Articles | Volume 15, issue 6
https://doi.org/10.5194/esd-15-1483-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/esd-15-1483-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Nov 2024
Research article |
| 28 Nov 2024
| 28 Nov 2024
Early warnings of the transition to a superrotating atmospheric state
Mark S. Williamson
CORRESPONDING AUTHOR
Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
Global Systems Institute, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
Timothy M. Lenton
Global Systems Institute, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
Related authors
Patric J. L. Boardman, Joseph Clarke, Peter M. Cox, Chris Huntingford, Christopher D. Jones, and Mark S. Williamson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4899, https://doi.org/10.5194/egusphere-2025-4899, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
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Climate sensitivity quantifies how much Earth warms for a given radiative forcing, and can be characterised by TCR. Although the IPCC estimates the most likely TCR to be 1.8 K, some models predict values >2.4 K. Record warmth in 2023–2024 raises questions as to whether the TCR may indeed be larger than previously suggested. Using up-to-date data, we estimate the TCR to be 1.81 K. We also show that future warming falls within the low–mid model range, making the 2 °C Paris target still feasible.
Joseph Clarke, Chris Huntingford, Paul David Longden Ritchie, Rebecca Varney, Mark Williamson, and Peter Cox
EGUsphere, https://doi.org/10.5194/egusphere-2025-3703, https://doi.org/10.5194/egusphere-2025-3703, 2025
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An increase in CO2 in the atmosphere warms the climate through the greenhouse effect, but also leads to uptake of CO2 by the land and ocean. However, the warming is also expected to suppress carbon uptake. If this suppression were strong enough, it could overwhelm the uptake of carbon, leading to a runaway feedback loop causing severe global warming. We find it is possible that this runaway could be relevant in complex climate models and even at the end of the last ice age.
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
Earth Syst. Dynam., 15, 829–852, https://doi.org/10.5194/esd-15-829-2024, https://doi.org/10.5194/esd-15-829-2024, 2024
Short summary
Short summary
Emergent constraints on equilibrium climate sensitivity (ECS) have generally got statistically weaker in the latest set of state-of-the-art climate models (CMIP6) compared to past sets (CMIP5). We look at why this weakening happened for one particular study (Cox et al, 2018) and attribute it to an assumption made in the theory that when corrected for restores there is a stronger relationship between predictor and ECS.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Short summary
Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Morgan Sparey, Peter Cox, and Mark S. Williamson
Biogeosciences, 20, 451–488, https://doi.org/10.5194/bg-20-451-2023, https://doi.org/10.5194/bg-20-451-2023, 2023
Short summary
Short summary
Accurate climate models are vital for mitigating climate change; however, projections often disagree. Using Köppen–Geiger bioclimate classifications we show that CMIP6 climate models agree well on the fraction of global land surface that will change classification per degree of global warming. We find that 13 % of land will change climate per degree of warming from 1 to 3 K; thus, stabilising warming at 1.5 rather than 2 K would save over 7.5 million square kilometres from bioclimatic change.
Patric J. L. Boardman, Joseph Clarke, Peter M. Cox, Chris Huntingford, Christopher D. Jones, and Mark S. Williamson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4899, https://doi.org/10.5194/egusphere-2025-4899, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
Short summary
Short summary
Climate sensitivity quantifies how much Earth warms for a given radiative forcing, and can be characterised by TCR. Although the IPCC estimates the most likely TCR to be 1.8 K, some models predict values >2.4 K. Record warmth in 2023–2024 raises questions as to whether the TCR may indeed be larger than previously suggested. Using up-to-date data, we estimate the TCR to be 1.81 K. We also show that future warming falls within the low–mid model range, making the 2 °C Paris target still feasible.
Antony Philip Emenyu, Thomas Pienkowski, Andrew M. Cunliffe, Timothy M. Lenton, and Tom W. R. Powell
Earth Syst. Dynam., 16, 1699–1710, https://doi.org/10.5194/esd-16-1699-2025, https://doi.org/10.5194/esd-16-1699-2025, 2025
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This paper proposes a new framework combining scaling theory with positive tipping points to explain how regenerative agriculture can scale rapidly. Drawing on the TIST programme (The International Small group and Tree planting programme) in East Africa, it shows that enabling conditions – like affordability, accessibility, and social trust – can trigger feedback loops such as social contagion and network effects. However, outcomes remain highly context-specific, requiring tailored approaches for sustained adoption.
