Papers on urban heat island

This is a list of papers on urban heat island with an emphasis on studies that deal with larger areas (generally no studies dealing with individual cities are included in this list). The list is not complete, and will most likely be updated in the future in order to make it more thorough and more representative. Note that the paperlist on global surface temperature contains several papers that discuss urban heat island issues also.

UPDATES March 22, 2023: Monteiro et al. (2021), Jiang et al. (2020), Paranunzio et al. (2019) added, thanks to Barry for pointing them out. July 24, 2013: Hausfather et al. (2013), Wickham et al. (2013), Parker (2010) added. April 5, 2010: Small et al. (2005) added. Full text link was added to Schmidt (2009), Gallo & Owen (1999), and Mitchell (1953).

Global studies

Evaluating the Effects of Urbanization Evolution on Air Temperature Trends Using Nightlight Satellite Data – Paranunzio et al. (2019) Confounding factors like urbanization and land-use change could introduce uncertainty to the estimation of global temperature trends related to climate change. In this work, we introduce a new way to investigate the nexus between temporal trends of temperature and urbanization data at the global scale in the period from 1992 to 2013. We analyze air temperature data recorded from more than 5000 weather stations worldwide and nightlight satellite measurements as a proxy for urbanization. By means of a range of statistical methods, our results quantify and outline that the temporal evolution of urbanization affects temperature trends at multiple spatial scales with significant differences at regional and continental scales. A statistically significant agreement in temperature and nightlight trends is detected, especially in low and middle-income regions, where urbanization is rapidly growing. Conversely, in continents such as Europe and North America, increases in temperature trends are typically detected along with non-significant nightlight trends. Paranunzio R, Ceola S, Laio F, Montanari A. (2019) Atmosphere 10(3):117. https://doi.org/10.3390/atmos10030117

Quantifying the effect of urbanization on U.S. Historical Climatology Network temperature records – Hausfather et al. (2013) “An assessment quantifying the impact of urbanization on temperature trends from the U.S. Historical Climatology Network (USHCN) is described. Stations were first classified as urban and nonurban (rural) using four different proxy measures of urbanity. Trends from the two station types were then compared using a pairing method that controls for differences in instrument type and via spatial gridding to account for the uneven distribution of stations. The comparisons reveal systematic differences between the raw (unadjusted) urban and rural temperature trends throughout the USHCN period of record according to all four urban classifications. According to these classifications, urbanization accounts for 14–21% of the rise in unadjusted minimum temperatures since 1895 and 6–9% since 1960. The USHCN version 2 homogenization process effectively removes this urban signal such that it becomes insignificant during the last 50–80 years. In contrast, prior to 1930, only about half of the urban signal is removed. Accordingly, the National Aeronautics and Space Administration Goddard Institute for Space Studies urban-correction procedure has essentially no impact on USHCN version 2 trends since 1930, but effectively removes the residual urban-rural temperature trend differences for years before 1930 according to all four urban proxy classifications. Finally, an evaluation of the homogenization of USHCN temperature series using subsets of rural-only and urban-only reference series from the larger U.S. Cooperative Observer (Coop) Network suggests that the composition of Coop stations surrounding USHCN stations is sufficiently “rural” to limit the aliasing of urban heat island signals onto USHCN version 2 temperature trends during homogenization.” Zeke Hausfather, Matthew J. Menne, Claude N. Williams, Troy Masters, Ronald Broberg, David Jones, Journal of Geophysical Research: Atmospheres, Volume 118, Issue 2, pages 481–494, 27 January 2013, DOI: 10.1029/2012JD018509. [Full text]

Influence of Urban Heating on the Global Temperature Land Average using Rural Sites Identified from MODIS Classifications – Wickham et al. (2013) “The effect of urban heating on estimates of global average land surface temperature is studied by applying an urban-rural classification based on MODIS satellite data to the Berkeley Earth temperature dataset compilation of 36,869 sites from 15 different publicly available sources. We compare the distribution of linear temperature trends for these sites to the distribution for a rural subset of 15,594 sites chosen to be distant from all MODISidentified urban areas. While the trend distributions are broad, with one-third of the stations in the US and worldwide having a negative trend, both distributions show significant warming. 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).” 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. [Full text]

