Abstract Urban citizens are particularly exposed to heat stress during heatwaves due to the urban climate conditions. Introducing more trees, changing building density and surface cover and materials are examples of planning measures that can be used to mitigate heat stress. One challenge as an urban planner is to have knowledge on which mitigation measure to implement to achieve the highest cooling effect with regards to outdoor heat stress at different spatial scales. The aim of this high-resolution modelling of outdoor thermal comfort on city-wide domains is to examine how different real-world urban settings reduce or exacerbate heat stress with regards to building density (plan area index), tree fraction, and ground cover. Here, we exploit the open-source tool Urban Multi-scale Environmental Predictor (UMEP), to investigate how real-world data on building density, tree fraction, and ground cover influence thermal comfort in the three largest cities in Sweden. Mean radiant temperature (T mrt ) and two thermal comfort indices are calculated and compared: Physiological Equivalent Temperature (PET) and Universal Thermal Comfort Index (UTCI). Automated chain processes using Python scripting is demonstrated, making it possible to derive microscale outdoor thermal comfort information (2-meter resolution) using a standard personal computer and open data sources. Results show that tree fraction is the single most effective outdoor heat mitigation measure, especially in areas with low building density. Results also show that building fraction has a minor cooling effect. This is probably due to the fact that shadowing at street level is dominated by trees due their 3D characteristics including trunk zones. T mrt shows very similar results compared with PET and UTCI, indicating that T mrt can capture the spatial variations of heat stress during warm, clear and calm days. Since trees is the single most effective measure to mitigate heat stress, it should be incorporated when creating practical guidelines to resilient urban planning strategies against heat stress.
Lindberg et al. (Mon,) studied this question.