Joseph Clarke, Chris Huntingford, Paul David Longden Ritchie, Rebecca Varney, Mark Williamson, and Peter Cox
EGUsphere, https://doi.org/10.5194/egusphere-2025-3703, https://doi.org/10.5194/egusphere-2025-3703, 2025
Short summary
Short summary
An increase in CO2 in the atmosphere warms the climate through the greenhouse effect, but also leads to uptake of CO2 by the land and ocean. However, the warming is also expected to suppress carbon uptake. If this suppression were strong enough, it could overwhelm the uptake of carbon, leading to a runaway feedback loop causing severe global warming. We find it is possible that this runaway could be relevant in complex climate models and even at the end of the last ice age.
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.
Chris A. Boulton, Joshua E. Buxton, and Timothy M. Lenton
Earth Syst. Dynam., 16, 411–421, https://doi.org/10.5194/esd-16-411-2025, https://doi.org/10.5194/esd-16-411-2025, 2025
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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.
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
Earth Syst. Dynam., 15, 829–852, https://doi.org/10.5194/esd-15-829-2024, https://doi.org/10.5194/esd-15-829-2024, 2024
Short summary
Short summary
Emergent constraints on equilibrium climate sensitivity (ECS) have generally got statistically weaker in the latest set of state-of-the-art climate models (CMIP6) compared to past sets (CMIP5). We look at why this weakening happened for one particular study (Cox et al, 2018) and attribute it to an assumption made in the theory that when corrected for restores there is a stronger relationship between predictor and ECS.
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.
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
Sci. Dril., 32, 1–25, https://doi.org/10.5194/sd-32-1-2023, https://doi.org/10.5194/sd-32-1-2023, 2023
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We present initial results from a 650 m long core of Late Triasssic to Early Jurassic (190–202 Myr) sedimentary strata from the Cheshire Basin, UK, which is shown to be an exceptional record of Earth evolution for the time of break-up of the supercontinent Pangaea. Further work will determine periodic changes in depositional environments caused by solar system dynamics and used to reconstruct orbital history.
Mila Kim-Chau Fiona Ong, Fenna Blomsma, and Timothy Michael Lenton
EGUsphere, https://doi.org/10.5194/egusphere-2023-2361, https://doi.org/10.5194/egusphere-2023-2361, 2023
Short summary
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We investigate the initially successful transition from regional bottle reuse for mineral water to a widespread bottle reuse system in Germany, its subsequent destabilisation, and what this teaches us about tipping dynamics in packaging systems. Our findings demonstrate opportunities to create an enabling environment for change, and the role of specific reinforcing feedback loops and interventions in accelerating or impeding sustainable transitions.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Short summary
Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
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
Short summary
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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.
Morgan Sparey, Peter Cox, and Mark S. Williamson
Biogeosciences, 20, 451–488, https://doi.org/10.5194/bg-20-451-2023, https://doi.org/10.5194/bg-20-451-2023, 2023
Short summary
Short summary
Accurate climate models are vital for mitigating climate change; however, projections often disagree. Using Köppen–Geiger bioclimate classifications we show that CMIP6 climate models agree well on the fraction of global land surface that will change classification per degree of global warming. We find that 13 % of land will change climate per degree of warming from 1 to 3 K; thus, stabilising warming at 1.5 rather than 2 K would save over 7.5 million square kilometres from bioclimatic change.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
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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.