Urban heat island effects on estimates of observed climate change – Parker (2010) “Urban heat islands are a result of the physical properties of buildings and other structures, and the emission of heat by human activities. They are most pronounced on clear, calm nights; their strength depends also on the background geography and climate, and there are often cool islands in parks and less-developed areas. Some old city centers no longer show warming trends relative to rural neighbourhoods, because urban development has stabilised. This article reviews the effects that urban heat islands may have on estimates of global near-surface temperature trends. These effects have been reduced by avoiding or adjusting urban temperature measurements. Comparisons of windy weather with calm-weather air temperature trends for a worldwide set of observing sites suggest that global near-surface temperature trends have not been greatly affected by urban warming trends; this is supported by comparisons with marine surface temperatures. The use of dynamical-model-based reanalyses to estimate urban influences has been hindered by the heterogeneity of the data input to the reanalyses and by biases in the models. However, improvements in reanalyses are increasing their utility for assessing the surface air temperature record. High-resolution climate models and data on changing land use offer potential for future assessment of worldwide urban warming influences. The latest assessments of the likely magnitude of the residual urban trend in available global near-surface temperature records are summarized, along with the uncertainties of these residual trends.” David E. Parker, Wiley Interdisciplinary Reviews: Climate Change, Volume 1, Issue 1, pages 123–133, January/February 2010, DOI: 10.1002/wcc.21.

Global urban land-use trends and climate impacts – Seto & Shepherd (2009) A review article. “Recent research points to mounting evidence that urbanization also affects cycling of water, carbon, aerosols, and nitrogen in the climate system. This review highlights advances in the understanding of urban land-use trends and associated climate impacts, concentrating on peer-reviewed papers that have been published over the last two years.” [Full text]

Urban Heat Islands: Observations, Impacts, and Adaptation – Yow (2007) A review article. “Urban heat islands are a clear, well-documented example of an anthropogenic modification to climate that has an atmospheric, biological, and economic impact. This review shows how field-based and modeling studies continue to help unravel the factors that are responsible for heat island development and are providing a basis for the development and application of sustainable adaptation strategies. As urban areas continue to expand, there is a heightened awareness that scientific knowledge of the urban heat island must be more effectively communicated to architects, engineers, and planners and translated into intelligent urban design.”

Quantifying the influence of anthropogenic surface processes and inhomogeneities on gridded global climate data – McKitrick & Michaels (2007) “Using a new database for all available land-based grid cells around the world we test the null hypothesis that the spatial pattern of temperature trends in a widely used gridded climate data set is independent of socioeconomic determinants of surface processes and data inhomogeneities. The hypothesis is strongly rejected (P = 7.1 × 10⁻¹⁴), indicating that extraneous (nonclimatic) signals contaminate gridded climate data. … We conclude that the data contamination likely leads to an overstatement of actual trends over land. Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.” [Full text]

A Demonstration That Large-Scale Warming Is Not Urban – Parker (2006) “On the premise that urban heat islands are strongest in calm conditions but are largely absent in windy weather, daily minimum and maximum air temperatures for the period 1950–2000 at a worldwide selection of land stations are analyzed separately for windy and calm conditions, and the global and regional trends are compared. The trends in temperature are almost unaffected by this subsampling, indicating that urban development and other local or instrumental influences have contributed little overall to the observed warming trends.” [Full text]

Spatial analysis of global urban extent from DMSP-OLS night lights – Small et al. (2005) “Previous studies of DMSP-OLS stable night lights have shown encouraging agreement between temporally stable lighted areas and various definitions of urban extent. However, these studies have also highlighted an inconsistent relationship between the actual lighted area and the boundaries of the urban areas considered. Applying detection frequency thresholds can reduce the spatial overextent of lighted area (“blooming”) but thresholding also attenuates large numbers of smaller lights and significantly reduces the information content of the night lights datasets. … Comparison of lighted area with built area estimates from Landsat imagery of 17 cities shows that lighted areas are consistently larger than even maximum estimates of built areas for almost all cities in every light dataset. … Even 100% thresholds significantly overestimate built area for the 1992/1993 and 2000 datasets.” [Full text]

Satellite-Based Adjustments for the Urban Heat Island Temperature Bias – Gallo & Owen (1999) “Monthly and seasonal relationships between urban–rural differences in minimum, maximum, and average temperatures measured at surface-based observation stations were compared to satellite-derived Advanced Very High Resolution Radiometer estimates of a normalized difference vegetation index (NDVI) and surface radiant temperature (T_sfc). … The use of satellite-derived data may contribute to a globally consistent method for analysis of the urban heat island bias.” [Full text]

