Articles | Volume 18, issue 4
https://doi.org/10.5194/cp-18-759-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-18-759-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Apr 2022
Research article |
| 12 Apr 2022
| 12 Apr 2022
Climate and ocean circulation in the aftermath of a Marinoan snowball Earth
Lennart Ramme
CORRESPONDING AUTHOR
Max Planck Institute for Meteorology, Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Hamburg, Germany
Jochem Marotzke
Max Planck Institute for Meteorology, Hamburg, Germany
Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
Related authors
Christopher Wells, Benjamin Blanz, Lennart Ramme, Jannes Breier, Beniamino Callegari, Adakudlu Muralidhar, Jefferson K. Rajah, Andreas Nicolaidis Lindqvist, Axel E. Eriksson, William Alexander Schoenberg, Alexandre C. Köberle, Lan Wang-Erlandsson, Cecilie Mauritzen, and Chris Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-2756, https://doi.org/10.5194/egusphere-2025-2756, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Computer models built to study future developments of human activity and climate change often exclude the impacts of climate change. Here, we include these effects in a new model. We create functions connecting changes in global temperature, carbon dioxide, and sea level to energy supply and demand, food systems, mortality, economic damages, and other important quantities. Including these effects will allow us to explore their impact on future changes in the human and climate realms.
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-1875, https://doi.org/10.5194/egusphere-2025-1875, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present FRISIA version 1.0, a model to represent the impacts of future sea level rise (SLR) in integrated assessment models (IAMs). FRISIA can reproduce the impacts calculated by a more detailed spatially resolved model. Furthermore, the inclusion of previously uncaptured coastal feedback in FRISIA leads to emerging new behaviour. Our model improves the represenation of SLR impacts in IAMs, contributing to better projections of the world's socio-economic evolution under climate change.
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2599, https://doi.org/10.5194/egusphere-2025-2599, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA v2.1 integrates these systems and generate results that suggest standard scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
Short summary
Short summary
In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Christopher Wells, Benjamin Blanz, Lennart Ramme, Jannes Breier, Beniamino Callegari, Adakudlu Muralidhar, Jefferson K. Rajah, Andreas Nicolaidis Lindqvist, Axel E. Eriksson, William Alexander Schoenberg, Alexandre C. Köberle, Lan Wang-Erlandsson, Cecilie Mauritzen, and Chris Smith
EGUsphere, https://doi.org/10.5194/egusphere-2025-2756, https://doi.org/10.5194/egusphere-2025-2756, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Computer models built to study future developments of human activity and climate change often exclude the impacts of climate change. Here, we include these effects in a new model. We create functions connecting changes in global temperature, carbon dioxide, and sea level to energy supply and demand, food systems, mortality, economic damages, and other important quantities. Including these effects will allow us to explore their impact on future changes in the human and climate realms.
Lennart Ramme, Benjamin Blanz, Christopher Wells, Tony E. Wong, William Schoenberg, Chris Smith, and Chao Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-1875, https://doi.org/10.5194/egusphere-2025-1875, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present FRISIA version 1.0, a model to represent the impacts of future sea level rise (SLR) in integrated assessment models (IAMs). FRISIA can reproduce the impacts calculated by a more detailed spatially resolved model. Furthermore, the inclusion of previously uncaptured coastal feedback in FRISIA leads to emerging new behaviour. Our model improves the represenation of SLR impacts in IAMs, contributing to better projections of the world's socio-economic evolution under climate change.
William Schoenberg, Benjamin Blanz, Jefferson K. Rajah, Beniamino Callegari, Christopher Wells, Jannes Breier, Martin B. Grimeland, Andreas Nicolaidis Lindqvist, Lennart Ramme, Chris Smith, Chao Li, Sarah Mashhadi, Adakudlu Muralidhar, and Cecilie Mauritzen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2599, https://doi.org/10.5194/egusphere-2025-2599, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
The current crop of models assessed by the Intergovernmental Panel on Climate Change to produce their assessment reports lack endogenous process-based representations of climate-driven changes to human activities, limiting understanding of the feedback between climate and humans. FRIDA v2.1 integrates these systems and generate results that suggest standard scenarios may overestimate economic growth, highlighting the importance of feedbacks for realistic projections and informed policymaking.
