HBCU-Excellence in Research: Improved Understanding of the Changing Seasonality and Magnitude of Precipitation Extremes in the Eastern United States

极端降水事件对生命和财产构成许多威胁，因此，确定其频率和程度具有科学和社会意义。但考虑到极端事件的定义是罕见的，这样的描述并不容易。例如，“百年一遇”指的是一场洪灾，其规模之大，不太可能在一个世纪内发生一次以上(从形式上讲，它在任何一年发生的概率都不到1%)。进一步考虑的是，极端降水的可能性受到季节和气候变化(如厄尔尼诺事件)的影响，也受到全球变暖导致的时间变化的影响。在受登陆飓风影响的地区，考虑到飓风与其他降雨风暴的许多不同之处，单独评估它们对极端降水的贡献也很重要。这里所做的工作使用了各种统计技术来估计美国东部极端降水事件的频率和强度。一组任务试图描述极端降水的季节性，理解极端事件的时间安排往往是多模式的，可能不会与预先定义的季节很好地匹配。极端事件的季节性是使用圆形密度方法来评估的，在该方法中，将年度周期映射到单位圆，并用角度相关的概率密度来表示一年中极端事件的发生时间。第二组任务使用分位数回归模型评估概率分布的长期变化，并进一步调查大尺度气候模式对降水概率的影响。其他工作是评估飓风对研究领域极端降水统计数据的影响。由于极端事件统计数据对于预测和减轻与降水有关的灾害的价值，这项工作具有更广泛的影响。私人投资机构特别关注将雨水管理作为交通问题，该项目包括对国家交通部门发布的雨水基础设施设计标准进行审查。此外，该项目还为两名本科生提供有偿暑期研究培训，这两名本科生也得到资助，参加本科生研究理事会的全国会议。学生辅导也通过小组会议、演讲、书面反馈和日记俱乐部进行。该项目还为博士后研究人员提供支持和培训。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。

Extreme precipitation events pose numerous threats to life and property, thus characterization of their frequency and magnitude is of both scientific and societal interest. But such characterization is not easy given that extreme events are, by definition, rare. For example a "100 year flood" is a flood so large that it is unlikely to occur more than once a century (formally, it has less than a one percent chance of happening in any given year). A further consideration is that extreme precipitation likelihood is affected by the season and by climate variations such as El Nino events, and also changes over time as a consequence of global warming. In regions affected by landfalling hurricanes it is also important to separately assess their contribution to extreme precipitation, given the many ways in which hurricanes differ from other rain-bearing storms.Work performed here uses a variety of statistical techniques to estimate the frequency and magnitude of extreme precipitation events over the eastern US. One set of tasks seeks to characterize the seasonality of extreme precipitation, with the understanding that extreme event timing is often multimodal and may not align well with pre-defined seasons. The seasonality of extremes is assessed using a circular density approach in which the annual cycle is mapped to the unit circle and the timing of extreme events over the course of the year is represented by an angle-dependent probability density. A second set of tasks evaluates secular changes in probability distributions using quantile regression models, and further investigates the effects of large-scale climate patterns on precipitation probabilities. Additional work evaluates the impact of hurricanes on statistics of extreme precipitation in the study domain.The work has broader impacts due to the value of extreme event statistics for anticipating and mitigating precipitation-related hazards. The PIs have a specific focus on stormwater management as a transportation issue, and the project includes a review of standards for stormwater infrastructure design issued by state departments of transportation. In addition, the project provides paid summer research training to two undergraduate students who are also funded to attend the national meeting of the Council on Undergraduate Research. Student mentoring is also conducted through group meetings, presentations, written feedback, and a journal club. The project also provides support and training to a postdoctoral research associate.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.