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Temperature (Urbanization Effects - General) -- Summary
How pervasive are urban heat island (UHI) perversions of instrumental temperatures?  In addressing this question, Hergerl et al. (2001) describe UHI-induced temperature perversions as one of three types of systematic error in the surface air temperature record whose magnitude "cannot be assessed at present."  Nevertheless, they go on to do just that, claiming "it has been estimated that temperature trends over rural stations only are very similar to trends using all station data, suggesting that the effect of urbanization on estimates of global-scale signals should be small."  This statement, however, is patently false.

Consider, for example, the study of De Laat and Maurellis (2004).  Using a global data set developed by Van Aardenne et al. (2001), which reveals the spatial distribution of various levels of industrial activity over the planet as quantified by the intensity of anthropogenic CO2 emissions, they divided the surface of the earth into non-industrial and industrial sectors of various intensity levels, after which they plotted the 1979-2001 temperature trends (C/decade) of the different sectors using data from both the surface and the lower and middle troposphere.

The two scientists report that "measurements of surface and lower tropospheric temperature change give a very different picture from climate model predictions and show strong observational evidence that the degree of industrialization is correlated with surface temperature increases as well as lower tropospheric temperature changes."  Specifically, they find that the surface and lower tropospheric warming trends of all industrial regions are greater than the mean warming trend of the earth's non-industrial regions, and that the difference in warming rate between the two types of land-use grows ever larger as the degree of industrialization increases.

In discussing the implications of their findings, De Laat and Maurellis say that "areas with larger temperature trends (corresponding to higher CO2 emissions) cover a considerable part of the globe," which implies that "the 'real' global mean surface temperature trend is very likely to be considerably smaller than the temperature trend in the CRU [Hadley Center/Climate Research Unit] data," since the temperature measurements that comprise that data base "are often conducted in the vicinity of human (industrial) activity."  These observations, in their words, "suggest a hitherto-overlooked driver of local surface temperature increases, which is linked to the degree of industrialization" and "lends strong support to other indications that surface processes (possibly changes in land-use or the urban heat effect) are crucial players in observed surface temperature changes (Kalnay and Cai, 2003; Gallo et al., 1996, 1999)."  Hence, they conclude that "the observed surface temperature changes might be a result of local surface heating processes and not related to radiative greenhouse gas forcing."  We agree, believing that the evidence for this proposition is so strong, in fact, that the words "might be" in the preceding sentence could actually be replaced with "are."

A very similar study was conducted by McKitrick and Michaels (2004), who calculated 1979-2000 linear trends of monthly mean near-surface air temperature for 218 stations in 93 countries, based upon data they obtained from the Goddard Institute of Space Studies (GISS), after which they regressed the results against indicators of local economic activity -- such as income, gross domestic product growth rates, and coal use -- to see if there was any evidence of these socioeconomic factors impacting the supposedly "pristine as possible" temperature data.  Then, they repeated the process using the gridded surface air temperature data of the Intergovernmental Panel on Climate Change (IPCC).

The two scientists report that the spatial pattern of trends they derived from the GISS data was "significantly correlated with non-climatic factors, including economic activity and sociopolitical characteristics."  Likewise, with respect to the IPCC data, they say that "very similar correlations appear, despite previous attempts to remove non-climatic effects."  These "socioeconomic effects," in the words of McKitrick and Michaels, "add up to a net warming bias," although they state that "precise estimation of its magnitude will require further work."

Actually, we can get a good feel for the magnitude of the "socioeconomic effect" in some past work, such as that of Oke (1973), who measured the urban heat island strength of ten settlements in the St. Lawrence Lowlands of Canada that had populations ranging from approximately 1,000 to 2,000,000 people, after which he compared his results with those obtained for a number of other cities in North America, as well as some in Europe.  Over the population range studied, Oke found that the magnitude of the urban heat island was linearly correlated with the logarithm of population; and this relationship indicated that at the lowest population value encountered, i.e., 1,000 inhabitants, there was an urban heat island effect of 2 to 2.5C, which warming is over twice as great as the increase in mean global air temperature believed to have occurred since the end of the Little Ice Age.  Hence, it should be abundantly clear there is ample opportunity for very large errors to occur in thermometer-derived surface air temperature histories of the 20th-century; and that error is probably best described as a large and growing warming bias.

That this urban heat island-induced error has indeed corrupted data bases that are claimed to be immune from it is suggested by the work of Hergerl and Wallace (2000), who attempted to determine if trends in recognizable atmospheric modes of variability could account for all or part of the observed trend in surface-troposphere temperature differential, i.e., lapse rate, which has been driven by the upward-inclined trend in surface-derived temperatures and the nearly level trend in satellite-derived tropospheric temperatures over the last two decades of the 20th century.  After doing everything they could conceive of doing, they had to conclude that "modes of variability that affect surface temperature cannot explain trends in the observed lapse rate," and that "no mechanism with clear spatial or time structure can be found that accounts for that trend."  In addition, they had to acknowledge that "all attempts to explain all or a significant part of the observed lapse rate trend by modes of climate variability with structured patterns from observations have failed," and that "an approach applying model data to isolate such a pattern has also failed."  Nor could they find any evidence "that interdecadal variations in radiative forcing, such as might be caused by volcanic eruptions, variations in solar output, or stratospheric ozone depletion alone, offer a compelling explanation."  Hence, the two scientists ultimately concluded that "there remains a gap in our fundamental understanding of the processes that cause the lapse rate to vary on interdecadal timescales."

