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继续改善，使天气预报能够更好地帮助社会为危险和破坏性的风暴做好准备。这种改进在很大程度上是通过使用详细模拟大部分大气的模型来理解严重雷暴的原因，这一过程需要现代计算机的速度和性能。这种计算能力允许为给定的风暴情况创建多个预报，而不是只创建一个预报，突出大气中导致不同严重程度风暴的特征--如湿度或风廓线。这些同时的预报还揭示了即将到来的风暴可能是严重的可能性有多大，这是基于不同的预报是否都符合严重条件(严重事件的可能性很高)，或者预报是否显示了大范围的风暴(严重事件的可能性较低)。虽然这些研究方法侧重于理解和改进日常的强风暴预报，但气候变化中的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险。这项研究的独特之处在于，它超越了其他研究，这些研究试图揭示严重风暴是会变得更频繁还是更少，而是确定它们是更可预测还是更难预测，这一特征与不同气候支持的一般大气条件有关。这项工作将通过创建和分析近期(20世纪末)和未来(21世纪末)气候中强风暴的数值天气模式预报的大数据集来进行。具体地说，将评估严重风暴情况的预报在不同世纪如何以及为什么演变不同，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。了解对严重风暴的概率预报是否会增加或减少不确定性，可以表明这种预报是否可以有效地应用于社会应用。一个这样的例子包括水库调度，它依赖于对洪水风险的准确预测来有效地管理水资源。如果洪水变得更可预测，这样受益于预报确定性的应用可能会变得更加普遍，极大地帮助地区供水，并减轻气候变化在变得更加干燥的地区的负面后果。这项研究还将涉及创建一个严重风暴消解模拟的大型数据集，让希望分析这些数据的科学家能够调查严重风暴-气候关系的其他方面，而不是这里建议的方面。几名研究生和本科生将通过几种方式参与研究：研究生和本科生通过期刊文章、学术课程以及在大学研讨会和专业科学会议上的演讲进行研究和传播。参与大学周边社区的普通公众和K-12学生也将受益于计划中的外联活动，包括周末在大学博物馆举行的活动，大学批准的夏令营，以及促进在非正式环境中与项目科学家进行一对一互动的开放参观活动。该项目由大气和地球空间科学部门的气候和大型动力学以及物理和动态气象学项目以及大气和地球空间科学部门联合资助，以支持各种机构类型的研究能力、能力和基础设施的提高。正如GEO拥抱DCL中概述的那样，该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.