What is the Effect of Urban Heat Islands on Global Warming Trends?

Baltimore's Inner Harbor

It is well-documented that cities are significantly warmer than rural areas. This effect is commonly described as an urban heat island (UHI). Some argue that some (or all) of the increase in global temperatures can be explained by the effect of the UHI effect on global temperatures. It makes some intuitive sense that this might be the case, but let's consider some important lines of evidence that suggest otherwise.

First, while urban areas are warmer than rural areas, urban areas are warming at about the same rate as rural areas, so temperature anomalies are not significantly affected by urban heat islands.[1]

Second, there is a well-documented bias that can be added to the temperature record from urbanization. As a rural area becomes more urban, it will warm at a faster rate than cities and rural areas. An area that is rural in 1950 but urban in 2020 will become progressively hotter due to urbanization, and not changing climatic conditions. However, numerous studies have shown that this potential source for bias in temperature trends is corrected by bias correction.[2][3] One interesting study concludes that UHI is insufficient to contaminate the temperature record: “If ∼30% of the highest population stations were removed from the analysis, no statistically significant urban heat island was detected. The implications of this work on U.S. climate change analyses is that, if the highest population stations are avoided (populations above 30 000 within 6 km), the analysis should not be expected to be contaminated by UHIs. However, comparison between U.S. Historical Climatology Network (HCN) time series from the full dataset and a subset excluding the high population sites indicated that the UHI contamination from the high population stations accounted for very little of the recent warming.”[4]

Third, using the US as a case study, if you compare the USCRN dataset (with significant homogenization) to the USHCN dataset (with fewer but well-sited stations) they are indistinguishable from each other during the years when they overlap. This confirms that bias correction is working, successfully removing bias from the data.[5] Consequently, rural, urban, and rapidly developing areas are all generally free from bias from urban heat islands. One study from 2013 says this: “Time series of the Earth’s average land temperature are estimated using the Berkeley Earth methodology applied to the full dataset and the rural subset; the difference of these is consistent with no urban heating effect over the period 1950 to 2010, with a slope of -0.10 ± 0.24/100yr (95% confidence).”[6]

Fourth, cities take up a small fraction of the globe's surface, so whatever bias may remain in the data after homogenization must be small. Most of the planet's surface is ocean, and most of the land's surface is natural land and rural.

There's an online tool you can use to generate graphs from GHCN data that lets you see a time series using all stations and two forms of rural data: one with 2167 rural stations and one with 1506 rural stations identified by areas with lights seen at night. As you can see above, no matter which group of thermometers you use, GMST trends are essentially identical. 

2024 Update: Jim Java has also shared a graph of Rural and Urban GHCN land data, both raw and unadjusted. He calculated the change in temperature from each from 1970-2023, and both rural and urban stations are warming at essentially the same rate. What these mean necessarily is that UHI is a non issue for global warming trends. It may still affect regional and local trends (and likely does), but trends in global warming are unaffected by urbanization.

References:

[1] Jones, P. D., Lister, D. H., and Li, Q. (2008), Urbanization effects in large‐scale temperature records, with an emphasis on China, J. Geophys. Res., 113, D16122, doi:10.1029/2008JD009916.
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2008JD009916

[2] Menne, M.J. and C. N. Williams Jr. “Homogenization of Temperature Series via Pairwise Comparisons.” Journal of Climate 22 (2009): 1700-1717. http://dx.doi.org/10.1175/2008JCLI2263.1

[3] Parker, D. E., 2006: A demonstration that large-scale warming is not urban. J. Climate, 19, 2882–2895.
https://journals.ametsoc.org/doi/10.1175/JCLI3730.1

[4] Peterson and Owen, “Urban Heat Island Assessment: Metadata Are Important” Journal of Climate 18 (2005): 2637-2646.
https://journals.ametsoc.org/doi/pdf/10.1175/JCLI3431.1

[5] https://www.ncdc.noaa.gov/news/how-ncdc%E2%80%99s-datasets-compare-each-other

[6] Wickham C, Rohde R, Muller RA, Wurtele J, Curry J, et al. (2013) Influence of Urban Heating on the Global Temperature Land Average using Rural Sites Identified from MODIS Classifications. Geoinfor Geostat: An Overview 1:2. doi:10.4172/2327-4581.1000104
https://static.berkeleyearth.org/papers/UHI-GIGS-1-104.pdf