Wolfgang A. Müller, Stephan Lorenz, Trang V. Pham, Andrea Schneidereit, Renate Brokopf, Victor Brovkin, Nils Brüggemann, Fatemeh Chegini, Dietmar Dommenget, Kristina Fröhlich, Barbara Früh, Veronika Gayler, Helmuth Haak, Stefan Hagemann, Moritz Hanke, Tatiana Ilyina, Johann Jungclaus, Martin Köhler, Peter Korn, Luis Kornblüh, Clarissa Kroll, Julian Krüger, Karel Castro-Morales, Ulrike Niemeier, Holger Pohlmann, Iuliia Polkova, Roland Potthast, Thomas Riddick, Manuel Schlund, Tobias Stacke, Roland Wirth, Dakuan Yu, and Jochem Marotzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2473, https://doi.org/10.5194/egusphere-2025-2473, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
ICON XPP is a newly developed Earth System model configuration based on the ICON modeling framework. It merges accomplishments from the recent operational numerical weather prediction model with well-established climate components for the ocean, land and ocean-biogeochemistry. ICON XPP reaches typical targets of a coupled climate simulation, and is able to run long integrations and large-ensemble experiments, making it suitable for climate predictions and projections, and for climate research.
Bjorn Stevens, Stefan Adami, Tariq Ali, Hartwig Anzt, Zafer Aslan, Sabine Attinger, Jaana Bäck, Johanna Baehr, Peter Bauer, Natacha Bernier, Bob Bishop, Hendryk Bockelmann, Sandrine Bony, Guy Brasseur, David N. Bresch, Sean Breyer, Gilbert Brunet, Pier Luigi Buttigieg, Junji Cao, Christelle Castet, Yafang Cheng, Ayantika Dey Choudhury, Deborah Coen, Susanne Crewell, Atish Dabholkar, Qing Dai, Francisco Doblas-Reyes, Dale Durran, Ayoub El Gaidi, Charlie Ewen, Eleftheria Exarchou, Veronika Eyring, Florencia Falkinhoff, David Farrell, Piers M. Forster, Ariane Frassoni, Claudia Frauen, Oliver Fuhrer, Shahzad Gani, Edwin Gerber, Debra Goldfarb, Jens Grieger, Nicolas Gruber, Wilco Hazeleger, Rolf Herken, Chris Hewitt, Torsten Hoefler, Huang-Hsiung Hsu, Daniela Jacob, Alexandra Jahn, Christian Jakob, Thomas Jung, Christopher Kadow, In-Sik Kang, Sarah Kang, Karthik Kashinath, Katharina Kleinen-von Königslöw, Daniel Klocke, Uta Kloenne, Milan Klöwer, Chihiro Kodama, Stefan Kollet, Tobias Kölling, Jenni Kontkanen, Steve Kopp, Michal Koran, Markku Kulmala, Hanna Lappalainen, Fakhria Latifi, Bryan Lawrence, June Yi Lee, Quentin Lejeun, Christian Lessig, Chao Li, Thomas Lippert, Jürg Luterbacher, Pekka Manninen, Jochem Marotzke, Satoshi Matsouoka, Charlotte Merchant, Peter Messmer, Gero Michel, Kristel Michielsen, Tomoki Miyakawa, Jens Müller, Ramsha Munir, Sandeep Narayanasetti, Ousmane Ndiaye, Carlos Nobre, Achim Oberg, Riko Oki, Tuba Özkan-Haller, Tim Palmer, Stan Posey, Andreas Prein, Odessa Primus, Mike Pritchard, Julie Pullen, Dian Putrasahan, Johannes Quaas, Krishnan Raghavan, Venkatachalam Ramaswamy, Markus Rapp, Florian Rauser, Markus Reichstein, Aromar Revi, Sonakshi Saluja, Masaki Satoh, Vera Schemann, Sebastian Schemm, Christina Schnadt Poberaj, Thomas Schulthess, Cath Senior, Jagadish Shukla, Manmeet Singh, Julia Slingo, Adam Sobel, Silvina Solman, Jenna Spitzer, Philip Stier, Thomas Stocker, Sarah Strock, Hang Su, Petteri Taalas, John Taylor, Susann Tegtmeier, Georg Teutsch, Adrian Tompkins, Uwe Ulbrich, Pier-Luigi Vidale, Chien-Ming Wu, Hao Xu, Najibullah Zaki, Laure Zanna, Tianjun Zhou, and Florian Ziemen
Earth Syst. Sci. Data, 16, 2113–2122, https://doi.org/10.5194/essd-16-2113-2024, https://doi.org/10.5194/essd-16-2113-2024, 2024
Short summary
Short summary
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
Short summary
Short summary
Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
Short summary
Short summary
In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Tim Rohrschneider, Johanna Baehr, Veit Lüschow, Dian Putrasahan, and Jochem Marotzke
Ocean Sci., 18, 979–996, https://doi.org/10.5194/os-18-979-2022, https://doi.org/10.5194/os-18-979-2022, 2022
Short summary
Short summary
This paper presents an analysis of wind sensitivity experiments in order to provide insight into the wind forcing dependence of the AMOC by understanding the behavior of its depth scale(s).
