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

HBCU-卓越研究：提高对美国东部降水极端事件的季节性和强度变化的了解

• 批准号: 1901426
• 负责人: Nirajan Dhakal
• 金额: $ 49.95万
• 依托单位: Spelman College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-15 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1901426&HistoricalAwards=false
• 关键词: HBCU; Excellence; Research; Improved; Understanding

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.

极端降水事件对生命和财产构成了许多威胁，因此确定其频率和强度具有科学和社会双重意义。但鉴于极端事件的定义是罕见的，这样的定性并不容易。例如，“百年一遇的洪水”是一种如此之大的洪水，以至于它不太可能在一个世纪内发生一次以上（正式地说，它在任何给定年份发生的几率不到1%）。进一步的考虑是，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，并且由于全球变暖而随时间变化。在受登陆飓风影响的地区，考虑到飓风与其他降雨风暴在许多方面的不同，单独评估它们对极端降水的贡献也很重要。这里进行的工作使用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。一组任务旨在描述极端降水的季节性特征，了解极端事件的时间往往是多模式的，可能与预先定义的季节不太一致。极端事件的季节性是用圆形密度方法评估的，在这种方法中，年周期被映射到单位圆上，极端事件在一年中发生的时间由角度相关的概率密度表示。第二组任务是利用分位数回归模型评估概率分布的长期变化，并进一步研究大尺度气候模式对降水概率的影响。额外的工作评估飓风对研究领域极端降水统计的影响。由于极端事件统计在预测和减轻与降水有关的危害方面的价值，这项工作具有更广泛的影响。这些项目特别关注作为交通问题的雨水管理，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的审查。此外，该项目还为两名本科生提供带薪暑期研究培训，并资助他们参加全国本科生研究委员会会议。学生指导也通过小组会议、演讲、书面反馈和期刊俱乐部进行。该项目还为博士后研究员提供支持和培训。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。

项目成果

Changing seasonality of daily and monthly precipitation extremes for the contiguous USA and possible connections with large‐scale climate patterns

• DOI: 10.1002/joc.7994
• 发表时间: 2023-01
• 期刊: International Journal of Climatology
• 作者: N. Dhakal;Bhikhari Tharu;Ali Aljoda