Study of Convective Hazards under Anthropogenic Climate Change using innovative approaches

由于各种因素决定了冰雹、强风和龙卷风的强度和频率，很难评估在气候变暖的情况下雷暴和龙卷风的严重程度。以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，研究小组将转而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结果。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。另一项努力将使用人口和住房数据，以帮助估计气候变暖时严重天气灾害的影响，从而解决人类对这些灾害的脆弱性。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，一直局限于使用环境参数和动态缩小尺度，这两种方法都有重大缺陷。PGW技术为实验和检验动力学和微物理过程中的因果关系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的多种实现。该项目将使用WRF-ARW，并使用气候变化三角洲的几个CMIP-5和CMIP-6模型的输入。将提出三个假设：1)在人为气候变化(ACC)下，典型的和特征的暖(冷)季龙卷风将不那么(更)强烈；2)在ACC下，具有代表性的破坏性直线风事件将更强烈，但相对较短的生存时间；以及3)尽管垂直风切变减少，融化层高度增加，但在ACC下，地面的冰雹条带面积和冰雹大小通常将增加。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。

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.