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Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events
Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961–2005 attribution period frequently underestimate the influence of gl...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080452/ https://www.ncbi.nlm.nih.gov/pubmed/32206708 http://dx.doi.org/10.1126/sciadv.aay2368 |
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author | Diffenbaugh, Noah S. |
author_facet | Diffenbaugh, Noah S. |
author_sort | Diffenbaugh, Noah S. |
collection | PubMed |
description | Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961–2005 attribution period frequently underestimate the influence of global warming on the probability of unprecedented extremes during the 2006–2017 period. This underestimation is particularly pronounced for hot and wet events, with greater uncertainty for dry events. The underestimation is reflected in discrepancies between probabilities predicted during the attribution period and frequencies observed during the out-of-sample verification period. These discrepancies are most explained by increases in climate forcing between the attribution and verification periods, suggesting that 21st-century global warming has substantially increased the probability of unprecedented hot and wet events. Hence, the use of temporally lagged periods for attribution—and, more broadly, for extreme event probability quantification—can cause underestimation of historical impacts, and current and future risks. |
format | Online Article Text |
id | pubmed-7080452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70804522020-03-23 Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events Diffenbaugh, Noah S. Sci Adv Research Articles Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961–2005 attribution period frequently underestimate the influence of global warming on the probability of unprecedented extremes during the 2006–2017 period. This underestimation is particularly pronounced for hot and wet events, with greater uncertainty for dry events. The underestimation is reflected in discrepancies between probabilities predicted during the attribution period and frequencies observed during the out-of-sample verification period. These discrepancies are most explained by increases in climate forcing between the attribution and verification periods, suggesting that 21st-century global warming has substantially increased the probability of unprecedented hot and wet events. Hence, the use of temporally lagged periods for attribution—and, more broadly, for extreme event probability quantification—can cause underestimation of historical impacts, and current and future risks. American Association for the Advancement of Science 2020-03-18 /pmc/articles/PMC7080452/ /pubmed/32206708 http://dx.doi.org/10.1126/sciadv.aay2368 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Diffenbaugh, Noah S. Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title | Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title_full | Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title_fullStr | Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title_full_unstemmed | Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title_short | Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events |
title_sort | verification of extreme event attribution: using out-of-sample observations to assess changes in probabilities of unprecedented events |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080452/ https://www.ncbi.nlm.nih.gov/pubmed/32206708 http://dx.doi.org/10.1126/sciadv.aay2368 |
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