Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Diurnal interaction between urban expansion, climate change and adaptation in US cities

Nature Climate Change volume 8, pages 1097–1103 (2018)Cite this article

Subjects

Abstract

Climate change and urban development are projected to substantially warm US cities, yet dynamic interaction between these two drivers of urban heat may modify the warming. Here, we show that business-as-usual GHG-induced warming and corresponding urban expansion would interact nonlinearly, reducing summer night-time warming by 0.5 K over the twenty-first century in most US regions. Nevertheless, large projected warming remains, particularly at night when the degree of urban expansion warming approaches that of climate change. Joint, high-intensity implementation of adaptation strategies, including cool and evaporative roofs and street trees, decreases projected daytime mean and extreme heat, but region- and emissions scenario-dependent nocturnal warming of 2–7 K persists. A novel adaptation strategy—lightweight urban materials—yields ~1 K night-time cooling and minor daytime warming in denser areas. Our findings highlight the diurnal interplay of urban warming and adaptation cooling, and underscore the inability of infrastructure-based adaptation to offset projected night-time warming, and the consequent necessity for simultaneous emissions reductions.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Summertime urban air temperature change resulting from the dynamically interactive combination of 90 years of projected urban expansion and climate change (2090–2099 compared with 2000–2009).
Fig. 2: Summertime nocturnal (03:00 LMST) urban air temperature change resulting from the dynamic interaction between 90 years of projected urban expansion and climate change.
Fig. 3: Diurnal variation of summertime urban air temperature change by US region resulting from select individual drivers.
Fig. 4: Change to the summertime diurnal range of urban air temperature by US region resulting from select individual drivers.
Fig. 5: Summertime urban air temperature change resulting from the interactive combination of 90 years of projected urban expansion and climate change, and full adaptation.
Fig. 6: Yearly increase in extreme heat afternoons by the end of the century resulting from the interactive combination of urban warming drivers and potential adaptation implementations.

Similar content being viewed by others

Data availability

Regional climate simulation output supporting the findings of this study is accessible at https://erams.com/UWIN/asu-conus-urban-and-climate-change-assessment-data/

References

  1. Gallo, K. P., Owen, T. W., Easterling, D. R. & Jamason, P. F. Temperature trends of the US historical climatology network based on satellite-designated land use/land cover. J. Clim. 12, 1344–1348 (1999).

    Article  Google Scholar 

  2. Qu, M., Wan, J. & Hao, X. Analysis of diurnal air temperature range change in the continental United States. Weather Clim. Extremes 4, 86–95 (2014).

    Article  Google Scholar 

  3. Revi, A. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 535–612 (IPCC, Cambridge Univ. Press, 2014).

  4. Alder, J. R. & Hostetler, S. W. CMIP5 Global Climate Change Viewer (US Geological Survey, 2013); http://regclim.coas.oregonstate.edu/gccv/index.html

  5. Bierwagen, B. G. et al. National housing and impervious surface scenarios for integrated climate impact assessments. Proc. Natl Acad. Sci. USA 107, 20887–20892 (2010).

    Article  CAS  Google Scholar 

  6. Georgescu, M., Moustaoui, M., Mahalov, A. & Dudhia, J. Summer-time climate impacts of projected megapolitan expansion in Arizona. Nat. Clim. Change 3, 37–41 (2013).

    Article  Google Scholar 

  7. Georgescu, M., Morefield, P. E., Bierwagen, B. G. & Weaver, C. P. Urban adaptation can roll back warming of emerging megapolitan regions. Proc. Natl Acad. Sci. USA 111, 2909–2914 (2014).

    Article  CAS  Google Scholar 

  8. Wouters, H. et al. Heat stress increase under climate change twice as large in cities as in rural areas: a study for a densely populated midlatitude maritime region. Geophys. Res. Lett. 44, 8997–9007 (2017).

    Article  Google Scholar 

  9. Hondula, D. M., Balling, R. C., Vanos, J. K. & Georgescu, M. Rising temperatures, human health, and the role of adaptation. Curr. Clim. Change Rep. 1, 144–154 (2015).

    Article  Google Scholar 

  10. Li, D. H., Yang, L. & Lam, J. C. Impact of climate change on energy use in the built environment in different climate zones—a review. Energy 42, 103–112 (2012).