Cited articles
Anderson, W.: Basic Notions Of Condensed Matter Physics, Basic Books, CRC Press, https://doi.org/10.4324/9780429494116, 1984. a
Armstrong McKay, D. I., Staal, A., Abrams, J. F., Winkelmann, R., Sakschewski, B., Loriani, S., Fetzer, I., Cornell, S. E., Rockström, J., and Lenton, T. M.: Exceeding 1.5°C global warming could trigger multiple climate tipping points, Science, 377, eabn7950, https://doi.org/10.1126/science.abn7950, 2022. a
Ashwin, P., Wieczorek, S., Vitolo, R., and Cox, P.: Tipping points in open systems: Bifurcation, noise-induced and rate-dependent examples in the climate system, Philos. T. Roy. Soc. A, 370, 1166–1184, 2012. a
Brovkin, V., Claussen, M., Petoukhov, V., and Ganopolski, A.: On the stability of the atmosphere-vegetation system in the Sahara/Sahel region, J. Geophys. Res.-Atmos., 103, 31613–31624, https://doi.org/10.1029/1998JD200006, 1998. a
Brunet, G.: Empirical Normal-Mode Analysis of Atmospheric Data, J. Atmos. Sci., 51, 932–952, https://doi.org/10.1175/1520-0469(1994)051<0932:ENMAOA>2.0.CO;2, 1994. a
Budišić, M., Mohr, R., and Mezić, I.: Applied Koopmanism, Chaos: An Interdisciplinary Journal of Nonlinear Science, 22, 047510, https://doi.org/10.1063/1.4772195, 2012. a
Bury, T. M., Bauch, C. T., and Anand, M.: Detecting and distinguishing tipping points using spectral early warning signals, J. R. Soc. Interface, 17, 20200482, https://doi.org/10.1098/rsif.2020.0482, 2020. a
Dakos, V., Scheffer, M., van Nes, E. H., Brovkin, V., Petoukhov, V., and Held, H.: Slowing down as an early warning signal for abrupt climate change, P. Natl. Acad. Sci. USA, 105, 14308–14312, 2008. a
Dakos, V., van Nes, E. H., and Scheffer, M.: Flickering as an early warning signal, Theor. Ecol., 6, 309–317, https://doi.org/10.1007/s12080-013-0186-4, 2013. a, b
Ditlevsen, P. D. and Johnsen, S. J.: Tipping points: Early warnings and wishful thinking, Geophys. Res. Lett., 37, L19703, https://doi.org/10.1029/2010GL044486, 2010. a
Dylewsky, D., Lenton, T. M., Scheffer, M., Bury, T. M., Fletcher, C. G., Anand, M., and Bauch, C. T.: Universal early warning signals of phase transitions in climate systems, J. R. Soc. Interface, 20, 20220562, https://doi.org/10.1098/rsif.2022.0562, 2023. a
Farrell, B. F. and Ioannou, P. J.: Stochastic dynamics of the midlatitude atmospheric jet, J. Atmos. Sci., 52, 1642–1656, 1995. a
Feudel, U.: Rate-induced tipping in ecosystems and climate: the role of unstable states, basin boundaries and transient dynamics, Nonlin. Processes Geophys., 30, 481–502, https://doi.org/10.5194/npg-30-481-2023, 2023. a
Gierasch, P. J.: Meridional Circulation and the Maintenance of the Venus Atmospheric Rotation, J. Atmos. Sci., 32, 1038–1044, https://doi.org/10.1175/1520-0469(1975)032<1038:MCATMO>2.0.CO;2, 1975. a
Gordon, C. T. and Stern, W. F.: A Description of the GFDL Global Spectral Model, Mon. Weather Rev., 110, 625–644, https://doi.org/10.1175/1520-0493(1982)110<0625:ADOTGG>2.0.CO;2, 1982. a
Hasselmann, K.: PIPs and POPs: The reduction of complex dynamical systems using principal interaction and oscillation patterns, J. Geophys. Res.-Atmos., 93, 11015–11021, https://doi.org/10.1029/JD093iD09p11015, 1988. a
Held, H. and Kleinen, T.: Detection of climate system bifurcations by degenerate fingerprinting, Geophys. Res. Lett., 31, L23207, https://doi.org/10.1029/2004GL020972, 2004. a
Held, I. M.: Equatorial superrotation in Earth-like atmospheric models, https://www.gfdl.noaa.gov/wp-content/uploads/files/user_files/ih/lectures/super.pdf (last access: 25 November 2024), 1999. a
Held, I. M. and Suarez, M. J.: A Proposal for the Intercomparison of the Dynamical Cores of Atmospheric General Circulation Models, B. Am. Meteor. Soc., 75, 1825–1830, https://doi.org/10.1175/1520-0477(1994)075<1825:APFTIO>2.0.CO;2, 1994. a, b