Flavio Lehner, Clara Deser, Nicola Maher, Jochem Marotzke, Erich M. Fischer, Lukas Brunner, Reto Knutti, and Ed Hawkins
Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, https://doi.org/10.5194/esd-11-491-2020, 2020
Short summary
Short summary
Projections of climate change are uncertain because climate models are imperfect, future greenhouse gases emissions are unknown and climate is to some extent chaotic. To partition and understand these sources of uncertainty and make the best use of climate projections, large ensembles with multiple climate models are needed. Such ensembles now exist in a public data archive. We provide several novel applications focused on global and regional temperature and precipitation projections.
Marlene Klockmann, Uwe Mikolajewicz, and Jochem Marotzke
Clim. Past, 12, 1829–1846, https://doi.org/10.5194/cp-12-1829-2016, https://doi.org/10.5194/cp-12-1829-2016, 2016
Short summary
Short summary
We study the response of the glacial AMOC to different forcings in a coupled AOGCM. The depth of the upper overturning cell remains almost unchanged in response to the full glacial forcing. This is the result of two opposing effects: a deepening due to the ice sheets and a shoaling due to the low GHG concentrations. Increased brine release in the Southern Ocean is key to the shoaling. With glacial ice sheets, a shallower cell can be simulated with GHG concentrations below the glacial level.
S. Tietsche, D. Notz, J. H. Jungclaus, and J. Marotzke
Ocean Sci., 9, 19–36, https://doi.org/10.5194/os-9-19-2013, https://doi.org/10.5194/os-9-19-2013, 2013
Related subject area
Subject: Climate Modelling | Archive: Modelling only | Timescale: Pre-Cenozoic
Exploring the mechanisms of Devonian oceanic anoxia: impact of ocean dynamics, palaeogeography, and orbital forcing
Diagnosing the controls on desert dust emissions through the Phanerozoic
Effects of ozone levels on climate through Earth history
Deep ocean temperatures through time
The Pliocene Model Intercomparison Project Phase 2: large-scale climate features and climate sensitivity
Paleogeographic controls on the evolution of Late Cretaceous ocean circulation
Stripping back the modern to reveal the Cenomanian–Turonian climate and temperature gradient underneath
Diminished greenhouse warming from Archean methane due to solar absorption lines
The faint young Sun problem revisited with a 3-D climate–carbon model – Part 1
The initiation of Neoproterozoic "snowball" climates in CCSM3: the influence of paleocontinental configuration
Albedo and heat transport in 3-D model simulations of the early Archean climate
Sea-ice dynamics strongly promote Snowball Earth initiation and destabilize tropical sea-ice margins
The Aptian evaporites of the South Atlantic: a climatic paradox?
The initiation of modern soft and hard Snowball Earth climates in CCSM4
Initiation of a Marinoan Snowball Earth in a state-of-the-art atmosphere-ocean general circulation model
Clouds and the Faint Young Sun Paradox
Model-dependence of the CO2 threshold for melting the hard Snowball Earth
Justin Gérard, Loïc Sablon, Jarno J. C. Huygh, Anne-Christine Da Silva, Alexandre Pohl, Christian Vérard, and Michel Crucifix
Clim. Past, 21, 239–260, https://doi.org/10.5194/cp-21-239-2025, https://doi.org/10.5194/cp-21-239-2025, 2025
Short summary
Short summary
We used cGENIE, a climate model, to explore how changes in continental configuration, CO2 levels, and orbital configuration affected ocean oxygen levels during the Devonian period (419–359 million years ago). Key factors contributing to ocean anoxia were identified, highlighting the influence of continental configurations, atmospheric conditions, and orbital changes. Our findings offer new insights into the causes and prolonged durations of Devonian ocean anoxic events.
