Collaborative Research: Combining Self-organized Maps and Idealized Storm-scale Simulations to Investigate the Effect of Future Climate Change on Severe Convective Storms
合作研究:结合自组织地图和理想化风暴规模模拟来研究未来气候变化对强对流风暴的影响
基本信息
- 批准号:2209052
- 负责人:
- 金额:$ 45.01万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-07-01 至 2025-06-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Severe thunderstorms and tornadoes cause significant damage and loss of life each year worldwide. It remains unclear whether future climate change will make this type of extreme weather worse. This project applies a new methodology to examine how severe thunderstorms and tornadoes may change in a future, warmer climate. This topic is difficult because climate change is a global phenomenon, yet thunderstorms are small – typically less than a few miles in diameter. Different types of computer models can be used to understand future climate change (climate models) and to simulate thunderstorms (storm models). However, one model cannot do both at the same time because of limits on computer power. To overcome this barrier, this project first uses data-based methods to examine how the environments that typically generate severe thunderstorms may change in climate model simulations. The effect of these changes on severe thunderstorms and tornadoes is then tested in simulations using a storm model. The results of both steps can be combined together to examine how severe thunderstorms may change in the future, which will help society better plan and adapt. Recent research suggests that future climate change may enhance the frequency and/or severity of severe convective storms (SCS), including severe thunderstorms and tornadoes. However, studies to date have focused principally on the large-scale environments favorable for SCS activity while neglecting potential changes in storm-scale dynamics. This project integrates climate models, machine learning, and idealized storm-scale ensemble simulations to understand how SCS activity may change in a future warmer climate. This is the first effort to examine future changes in SCS activity by simultaneously accounting for both changes in large-scale environments and storm-scale dynamics. The project has three objectives: 1. Use self-organized maps to quantify changes in structure and variability in SCS soundings in a future warmer climate; 2. Use idealized storm-scale simulations to examine how these changes in SCS soundings will alter probabilities of SCS activity and hazards; 3. Combine results to investigate how SCS activity and hazards may shift geographically and seasonally in a future warmer climate, and understand the underlying environmental vs. storm-scale drivers. This novel approach greatly reduces the high complexity of this problem at both large and small scales across climate states. The outcomes of the project will be compared to prior approaches to this problem to yield a more comprehensive understanding of how SCS activity may change in a future warmer climate.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.
严重的雷暴和龙卷风每年在世界范围内造成重大的破坏和生命损失。目前尚不清楚未来的气候变化是否会使这种极端天气变得更糟。该项目采用一种新的方法来研究在未来变暖的气候下,严重的雷暴和龙卷风会如何变化。这个话题很困难,因为气候变化是一个全球性的现象,而雷暴的直径通常小于几英里。不同类型的计算机模型可用于了解未来的气候变化(气候模型)和模拟雷暴(风暴模型)。然而,由于计算机能力的限制,一个模型不能同时做到这两点。为了克服这一障碍,该项目首先使用基于数据的方法来研究气候模型模拟中通常产生严重雷暴的环境如何变化。这些变化对强雷暴和龙卷风的影响,然后在模拟中使用风暴模型进行测试。这两个步骤的结果可以结合在一起,以研究严重雷暴在未来可能如何变化,这将有助于社会更好地规划和适应。最近的研究表明,未来的气候变化可能会增加强对流风暴(SCS)的频率和/或严重程度,包括强雷暴和龙卷风。然而,迄今为止的研究主要集中在有利于南海活动的大尺度环境上,而忽视了风暴尺度动力学的潜在变化。该项目整合了气候模型、机器学习和理想风暴尺度集合模拟,以了解南海活动如何在未来变暖的气候中发生变化。这是通过同时考虑大尺度环境和风暴尺度动力学的变化来研究南海活动未来变化的第一次努力。该项目有三个目标:1。使用自组织地图量化未来变暖气候下南海探测的结构变化和变异性;2. 使用理想的风暴尺度模拟来研究南海探测的这些变化将如何改变南海活动和危害的可能性;3. 结合结果,研究在未来变暖的气候中,南海活动和危害如何在地理和季节上发生变化,并了解潜在的环境与风暴尺度驱动因素。这种新颖的方法大大降低了这个问题在气候状态的大尺度和小尺度上的高度复杂性。该项目的结果将与先前解决该问题的方法进行比较,以更全面地了解南海活动在未来变暖的气候中如何变化。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
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Entrainment Makes Pollution More Likely to Weaken Deep Convective Updrafts Than Invigorate Them
- DOI:10.1029/2023gl103314
- 发表时间:2023-06
- 期刊:
- 影响因子:5.2
- 作者:J. Peters;Z. Lebo;D. Chavas;Chun‐Yian Su
- 通讯作者:J. Peters;Z. Lebo;D. Chavas;Chun‐Yian Su
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Daniel Chavas其他文献
Daniel Chavas的其他文献
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{{ truncateString('Daniel Chavas', 18)}}的其他基金
Ice Storm Risk Workshop; West Lafayette, Indiana; October 11-12, 2021
冰暴风险研讨会;
- 批准号:
2144406 - 财政年份:2021
- 资助金额:
$ 45.01万 - 项目类别:
Standard Grant
CAREER: Climate Controls on Hurricane Landfall via the Subtropical High
职业:对通过副热带高压登陆的飓风进行气候控制
- 批准号:
1945113 - 财政年份:2020
- 资助金额:
$ 45.01万 - 项目类别:
Standard Grant
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:
1648681 - 财政年份:2017
- 资助金额:
$ 45.01万 - 项目类别:
Standard Grant
AGS-PRF: Improving Tropical Cyclone Risk Assessment by Incorporating Storm Size Physics
AGS-PRF:通过结合风暴大小物理学改进热带气旋风险评估
- 批准号:
1331362 - 财政年份:2013
- 资助金额:
$ 45.01万 - 项目类别:
Fellowship Award
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- 批准号:10774081
- 批准年份:2007
- 资助金额:45.0 万元
- 项目类别:面上项目
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