Articles | Volume 16, issue 2
https://doi.org/10.5194/esd-16-411-2025
© Author(s) 2025. This work is distributed under
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the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/esd-16-411-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Mar 2025
Research article |
| 12 Mar 2025
| 12 Mar 2025
Early opportunity signals of a tipping point in the UK's second-hand electric vehicle market
Chris A. Boulton
CORRESPONDING AUTHOR
Global Systems Institute, University of Exeter, Exeter, EX4 4QE, UK
Joshua E. Buxton
Global Systems Institute, University of Exeter, Exeter, EX4 4QE, UK
Timothy M. Lenton
Global Systems Institute, University of Exeter, Exeter, EX4 4QE, UK
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Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
Earth Syst. Dynam., 15, 1117–1135, https://doi.org/10.5194/esd-15-1117-2024, https://doi.org/10.5194/esd-15-1117-2024, 2024
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Tipping points are abrupt, rapid, and sometimes irreversible changes, and numerous approaches have been proposed to detect them in advance. Such approaches have been termed early warning signals and represent a set of methods for identifying changes in the underlying behaviour of a system across time or space that might indicate an approaching tipping point. Here, we review the literature to explore where, how, and which early warnings have been used in real-world case studies so far.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
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Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Jakob Deutloff, Hermann Held, and Timothy M. Lenton
Earth Syst. Dynam., 16, 565–583, https://doi.org/10.5194/esd-16-565-2025, https://doi.org/10.5194/esd-16-565-2025, 2025
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We investigate the probabilities of triggering climate tipping points under various emission scenarios and how they are altered by additional carbon emissions from the tipping of the Amazon and permafrost. We find that there is a high risk for triggering climate tipping points under a scenario comparable to current policies. However, the additional warming and hence the additional risk of triggering other climate tipping points from the tipping of the Amazon and permafrost remain small.
Mark S. Williamson and Timothy M. Lenton
Earth Syst. Dynam., 15, 1483–1508, https://doi.org/10.5194/esd-15-1483-2024, https://doi.org/10.5194/esd-15-1483-2024, 2024
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Climate models have transitioned to a superrotating atmospheric state under a broad range of warm climates. Such a transition would change global weather patterns should it occur. Here we simulate this transition using an idealized climate model and look for any early warnings of the superrotating state before it happens. We find several early warning indicators that we attribute to an oscillating pattern in the windfield fluctuations.
Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
Earth Syst. Dynam., 15, 1117–1135, https://doi.org/10.5194/esd-15-1117-2024, https://doi.org/10.5194/esd-15-1117-2024, 2024
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Tipping points are abrupt, rapid, and sometimes irreversible changes, and numerous approaches have been proposed to detect them in advance. Such approaches have been termed early warning signals and represent a set of methods for identifying changes in the underlying behaviour of a system across time or space that might indicate an approaching tipping point. Here, we review the literature to explore where, how, and which early warnings have been used in real-world case studies so far.
Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm
Earth Syst. Dynam., 15, 789–800, https://doi.org/10.5194/esd-15-789-2024, https://doi.org/10.5194/esd-15-789-2024, 2024
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Cascading effects through cross-system interactions are one of the biggest promises of positive tipping points to create rapid climate and sustainability action. Here, we review these in terms of their interactions with sociotechnical systems such as energy, transport, agriculture, society, and policy.
Antony Philip Emenyu, Thomas Pienkowski, Andrew M. Cunliffe, Timothy M. Lenton, and Tom Powell
EGUsphere, https://doi.org/10.5194/egusphere-2023-2531, https://doi.org/10.5194/egusphere-2023-2531, 2023
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This paper explores what processes could boost adoption rates for regenerative agriculture programs in Africa and draws on insights from successful rapid scaling of TIST in east Africa. Found that the cultivation of reinforcing feedback processes that strengthened the social capital around adoption and elimination of barriers to carbon accreditation for RA projects to be key success factors and possible opportunities new and ongoing RA programs to boost their adoption rates.
Stephen P. Hesselbo, Aisha Al-Suwaidi, Sarah J. Baker, Giorgia Ballabio, Claire M. Belcher, Andrew Bond, Ian Boomer, Remco Bos, Christian J. Bjerrum, Kara Bogus, Richard Boyle, James V. Browning, Alan R. Butcher, Daniel J. Condon, Philip Copestake, Stuart Daines, Christopher Dalby, Magret Damaschke, Susana E. Damborenea, Jean-Francois Deconinck, Alexander J. Dickson, Isabel M. Fendley, Calum P. Fox, Angela Fraguas, Joost Frieling, Thomas A. Gibson, Tianchen He, Kat Hickey, Linda A. Hinnov, Teuntje P. Hollaar, Chunju Huang, Alexander J. L. Hudson, Hugh C. Jenkyns, Erdem Idiz, Mengjie Jiang, Wout Krijgsman, Christoph Korte, Melanie J. Leng, Timothy M. Lenton, Katharina Leu, Crispin T. S. Little, Conall MacNiocaill, Miguel O. Manceñido, Tamsin A. Mather, Emanuela Mattioli, Kenneth G. Miller, Robert J. Newton, Kevin N. Page, József Pálfy, Gregory Pieńkowski, Richard J. Porter, Simon W. Poulton, Alberto C. Riccardi, James B. Riding, Ailsa Roper, Micha Ruhl, Ricardo L. Silva, Marisa S. Storm, Guillaume Suan, Dominika Szűcs, Nicolas Thibault, Alfred Uchman, James N. Stanley, Clemens V. Ullmann, Bas van de Schootbrugge, Madeleine L. Vickers, Sonja Wadas, Jessica H. Whiteside, Paul B. Wignall, Thomas Wonik, Weimu Xu, Christian Zeeden, and Ke Zhao
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Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
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C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
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Short summary
Early warning signals used to detect tipping points are tested on a dataset of daily views of online electric vehicle (EV) adverts. The attention given to EV adverts spikes upwards after specific events before returning to normality more slowly over time. Alongside increases in autocorrelation and variance, these results are consistent with the movement towards a tipping point to an EV-dominated market, highlighting the ability of these signals to work in previously untested social systems.
Early warning signals used to detect tipping points are tested on a dataset of daily views of...
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