Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 4
Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1667-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1667-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 4
Development and technical paper
 | 
26 Feb 2024
Development and technical paper |  | 26 Feb 2024

High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning

Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen

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Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
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