Yixuan Xie, Daniel J. Lunt, and Paul J. Valdes
Clim. Past, 20, 2561–2585, https://doi.org/10.5194/cp-20-2561-2024, https://doi.org/10.5194/cp-20-2561-2024, 2024
Short summary
Short summary
Desert dust plays a crucial role in the climate system; while it is relatively well studied for the present day, we still lack knowledge on how it was in the past and on its underlying mechanism in the multi-million-year timescale of Earth’s history. For the first time, we simulate dust emissions using the newly developed DUSTY1.0 model over the past 540 million years with a temporal resolution of ~5 million years. We find that palaeogeography is the primary control of these variations.
Russell Deitrick and Colin Goldblatt
Clim. Past, 19, 1201–1218, https://doi.org/10.5194/cp-19-1201-2023, https://doi.org/10.5194/cp-19-1201-2023, 2023
Short summary
Short summary
Prior to 2.5 billion years ago, ozone was present in our atmosphere only in trace amounts. To understand how climate has changed in response to ozone build-up, we have run 3-D climate simulations with different amounts of ozone. We find that Earth's surface is about 3 to 4 °C degrees cooler with low ozone. This is caused by cooling of the upper atmosphere, where ozone is a warming agent. Its removal causes the upper atmosphere to become drier, weakening the greenhouse warming by water vapor.
Paul J. Valdes, Christopher R. Scotese, and Daniel J. Lunt
Clim. Past, 17, 1483–1506, https://doi.org/10.5194/cp-17-1483-2021, https://doi.org/10.5194/cp-17-1483-2021, 2021
Short summary
Short summary
Deep ocean temperatures are widely used as a proxy for global mean surface temperature in the past, but the underlying assumptions have not been tested. We use two unique sets of 109 climate model simulations for the last 545 million years to show that the relationship is valid for approximately the last 100 million years but breaks down for older time periods when the continents (and hence ocean circulation) are in very different positions.
Alan M. Haywood, Julia C. Tindall, Harry J. Dowsett, Aisling M. Dolan, Kevin M. Foley, Stephen J. Hunter, Daniel J. Hill, Wing-Le Chan, Ayako Abe-Ouchi, Christian Stepanek, Gerrit Lohmann, Deepak Chandan, W. Richard Peltier, Ning Tan, Camille Contoux, Gilles Ramstein, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Qiong Zhang, Qiang Li, Youichi Kamae, Mark A. Chandler, Linda E. Sohl, Bette L. Otto-Bliesner, Ran Feng, Esther C. Brady, Anna S. von der Heydt, Michiel L. J. Baatsen, and Daniel J. Lunt
Clim. Past, 16, 2095–2123, https://doi.org/10.5194/cp-16-2095-2020, https://doi.org/10.5194/cp-16-2095-2020, 2020
Short summary
Short summary
The large-scale features of middle Pliocene climate from the 16 models of PlioMIP Phase 2 are presented. The PlioMIP2 ensemble average was ~ 3.2 °C warmer and experienced ~ 7 % more precipitation than the pre-industrial era, although there are large regional variations. PlioMIP2 broadly agrees with a new proxy dataset of Pliocene sea surface temperatures. Combining PlioMIP2 and proxy data suggests that a doubling of atmospheric CO2 would increase globally averaged temperature by 2.6–4.8 °C.
Jean-Baptiste Ladant, Christopher J. Poulsen, Frédéric Fluteau, Clay R. Tabor, Kenneth G. MacLeod, Ellen E. Martin, Shannon J. Haynes, and Masoud A. Rostami
Clim. Past, 16, 973–1006, https://doi.org/10.5194/cp-16-973-2020, https://doi.org/10.5194/cp-16-973-2020, 2020
Short summary
Short summary
Understanding of the role of ocean circulation on climate is contingent on the ability to reconstruct its modes and evolution. Here, we show that earth system model simulations of the Late Cretaceous predict major changes in ocean circulation as a result of paleogeographic and gateway evolution. Comparisons of model results with available data compilations demonstrate reasonable agreement but highlight that various plausible theories of ocean circulation change coexist during this period.
