Beyond bifurcation: using complex models to understand and predict abrupt climate change
Research on the possibility of future abrupt climate change has been popularized under the term ‘tipping points’ and has often been motivated by using simple, low-dimensional concepts. These include the iconic fold bifurcation, where abrupt change occurs when a stable equilibrium is lost, and ea...
Published in: | Dynamics and Statistics of the Climate System |
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Online Access: | http://hdl.handle.net/2078.1/181322 https://doi.org/10.1093/climsys/dzw004 |
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ftunivlouvain:oai:dial.uclouvain.be:boreal:181322 2024-05-12T08:00:35+00:00 Beyond bifurcation: using complex models to understand and predict abrupt climate change Bathiany, Sebastian Dijkstra, Henk Crucifix, Michel Dakos, Vasilis Brovkin, Victor Williamson, Mark S. Lenton, Timothy M. Scheffer, Marten UCL - SST/ELI/ELIC - Earth & Climate 2016 http://hdl.handle.net/2078.1/181322 https://doi.org/10.1093/climsys/dzw004 eng eng Oxford University Press boreal:181322 http://hdl.handle.net/2078.1/181322 doi:10.1093/climsys/dzw004 urn:ISSN:2059-6987 urn:EISSN:2059-6987 info:eu-repo/semantics/openAccess Dynamics and Statistics of the Climate System, Vol. 1, no. 1, p. dzw004 (2016) info:eu-repo/semantics/article 2016 ftunivlouvain https://doi.org/10.1093/climsys/dzw004 2024-04-17T17:00:26Z Research on the possibility of future abrupt climate change has been popularized under the term ‘tipping points’ and has often been motivated by using simple, low-dimensional concepts. These include the iconic fold bifurcation, where abrupt change occurs when a stable equilibrium is lost, and early warning signals of such a destabilization that can be derived based on a simple stochastic model approach. In this paper, we review the challenges and limitations that are associated with this view, and we discuss promising research paths to explore the causes and the likelihood of abrupt changes in future climate. We focus on several climate system components and ecosystems that have been proposed as candidates for tipping points, with an emphasis on ice sheets, the Atlantic Ocean circulation, vegetation in North Africa and Arctic sea ice. In most example cases, multiple equilibria found in simple models do not appear in complex models or become more difficult to find, while the potential for abrupt change still remains. We also discuss how the low-dimensional logic of current methods to detect and interpret the existence of multiple equilibria can fail in complex models. Moreover, we highlight promising methods to detect abrupt shifts and to obtain information about the mechanisms behind them. These methods include linear approaches such as statistical stability indicators and radiative feedback analysis as well as non-linear approaches to detect dynamical transitions and infer the causality behind events. Given the huge complexity of comprehensive process-based climate models and the non-linearity and regional peculiarities of the processes involved, the uncertainties associated with the possible future occurrence of abrupt shifts are large and not well quantified. We highlight the potential of data mining approaches to tackle this problem and finally discuss how the scientific community can collaborate to make efficient progress in understanding abrupt climate shifts. Article in Journal/Newspaper Arctic Climate change Sea ice DIAL@UCLouvain (Université catholique de Louvain) Arctic Dynamics and Statistics of the Climate System dzw004 |
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Open Polar |
collection |
DIAL@UCLouvain (Université catholique de Louvain) |
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ftunivlouvain |
language |
English |
description |
Research on the possibility of future abrupt climate change has been popularized under the term ‘tipping points’ and has often been motivated by using simple, low-dimensional concepts. These include the iconic fold bifurcation, where abrupt change occurs when a stable equilibrium is lost, and early warning signals of such a destabilization that can be derived based on a simple stochastic model approach. In this paper, we review the challenges and limitations that are associated with this view, and we discuss promising research paths to explore the causes and the likelihood of abrupt changes in future climate. We focus on several climate system components and ecosystems that have been proposed as candidates for tipping points, with an emphasis on ice sheets, the Atlantic Ocean circulation, vegetation in North Africa and Arctic sea ice. In most example cases, multiple equilibria found in simple models do not appear in complex models or become more difficult to find, while the potential for abrupt change still remains. We also discuss how the low-dimensional logic of current methods to detect and interpret the existence of multiple equilibria can fail in complex models. Moreover, we highlight promising methods to detect abrupt shifts and to obtain information about the mechanisms behind them. These methods include linear approaches such as statistical stability indicators and radiative feedback analysis as well as non-linear approaches to detect dynamical transitions and infer the causality behind events. Given the huge complexity of comprehensive process-based climate models and the non-linearity and regional peculiarities of the processes involved, the uncertainties associated with the possible future occurrence of abrupt shifts are large and not well quantified. We highlight the potential of data mining approaches to tackle this problem and finally discuss how the scientific community can collaborate to make efficient progress in understanding abrupt climate shifts. |
author2 |
UCL - SST/ELI/ELIC - Earth & Climate |
format |
Article in Journal/Newspaper |
author |
Bathiany, Sebastian Dijkstra, Henk Crucifix, Michel Dakos, Vasilis Brovkin, Victor Williamson, Mark S. Lenton, Timothy M. Scheffer, Marten |
spellingShingle |
Bathiany, Sebastian Dijkstra, Henk Crucifix, Michel Dakos, Vasilis Brovkin, Victor Williamson, Mark S. Lenton, Timothy M. Scheffer, Marten Beyond bifurcation: using complex models to understand and predict abrupt climate change |
author_facet |
Bathiany, Sebastian Dijkstra, Henk Crucifix, Michel Dakos, Vasilis Brovkin, Victor Williamson, Mark S. Lenton, Timothy M. Scheffer, Marten |
author_sort |
Bathiany, Sebastian |
title |
Beyond bifurcation: using complex models to understand and predict abrupt climate change |
title_short |
Beyond bifurcation: using complex models to understand and predict abrupt climate change |
title_full |
Beyond bifurcation: using complex models to understand and predict abrupt climate change |
title_fullStr |
Beyond bifurcation: using complex models to understand and predict abrupt climate change |
title_full_unstemmed |
Beyond bifurcation: using complex models to understand and predict abrupt climate change |
title_sort |
beyond bifurcation: using complex models to understand and predict abrupt climate change |
publisher |
Oxford University Press |
publishDate |
2016 |
url |
http://hdl.handle.net/2078.1/181322 https://doi.org/10.1093/climsys/dzw004 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Sea ice |
genre_facet |
Arctic Climate change Sea ice |
op_source |
Dynamics and Statistics of the Climate System, Vol. 1, no. 1, p. dzw004 (2016) |
op_relation |
boreal:181322 http://hdl.handle.net/2078.1/181322 doi:10.1093/climsys/dzw004 urn:ISSN:2059-6987 urn:EISSN:2059-6987 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1093/climsys/dzw004 |
container_title |
Dynamics and Statistics of the Climate System |
container_start_page |
dzw004 |
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1798842495667273728 |