Chinese Geographical Science

, Volume 18, Issue 3, pp 268–275

Identification and categorization of climate change risks

  • Yuehong Zhang
  • Shaohong Wu
  • Erfu Dai
  • Dengwei Liu
  • Yunhe Yin
Article

DOI: 10.1007/s11769-008-0268-1

Cite this article as:
Zhang, Y., Wu, S., Dai, E. et al. Chin. Geogr. Sci. (2008) 18: 268. doi:10.1007/s11769-008-0268-1
  • 48 Downloads

Abstract

The scientific evidence that climate is changing due to greenhouse gas emission is now incontestable, which may put many social, biological, and geophysical systems in the world at risk. In this paper, we first identified main risks induced from or aggravated by climate change. Then we categorized them applying a new risk categorization system brought forward by Renn in a framework of International Risk Governance Council. We proposed that “uncertainty” could be treated as the classification criteria. Based on this, we established a quantitative method with fuzzy set theory, in which “confidence” and “likelihood”, the main quantitative terms for expressing uncertainties in IPCC, were used as the feature parameters to construct the fuzzy membership functions of four risk types. According to the maximum principle, most climate change risks identified were classified into the appropriate risk types. In the mean time, given that not all the quantitative terms are available, a qualitative approach was also adopted as a complementary classification method. Finally, we get the preliminary results of climate change risk categorization, which might lay the foundation for the future integrated risk management of climate change.

Keywords

climate change risk identification risk categorization uncertainty degree of membership 

Copyright information

© Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag GmbH 2008

Authors and Affiliations

  • Yuehong Zhang
    • 1
    • 2
  • Shaohong Wu
    • 1
  • Erfu Dai
    • 1
  • Dengwei Liu
    • 3
  • Yunhe Yin
    • 1
  1. 1.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.Graduate University of the Chinese Academy of SciencesBeijingChina
  3. 3.Development Research CenterMinistry of Water ResourcesBeijingChina

Personalised recommendations