Marie Laugié, Yannick Donnadieu, Jean-Baptiste Ladant, J. A. Mattias Green, Laurent Bopp, and François Raisson
Clim. Past, 16, 953–971, https://doi.org/10.5194/cp-16-953-2020, https://doi.org/10.5194/cp-16-953-2020, 2020
Short summary
Short summary
To quantify the impact of major climate forcings on the Cretaceous climate, we use Earth system modelling to progressively reconstruct the Cretaceous state by changing boundary conditions one by one. Between the preindustrial and the Cretaceous simulations, the model simulates a global warming of more than 11°C. The study confirms the primary control exerted by atmospheric CO2 on atmospheric temperatures. Palaeogeographic changes represent the second major contributor to the warming.
B. Byrne and C. Goldblatt
Clim. Past, 11, 559–570, https://doi.org/10.5194/cp-11-559-2015, https://doi.org/10.5194/cp-11-559-2015, 2015
Short summary
Short summary
High methane concentrations are thought to have helped sustain warm surface temperatures on the early Earth (~3 billion years ago) when the sun was only 80% as luminous as today. However, radiative transfer calculations with updated spectral data show that methane is a stronger absorber of solar radiation than previously thought. In this paper we show that the increased solar absorption causes a redcution in the warming ability of methane in the Archaean atmosphere.
G. Le Hir, Y. Teitler, F. Fluteau, Y. Donnadieu, and P. Philippot
Clim. Past, 10, 697–713, https://doi.org/10.5194/cp-10-697-2014, https://doi.org/10.5194/cp-10-697-2014, 2014
Y. Liu, W. R. Peltier, J. Yang, and G. Vettoretti
Clim. Past, 9, 2555–2577, https://doi.org/10.5194/cp-9-2555-2013, https://doi.org/10.5194/cp-9-2555-2013, 2013
H. Kienert, G. Feulner, and V. Petoukhov
Clim. Past, 9, 1841–1862, https://doi.org/10.5194/cp-9-1841-2013, https://doi.org/10.5194/cp-9-1841-2013, 2013
A. Voigt and D. S. Abbot
Clim. Past, 8, 2079–2092, https://doi.org/10.5194/cp-8-2079-2012, https://doi.org/10.5194/cp-8-2079-2012, 2012
A.-C. Chaboureau, Y. Donnadieu, P. Sepulchre, C. Robin, F. Guillocheau, and S. Rohais
Clim. Past, 8, 1047–1058, https://doi.org/10.5194/cp-8-1047-2012, https://doi.org/10.5194/cp-8-1047-2012, 2012
J. Yang, W. R. Peltier, and Y. Hu
Clim. Past, 8, 907–918, https://doi.org/10.5194/cp-8-907-2012, https://doi.org/10.5194/cp-8-907-2012, 2012
A. Voigt, D. S. Abbot, R. T. Pierrehumbert, and J. Marotzke
Clim. Past, 7, 249–263, https://doi.org/10.5194/cp-7-249-2011, https://doi.org/10.5194/cp-7-249-2011, 2011
C. Goldblatt and K. J. Zahnle
Clim. Past, 7, 203–220, https://doi.org/10.5194/cp-7-203-2011, https://doi.org/10.5194/cp-7-203-2011, 2011
Y. Hu, J. Yang, F. Ding, and W. R. Peltier
Clim. Past, 7, 17–25, https://doi.org/10.5194/cp-7-17-2011, https://doi.org/10.5194/cp-7-17-2011, 2011
Cited articles
Abbot, D. S. and Pierrehumbert, R. T.: Mudball: Surface dust and snowball Earth
deglaciation, J. Geophys. Res.-Atmos., 115, D03104, https://doi.org/10.1029/2009JD012007, 2010. a
Abbot, D. S., Eisenman, I., and Pierrehumbert, R. T.: The importance of ice
vertical resolution for Snowball climate and deglaciation, J. Climate, 23,
6100–6109, https://doi.org/10.1175/2010JCLI3693.1, 2010. a, b
Abbot, D. S., Voigt, A., Li, D., Hir, G. L., Pierrehumbert, R. T., Branson, M.,
Pollard, D., and B. Koll, D. D.: Robust elements of Snowball Earth
atmospheric circulation and oases for life, J. Geophys. Res.-Atmos., 118,