Herbert, C., Caballero, R., and Bouchet, F.: Atmospheric Bistability and Abrupt Transitions to Superrotation: Wave-Jet Resonance and Hadley Cell Feedbacks, J. Atmos. Sci., 77, 31–49, https://doi.org/10.1175/JAS-D-19-0089.1, 2020. a
Hide, R.: Dynamics of the Atmospheres of the Major Planets with an Appendix on the Viscous Boundary Layer at the Rigid Bounding Surface of an Electrically-Conducting Rotating Fluid in the Presence of a Magnetic Field, J. Atmos. Sci., 26, 841–853, https://doi.org/10.1175/1520-0469(1969)026<0841:DOTAOT>2.0.CO;2, 1969. a
Huang, H.-P., Weickmann, K. M., and Hsu, C. J.: Trend in Atmospheric Angular Momentum in a Transient Climate Change Simulation with Greenhouse Gas and Aerosol Forcing, J. Climate, 14, 1525–1534, https://doi.org/10.1175/1520-0442(2001)014<1525:TIAAMI>2.0.CO;2, 2001. a, b, c
IPCC: The Ocean and Cryosphere in a Changing Climate: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, https://doi.org/10.1017/9781009157964, 2019. a
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2023. a
Laraia, A. L. and Schneider, T.: Superrotation in Terrestrial Atmospheres, J. Atmos. Sci., 72, 4281–4296, https://doi.org/10.1175/JAS-D-15-0030.1, 2015. a
Lenton, T., Rockström, J., Gaffney, O., Rahmstorf, S., Richardson, K., Steffen, W., and Schellnhuber, H.: Climate tipping points – too risky to bet against, Nature, 575, 592–595, https://doi.org/10.1038/d41586-019-03595-0, 2019. a
Lenton, T. M., Livina, V. N., Dakos, V., van Nes, E. H., and Scheffer, M.: Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness, Philos. T. R. Soc. A, 370, 1185–1204, 2012. a
Livina, V. N. and Lenton, T. M.: A modified method for detecting incipient bifurcations in a dynamical system, Geophys. Res. Lett., 34, L03712, https://doi.org/10.1029/2006GL028672, 2007. a
Loriani, S., Aksenov, Y., Armstrong McKay, D., Bala, G., Born, A., Chiessi, C. M., Dijkstra, H., Donges, J. F., Drijfhout, S., England, M. H., Fedorov, A. V., Jackson, L., Kornhuber, K., Messori, G., Pausata, F., Rynders, S., Salée, J.-B., Sinha, B., Sherwood, S., Swingedouw, D., and Tharammal, T.: Tipping points in ocean and atmosphere circulations, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2589, 2023. a
Mecking, J. V., Drijfhout, S. S., Jackson, L. C., and Graham, T.: Stable AMOC off state in an eddy-permitting coupled climate model, Clim. Dynam., 47, 2455–2470, https://doi.org/10.1007/s00382-016-2975-0, 2016. a, b
Penland, C.: Random forcing and forecasting using principal oscillation pattern analysis, Mon. Weather Rev., 117, 2165–2185, https://doi.org/10.1175/1520-0493(1989)117<2165:RFAFUP>2.0.CO;2, 1989. a
Penland, C. and Ghil, M.: Forecasting Northern Hemisphere 700 mb geopotential height anomalies using empirical normal modes, Mon. Weather Rev., 121, 2355–2371, https://doi.org/10.1175/1520-0493(1993)121<2355:FNHMGH>2.0.CO;2, 1993. a
Penland, C. and Magorian, T.: Prediction of Niño 3 Sea Surface Temperatures Using Linear Inverse Modeling, J. Climate, 6, 1067–1076, http://www.jstor.org/stable/26197251, 1993. a
Pierrehumbert, R. T.: Climate change and the tropical Pacific: The sleeping dragon wakes, P. Natl. Acad. Sci. USA, 97, 1355–1358, https://doi.org/10.1073/pnas.97.4.1355, 2000. a, b
Read, P. L.: Super-rotation and diffusion of axial angular momentum: II. A review of quasi-axisymmetric models of planetary atmospheres, Q. J. Roy. Meteor. Soc., 112, 253–272, https://doi.org/10.1002/qj.49711247114, 1986. a
Read, P. L. and Lebonnois, S.: Superrotation on Venus, on Titan, and Elsewhere, Annu. Rev. Earth Planet. Sci., 46, 175–202, https://doi.org/10.1146/annurev-earth-082517-010137, 2018. a
