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Advancing Our Understanding of Intraseasonal United States Severe Convective Storm Variability

增进我们对美国季节内强对流风暴变化的理解

基本信息

批准号：
2048770
负责人：
Vittorio Gensini
金额：
$ 47.47万
依托单位：
Northern Illinois University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048770&HistoricalAwards=false
关键词：
Advancing Our Understanding Intraseasonal United

项目摘要

Severe thunderstorms and associated hazardous weather are often concentrated in time, where outbreaks of severe weather are clustered over short periods on the order of days to weeks. The frequency of favorable weather patterns for severe thunderstorms suggests the connection to large scale weather patterns. This award will allow for further study of the physical mechanisms that drive intraseasonal variability in severe convective storms. The outcomes from this award will be based on the potential for improvement in the prediction of severe weather outbreaks at the subseasonal scale, which is relevant to stakeholders in the agriculture, aviation, and insurance sectors of the economy. Outreach will be conducted to improve public understanding of science, and education and training will take place through the inclusion of multiple graduate and undergraduate students in the project. Students at the US Naval Academy will also be involved in the project as collaborators.The research team will conduct a study to advance community understanding of the physical mechanisms that drive observed intraseasonal variability in severe convective storms and their associated hazards. The researchers hypothesize that extremely active and inactive episodes of severe convective storms in the continental US may result from the projection of intraseasonal teleconnections onto synoptic and mesoscale severe weather parameters. The three sources of forcing for US weather variability are the Madden-Julian Oscillation (MJO), Atmospheric angular momentum (AAM) or Global Wind Oscillation (GWO), and the El Nino Southern Oscillation (ENSO). The following science questions will be addressed through the use of reanalysis data, historical records of severe storm activity, and compositing techniques: 1) What are the physical pathways by which the intraseasonal frequency of severe convective storms is modulated by the MJO and GWO, what fraction of intraseasonal severe storm variability is explained by the MJO and GWO, and at what time lags does the modulation pathway tend to be strongest and weakest? 2) What observational evidence, taken from Rossby wave packet tracing and composites of synoptic- and mesoscale variables known to be associated with severe weather in the U.S. physically supports intraseasonal severe weather variability? 3) How does the modulation of severe weather events and favorable environmental conditions vary by geographic region, by time of year, by diurnal cycle, and by phase of ENSO and how does the time lag identified in question 1 vary with any of the above factors? 4) How common are intraseasonal Forecasts of Opportunity, null events, and extended periods with little-to-no severe convective storm activity and on what do they depend?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.

强雷暴和相关的危险天气往往集中在时间上，在那里，恶劣天气的爆发集中在几天到几周的短时间内。强雷暴有利天气模式的频率表明与大尺度天气模式有关。该奖项将允许进一步研究驱动强对流风暴季节内变化的物理机制。该奖项的结果将基于在亚季节尺度上改善恶劣天气爆发预测的潜力，这与农业，航空和保险部门的利益相关者有关。将开展外联活动，以提高公众对科学的理解，并将通过将多名研究生和本科生纳入该项目来开展教育和培训。美国海军学院的学生也将作为合作者参与该项目。研究小组将进行一项研究，以促进社区对驱动观测到的强对流风暴季节内变化及其相关危害的物理机制的理解。研究人员假设，美国大陆极端活跃和不活跃的强对流风暴事件可能是由于季节内遥相关对天气和中尺度恶劣天气参数的预测。美国天气变率的三个强迫源是马登-朱利安振荡（MJO），大气角动量（AAM）或全球风振荡（GWO）和厄尔尼诺南方涛动（ENSO）。将通过使用再分析数据、强风暴活动的历史记录和合成技术来解决以下科学问题： 1)MJO和GWO调制季内强对流风暴频率的物理路径是什么？MJO和GWO解释了季内强风暴变率的多少？调制路径在什么样的时滞下最强和最弱？ 2)从Rossby波包追踪和已知与美国恶劣天气相关的天气和中尺度变量的合成中获得的观测证据在物理上支持季节内恶劣天气变率？ 3)恶劣天气事件和有利环境条件的调节如何随地理区域、一年中的时间、日周期和ENSO阶段而变化，问题1中确定的时滞如何随上述任何因素而变化？ 4)季节内机会预报、零事件和长时间几乎没有强对流风暴活动的情况有多常见？它们取决于什么？该奖项反映了NSF的法定使命，并被认为是值得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的支持。