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Climatic Change

, Volume 110, Issue 1–2, pp 385–401 | Cite as

Extreme climate events in China: IPCC-AR4 model evaluation and projection

  • Zhihong Jiang
  • Jie Song
  • Laurent Li
  • Weilin Chen
  • Zhifu Wang
  • Ji Wang
Article

Abstract

Observations from 550 surface stations in China during 1961–2000 are used to evaluate the skill of seven global coupled climate models in simulating extreme temperature and precipitation indices. It is found that the models have certain abilities to simulate both the spatial distributions of extreme climate indices and their trends in the observed period. The models’ abilities are higher overall for extreme temperature indices than for extreme precipitation indices. The well-simulated temperature indices are frost days (Fd), heat wave duration index (HWDI) and annual extreme temperature range (ETR). The well-simulated precipitation indices are the fraction of annual precipitation total due to events exceeding the 95th percentile (R95T) and simple daily intensity index (SDII). In a general manner, the multi-model ensemble has the best skill. For the projections of the extreme temperature indices, trends over the twenty-first century and changes at the end of the twenty-first century go into the same direction. Both frost days and annual extreme temperature range show decreasing trends, while growing season length, heat wave duration and warm nights show increasing trends. The increases are especially manifested in the Tibetan Plateau and in Southwest China. For extreme precipitation indices, the end of the twenty-first century is expected to have more frequent and more intense extreme precipitation. This is particularly visible in the middle and lower reaches of the Yangtze River, in the Southeast coastal region, in the west part of Northwest China, and in the Tibetan Plateau. In the meanwhile, accompanying the decrease in the maximum number of consecutive dry days in Northeast and Northwest, drought situation will reduce in these regions.

Keywords

Tibetan Plateau Precipitation Index Extreme Index Extreme Climate Event Grow Season Length 
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.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Zhihong Jiang
    • 1
  • Jie Song
    • 1
    • 2
  • Laurent Li
    • 1
    • 3
  • Weilin Chen
    • 1
  • Zhifu Wang
    • 1
  • Ji Wang
    • 1
  1. 1.Key Laboratory of Meteorological Disaster, Ministry of EducationNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Northern Illinois UniversityDeKalbUSA
  3. 3.Laboratoire de Météorologie Dynamique, IPSL, CNRS, UPMCParisFrance

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