State-of-the-art global models underestimate impacts from climate extremes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Jacob Schewe, Simon N Gosling, Christopher Reyer, Fang Zhao, Philippe Ciais, Joshua Elliott, Louis Francois, Veronika Huber, Heike K Lotze, Sonia I Seneviratne, Michelle T H van Vliet, Robert Vautard, Yoshihide Wada, Lutz Breuer, Matthias Büchner, David A Carozza, Jinfeng Chang, Marta Coll, Delphine Deryng, Allard de Wit, Tyler D Eddy, Christian Folberth, Katja Frieler, Andrew D Friend, Dieter Gerten, Lukas Gudmundsson, Naota Hanasaki, Akihiko Ito, Nikolay Khabarov, Hyungjun Kim, Peter Lawrence, Catherine Morfopoulos, Christoph Müller, Hannes Müller Schmied, René Orth, Sebastian Ostberg, Yadu Pokhrel, Thomas A M Pugh, Gen Sakurai, Yusuke Satoh, Erwin Schmid, Tobias Stacke, Jeroen Steenbeek, Jörg Steinkamp, Qiuhong Tang, Hanqin Tian, Derek P Tittensor, Jan Volkholz, Xuhui Wang, Lila Warszawski

ABSTRACT

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. More... »

PAGES

1005

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-019-08745-6

    DOI

    http://dx.doi.org/10.1038/s41467-019-08745-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112473762

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30824763


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    756 https://www.grid.ac/institutes/grid.7445.2 schema:alternateName Imperial College London
    757 schema:name Imperial College of London, Department of Life Science, Silwood Park Campus Buckhurst Rd, Berks, SL5 7PY, UK.
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    759 https://www.grid.ac/institutes/grid.7468.d schema:alternateName Humboldt University of Berlin
    760 schema:name Geography Department, Humboldt-Universität zu Berlin, 10099, Berlin, Germany.
    761 IRI THEsys, Humboldt University of Berlin, 10117, Berlin, Germany.
    762 Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, 15374, Germany.
    763 Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, 14473, Potsdam, Germany.
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    765 https://www.grid.ac/institutes/grid.75276.31 schema:alternateName International Institute for Applied Systems Analysis
    766 schema:name International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361, Laxenburg, Austria.
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    768 https://www.grid.ac/institutes/grid.7839.5 schema:alternateName Goethe University Frankfurt
    769 schema:name Institute of Physical Geography, Goethe-University Frankfurt, Altenhöferallee 1, 60438, Frankfurt am Main, Germany.
    770 Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Senckenberganlage 25, 60325, Frankfurt, Germany.
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    773 schema:name Centre for International Development and Environmental Research (ZEU), Justus Liebig University Giessen, Senckenbergstraße 3, 35392, Giessen, Germany.
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