the following four goals: 1) Identify environmental controls on hail production for different hail threat classes (e.g., giant hail or 10 cm or 4 in, large amounts of small hail) and identify regime, seasonal and regional differences.2) Establish the physical relationship between hail threat class occurrence and environmental conditions. Determine what embryo source region characteristics increase the probability of favorable hail growth trajectories for different classes of hail threats and how these vary across realistic storm environments.3) Validate a microphysically complex hail trajectory model in light of newly available time-varying radar-retrieved wind and buoyancy fields and surface hail observations.4) Integrate new knowledge about environmental controls, three-dimensional hail trajectories, and embryo source regions into the CAM-HAILCAST hail model to improve operational forecasts of hail threats.Objective 1 will use an extensive hailstorm proximity sounding database available from the Storm Prediction Center (SPC) to explore environmental controls. Objective 2 will use idealized simulations to explore sensitivity to both environmental conditions and microphysical processes. Objective 3 will use a newly-developed radar-derived wind and microphysical dataset to drive a hail trajectory model which will be validated with surface hail observations. Finally, the improved hail forecasting model developed in Objective 4 will be tested against an independent subset of hail threat events from the SPC database. This proposed research will improve understanding of the basic processes underlying hail growth on both environmental- and storm-scales and how those vary across environments. It will determine which environments are most favorable to different hail threat classes (such as giant hail or large amounts of small hail) or hail sizes. It also moves beyond a purely statistical endeavor to ensure the physical processes underlying the environmental controls for each hail threat class are understood, including large updraft volumes, favorable placement of embryo source regions, and appropriate embryo sizes.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.

美国每年因破坏性的冰雹风暴遭受数十亿美元的保险损失，这种风暴的社会和经济成本一直在增加。仅在2017年，美国就有超过1000万处房产因冰雹而受损。最近的灾难性冰雹事件包括2017年丹佛损失23亿美元的冰雹事件，2016年4月圣安东尼奥损失14亿美元的冰雹事件，其中包括4.5英寸以上的冰雹，以及2012年德克萨斯州阿马里洛的冰雹，产生了2米的冰雹，冲毁了道路并使交通陷入停顿。不幸的是，这些事件都没有提前预料到。这项建议将确定什么类型的环境产生这样的高影响冰雹事件，以及如何产生冰雹的物理过程受到环境过程的影响。对冰雹增长的更好理解将被纳入国家天气预报模型内的冰雹预报系统，以改善冰雹预报，这符合NSF促进国家健康、繁荣和福利以及确保国防的使命。通过改进短期（1小时）冰雹预报，可以避免直接威胁，例如建议户外体育场或活动的参与者采取庇护措施。改进的中期预报（1-3天）可能会导致建议采取需要更多时间密集型规划的行动，例如将飞机转移到避难所，通知保险理算员，并与县级应急管理人员合作，为公共户外活动制定应急计划。除了冰雹的大小之外，对预期事件类型的了解，例如巨大的冰雹或大量的小冰雹（或“暴风雪”冰雹），将使预报员能够更好地为公众做好准备：例如，预报的“暴风雪”冰雹事件可能需要一个城市准备好其犁设备，并建议公众避开可能发生洪水的低洼地区。此外，了解哪些环境与哪些冰雹事件类型有关，是在较长时间尺度上、从亚季节到季节尺度以及更长时间尺度上进行冰雹预报的必要步骤。该提案还将支持获得博士学位的研究生。两名研究生获得硕士学位。为了提高可预测性和减少冰雹对社会日益显著的影响，本提案将实现以下四个目标：1）确定不同冰雹威胁等级（例如，大冰雹或10厘米或4英寸，大量的小冰雹）和识别制度，季节和区域差异。2）建立冰雹威胁等级发生和环境条件之间的物理关系。确定哪些胚胎源区特征会增加不同类别冰雹威胁的有利冰雹生长轨迹的可能性，以及这些特征在现实风暴环境中如何变化。3）根据新可用的时变雷达检索的风和浮力场以及地面冰雹观测，验证微物理复杂冰雹轨迹模型。4）整合有关环境控制、三维冰雹轨迹、和胚胎源区到CAM-HAILCAST冰雹模式，以提高业务预报冰雹威胁。目标1将使用一个广泛的冰雹风暴接近探空数据库从风暴预报中心（SPC），探索环境控制。目标2将使用理想化的模拟来探索对环境条件和微物理过程的敏感性。目标3将使用新开发的雷达导出的风和微物理数据集来驱动冰雹轨迹模型，该模型将通过地面冰雹观测进行验证。最后，改进的冰雹预测模型开发的目标4将测试对一个独立的子集冰雹威胁事件从SPC数据库。这项拟议的研究将提高对环境和风暴尺度下冰雹增长的基本过程以及这些过程如何在不同环境中变化的理解。它将确定哪些环境最有利于不同的冰雹威胁类别（如巨大的冰雹或大量的小冰雹）或冰雹大小。它也超越了纯粹的统计奋进，以确保物理过程的基础上的环境控制，为每一个冰雹威胁等级的理解，包括大的上升气流量，有利的位置胚胎源区，和适当的胚胎大小。这一奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

项目成果

Ice from Above: Toward a Better Understanding of Hailstorms

上面的冰：更好地了解冰雹

• DOI: 10.1029/2020eo148818
• 发表时间: 2020
• 期刊: Eos
• 作者: Allen, John;Giammanco, Ian;Kumjian, Matthew;Punge, Heinz;Kunz, Michael;Zhang, Qinghong;Groenemeijer, Pieter
• 通讯作者: Groenemeijer, Pieter

Hodographs and Skew Ts of Hail-Producing Storms

产生冰雹的风暴的均线图和倾斜 T 值

• DOI: 10.1175/waf-d-23-0031.1
• 发表时间: 2023
• 期刊: Weather and Forecasting
• 影响因子: 2.9
• 作者: Nixon, Cameron J.;Allen, John T.;Taszarek, Mateusz
• 通讯作者: Taszarek, Mateusz

Understanding Hail in the Earth System

• DOI: 10.1029/2019rg000665
• 发表时间: 2020-03
• 期刊: Reviews of Geophysics
• 影响因子: 25.2
• 作者: J. Allen;I. Giammanco;M. Kumjian;Heinz Jurgen Punge;Qinghong Zhang;P. Groenemeijer;M. Kunz;K. Ortega

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

• DOI: 10.1175/aies-d-22-0042.1
• 发表时间: 2023-06
• 期刊: Artificial Intelligence for the Earth Systems
• 作者: B. Scarino;K. Itterly;Kristopher Bedka;C. Homeyer;J. Allen;S. Bang;Daniel J. Cecil

Distinguishing between Hodographs of Severe Hail and Tornadoes

区分严重冰雹和龙卷风的速动仪

• DOI: 10.1175/waf-d-21-0136.1
• 发表时间: 2022
• 期刊: Weather and Forecasting
• 影响因子: 2.9
• 作者: Nixon, Cameron J.;Allen, John T.
• 通讯作者: Allen, John T.