There is a new paper that documents the continuning effect of urbanization on surface air temperature trends [h/t Koji Dairaku]
Aoyagi, T., N. Kayaba and Seino, N., 2012: Numerical Simulation of the Surface Air Temperature Change Caused by Increases of Urban Area, Anthropogenic Heat, and Building Aspect Ratio in the Kanto-Koshin Area. Journal of the Meteorological Society of Japan, Vol. 90B, pp. 11–31, 2012 11 doi:10.2151/jmsj.2012-B02
The abstract reads
We investigated a warming trend in the Kanto-Koshin area during a 30-year period (1976-2006). The warming trends at AMeDAS stations were estimated to average a little less than 1.3°C/30 years in both summer and winter. These warming trends were considered to include the trends of large-scale and local-scale warming effects. Because a regional climate model with 20-km resolution without any urban parameterization could not well express the observed warming trends and their daily variations, we investigated whether a mesoscale atmospheric model with an urban canopy scheme could express them. To make the simulations realistic, we used 3 sets of real data: National Land Numerical Information datasets for the estimation of the land use area fractions, anthropogenic heat datasets varying in space and time, and GIS datasets of building shapes in the Tokyo Metropolis for the setting of building aspect ratios. The time integrations over 2 months were executed for both summer and winter. A certain level of correlation was found between the simulated temperature rises and the observed warming trends at the AMeDAS stations. The daily variation of the temperature rises in urban grids was higher at night than in the daytime, and its range was larger in winter than in summer. Such tendencies were consistent with the observational results. From factor analyses, we figured out the classic and some unexpected features of urban warming, as follows: (1) Land use distribution change (mainly caused by the decrease of vegetation cover) had the largest daytime warming effect, and the effect was larger in summer than in winter; (2) anthropogenic heat had a warming effect with 2 small peaks owing to the daily variation of the released heat and the timing of stable atmospheric layer formation; and (3) increased building height was the largest factor contributing to the temperature rises, with a single peak in early morning.
The conclusions state that
By numerical simulations using the JMA-NHM, we studied how much 3 bottom boundary condition changes, namely, in land use area fraction, anthropogenic heat release, and increased building aspect ratio, could explain the warming trends observed at the AMeDAS stations during a 30-year period (1976–2006).
A sensitivity study of land use modification, i.e., the spread of urban area, showed a warming effect on average, and that the effect was larger in grids where the land use modification rate was larger. The e¤ects were very small in central Tokyo because the urban area fraction was already saturated there by 1976. This effect was larger in summer when the Bowen ratio is originally small.
The warming effect of anthropogenic heat was concentrated to the central urban area where the heat was mainly loaded. The effect was larger in winter owing to relatively stable atmospheric conditions. Maximum warming was observed in the morning and a secondary peak was seen in the evening if we set the heat to vary realistically with time.
The increase of the aspect ratio of the buildings also had a warming effect on the surface air temperature. It was mainly caused by the inhibition of radiative cooling during nighttime, and the effect was larger in winter. The daily variation of this effect had a single peak in the morning.
This is a very important study, as it documents that climate observating stations that are in locations which are undergoing urbanization will have a warming (positive temperature trend) which is separate from any larger scale warming. As shown in the post
urbanization continues unabated. NCDC, GISS, CRU and BEST, in their analyses have not adequately considered the bias that urbanization produces in their analyses.