    Article  Google Scholar 

  11. Oleson, K. W., Bonan, G. B., Feddema, J. & Jackson, T. An examination of urban heat island characteristics in a global climate model. Int. J. Climatol. 31, 1848–1865 (2011).

    Article  Google Scholar 

  12. Oleson, K. Contrasts between urban and rural climate in CCSM4 CMIP5 climate change scenarios. J. Clim. 25, 1390–1412 (2012).

    Article  Google Scholar 

  13. Argüeso, D., Evans, J. P., Fita, L. & Bormann, K. J. Temperature response to future urbanization and climate change. Clim. Dynam. 42, 2183–2199 (2014).

    Article  Google Scholar 

  14. Zhao, L., Lee, X. & Schultz, N. M. A wedge strategy for mitigation of urban warming in future climate scenarios. Atmos. Chem. Phys. 17, 9067–9080 (2017).

    Article  CAS  Google Scholar 

  15. Stein, U. & Alpert, P. Factor separation in numerical simulations. J. Atmos. Sci. 50, 2107–2115 (1993).

    Article  Google Scholar 

  16. Bowler, D. E., Buyung-Ali, L., Knight, T. M. & Pullin, A. S. Urban greening to cool towns and cities: a systematic review of the empirical evidence. Landsc. Urban Plan. 97, 147–155 (2010).

    Article  Google Scholar 

  17. Krayenhoff, E. S. & Voogt, J. A. Impacts of urban albedo increase on local air temperature at daily–annual time scales: model results and synthesis of previous work. J. Appl. Meteorol. Climatol. 49, 1634–1648 (2010).

    Article  Google Scholar 

  18. Skamarock, W. C. & Klemp, J. B. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys. 227, 3465–3485 (2008).

    Article  Google Scholar 

  19. Kusaka, H., Kondo, H., Kikegawa, Y. & Kimura, F . A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Bound. Layer Meteorol. 101, 329–358 (2001).

    Article  Google Scholar 

  20. Chapman, S., Watson, J. E., Salazar, A., Thatcher, M. & McAlpine, C. A. The impact of urbanization and climate change on urban temperatures: a systematic review. Landsc. Ecol. 32, 1921–1935 (2017).

    Article  Google Scholar 

  21. Höppe, P. The physiological equivalent temperature—a universal index for the biometeorological assessment of the thermal environment. Int. J. Biometeorol. 43, 71–75 (1999).

    Article  Google Scholar 

  22. Jendritzky, G., de Dear, R. & Havenith, G. UTCI—why another thermal index? Int. J. Biometeorol. 56, 421–428 (2012).

    Article  Google Scholar 

  23. Patz, J. A., Campbell-Lendrum, D., Holloway, T. & Foley, J. A. Impact of regional climate change on human health. Nature 438, 310–317 (2005).

    Article  CAS  Google Scholar 

  24. Chen, F. et al. The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems. Int. J. Climatol. 31, 273–288 (2011).

    Article  Google Scholar 

  25. Wang, M. et al. On the long-term hydroclimatic sustainability of perennial bioenergy crop expansion over the United States. J. Clim. 30, 2535–2557 (2017).

    Article  Google Scholar 

  26. European Centre for Medium-Range Weather Forecasts ERA-Interim Project 2009 (Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, accessed 29 November 2016); https://doi.org/10.5065/D6CR5RD9

  27. Monaghan, A. J., Steinhoff, D. F., Bruyere, C. L. and Yates, D. M NCAR CESM Global Bias-Corrected CMIP5 Output to Support WRF/MPAS Research 2014 (Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, accessed 23 June 2016); https://doi.org/10.5065/D6DJ5CN4

  28. CMIP5 Data Availability (Geophysical Fluid Dynamics Laboratory, accessed 4 November 2016); http://nomads.gfdl.noaa.gov:8080/DataPortal/cmip5.jsp

  29. Dunne, J. P. et al. GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J. Clim. 25, 6646–6665 (2012).

    Article  Google Scholar 

  30. ICLUS Tools and Datasets ( Version 1.3.2) (US Environmental Protection Agency, 2010); https://go.nature.com/2S8homy

  31. IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).

  32. US Environmental Protection Agency ICLUS v1.3 User’s Manual: ArcGIS Tools and Datasets for Modeling US Housing Density Growth (Global Change Research Program, National Center for Environmental Assessment, 2010).