Saravanan, R.: Equatorial Superrotation and Maintenance of the General Circulation in Two-Level Models, J. Atmos. Sci., 50, 1211–1227, https://doi.org/10.1175/1520-0469(1993)050<1211:ESAMOT>2.0.CO;2, 1993. a, b, c
Scheffer, M., Bacompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., and Sugihara, G.: Early warning signals for critical transitions, Nature, 461, 53–59, 2009. a
Scheffer, M., Carpenter, S. R., Lenton, T. M., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I. A., Levin, S. A., van Nes, E. H., Pascual, M., and Vandermeer, J.: Anticipating Critical Transitions, Science, 338, 344–348, 2012. a
Scott, R. K. and Polvani, L. M.: Equatorial superrotation in shallow atmospheres, Geophys. Res. Lett., 35, L24202, https://doi.org/10.1029/2008GL036060, 2008. a
Shell, K. M. and Held, I. M.: Abrupt Transition to Strong Superrotation in an Axisymmetric Model of the Upper Troposphere, J. Atmos. Sci., 61, 2928–2935, https://doi.org/10.1175/JAS-3312.1, 2004. a, b
Strogatz, S. H.: Nonlinear Dynamics and Chaos, Westview Press, https://doi.org/10.1201/9780429492563, 2001. a, b
Tantet, A., van der Burgt, F. R., and Dijkstra, H. A.: An early warning indicator for atmospheric blocking events using transfer operators, Chaos, 25, 036406, https://doi.org/10.1063/1.4908174, 2015. a
Thompson, J. M. T. and Sieber, J.: Predicting climate tipping as a noisy bifurcation: A review, Int. J. Bif. Chaos, 21, 399–423, 2011. a
Thompson, J. M. T., Stewart, H. B., and Ueda, Y.: Safe, explosive, and dangerous bifurcations in dissipative dynamical systems, Phys. Rev. E, 49, 1019–1027, https://doi.org/10.1103/PhysRevE.49.1019, 1994. a
Tziperman, E. and Farrell, B.: Pliocene equatorial temperature: Lessons from atmospheric superrotation, Paleoceanography, 24, PA1101, https://doi.org/10.1029/2008PA001652, 2009. a, b, c
Vallis, G. K., Colyer, G., Geen, R., Gerber, E., Jucker, M., Maher, P., Paterson, A., Pietschnig, M., Penn, J., and Thomson, S. I.: Isca, v1.0: a framework for the global modelling of the atmospheres of Earth and other planets at varying levels of complexity, Geosci. Model Dev., 11, 843–859, https://doi.org/10.5194/gmd-11-843-2018, 2018. a
von Storch, H. and Zwiers, F. W.: Statistical Analysis in Climate Research, Cambridge University Press, https://doi.org/10.1017/CBO9780511612336, 1999. a, b, c
Wang, P. and Mitchell, J. L.: Planetary ageostrophic instability leads to superrotation, Geophys. Res. Lett., 41, 4118–4126, https://doi.org/10.1002/2014GL060345, 2014. a, b, c, d
Wieczorek, S., Ashwin, P., Luke, C. M., and Cox, P. M.: Excitability in ramped systems: The compost-bomb instability, P. R. Soc. A, 10, 1098, https://doi.org/10.1098/rspa.2010.0485, 2010. a
Wiesenfeld, K.: Noisy precursors of nonlinear instabilities, J. Stat. Phys., 38, 1071–1097, 1985. a
Williams, G. P.: Barotropic Instability and Equatorial Superrotation, J. Atmos. Sci., 60, 2136–2152, https://doi.org/10.1175/1520-0469(2003)060<2136:BIAES>2.0.CO;2, 2003. a, b
Williamson, M.: Dynamic evolution of eigenmodes of J, TIB AV-Portal [video], https://doi.org/10.5446/63009, 2024. a
Williamson, M. S. and Lenton, T. M.: Detection of bifurcations in noisy coupled systems from multiple time series, Chaos, 25, 036407, https://doi.org/10.1063/1.4908603, 2015. a, b, c
Zurita-Gotor, P. and Held, I. M.: The Finite-Amplitude Evolution of Mixed Kelvin–Rossby Wave Instability and Equatorial Superrotation in a Shallow-Water Model and an Idealized GCM, J. Atmos. Sci., 75, 2299–2316, https://doi.org/10.1175/JAS-D-17-0386.1, 2018. a, b, c, d
Short summary
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.
Climate models have transitioned to a superrotating atmospheric state under a broad range of...
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