Regional studies

Assessment of Urban Heat Islands in Brazil based on MODIS remote sensing data – Monteiro et al. (2021) Estimates indicate that by 2050, 70% of the world’s population will live in urban areas, expanding the total built-up space and density of those areas. The urban heat island (UHI) phenomenon causes increased temperatures in urban areas compared to outlying regions. It is considered one of the main anthropogenic climate modifications and is directly linked to land-use patterns. The objective of this study was to analyze the presence of the UHI effect, diurnal and nocturnal, in the dry season in 21 Brazilian metropolitan areas from 2000 to 2016. Surface temperature, mean albedo, and normalized difference vegetation index (NDVI) values generated by the MODIS sensor (Moderate-resolution Imaging Spectroradiometer) were used. The results obtained showed substantial differences between diurnal and nocturnal UHI effects. Manaus, Porto Alegre, Belém, and Recife presented the highest values of diurnal UHI, whereas Curitiba, Brasília, São Paulo, and Rio de Janeiro showed higher heat island effects at night. The results are an alert to policymakers of the need to rethink land occupation regulations and also give support to actions to mitigate the phenomenon. Felipe Ferreira Monteiro, Weber Andrade Gonçalves, Lara de Melo Barbosa Andrade, Lourdes Milagros Mendoza Villavicencio, Cássia Monalisa dos Santos Silva (2020). Urban Climate 35(January 2021):100726. https://doi.org/10.1016/j.uclim.2020.100726

Rapid Local Urbanization around Most Meteorological Stations Explains the Observed Daily Asymmetric Warming Rates across China from 1985 to 2017 – Jiang et al. (2020) The increasing rate of the observed daily minimum temperature Tmin has been much higher than that of the observed daily maximum temperature Tmax during the past six decades across China. In this study, the local urbanization impact on these observed asymmetric warming rates was investigated. The latest released land-cover data with a 30-m spatial resolution and annual temporal resolution from 1985 to 2017 were used to quantify the urbanization ratios around weather stations. Although urbanized areas occupied only 2.25% of the landmass in China, the percentage of stations with an urbanization ratio over 20% increased from 22.1% to 68.2% during the period 1985–2017. Significant asymmetric warming rates at urban stations were identified, which were approximately 3 times larger compared to the average asymmetry observed at all 2454 stations in China. However, this asymmetry disappeared at rural stations. These differences are mainly due to the rapid local urbanization around most meteorological stations in China since 1985, which affected the spatial representation of observations and led to the observed asymmetry warming rates. The results reported here indicate that the observed asymmetric warming rate over China from 1985 to 2017 is an observational bias due to local urbanization around most stations rather than large-scale climate change. The results also explain the phenomenon that the observed warming rate of Tmin remains higher than that of Tmax after 1990 when the surface solar radiation stops decreasing in China. Jiang, S., K. Wang, and Y. Mao, 2020. J. Climate, 33, 9045–9061, https://doi.org/10.1175/JCLI-D-20-0118.1.

Spurious correlations between recent warming and indices of local economic activity – Schmidt (2009) “A series of climate model simulations of the 20th Century are analysed to investigate a number of published correlations between indices of local economic activity and recent global warming. These correlations have been used to support a hypothesis that the observed surface warming record has been contaminated in some way and thus overestimates true global warming. However, the basis of the results are correlations over a very restricted set of locations (predominantly western Europe, Japan and the USA) which project strongly onto naturally occurring patterns of climate variability, or are with fields with significant amounts of spatial auto-correlation. Across model simulations, the correlations vary widely due to the chaotic weather component in any short-term record. The reported correlations do not fall outside the simulated distribution, and are probably spurious (i.e. are likely to have arisen from chance alone). Thus, though this study cannot prove that the global temperature record is unbiased, there is no compelling evidence from these correlations of any large-scale contamination.” [Full text]

Urbanization effects in large-scale temperature records, with an emphasis on China – Jones et al. (2008) “We show examples of the UHIs at London and Vienna, where city center sites are warmer than surrounding rural locations. Both of these UHIs however do not contribute to warming trends over the 20th century because the influences of the cities on surface temperatures have not changed over this time. In the main part of the paper, for China, we compare a new homogenized station data set with gridded temperature products and attempt to assess possible urban influences using sea surface temperature (SST) data sets for the area east of the Chinese mainland. We show that all the land-based data sets for China agree exceptionally well and that their residual warming compared to the SST series since 1951 is relatively small compared to the large-scale warming. Urban-related warming over China is shown to be about 0.1°C decade⁻¹ over the period 1951–2004, with true climatic warming accounting for 0.81°C over this period.”

