Building a community and research agenda for machine learning in urban climate: the AI4UrbanClimate initiative

Machine learning (ML) and artificial intelligence (AI) have become integral to modern weather and climate science, and their rapid evolution is driving new opportunities for urban climate research. Across the urban climate community, ML methods of varying complexities are being used for tasks ranging from fast point-based predictions to neighborhood- or city‑scale urban climate modelling for one or multiple (bio)meteorological variables. For instance, novel ML and AI approaches support scenario generation for impact studies such as quantifying the effects of urban vegetation, assessing thermal comfort under different warming pathways, or identifying locations for future cool spaces. In addition, ML techniques are also being applied to provide boundary conditions for micro‑scale models. 

While the field is expanding quickly, it remains highly fragmented. AI/ML in urban climate research spans diverse methods, scales, datasets, and scientific aims, making it difficult to define a common research agenda or benchmarks. The lack of an established interdisciplinary network between AI and urban climate communities further increases the risk of duplicated efforts and missed opportunities for coordinated progress. 

The newly founded AI4UrbanClimate working group addresses this gap by establishing an international community focused on AI/ML applications in urban climate research. Our goals are to (1) bring people together with similar research interests, (2) develop a common understanding of the scope and landscape of ML-based urban climate research, (3) review existing work across domains, and (4) identify persistent challenges and priorities and initiate and coordinate collective action - such as benchmarking datasets, standardized evaluation metrics, and best‑practice guidelines. 

As an initial step, we are mapping ongoing activities across the community to enable the development of meaningful benchmarks and identify where joint efforts could accelerate research. We will present the first outcomes from the initiative’s activities, including insights on who is currently involved and thoughts that were shared during the kick‑off meeting and online social event. We will also outline how you can join the AI4UrbanClimate network and contribute to building this emerging community.