6017–6027, https://doi.org/10.1002/jgrd.50540, 2013. a, b, c
Allen, P. A. and Hoffman, P. F.: Extreme winds and waves in the aftermath of a Neoproterozoic glaciation, Nature, 433, 123–127, https://doi.org/10.1038/nature03176, 2005. a
Ashkenazy, Y., Gildor, H., Losch, M., Macdonald, F. A., Schrag, D. P., and
Tziperman, E.: Dynamics of a Snowball Earth ocean, Nature, 495, 90–93,
https://doi.org/10.1038/nature11894, 2013. a, b
Bao, H., Lyons, J., and Zhou, C.: Triple oxygen isotope evidence for elevated
CO2 levels after a Neoproterozoic glaciation, Nature, 453, 504–506,
https://doi.org/10.1038/nature06959, 2008. a, b
Benn, D. I., Le Hir, G., Bao, H., Donnadieu, Y., Dumas, C., Fleming, E. J.,
Hambrey, M. J., McMillan, E. A., Petronis, M. S., Ramstein, G., Stevenson, Carl, T. E., Wynn, P. M., and Fairchild, I. J.:
Orbitally forced ice sheet fluctuations during the Marinoan Snowball Earth
glaciation, Nat. Geosci., 8, 704–707, https://doi.org/10.1038/ngeo2502, 2015. a, b, c
Brocks, J. J., Jarrett, A. J., Sirantoine, E., Hallmann, C., Hoshino, Y., and
Liyanage, T.: The rise of algae in Cryogenian oceans and the emergence of
animals, Nature, 548, 578–581, https://doi.org/10.1038/nature23457, 2017. a
Bryan, K. and Cox, M. D.: The circulation of the world ocean: a numerical
study. Part I, a homogeneous model, J. Phys. Oceanogr., 2, 319–335,
https://doi.org/10.1175/1520-0485(1972)002<0319:TCOTWO>2.0.CO;2, 1972. a
Calver, C., Crowley, J., Wingate, M., Evans, D., Raub, T., and Schmitz, M.:
Globally synchronous Marinoan deglaciation indicated by U-Pb geochronology of
the Cottons Breccia, Tasmania, Australia, Geology, 41, 1127–1130,
https://doi.org/10.1130/G34568.1, 2013. a, b
Campin, J.-M., Marshall, J., and Ferreira, D.: Sea ice–ocean coupling using a
rescaled vertical coordinate z∗, Ocean Model., 24, 1–14,
https://doi.org/10.1016/j.ocemod.2008.05.005, 2008. a
Cariolle, D. and Teyssèdre, H.: A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations, Atmos. Chem. Phys., 7, 2183–2196, https://doi.org/10.5194/acp-7-2183-2007, 2007. a
Crueger, T., Giorgetta, M. A., Brokopf, R., Esch, M., Fiedler, S., Hohenegger,
C., Kornblueh, L., Mauritsen, T., Nam, C., Naumann, A. K., Peters, K., Rast, S., Roeckner, E., Sakradzija, M., Schmidt,
H., Vial, J., Vogel, R., and Stevens, B.: ICON-A,
The atmosphere component of the ICON Earth system model: II. Model
evaluation, J. Adv. Model. Earth. Sy., 10, 1638–1662,
https://doi.org/10.1029/2017MS001233, 2018. a
Dohrmann, M. and Wörheide, G.: Dating early animal evolution using
phylogenomic data, Sci. Rep., 7, 1–6, https://doi.org/10.1038/s41598-017-03791-w,
2017. a
Ferreira, D., Marshall, J., and Rose, B.: Climate determinism revisited:
Multiple equilibria in a complex climate model, J. Climate, 24, 992–1012,
https://doi.org/10.1175/2010JCLI3580.1, 2011. a
Fiorella, R. P. and Poulsen, C. J.: Dehumidification over tropical continents
reduces climate sensitivity and inhibits snowball Earth initiation, J.
Climate, 26, 9677–9695, https://doi.org/10.1175/JCLI-D-12-00820.1, 2013. a
Font, E., Nédélec, A., Trindade, R., and Moreau, C.: Fast or slow
melting of the Marinoan snowball Earth? The cap dolostone record,
Palaeogeogr. Palaeoclimatol. Palaeoecol., 295, 215–225,
https://doi.org/10.1016/j.palaeo.2010.05.039, 2010. a
Gent, P. R., Willebrand, J., McDougall, T. J., and McWilliams, J. C.:
Parameterizing eddy-induced tracer transports in ocean circulation models, J.