On the other hand, the reason why no meteorological or climatic explanation could be found for the ever-increasing difference between the surface- and satellite-derived temperature trends of the past 20-plus years may be that one of the temperature records is incorrect.  Faced with this possibility, one would logically want to determine which of the records is likely to be erroneous and then assess the consequences of that determination.  Although this task may seem daunting, it is really not that difficult.  One reason why is the good correspondence Hergerl and Wallace found to exist between the satellite and radiosonde temperature trends, which leaves little reason for doubting the veracity of the satellite results, since this comparison essentially amounts to an in situ validation of the satellite record.  A second important reason comes from the realization that it would be extremely easy for a spurious warming of 0.12C per decade to be introduced into the surface air temperature trend as a consequence of the worldwide intensification of the urban heat island effect that was likely driven by the world population increase that occurred in most of the places where surface air temperature measurements were made over the last two decades of the 20th century.

One final question that may arise in relation to this topic is the direct heating of near-surface air in towns and cities by the urban CO2 dome that occurs above them.  Does it contribute significantly to the urban heat island?

In a study designed to answer this question, Balling et al. (2002) obtained vertical profiles of atmospheric CO2 concentration, temperature and humidity over Phoenix, Arizona from measurements made in association with once-daily aircraft flights conducted over a 14-day period in January 2000 that extended through, and far above, the top of the city's urban CO2 dome during the times of its maximum manifestation.  They then employed a one-dimensional infrared radiation simulation model to determine the thermal impact of the urban CO2 dome on the near-surface temperature of the city.  These exercises revealed that the CO2 concentration of the air over Phoenix dropped off rapidly with altitude, returning from a central-city surface value on the order of 600 ppm to a normal non-urban background value of approximately 378 ppm at an air pressure of 800 hPa, creating a calculated surface warming of only 0.12C at the time of maximum CO2-induced warming potential, which is about an order of magnitude less than the urban heat island effect of cities the size of Phoenix.  In fact, the authors concluded that the warming induced by the urban CO2 dome of Phoenix is possibly two orders of magnitude smaller than that produced by other sources of the city's urban heat island.  Hence, although the doings of man are indeed responsible for high urban air temperatures (which can sometimes rise 10C or more above those of surrounding rural areas), these high values are not the result of a local CO2-enhanced greenhouse effect.

In conclusion, it would appear almost certain that surface-based temperature histories of the globe contain a significant warming bias introduced by insufficient corrections for the non-greenhouse-gas-induced urban heat island effect.  Furthermore, it may well be next to impossible to make proper corrections for this deficiency, as the urban heat island of even small towns totally dwarfs any concomitant augmented greenhouse effect that may be present.  Consequently, the only recourse we would seem to have to make valid comparisons with other periods of warmth in earth's past history is to extend the proxy-based reconstructions that reveal their presence up to the present time.  Only then will we know for sure if the Medieval and Roman Warm Periods were as warm as,or warmer than, the latter part of the 20th century, which knowledge is absolutely crucial for assessing the likelihood that modern warmth is or is not due to enhanced greenhouse gas forcing.

Balling Jr., R.C., Cerveny, R.S. and Idso, C.D.  2002.  Does the urban CO2 dome of Phoenix, Arizona contribute to its heat island?  Geophysical Research Letters 28: 4599-4601.

De Laat, A.T.J. and Maurellis, A.N.  2004.  Industrial CO2 emissions as a proxy for anthropogenic influence on lower tropospheric temperature trends.  Geophysical Research Letters 31: 10.1029/2003GL019024.

Gallo, K.P., Easterling, D.R. and Peterson, T.C.  1996.  The influence of land use/land cover on climatological values of the diurnal temperature range.  Journal of Climate 9: 2941-2944.

Gallo, K.P., Owen, T.W., Easterling, D.R. and Jameson, P.F.  1999.  Temperature trends of the historical climatology network based on satellite-designated land use/land cover.  Journal of Climate 12: 1344-1348.

Hegerl, G.C., Jones, P.D. and Barnett, T.P.  2001.  Effect of observational sampling error on the detection of anthropogenic climate change.  Journal of Climate 14: 198-207.

Hegerl, G.C. and Wallace, J.M.  2002.  Influence of patterns of climate variability on the difference between satellite and surface temperature trends.  Journal of Climate 15: 2412-2428.

Kalnay, E. and Cai, M.  2003.  Impact of urbanization and land use change on climate.  Nature 423: 528-531.

McKitrick, R. and Michaels, P.J.  2004.  A test of corrections for extraneous signals in gridded surface temperature data.  Climate Research 26: 159-173.

Oke, T.R.  1973.  City size and the urban heat island.  Atmospheric Environment 7: 769-779.

Van Aardenne, J.A., Dentener, F.J., Olivier, J.G.J., Klein Goldewijk, C.G.M. and Lelieveld, J.  2001.  A 1 x 1 resolution data set of historical anthropogenic trace gas emissions for the period 1890-1990.  Global Biogeochemical Cycles 15: 909-928.

Last updated 6 April 2005