Cities are hotspots for climate change – for mitigating greenhouse gas emissions and adapting to impacts of future extreme weather events such as heatwaves. Cities are particularly vulnerable to heat due to high population densities, complex and sensitive infrastructure and economic activities. Generally, daytime and nighttime heat stress is increased in cities due to three-dimensional radiation effects, reduced wind at pedestrian-level, and the urban heat island - yet depending on context (shading, surface materials) there are large differences at micro- and local-scale within cities. At the same time, cities are also hubs of creativity, innovation and transformation – hence driving climate adaptation. A key challenge in the process of transforming our current built environments into more resilient cities is the assessment and optimization of responsible and effective local measures for climate adaptation, which requires high-resolution, timely and reliable information on urban climate and climate change impacts, for example heat exposure must be assessed spatially and temporally at high-resolution and for different development scenarios.

The talk will highlight recent research supporting the simulation and assessment of urban heat as part of the BMU-funded “I4C-Intelligence for Cities” project, from our ERC Synergy Grant “urbisphere” and our latest EU-funded “UrbanAIR” project to develop a Destiny Earth Digital Twin for urban regions. In all three projects, we address urban heat at different scales and by integrating different technologies resolving physical as well as social science aspects. We couple high-resolution weather- and climate models with urban surface models to simulate urban energy, water and airflow dynamics. This enables precise intra-urban forecasts, warnings and climate projections of heat at the neighborhood-level. New networks of distributed environmental and weather sensors in cities provide valuable real-time data on intra-urban variability and can be used for evaluating new models. Emulating complex physical simulations with artificial intelligence can considerably speed up computationally expensive simulations of scenarios and helps to integrate them in building-resolving digital twins or combine them with mobility data to assess and opitimise different climate, planning and development options across entire cities.

Future heat impact, decision and support systems can help to make cities more resilient, sustainable and equitable – and thus preparing them to face the challenges of climate change and increasing heat waves. However, in developing and combining all these technologies, meteorological and physical processes must be combined with quantitative data on urban population, mobility and in order to obtain a sound basis for decision-making, which remains challenge for integrated urban climate services.