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Climatic Change

, Volume 122, Issue 4, pp 595–608 | Cite as

Detection of urbanization signals in extreme winter minimum temperature changes over Northern China

  • Qingxiang LiEmail author
  • Jiayou Huang
  • Zhihong Jiang
  • Liming Zhou
  • Peng Chu
  • Kaixi Hu
Article

Abstract

Although previous studies show that urbanization contributes to less than 10 % of the long-term regional total warming trend of mean surface air temperature in northeast China (Li et al. 2010), the urban heat island (UHI) impact on extreme temperatures could be more significant. This paper examines the urbanization impact on extreme winter minimum temperatures from 33 stations in North China during the period of 1957–2010. We use the Generalized Extreme Value (GEV) distribution to analyze the distribution of extreme minimum temperatures and the long-term variations of the three distributional characteristics parameters. Results suggest that among the three distribution parameters, the position parameter is the most representative in terms of the long-term extreme minimum temperature change. A new classification method based on the intercommunity (factors analysis method) of the temperature change is developed to detect the urbanization effect on winter extreme minimum temperatures in different cities. During the period of rapid urbanization (after 1980), the magnitude of variations of the three distribution parameters for the urban station group is larger than that for the reference station group, indicating a higher chance of occurrence of warmer weather and a larger fluctuation of temperatures. Among different types of cities, the three parameters of extreme minimum temperature distribution of the urban station group are, without exception, higher than those of the reference station group. The urbanization of different types of cities all show a warming effect, with small-size cities have the most evident effects on extreme minimum temperatures.

Keywords

Station Group Urban Heat Island Generalize Extreme Value Urban Station Generalize Extreme Value Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The study is supported by: the State Key Development Program of Basic Research of China (2010CB951600; 2010CB428505), the National Science and Technology Supporting Plan of the Twelfth Five-Year (2012BAC22B05), National Natural Science Foundation of China (grant 40605021),China Meteorological Administration Special Foundation for Climate Change (CCSF201224). The first author has made an in-depth discussion with Dr. Wang Xiaolan on the separation of urbanization signal by GEV method during his visit to the Ministry of Environment in Canada. Dr. Yang Xuchao of Zhejiang Provincial Metrological Bureau provided data on nocturnal illumination and also technical support for the present study. And we would like to thank Prof. Phil Jones and Mr David Parker for their kindly reviewing an early version of this manuscript and their helpful comments to it.

Supplementary material

10584_2013_1013_MOESM1_ESM.doc (68 kb)
ESM 1 (DOC 68 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Qingxiang Li
    • 1
    Email author
  • Jiayou Huang
    • 2
  • Zhihong Jiang
    • 3
  • Liming Zhou
    • 4
  • Peng Chu
    • 3
  • Kaixi Hu
    • 1
  1. 1.China Meteorological AdministrationNational Meteorological Information CenterBeijingChina
  2. 2.Department of Atmospheric and Oceanic Science, School of PhysicsPeking UniversityBeijingChina
  3. 3.School of Atmospheric ScienceNanjing University of Information Science and TechnologyNanjingChina
  4. 4.Department of Atmospheric and Environmental SciencesUniversity at Albany, State University of New YorkAlbanyUSA

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