Quantifying the decrease in heat exposure through adaptation and mitigation in twenty-first-century US cities

Quantifying the decrease in heat exposure through adaptation and mitigation in twenty-first-century US cities | Nature Cities

Abstract

The continued increase in the duration, frequency and intensity of heat waves is especially problematic in cities, where more than half of the world’s population lives. Here we combine decadal-scale regional climate modeling simulations with projections of urban expansion, greenhouse gas emissions and population migration to examine the extent to which adaptation and mitigation strategies, in isolation and in tandem, can reduce population heat exposure in US cities at the end of the century. We show that adaptation and mitigation strategies, when deployed in isolation, lead to the largest reduction in population heat exposure for Northeast and Midwest cities compared with Southeast, Great Plains and Southwest cities, relative to a contemporary start-of-century baseline. Our results demonstrate synergistic interactions between adaptation and mitigation strategies when deployed in tandem. This results in an end-of-century decrease in population heat exposure that is greater than the sum of their individual parts for the lowest extreme heat thresholds, but less than the sum of their individual parts for the highest extreme heat thresholds, for US cities across all regions.

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Data availability

We used version 3.6.1 of the WRF-ARW regional climate model (freely available at: https://www2.mmm.ucar.edu/wrf/users/download/get_source.html) to generate all results. Modest modifications to WRF were made to incorporate subgrid features 33. The data that supported the findings communicated in this manuscript can be obtained by accessing the ASU Library Research Data Repository at: https://doi.org/10.48349/ASU/3TYXZI.

Code availability

Analysis was performed using custom-made scripts coded in Python v.2.7.12. The WRF source code for the latest version of the modeling system is available from the public WRF-Model Release page on GitHub at: https://github.com/wrf-model/WRF/releases. The WRF source code for the version of the code used here is freely available via the WRF User’s Page and can be obtained from: https://www2.mmm.ucar.edu/wrf/users/download/get_source.html. The code modification used to derive the subgrid representation of urban air temperature is available from the corresponding author upon reasonable request.
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Acknowledgements

This work was supported by National Science Foundation Sustainability Research Network Cooperative Agreement Number 1444758, the Urban Water Innovation Network. M.G. also acknowledges support courtesy of the US Department of Energy, Office of Science, Office of Biological and Environmental Research’s Urban Integrated Field Laboratories research activity, under Award Number DE-SC0023520. The authors acknowledge support from Research Computing at Arizona State University for the provision of high-performance supercomputing services and from ASU Libraries for storage of model simulation output at: https://dataverse.asu.edu/dataset.xhtml?persistentId=doi:10.48349/ASU/3….

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Nature Cities thanks Cascade Tuholske, Pouya Vahmani and Kangning Huang for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Figs. 1–10.

Supplementary Table 1

Description and naming convention of WRF experiments.

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Georgescu, M., Broadbent, A.M. & Krayenhoff, E.S. Quantifying the decrease in heat exposure through adaptation and mitigation in twenty-first-century US cities. Nat Cities (2023). https://doi.org/10.1038/s44284-023-00001-9
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DOI: https://doi.org/10.1038/s44284-023-00001-9