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: 1855100
• 负责人: Conrad Ziegler
• 金额: $ 16.86万
• 依托单位: University of Oklahoma Norman Campus
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855100&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1000万处房产遭到冰雹破坏。最近的灾难性冰雹的例子包括2017年影响丹佛的23亿美元损失冰雹事件，2016年4月在圣安东尼奥发生的14亿美元损失冰雹事件，其中包括4.5英寸以上的冰雹，以及2012年在德克萨斯州阿马里洛发生的冰雹，产生了2米厚的冰雹，冲毁了道路，导致交通停滞。不幸的是，这些事件都没有事先预料到。该提案将确定哪种类型的环境会产生如此高影响的冰雹事件，以及产生冰雹的物理过程如何受到环境过程的影响。将对冰雹增长的认识提高到国家天气预报模型内的冰雹预报系统中，以提高冰雹预报水平，这符合NSF促进国民健康、繁荣、福利和保障国防的使命。随着短期（1小时）冰雹预报的改进，可以避免直接威胁，例如建议户外体育场馆或活动的参与者寻求庇护。改进中期预报（1-3天）可能导致需要更多时间密集规划的建议行动，例如将飞机移到避难所，通知保险理算员，以及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，如巨大冰雹或大量小冰雹（或“暴雪”冰雹），将使预报员能够更好地为公众做好准备：例如，预测的“暴雪”冰雹事件可能需要一个城市准备好犁地设备，并建议公众避开可能发生洪水的低洼地区。此外，了解哪种环境与哪种冰雹事件类型有关，是在较长时间尺度（从亚季节尺度到季节尺度以及更长的时间尺度）上进行冰雹预报的必要步骤。该提案还将支持一名获得博士学位的研究生，两名获得硕士学位的研究生和三名本科生。为了提高可预测性并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，巨型冰雹或10厘米或4英寸，大量小冰雹）对冰雹产生的环境控制，并确定制度，季节和区域差异。2)建立冰雹威胁等级发生与环境条件的物理关系。确定在不同类型的冰雹威胁中，什么样的胚胎源区域特征会增加有利冰雹生长轨迹的概率，以及这些特征在现实风暴环境中如何变化。3)根据最新的时变雷达反演风场和浮力场以及地面冰雹观测资料，验证微物理复杂冰雹轨迹模型。4)将环境控制、三维冰雹轨迹和胚源区域的新知识整合到CAM-HAILCAST冰雹模型中，以改进冰雹威胁的业务预报。目标1将使用风暴预测中心（SPC）提供的广泛的冰雹接近探测数据库来探索环境控制。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衍生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，在目标4中开发的改进的冰雹预报模型将针对SPC数据库中冰雹威胁事件的独立子集进行测试。这项拟议的研究将提高对环境和风暴尺度下冰雹生长的基本过程的理解，以及这些过程在不同环境下的变化。它将确定哪种环境最有利于不同的冰雹威胁等级（如巨大冰雹或大量小冰雹）或冰雹大小。它也超越了纯粹的统计努力，以确保了解每种冰雹威胁等级的环境控制的物理过程，包括大的上升气流量，胚胎源区域的有利位置和适当的胚胎大小。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。