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Title: Comparing regional precipitation and temperature extremes in climate model and reanalysis products

A growing field of research aims to characterise the contribution of anthropogenic emissions to the likelihood of extreme weather and climate events. These analyses can be sensitive to the shapes of the tails of simulated distributions. If tails are found to be unrealistically short or long, the anthropogenic signal emerges more or less clearly, respectively, from the noise of possible weather. Here we compare the chance of daily land-surface precipitation and near-surface temperature extremes generated by three Atmospheric Global Climate Models typically used for event attribution, with distributions from six reanalysis products. The likelihoods of extremes are compared for area-averages over grid cell and regional sized spatial domains. Results suggest a bias favouring overly strong attribution estimates for hot and cold events over many regions of Africa and Australia, and a bias favouring overly weak attribution estimates over regions of North America and Asia. For rainfall, results are more sensitive to geographic location. Although the three models show similar results over many regions, they do disagree over others. Equally, results highlight the discrepancy amongst reanalyses products. This emphasises the importance of using multiple reanalysis and/or observation products, as well as multiple models in event attribution studies.
 [1] ;  [1] ;  [1] ;  [2] ;  [1] ;  [2] ;  [3] ;  [4] ;  [4]
  1. University of New South Wales (UNSW), Sydney (Australia). Climate Change Research Centre and ARC Centre of Excellence for Climate System Science
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. National Institute for Environmental Studies, Tsukuba (Japan)
  4. Met Office Hadley Centre, Exeter (United Kingdom)
Publication Date:
Grant/Contract Number:
AC02-05CH11231; AC02- 05CH11231; GA01101
Published Article
Journal Name:
Weather and Climate Extremes
Additional Journal Information:
Journal Volume: 13; Journal Issue: C; Journal ID: ISSN 2212-0947
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; Extremes; Evaluation; Event attribution; CAM5.1; MIROC5; HadGEM3-A-N216
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1377441