Collaborative Research: Mesoscale Predictability Across Climate Regimes

对龙卷风、大冰雹和洪水等恶劣天气的预测不断提高，使天气预报能够更好地帮助社会为危险和破坏性风暴做好准备。这种改进很大程度上是通过使用模型来详细模拟大部分大气来理解强雷暴的原因，这一过程需要现代计算机的速度和性能。这样的计算能力可以为给定的风暴情况创建多个预报，而不仅仅是一个预报，突出显示大气中的特征——比如湿度程度或风廓线——导致不同严重程度的风暴。这些同步预报还揭示了即将到来的风暴有多大可能是严重的，这取决于不同的预报是否都一致地预测了严重的条件（严重事件的高可能性），或者如果预报显示了范围广泛的风暴（严重事件的低可能性）。虽然这些研究方法侧重于了解和改进日常的强风暴预测，但在不断变化的气候中，高影响天气事件的可预测性尚不清楚。这项研究旨在了解随着地球气候变暖，是否可以更好地预测严重风暴及其相关危害。这项研究的独特之处在于，它超越了其他试图揭示严重风暴是否会变得更频繁或更少的研究，而是确定它们是否更可预测，这一特征与不同气候所支持的一般大气条件有关。这项工作将通过创建和分析最近（20世纪末）和未来（21世纪末）气候的强风暴数值天气模式预报的大数据集来完成。具体地说，将评估不同世纪对强风暴情况的预报如何以及为什么会有不同的演变，以了解气候变化在大气预报中所起的作用。这项工作对科学界和社会有许多预期的影响。了解强风暴的概率预测是否会增加或减少不确定性，可以显示这种预测是否可以有效地用于社会应用。一个这样的例子包括水库运营，它依赖于对洪水风险的准确预测来有效地管理水资源。如果洪水变得更加可预测，像这样受益于预测确定性的应用可能会变得更加普遍，从而大大帮助区域供水，减轻气候变化对干旱地区的负面影响。这项研究还将涉及创建一个大型的强风暴解决模拟数据集，使希望分析数据的科学家能够研究强风暴与气候关系的其他方面，而不仅仅是这里所建议的。一些研究生和本科生将以几种方式参与研究：研究生和本科生的研究和通过期刊文章、学术课程、在大学专题讨论会和专业科学会议上的演讲进行传播。参与大学周围社区的普通公众和K-12学生也将受益于计划中的外展活动，包括周末在大学博物馆举办的活动，大学批准的夏令营，以及在休闲环境中促进与项目科学家一对一互动的开放日活动。该项目由大气与地球空间科学部的气候与大尺度动力学和物理与动态气象学项目以及大气与地球空间科学部共同资助，以支持提高各种机构类型的研究能力、能力和基础设施的项目，如GEO EMBRACE DCL所述。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。

The prediction of severe weather such as tornadoes, large hail, and flooding continues to improve, allowing weather forecasts to better help society prepare for dangerous and damaging storms. Much of this improvement has come through understanding the causes of severe thunderstorms using models that simulate large portions of the atmosphere in detail, a procedure that requires the speed and performance of modern-day computers. Such computational capability allows the creation of multiple forecasts instead of just one for a given storm situation, highlighting the features in the atmosphere – like the degree of moisture or the wind profile – that lead to storms of different severity. These simultaneous forecasts also reveal how likely it is that upcoming storms may be severe, based on whether the different forecasts all agree on severe conditions (high likelihood of a severe event) or if forecasts show storms with a wide range of magnitudes (lower likelihood of a severe event). While these research methods have focused on understanding and improving severe storm prediction on a day-to-day basis, the predictability of high-impact weather events in a changing climate is unclear. The research aims to understand whether severe storms and their associated hazards can be better predicted as Earth's climate warms. This research is unique in that it goes beyond other studies that seek to uncover whether severe storms will become more or less frequent, instead determining if they are more or less predictable, a characteristic linked to the general atmospheric conditions that different climates support. The work will be performed by creating and analyzing big datasets of numerical weather model forecasts of severe storms in both recent (end of 20th century) and future (end of 21st century) climates. Specifically, how and why forecasts for severe storm situations evolve differently in different centuries will be assessed to understand the role climate change plays in atmospheric prediction.There are numerous expected impacts of this work on the scientific community and society. Understanding if probabilistic forecasts of severe storms will have increased or decreased uncertainty could show whether such forecasts could be used effectively in societal applications. One such example includes water reservoir operations, which rely on accurate predictions of flood risk to efficiently manage water resources. If flooding were to become more predictable, applications like this that benefit from forecast certainty could become more common, substantially helping regional water supply and mitigating the negative consequences of climate change in areas that become drier. The research will also involve the creation of a large dataset of severe storm-resolving simulations, allowing scientists who wish to analyze the data to investigate other aspects of severe storm-climate relationships beyond that suggested here. Several graduate and undergraduate students will be involved in the research in several ways: graduate and undergraduate research and dissemination through journal articles, academic coursework, and presentations at university symposia and professional scientific conferences. The general public and K-12 students in communities surrounding the participating universities will also benefit from planned outreach events including weekend events at university museums, university-sanctioned summer camps, and open house events that promote 1-on-1 interaction in casual environments with project scientists.This project is jointly funded by the Climate and Large-Scale Dynamics and Physical and Dynamic Meteorology programs in the Division of Atmospheric and Geospace Sciences as well as the Division of Atmospheric and Geospace Sciences to support projects that increase research capabilities, capacity and infrastructure at a wide variety of institution types, as outlined in the GEO EMBRACE DCL.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.