Study of Convective Hazards under Anthropogenic Climate Change using innovative approaches

很难评估雷暴和龙卷风在温暖的气候中会如何变化，因为各种因素决定了冰雹，强风和龙卷风的强度和频率。 先前确定恶劣天气潜在变化的努力是基于对恶劣天气可能性的间接和统计测量。 在这个项目中，研究小组将调查历史上的恶劣天气事件，然后修改它们的环境，以匹配气候模型模拟的输出。 该项目的结果将是更好地了解这些危险的潜在原因和频率。 另一项工作将利用人口和住房数据，帮助估计气候变暖时严重天气灾害的影响，从而解决人类易受这些灾害影响的问题。 研究生将参与该项目，确保下一代研究人员的专业发展。研究团队将使用伪全球变暖（PGW）方法进行数值模拟研究，其中各种历史对流天气事件将在真实的4D环境中以及在经过气候变化措施修改的4D环境中进行模拟。 研究小组认为，过去关于这一主题的工作，包括他们自己的工作，仅限于使用环境参数和动态降尺度，这两种方法都有明显的缺点。 PGW技术为动力学和微物理过程中的因果关系的实验和检查提供了一个灵活的框架，并允许使用更高的分辨率和单一情况下的多个实现。 该项目将使用WRF-ARW，并从几个CMIP-5和CMIP-6气候变化三角洲模型中获得输入。 将讨论三个假设：1）在人为气候变化（ACC）下，代表性和特征性的暖（冷）季龙卷风将不那么（更）强烈，2）在ACC下，代表性的破坏性直线风事件将更强烈，但相对较短，3）尽管垂直风切变减少，融化层高度增加，在ACC下，冰雹带面积和地面冰雹的大小通常会增加。2该奖项反映了NSF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。

It is difficult to assess how severe thunderstorms and tornadoes may change in a warmer climate because various factors dictate the strength and frequency of hail, severe winds, and tornadoes. Prior efforts to determine potential changes in severe weather have been based on indirect and statistical measures of the likelihood for severe weather. In this project, the research team will instead investigate historical severe weather events and then modify their environments to match outputs from climate model simulations. The result of the project will be a better physical understanding of the potentials causes and frequency of these hazards. An additional effort will use population and housing data to help estimate the impacts of severe weather hazards in a warmer climate, thereby addressing human vulnerability to these hazards. Graduate students would be involved in the project, ensuring the professional development of the next generation of researchers.The research team will conduct a numerical modeling study using the pseudo-global-warming (PGW) approach, wherein a variety of historical convective-weather events will be simulated both in their true 4D environment as well as in a 4D environment modified by a measure of climate change. The research team argues that past work, including their own, on the topic has been limited to the use of environmental parameters and dynamic downscaling, both of which have significant drawbacks. The PGW technique provides a flexible framework for experimentation and examination of cause and effect in dynamical and microphysical processes and allows for the use of higher resolutions and multiple realizations of a single case. The project will use the WRF-ARW with input from several of the CMIP-5 and CMIP-6 models for the climate change delta. Three hypotheses will be addressed: 1) Representative and characteristic warm- (cool-) season tornadoes will be less (more) intense under anthropogenic climate change (ACC), 2) Representative damaging straight-line wind events will be more intense, but relatively shorter-lived, under ACC, and 3) Despite decreases in vertical wind shear and increases in the height of the melting level, hailfall swath area and hailstone size at the ground will generally increase under ACC.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.