Letter | Published:

Strong contributions of local background climate to urban heat islands

Nature volume 511, pages 216219 (10 July 2014) | Download Citation

Abstract

The urban heat island (UHI), a common phenomenon in which surface temperatures are higher in urban areas than in surrounding rural areas, represents one of the most significant human-induced changes to Earth’s surface climate1,2. Even though they are localized hotspots in the landscape, UHIs have a profound impact on the lives of urban residents, who comprise more than half of the world’s population3. A barrier to UHI mitigation is the lack of quantitative attribution of the various contributions to UHI intensity4 (expressed as the temperature difference between urban and rural areas, ΔT). A common perception is that reduction in evaporative cooling in urban land is the dominant driver of ΔT (ref. 5). Here we use a climate model to show that, for cities across North America, geographic variations in daytime ΔT are largely explained by variations in the efficiency with which urban and rural areas convect heat to the lower atmosphere. If urban areas are aerodynamically smoother than surrounding rural areas, urban heat dissipation is relatively less efficient and urban warming occurs (and vice versa). This convection effect depends on the local background climate, increasing daytime ΔT by 3.0 ± 0.3 kelvin (mean and standard error) in humid climates but decreasing ΔT by 1.5 ± 0.2 kelvin in dry climates. In the humid eastern United States, there is evidence of higher ΔT in drier years. These relationships imply that UHIs will exacerbate heatwave stress on human health in wet climates where high temperature effects are already compounded by high air humidity6,7 and in drier years when positive temperature anomalies may be reinforced by a precipitation–temperature feedback8. Our results support albedo management as a viable means of reducing ΔT on large scales9,10.

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Acknowledgements

This research was supported by the Ministry of Education of China (grant PCSIRT), the Yale Climate and Energy Institute, the Yale Institute of Biospheric Studies, and a Yale University Graduate Fellowship. K.O. acknowledges support from NASA grant NNX10AK79G (the SIMMER project) and the NCAR WCIASP. NCAR is sponsored by the US National Science Foundation. The model simulations were supported by the Yale University Faculty of Arts and Sciences High Performance Computing Center.

Author information

Affiliations

  1. Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China

    • Lei Zhao
    •  & Xuhui Lee
  2. School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut 06511, USA

    • Lei Zhao
    •  & Xuhui Lee
  3. Department of Geology and Geophysics, Yale University, New Haven, Connecticut 06511, USA

    • Ronald B. Smith
  4. National Center for Atmospheric Research, Boulder, Colorado 80305, USA

    • Keith Oleson

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Contributions

X.L. designed the research. L.Z. carried out the model simulation and data analysis. R.B.S. contributed ideas to the research design. K.O. contributed ideas to the model simulation. X.L. and L.Z. drafted the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Xuhui Lee.

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DOI

https://doi.org/10.1038/nature13462

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