Extreme urban heat is a growing public health hazard worldwide. As cities work to protect people when it's hot out, they need better data to understand heat hazard and to evaluate ways in which infrastructure can cool the city. Heat is a regional phenomenon, but is experienced at local scales. Data to inform resilience planning must account for the varied urban spaces where people are exposed to heat.

This open-source method for modeling the Universal Thermal Climate Index (UTCI) provides a globally scalable and transferrable approach for evaluating heat exposure at a 1 meter resolution in cities. Supported by the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model and open-access data, it estimates UTCI with a mean absolute error of 0.39°C when validated against LiDAR-supported models. High-resolution UTCI, shade, and urban land use data show heat exposure and the potential to mitigate its effects.

As a part of WRI's Cool Cities Lab (CCL), these datasets provide insights into the design, prioritization, and deployment of heat-resilient infrastructure interventions. The modeling methods are used to evaluate differential heat exposure across planning scenarios for tree planting, shade structures, and cool surfaces. They demonstrate the cooling potential, measured in air temperature and UTCI, of these interventions in diverse urban environments.

Executive Summary:

Extreme heat is among the deadliest climate hazards worldwide, and its effects grow each year as cities become both hotter and more populous. For policymakers to design effective interventions to mitigate the effects of extreme heat, they require local-scale data on heat exposure. It is difficult and expensive to produce high-resolution intra-urban heat data, and many cities lack sufficient data to support heat-resilient planning. Here, we present a fully open-source method, usable worldwide, for modeling 1-meter thermal comfort in cities. We calculate the Universal Thermal Climate Index (UTCI) and other related metrics, such as shade cover and air temperature, using the open-source SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model supported by freely available data sets. We model baseline heat conditions and also incorporate into the model achievable infrastructure changes to improve heat resilience. Our open-source UTCI results have a mean absolute error of 0.39°C when validated against modeled runs supported by lidar-derived data sets. This modeling approach can support realistic, actionable heat-resilience planning in cities globally.

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