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差距和障碍，导致在理解城市气候驱动的风险和为基础设施系统设计和运营提供信息方面的重大挑战方面存在系统性缺陷。该项目将通过解决两个主要研究问题来推动全球城市科学和工程，从而缓解这些障碍：(I)大规模气候变化加上城市化如何影响当地的城市气候？以及(Ii)这种城市环境知识如何告知基础设施系统和适应战略面临的相关风险？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)变暖驱动的本地规模城市气候变化、可变性和不确定性的全球规模多模型表征；(Iii)促进开发新的动态-城市社区地球系统模型(CESM)，以及(Iv)建立新的混合城市建模框架，以帮助打造新的全球城市科学和工程。该项目旨在通过开发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，为城市气候科学和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。这项研究的目标是(I)在温室气体(GHG)变暖与城市化相结合的情况下，强有力地描述城市气候变化、变异性和不确定性，(Ii)建立一条利用稳健的城市预测为基础设施系统设计和运营提供信息的途径，以及(Iii)建立一种方法来评估和设计大规模的适应解决方案。研究工作将与教育计划相结合，旨在(I)激励、吸引和激励年轻人和公众应对严峻的城市挑战，以及(Ii)在城市气候科学和工程方面形成融合教育，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。每年将在UIUC暑期项目中设计和展示动手课程和演示，以吸引K-12学生，特别是女性和代表性不足的学生。将开发和实施新的跨部门研讨会系列和新的课程材料。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.