Attribution of extreme temperature changes during 1951᾿010

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• 作者：Yeon-Hee Kim ; Seung-Ki Min ; Xuebin Zhang ; Francis Zwiers…
• 关键词：Detection and attribution ; Extreme temperature ; Anthropogenic forcing ; Natural variability ; CMIP5 models
• 刊名：Climate Dynamics
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：46
• 期：5-6
• 页码：1769-1782
• 全文大小：5,092 KB
• 参考文献：Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109
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• 作者单位：Yeon-Hee Kim (1)
  Seung-Ki Min (1)
  Xuebin Zhang (2)
  Francis Zwiers (3)
  Lisa V. Alexander (4)
  Markus G. Donat (4)
  Yu-Shiang Tung (5)
  
  1. School of Environmental Science and Engineering, Pohang University of Science and Technology, Pohang, Gyeongbuk, 790-784, Korea
  2. Climate Research Division, Environment Canada, Toronto, ON, Canada
  3. Pacific Climate Impacts Consortium, Victoria, BC, Canada
  4. Climate Change Research Centre and ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW, Australia
  5. National Science and Technology Center for Disaster Reduction, Taipei, Taiwan
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geophysics and Geodesy
  Meteorology and Climatology
  Oceanography
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1432-0894

文摘

An attribution analysis of extreme temperature changes is conducted using updated observations (HadEX2) and multi-model climate simulation (CMIP5) datasets for an extended period of 1951–2010. Compared to previous HadEX/CMIP3-based results, which identified human contributions to the observed warming of extreme temperatures on global and regional scales, the current results provide better agreement with observations, particularly for the intensification of warm extremes. Removing the influence of two major modes of natural internal variability (the Arctic Oscillation and Pacific Decadal Oscillation) from observations further improves attribution results, reducing the model-observation discrepancy in cold extremes. An optimal fingerprinting technique is used to compare observed changes in annual extreme temperature indices of coldest night and day (TNn, TXn) and warmest night and day (TNx, TXx) with multi-model simulated changes that were simulated under natural-plus-anthropogenic and natural-only (NAT) forcings. Extreme indices are standardized for better intercomparisons between datasets and locations prior to analysis and averaged over spatial domains from global to continental regions following a previous study. Results confirm previous HadEX/CMIP3-based results in which anthropogenic (ANT) signals are robustly detected in the increase in global mean and northern continental regional means of the four indices of extreme temperatures. The detected ANT signals are also clearly separable from the response to NAT forcing, and results are generally insensitive to the use of different model samples as well as different data availability.