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On the nonlinearity of spatial scales in extreme weather attribution statements

Journal Article · · Climate Dynamics
 [1];  [2];  [1];  [1];  [2];  [3];  [4];  [5];  [5]
  1. Univ. of New South Wales, Sydney, NSW (Australia)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. National Inst. for Environmental Studies, Tsukaba (Japan)
  4. Univ. of Cape Town (South Africa)
  5. Met Office Hadley Centre, Exeter (United Kingdom)
+ Show Author Affiliations
In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1379890
Journal Information:
Climate Dynamics, Journal Name: Climate Dynamics Journal Issue: 7-8 Vol. 50; ISSN 0930-7575
Publisher:
Springer-VerlagCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (4)

Calibrating Climate Model Ensembles for Assessing Extremes in a Changing Climate journal June 2018
Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales journal October 2019
Embracing the complexity of extreme weather events when quantifying their likelihood of recurrence in a warming world journal February 2019
Importance of Framing for Extreme Event Attribution: The Role of Spatial and Temporal Scales text January 2019

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