Urban areas are increasingly vulnerable to large-scale weather events like storms, heat waves, and flooding, which pose significant risks to health, energy, infrastructure, and security. This session seeks submissions that utilize physical modeling, advanced observational techniques, artificial intelligence (AI), and machine learning (ML) to better understand these challenges and inform robust policy responses. The focus areas include: (i) Modeling extreme events—using physical models and AI/ML to explore the links between extreme weather, air pollution, and urbanization.; (ii) Impacts of extremes—analyzing effects of severe weather on human health, air quality, energy systems, and the urban hydrological cycle through modeling and risk analysis techniques; (iii) Strategies for mitigation and adaptation—developing physics-based and ML-informed models to tackle future climate shifts and inform urban planning; (iv) Interdisciplinary solutions—creating cross-sector modeling strategies to enhance resilience. (v) Digital twins for climate resilience—employing digital twin platforms for real-time urban condition monitoring and scenario planning, and emergency preparedness.

• GC - Global Environmental Change
• GH - GeoHealth
• H - Hydrology