CAREER: CAS-Climate: Climate Driven Risks to Urban Environment – Hybrid Modeling and Adaptation Strategies

目前全球范围的地球系统研究给城市地区留下了严重的空白和障碍，导致在理解城市气候驱动风险方面存在系统性缺陷，并为基础设施系统设计和运营提供信息面临重大挑战。本项目将通过解决两个首要的研究问题来推进全球城市科学和工程，从而减轻这些障碍：(i)大规模气候变化与城市化如何影响当地城市气候？（ii）这些城市场所知识如何为基础设施系统和适应策略的相关风险提供信息？该项目的成果将：(i)推进全球城市气候变化、影响和解决方案的知识前沿；（ii）提供由城市化和温室气体（GHG）变暖驱动的局地尺度城市气候变化、变率和不确定性的全球尺度多模式特征；(3)有助于建立一个新的动态城市社区地球系统模型（CESM）；(4)建立一个新的混合城市建模框架，以帮助形成新的全球城市科学和工程。该项目旨在通过开发一种结合基于过程的建模和深度学习方法的新的混合建模框架，为城市气候科学与工程的新领域做出贡献。该项目将推进气候驱动的建筑环境风险和适应战略方面的知识前沿。本研究的目标是：(i)在温室气体（GHG）变暖与城市化相结合的情况下，对城市气候变化、变率和不确定性进行稳健表征；（ii）利用稳健的城市预测，为基础设施系统的设计和运行提供信息；（iii）建立一种方法，在大尺度上评估和设计适应解决方案。研究工作将与一项教育计划相结合，旨在(i)激励、吸引和激励年轻人和公众解决关键的城市挑战，（ii）在城市气候科学和工程方面建立融合教育，以培养学生的创造力。将开发并公开发布一个在线、互动的全球城市气候风险地图网络工具。每年的夏季课程都将设计和展示实践课程和演示，以吸引K-12学生，特别是女性和代表性不足的学生。将编制和实施新的跨部门系列研讨会和新的课程材料。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。

Current global-scale Earth systems research leaves critical gaps and barriers for urban areas, which leads to systematic deficiencies in understanding urban climate-driven risks and critical challenges for informing infrastructure system design and operation. This project will mitigate these barriers by advancing global urban science and engineering through addressing two overarching research questions: (i) how does large-scale climate change coupled with urbanization affect local urban climates? and (ii) how can this urban locale knowledge inform the associated risks to infrastructure systems and adaptation strategies? Outcomes from this project will: (i) advance the knowledge frontier of global urban climate change, impacts, and solutions; (ii) provide a global-scale multi-model characterization of local-scale urban climate change, variability, and uncertainty driven by urbanization coupled with greenhouse gas (GHG) warming; (iii) contribute to development of a new dynamic-urban Community Earth System Model (CESM), and (iv) build a new hybrid urban modeling framework to help forge new global urban science and engineering.This project aims to contribute to the new field of urban climate science and engineering through developing a new hybrid modeling framework that combines process-based modeling and deep learning approaches. The project will advance the knowledge frontier in climate-driven risks to built environments and adaptation strategies. Objectives of the research are to (i) robustly characterize urban climate change, variability, and uncertainty under greenhouse gas (GHG) warming coupled with urbanization, (ii) establish a pathway to inform infrastructure system design and operation using robust urban projections, and (iii) establish a methodology to evaluate and devise adaptation solutions on large scales. Research efforts will be integrated with an educational plan designed to (i) motive, engage and inspire young minds and the public to address critical urban challenges and (ii) forge convergent education in urban climate science and engineering to foster students’ creativity. An online, interactive Global Urban Climate Risks Map webtool will be developed and publicly released. Hands-on sessions and demos will be designed and showcased every year at UIUC summer programs to engage K-12 students, especially female and underrepresented students. A new inter-departmental seminar series and new course materials will be developed and implemented.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.