Urban and rural temperature trends in proximity to large US cities: 1951-2000 – Stone (2007) “In this study, temperature data from urban and proximate rural stations for 50 large US metropolitan areas are analysed to establish the mean decadal rate of change in urban temperatures, rural temperatures, and heat island intensity over five decades. The results of this analysis find the mean decadal rate of change in the heat island intensity of large US cities between 1951 and 2000 to be 0.05 °C and further show a clear division in temperature trends between cities situated in the northeastern and southern regions of the country.” [Full text]

Urban heat island effect on annual mean temperature during the last 50 years in China – Li et al. (2004) “To detect the UHI effect, the annual mean surface air temperature (SAT) time series were firstly classified into 5 subregions by using Rotated Principal Components Analysis (RPCA) according to its high and low frequency climatic change features. Then the average UHI effect on each subregions regional annual mean STA was studied. Results indicate that the UHI effect on the annual mean temperatures includes three aspects: increase of the average values, decrease of variances and change of the climatic trends. The effect on the climatic trends is different from region to region.”

Assessment of Urban Versus Rural In Situ Surface Temperatures in the Contiguous United States: No Difference Found – Peterson (2003) “Using satellite night-lights–derived urban/rural metadata, urban and rural temperatures from 289 stations in 40 clusters were compared using data from 1989 to 1991. Contrary to generally accepted wisdom, no statistically significant impact of urbanization could be found in annual temperatures. It is postulated that this is due to micro- and local-scale impacts dominating over the mesoscale urban heat island. Industrial sections of towns may well be significantly warmer than rural sites, but urban meteorological observations are more likely to be made within park cool islands than industrial regions.” [Full text]

A Technique for Using Composite DMSP/OLS ”City Lights” Satellite Data to Map Urban Area – Imhoff et al. (1997) “A Tresholding technique was used to convert a prototype “city lights” data set from the National Oceanic and Atmospheric Administration’s National Geophysical Data Center (NOAAINGDC) into a map of “urban areas” for the continental United States. … We found that a threshold of %89% yielded the best results, removing ephemeral light sources and “blooming” of light onto water when adjacent to cities while still leaving the dense urban core intact. This approach gave very good results when compared with the urban areas as defined by the 1990 U. S. Census; the “urban” area from our analysis being only 5% less than that of the Census.”

Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology – Roth et al. (1989) “NOAA AVHRR satellite infra-red data are used to display the surface radiant temperature heat islands of Vancouver, British Columbia, Seattle, Washington, and Los Angeles, California. Heat island intensities are largest in the day-time and in the warm season. Day-time intra-urban thermal patterns are strongly correlated with land-use; industrial areas are warmest and vegetated, riverine or coastal areas are coolest. Nocturnal heat island intensities and the correlation of the surface radiant temperature distribution with land use are less. This is the reverse of the known characteristics of near-surface air temperature heat islands. Several questions relating to the interpretation and limitations of satellite data in heat island analysis and urban climate modelling are addressed.”

Urbanization: Its Detection and Effect in the United States Climate Record – Karl et al. (1988) “The results indicate that urban effects on temperature are detectable even for small towns with populations under 10 000. Stations with populations near 10 000 are shown to average 0.1°C warmer for the mean annual temperature than nearby stations located in rural areas with populations less than 2000. Urbanization decreases the daily maxima in all seasons except winter and the temperature range in all seasons. It increases the diurnal minima and the daily means in all seasons. The equations indicate that, for the annual mean temperature, urbanization during the twentieth century accounts for a warm bias of about 0.06°C in the U.S. Historical Climatology Network (HCN).” [Full text]

City size and the urban heat island – Oke (1973) “The paper demonstrates the relationship existing between the size of a village, town or city (as measured by its population), and the magnitude of the urban heat island it produces. This is accomplished by analyzing data gathered by automobile traverses in 10 settlements on the St. Lawrence Lowland, whose populations range from 1000 to 2 million inhabitants. The locations of these settlements effectively eliminate all non-urban climatic influences. The results are compared with previously published data.”

On the causes of instrumentally observed secular temperature trends – Mitchell (1953) “Three independent studies of city influence are presented. In the first, recent overlapping observations between the New Haven city and airport stations are used to estimate the local city influence which in turn is used to revise the secular station trend. In the second, evidence of negligible city influence but of real climatic change at Blue Hill Observatory since 1890 is discussed. In the third, a statistical study involving 77 stations in the United States, whose temperature records were observationally homogeneous between 1900 and 1940, bears out the prevalence of important city influence in this country. Except in the period of rapid climatic temperature change occurring since about 1890, observed temperature records, with few individual exceptions, are concluded to be very misleading as direct measures of macroclimatic change over periods longer than a few decades. With their use in climatic studies, particularly those extending back of 1900, isolation of the effects of widespread urban development and frequent thermometer relocation is imperative. At average stations in the United States, urban development has contributed local temperature rises at the rate of more than 1F in a century. The influence of very large cities has not been in proportion.” [Full text]

Closely related

How Researchers Measure Urban Heat Islands – James Voogt

Does Urban Heat Island effect exaggerate global warming trends? – John Cook