Description:

Atmospheric urban digital twins are powerful tools for simulating and understanding the multiscale urban  environment and socioeconomic feedbacks. This session invites submissions that explore the integration of AI/ML and digital twin framework for  urban modeling, urban planning and disaster management to enhance community resilience. The session is particularly interested in developing definitions, case studies, data and policy integration studies, and application of multiscale models within climate and weather ready nation. Submissions should highlight innovative approaches that combine data science, atmospheric science, urban planning, and community engagement to create more resilient urban environments. The session welcomes multidisciplinary, convergent research that utilizes atmospheric urban digital twins to analyze adaptation strategies, risk assessment, and mitigation efforts, aiming to bridge the gap between technology and societal needs.