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State-of-the-art global models underestimate impacts from climate extremes
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397256/ https://www.ncbi.nlm.nih.gov/pubmed/30824763 http://dx.doi.org/10.1038/s41467-019-08745-6 |
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author | Schewe, Jacob Gosling, Simon N. Reyer, Christopher Zhao, Fang Ciais, Philippe Elliott, Joshua Francois, Louis Huber, Veronika Lotze, Heike K. Seneviratne, Sonia I. van Vliet, Michelle T. H. Vautard, Robert Wada, Yoshihide Breuer, Lutz Büchner, Matthias Carozza, David A. Chang, Jinfeng Coll, Marta Deryng, Delphine de Wit, Allard Eddy, Tyler D. Folberth, Christian Frieler, Katja Friend, Andrew D. Gerten, Dieter Gudmundsson, Lukas Hanasaki, Naota Ito, Akihiko Khabarov, Nikolay Kim, Hyungjun Lawrence, Peter Morfopoulos, Catherine Müller, Christoph Müller Schmied, Hannes Orth, René Ostberg, Sebastian Pokhrel, Yadu Pugh, Thomas A. M. Sakurai, Gen Satoh, Yusuke Schmid, Erwin Stacke, Tobias Steenbeek, Jeroen Steinkamp, Jörg Tang, Qiuhong Tian, Hanqin Tittensor, Derek P. Volkholz, Jan Wang, Xuhui Warszawski, Lila |
author_facet | Schewe, Jacob Gosling, Simon N. Reyer, Christopher Zhao, Fang Ciais, Philippe Elliott, Joshua Francois, Louis Huber, Veronika Lotze, Heike K. Seneviratne, Sonia I. van Vliet, Michelle T. H. Vautard, Robert Wada, Yoshihide Breuer, Lutz Büchner, Matthias Carozza, David A. Chang, Jinfeng Coll, Marta Deryng, Delphine de Wit, Allard Eddy, Tyler D. Folberth, Christian Frieler, Katja Friend, Andrew D. Gerten, Dieter Gudmundsson, Lukas Hanasaki, Naota Ito, Akihiko Khabarov, Nikolay Kim, Hyungjun Lawrence, Peter Morfopoulos, Catherine Müller, Christoph Müller Schmied, Hannes Orth, René Ostberg, Sebastian Pokhrel, Yadu Pugh, Thomas A. M. Sakurai, Gen Satoh, Yusuke Schmid, Erwin Stacke, Tobias Steenbeek, Jeroen Steinkamp, Jörg Tang, Qiuhong Tian, Hanqin Tittensor, Derek P. Volkholz, Jan Wang, Xuhui Warszawski, Lila |
author_sort | Schewe, Jacob |
collection | PubMed |
description | Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought. |
format | Online Article Text |
id | pubmed-6397256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63972562019-03-04 State-of-the-art global models underestimate impacts from climate extremes Schewe, Jacob Gosling, Simon N. Reyer, Christopher Zhao, Fang Ciais, Philippe Elliott, Joshua Francois, Louis Huber, Veronika Lotze, Heike K. Seneviratne, Sonia I. van Vliet, Michelle T. H. Vautard, Robert Wada, Yoshihide Breuer, Lutz Büchner, Matthias Carozza, David A. Chang, Jinfeng Coll, Marta Deryng, Delphine de Wit, Allard Eddy, Tyler D. Folberth, Christian Frieler, Katja Friend, Andrew D. Gerten, Dieter Gudmundsson, Lukas Hanasaki, Naota Ito, Akihiko Khabarov, Nikolay Kim, Hyungjun Lawrence, Peter Morfopoulos, Catherine Müller, Christoph Müller Schmied, Hannes Orth, René Ostberg, Sebastian Pokhrel, Yadu Pugh, Thomas A. M. Sakurai, Gen Satoh, Yusuke Schmid, Erwin Stacke, Tobias Steenbeek, Jeroen Steinkamp, Jörg Tang, Qiuhong Tian, Hanqin Tittensor, Derek P. Volkholz, Jan Wang, Xuhui Warszawski, Lila Nat Commun Article Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought. Nature Publishing Group UK 2019-03-01 /pmc/articles/PMC6397256/ /pubmed/30824763 http://dx.doi.org/10.1038/s41467-019-08745-6 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schewe, Jacob Gosling, Simon N. Reyer, Christopher Zhao, Fang Ciais, Philippe Elliott, Joshua Francois, Louis Huber, Veronika Lotze, Heike K. Seneviratne, Sonia I. van Vliet, Michelle T. H. Vautard, Robert Wada, Yoshihide Breuer, Lutz Büchner, Matthias Carozza, David A. Chang, Jinfeng Coll, Marta Deryng, Delphine de Wit, Allard Eddy, Tyler D. Folberth, Christian Frieler, Katja Friend, Andrew D. Gerten, Dieter Gudmundsson, Lukas Hanasaki, Naota Ito, Akihiko Khabarov, Nikolay Kim, Hyungjun Lawrence, Peter Morfopoulos, Catherine Müller, Christoph Müller Schmied, Hannes Orth, René Ostberg, Sebastian Pokhrel, Yadu Pugh, Thomas A. M. Sakurai, Gen Satoh, Yusuke Schmid, Erwin Stacke, Tobias Steenbeek, Jeroen Steinkamp, Jörg Tang, Qiuhong Tian, Hanqin Tittensor, Derek P. Volkholz, Jan Wang, Xuhui Warszawski, Lila State-of-the-art global models underestimate impacts from climate extremes |
title | State-of-the-art global models underestimate impacts from climate extremes |
title_full | State-of-the-art global models underestimate impacts from climate extremes |
title_fullStr | State-of-the-art global models underestimate impacts from climate extremes |
title_full_unstemmed | State-of-the-art global models underestimate impacts from climate extremes |
title_short | State-of-the-art global models underestimate impacts from climate extremes |
title_sort | state-of-the-art global models underestimate impacts from climate extremes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6397256/ https://www.ncbi.nlm.nih.gov/pubmed/30824763 http://dx.doi.org/10.1038/s41467-019-08745-6 |
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