Collaborative Research: Understanding the Origins of Hazardous Convective Weather Environments through Reduced-complexity Climate Modeling Experiments

合作研究：通过降低复杂性的气候模拟实验了解危险对流天气环境的起源

• 批准号: 1648629
• 负责人: Kevin Reed
• 金额: $ 33.08万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1648629&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Origins; Hazardous

Hazardous convective weather (HCW), including tornadoes, damaging wind, and hail, poses significant risk to life and property each year. HCW events are small scale with short duration time, which makes it extremely difficult to predict their occurrence even a few hours in advance. However, they do often form and develop preferentially within certain larger-scale environments and primarily in a few geographical regions globally, the most prominent of which is the Eastern United States. Why these potentially deadly larger-scale environments are confined to such specific regions is not well understood. This lack of knowledge greatly limits our ability to predict how the risk posed to society by these events vary on inter-annual and multi-decadal timescales. This research project aims to examine the factors (such as land-sea contrasts, elevated terrain upstream, and their interferences with atmospheric jet streams) that contribute to environments favorable for the generation of HCW events. Because it is difficult to disentangle specific physical mechanisms that are responsible for HCW environments using observations and realistic modeling simulations alone, the PIs will perform a series of experiments using reduced-complexity models where gross representations of land and terrain are imposed under various complexity configurations. The project is designed to enhance understanding of the fundamental processes underlying the natural hazards associated with convective weather. It aims to improve our capability to model weather hazards by determining the key elements that must be included in models to capture the distribution of HCWs and the risks they pose. The work addresses forecasting in an aggregate sense, focusing on how HCW activity is likely to change with large-scale conditions. The goal is to predict how HCW environments and, in turn, how the associated societal impacts, including loss of life and property damage, may change from year to year, decade to decade, and beyond. The project will train graduate student and post-doctoral scientists who will make future contributions to the burgeoning field of hazardous convective weather and climate.

危险对流天气 (HCW)，包括龙卷风、破坏性大风和冰雹，每年都会对生命和财产造成重大风险。医护人员事件规模小、持续时间短，因此即使提前几个小时预测其发生也极其困难。然而，它们确实经常在某些更大范围的环境中优先形成和发展，主要是在全球的几个地理区域，其中最突出的是美国东部。为什么这些潜在致命的大规模环境仅限于这些特定区域尚不清楚。这种知识的缺乏极大地限制了我们预测这些事件对社会造成的风险在年际和数十年时间尺度上如何变化的能力。该研究项目旨在研究有利于 HCW 事件发生的环境因素（例如陆地与海洋对比、上游地形升高及其对大气急流的干扰）。由于仅使用观察和现实建模模拟很难理清造成 HCW 环境的特定物理机制，PI 将使用降低复杂性的模型进行一系列实验，其中在各种复杂性配置下强加土地和地形的总体表示。该项目旨在加强对与对流天气相关的自然灾害的基本过程的了解。 它旨在通过确定模型中必须包含的关键要素来捕获医护人员的分布及其构成的风险，从而提高我们对天气灾害进行建模的能力。 这项工作涉及总体意义上的预测，重点关注医护人员的活动可能如何随着大规模条件的变化而变化。 目标是预测医护人员的环境以及相关的社会影响（包括生命损失和财产损失）每年、十年乃至更长时间可能发生的变化。该项目将培训研究生和博士后科学家，他们将为危险对流天气和气候这一新兴领域做出未来的贡献。

项目成果

The Role of Elevated Terrain and the Gulf of Mexico in the Production of Severe Local Storm Environments over North America

高地和墨西哥湾在北美地区严重风暴环境中的作用

• DOI: 10.1175/jcli-d-20-0607.1
• 发表时间: 2021-10
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Li, Funing;Chavas, Daniel R.;Reed, Kevin A.;Rosenbloom, Nan;Dawson II, Daniel T.
• 通讯作者: Dawson II, Daniel T.

Characterizing the North American Monsoon in the Community Atmosphere Model: Sensitivity to Resolution and Topography

在社区大气模型中描述北美季风：对分辨率和地形的敏感性

• DOI: 10.1175/jcli-d-18-0567.1
• 发表时间: 2019-11-12
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: A. Varuolo;K. Reed;B. Medeiros
• 通讯作者: B. Medeiros

The Dependence of Tropical Modes of Variability on Zonal Asymmetry

热带变率模式对纬向不对称性的依赖性

• DOI: 10.1029/2021gl093966
• 发表时间: 2021-04-23
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Xiaoning Wu;K. Reed;C. Wolfe;G. Marques;S. Bachman;F. Bryan
• 通讯作者: F. Bryan

On resolution sensitivity in the Community Atmosphere Model

论社区大气模型中的分辨率敏感性

• DOI: 10.1002/qj.3873
• 发表时间: 2020-09
• 期刊: Quarterly Journal of the Royal Meteorological Society
• 影响因子: 8.9
• 作者: Herrington, Adam R.;Reed, Kevin A.
• 通讯作者: Reed, Kevin A.

Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

ERA5 再分析和 CAM6 模拟中北美地区严重局地风暴环境和天气尺度特征的气候学

• DOI: 10.1175/jcli-d-19-0986.1
• 发表时间: 2020-10
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: Li, Funing;Chavas, Daniel R.;Reed, Kevin A.;Dawson II, Daniel T.
• 通讯作者: Dawson II, Daniel T.