Towards an Improved Mechanistic Understanding of Dangerous Heat Extremes Affecting US Cities in the Historical Records and Future Climate Projections

改善历史记录和未来气候预测中影响美国城市的危险极端高温的机制

• 批准号: 2243602
• 负责人: Andrew Dessler
• 金额: $ 59.12万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243602&HistoricalAwards=false
• 关键词: Towards; Improved; Mechanistic; Understanding; Dangerous

Heat extremes are happening more often and negatively affect natural environments, communities, and public health. This project studies these heat extremes, particularly those causing increased mortality in urban areas of the United States, with the goal of enhancing our understanding of these severe heat events and their anticipated changes in the coming decades. Initially, the project evaluates different metrics to identify climate variables that most robustly represent heat risks. Notably, it goes beyond temperature, including factors like humidity, solar and thermal radiation, and wind speed at the surface. It then connects major historical heat extremes to patterns in weather and long-term climate drivers. The results from analyzed data will be compared to output from global climate models using advanced statistical techniques. Lastly, the project uses high-resolution climate predictions to understand how lethal heat events may change in the future.This work will extend the community’s understanding of extreme heat and mortality, but the importance of this research extends beyond scientific understanding. Communities vulnerable to climate change, especially those with limited means to adapt, face substantial risks from heat extremes. Despite recognizing the social implications of these heat extremes, our ability to predict them on a seasonal to decadal scale is insufficient. This project addresses this issue by using a data-driven approach to associate lethal heat extremes with large-scale weather patterns. The findings from this research will be communicated to public health and urban planning partners to aid in their response to these threats. The physical insights generated through these analyses can help guide interpretation of climate model-based projection of future occurrence and severity of these dangerous heat extremes. Additionally, this project offers valuable training for graduate students in statistical modeling, data visualization, climate modeling, and climate communication. Thus, it contributes to the broader scientific community and society, not only through its results but also by training the next generation of climate scientists.This project is co-funded by the Directorate for Geosciences to support AI/ML advancement in the geosciences.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.

极端高温事件越来越频繁地发生，并对自然环境、社区和公共卫生产生负面影响。该项目研究这些极端高温事件，特别是导致美国城市地区死亡率增加的极端高温事件，目的是增强我们对这些严重高温事件的了解。最初，这些项目采用了不同的指标来确定最能代表热风险的气候变量，值得注意的是，它不仅仅包括温度，还包括湿度、太阳和热辐射以及地表风速等因素的评估。然后它将历史上主要的高温极端事件与模式联系起来。最后，该项目将利用先进统计技术将分析数据的结果与全球气候模型的输出进行比较，以了解致命的高温事件未来可能发生的变化。这项工作将扩大社区对极端高温和死亡率的认识，但这项研究的重要性超出了科学理解的范畴，尽管认识到极端高温的社会影响，但易受气候变化影响的社区，尤其是那些适应能力有限的社区，仍面临着巨大的风险。对于这些极端高温，我们预测它们的能力该项目通过使用数据驱动的方法将致命的极端高温与大规模天气模式联系起来来解决这个问题，该研究的结果将传达给公共卫生和城市规划合作伙伴，以帮助解决这一问题。通过这些分析产生的物理见解可以帮助指导解释基于气候模型的对这些危险极端高温的未来发生和严重程度的预测。此外，该项目还为研究生提供了统计建模和数据可视化方面的宝贵培训。 、气候建模和气候通信。不仅通过其成果，还通过培训下一代气候科学家，向更广泛的科学界和社会提供帮助。该项目由地球科学理事会共同资助，以支持地球科学领域的 AI/ML 进步。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。