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Title: On the nonlinearity of spatial scales in extreme weather attribution statements

Abstract

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 ofmore » 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.« less

Authors:
ORCiD logo [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)
Publication Date:
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)
OSTI Identifier:
1379890
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Climate Dynamics
Additional Journal Information:
Journal Volume: 50; Journal Issue: 7-8; Journal ID: ISSN 0930-7575
Publisher:
Springer-Verlag
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Angélil, Oliver, Stone, Daíthí, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Wehner, Michael, Shiogama, Hideo, Wolski, Piotr, Ciavarella, Andrew, and Christidis, Nikolaos. On the nonlinearity of spatial scales in extreme weather attribution statements. United States: N. p., 2017. Web. doi:10.1007/s00382-017-3768-9.
Angélil, Oliver, Stone, Daíthí, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Wehner, Michael, Shiogama, Hideo, Wolski, Piotr, Ciavarella, Andrew, & Christidis, Nikolaos. On the nonlinearity of spatial scales in extreme weather attribution statements. United States. doi:10.1007/s00382-017-3768-9.
Angélil, Oliver, Stone, Daíthí, Perkins-Kirkpatrick, Sarah, Alexander, Lisa V., Wehner, Michael, Shiogama, Hideo, Wolski, Piotr, Ciavarella, Andrew, and Christidis, Nikolaos. Sat . "On the nonlinearity of spatial scales in extreme weather attribution statements". United States. doi:10.1007/s00382-017-3768-9. https://www.osti.gov/servlets/purl/1379890.
@article{osti_1379890,
title = {On the nonlinearity of spatial scales in extreme weather attribution statements},
author = {Angélil, Oliver and Stone, Daíthí and Perkins-Kirkpatrick, Sarah and Alexander, Lisa V. and Wehner, Michael and Shiogama, Hideo and Wolski, Piotr and Ciavarella, Andrew and Christidis, Nikolaos},
abstractNote = {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.},
doi = {10.1007/s00382-017-3768-9},
journal = {Climate Dynamics},
number = 7-8,
volume = 50,
place = {United States},
year = {2017},
month = {6}
}

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