  33. Monaghan, A. J., Hu, L., Brunsell, N. A., Barlage, M. & Wilhelmi, O. V. Evaluating the impact of urban morphology configurations on the accuracy of urban canopy model temperature simulations with MODIS. J. Geophys. Res. Atmos. 119, 6376–6392 (2014).

    Article  Google Scholar 

  34. Stewart, I. D., Oke, T. R. & Krayenhoff, E. S. Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations. Int. J. Climatol. 34, 1062–1080 (2014).

    Article  Google Scholar 

  35. ENERGY STAR Roof Product List (Energy Star, 2013); https://go.nature.com/2CuhGPn

  36. Scherba, A., Sailor, D. J., Rosenstiel, T. N. & Wamser, C. C. Modeling impacts of roof reflectivity, integrated photovoltaic panels and green roof systems on sensible heat flux into the urban environment. Build. Environ. 46, 2542–2551 (2011).

    Article  Google Scholar 

  37. Krayenhoff, E. S., Christen, A., Martilli, A. & Oke, T. R . A multi-layer radiation model for urban neighbourhoods with trees. Bound. Layer Meteorol. 151, 139–178 (2014).

    Article  Google Scholar 

  38. Kenney, W. A. in Ecology, Planning, and Management of Urban Forests 336–345 (Springer, New York, 2008).

  39. Upreti, R., Wang, Z. H. & Yang, J. Radiative shading effect of urban trees on cooling the regional built environment. Urban For. Urban Green. 26, 18–24 (2017).

    Article  Google Scholar 

  40. Yaghoobian, N., Kleissl, J. & Krayenhoff, E. S. Modeling the thermal effects of artificial turf on the urban environment. J. Appl. Meteorol. Climatol. 49, 332–345 (2010).

    Article  Google Scholar 

  41. Oke, T. R., Mills, G., Christen, A. & Voogt, J. A. Urban Climates (Cambridge Univ. Press, Cambridge, 2017).

  42. Oleson, K. W., Bonan, G. B. & Feddema, J. Effects of white roofs on urban temperature in a global climate model. Geophys. Res. Lett. 37, L03701 (2010).

    Article  Google Scholar 

  43. McCarthy, M. P., Best, M. J. & Betts, R. A. Climate change in cities due to global warming and urban effects. Geophys. Res. Lett. 37, L09705 (2010).

    Article  Google Scholar 

  44. Janssen, E., Wuebbles, D. J., Kunkel, K. E., Olsen, S. C. & Goodman, A. Observational‐ and model‐based trends and projections of extreme precipitation over the contiguous United States. Earth’s Future 2, 99–113 (2014).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by National Science Foundation Sustainability Research Network Cooperative Agreement 1444758, the Urban Water Innovation Network, and NSF grants SES-1520803 and EAR‐1204774. The authors acknowledge support from Research Computing at Arizona State University for the provision of high-performance supercomputing services. We also thank A. Martilli for helpful discussions.

Author information

Authors and Affiliations

  1. Urban Climate Research Center, Arizona State University, Tempe, AZ, USA

    E. Scott Krayenhoff, Mohamed Moustaoui, Ashley M. Broadbent, Vishesh Gupta & Matei Georgescu

  2. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA

    E. Scott Krayenhoff, Ashley M. Broadbent, Vishesh Gupta & Matei Georgescu

  3. School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada

    E. Scott Krayenhoff

  4. School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA

    Mohamed Moustaoui & Matei Georgescu

  5. Julie Ann Wrigley Global Institute of Sustainability, Arizona State University, Tempe, AZ, USA

    Mohamed Moustaoui & Matei Georgescu

Authors
  1. E. Scott Krayenhoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohamed Moustaoui
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ashley M. Broadbent
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vishesh Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matei Georgescu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.S.K., M.M. and M.G. designed the research. E.S.K., M.M., A.M.B. and M.G. performed the model simulations. E.S.K., A.M.B. and V.G. analysed the model output. All authors contributed to the writing of the manuscript.

Corresponding authors

Correspondence to E. Scott Krayenhoff or Matei Georgescu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Methods, Supplementary Figures 1–22, Supplementary Tables 1–3, Supplementary References

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krayenhoff, E.S., Moustaoui, M., Broadbent, A.M. et al. Diurnal interaction between urban expansion, climate change and adaptation in US cities. Nature Clim Change 8, 1097–1103 (2018). https://doi.org/10.1038/s41558-018-0320-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-018-0320-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing