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

Research output: Contribution to journalArticle

Authors

  • Jacob Schewe
  • Simon Gosling
  • Christopher Reyer
  • Fang Zhao
  • Philippe Ciais
  • Joshua Elliott
  • Louis Francois
  • Veronika Huber
  • Heike Lotze
  • Sonia Seneviratne
  • Michelle van Vliet
  • Robert Vautard
  • Yoshihide Wada
  • Lutz Breuer
  • Matthias Büchner
  • David A. Carozza
  • Jingfeng 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
  • 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

Colleges, School and Institutes

External organisations

  • ETH Zurich
  • Max Planck Institute for Meteorology

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.

Details

Original languageEnglish
JournalNature Communications
Publication statusPublished - 1 Mar 2019