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Advances in Meteorology
Volume 2015, Article ID 352360, 12 pages
Research Article

A Comparison of Two Methods on the Climatic Effects of Urbanization in the Beijing-Tianjin-Hebei Metropolitan Area

1Key Laboratory of Computational Geodynamics, Chinese Academy of Sciences, Beijing 100049, China
2College of Earth Science, University of Chinese Academy of Sciences, Beijing 100049, China
3State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China

Received 28 September 2014; Revised 25 March 2015; Accepted 8 April 2015

Academic Editor: Charles Jones

Copyright © 2015 Mingna Wang and Xiaodong Yan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Both the “urban minus rural” (UMR) and the “observation minus reanalysis” (OMR) methods were used to quantify the potential impacts of urbanization on regional temperature changes in the Beijing-Tianjin-Hebei metropolitan area in China. DMSP/OLS nighttime light imagery and population census data were used to classify stations into four classes: rural, small city, medium city, and large city groups. The regional average annual mean temperature was estimated to increase by 0.12°C decade−1 derived from urban warming, accounting for 40% of total climate warming from 1960 to 2009 using the UMR method. The OMR method also indicates that rapid urbanization has a significant influence on surface warming trend although the urban warming intensity is dependent on reanalysis dataset. The seasonal cycle patterns from all three datasets are consistent with each other, which is contrary to the UMR result owing to the cooling effect of agriculture activity in the rural stations confusing the UMR result. So in this paper we found a deficiency of the UMR method where it would underestimate the effects of urbanization in summer. In this regard, the results from the OMR method are relatively more convincing although we admit it still has many other problems.