Phys. Oceanogr., 25, 463–474,
https://doi.org/10.1175/1520-0485(1995)025<0463:PEITTI>2.0.CO;2, 1995. a
Gernon, T., Hincks, T., Tyrrell, T., Rohling, E., and Palmer, M.: Snowball
Earth ocean chemistry driven by extensive ridge volcanism during Rodinia
breakup, Nat. Geosci., 9, 242–248, https://doi.org/10.1038/ngeo2632, 2016. a
Giorgetta, M. A., Brokopf, R., Crueger, T., Esch, M., Fiedler, S., Helmert, J.,
Hohenegger, C., Kornblueh, L., Köhler, M., Manzini, E., Mauritsen, T., Nam, C., Raddatz, T., Rast, S., Reinert, D.,
Sakradzija, M., Schmidt, H., Schneck, R. Schnur, R., Silvers, L., Wan, H., Zängl, G., and Stevens, B: ICON-A,
the atmosphere component of the ICON Earth System Model: I. Model
description, J. Adv. Model. Earth. Sy., 10, 1613–1637,
https://doi.org/10.1029/2017MS001242, 2018. a, b
Gough, D. O.: Solar interior structure and luminosity variations,
Sol. Phys., 74, 21–34, https://doi.org/10.1007/978-94-010-9633-1_4,
1981. a
Hanke, M., Redler, R., Holfeld, T., and Yastremsky, M.: YAC 1.2. 0: new aspects
for coupling software in Earth system modelling, Geosci. Model Dev., 9,
2755–2769, https://doi.org/10.5194/gmd-9-2755-2016, 2016. a
Hoffman, P. F.: Strange bedfellows: glacial diamictite and cap carbonate from
the Marinoan (635 Ma) glaciation in Namibia, Sedimentology, 58, 57–119,
https://doi.org/10.1111/j.1365-3091.2010.01206.x, 2011. a, b, c
Hoffman, P. F., Kaufman, A. J., Halverson, G. P., and Schrag, D. P.: A
Neoproterozoic snowball earth, Science, 281, 1342–1346,
https://doi.org/10.1126/science.281.5381.1342, 1998. a, b
Hyde, W. T., Crowley, T. J., Baum, S. K., and Peltier, W. R.: Neoproterozoic
‘snowball Earth’ simulations with a coupled climate/ice-sheet model,
Nature, 405, 425–429, https://doi.org/10.1038/35013005, 2000. a, b
Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V., Brüggemann, N.,
Chegini, F., De-Vrese, P., Gayler, V., Giorgetta, M. A., Gutjahr, O., Haak,
H., Hagemann, S., Hanke, M., Ilyina, T., Korn, P., Kröger, J.,
Linardakis, L., Mehlmann, C., Mikolajewicz, U., Müller, W. A., Nabel, J.
E. M. S., Notz, D., Pohlmann, H., Putrasahan, D., Raddatz, T., Ramme, L.,
Redler, R., Reick, C. H., Riddick, T., Sam, T., Schneck, R., Schnur, R.,
Schupfner, M., von Storch, J.-S., Wachsmann, F., Wieners, K.-H., Ziemen, F.,
Stevens, B., Marotzke, J., and Claussen, M.: The ICON Earth System Model
Version 1.0, J. Adv. Model. Earth. Sy., https://doi.org/10.1029/2021MS002813, in press, 2022. a, b
Kasemann, S. A., Hawkesworth, C. J., Prave, A. R., Fallick, A. E., and Pearson,
P. N.: Boron and calcium isotope composition in Neoproterozoic carbonate
rocks from Namibia: evidence for extreme environmental change, Earth Planet.
Sci. Lett., 231, 73–86, https://doi.org/10.1016/j.epsl.2004.12.006, 2005. a, b, c
Kendall, B., Creaser, R. A., and Selby, D.: Re-Os geochronology of postglacial
black shales in Australia: Constraints on the timing of “Sturtian”
glaciation, Geology, 34, 729–732, https://doi.org/10.1130/G22775.1, 2006. a
Kennedy, M. J.: Stratigraphy, sedimentology, and isotopic geochemistry of
Australian Neoproterozoic postglacial cap dolostones; deglaciation, delta13C excursions, and carbonate precipitation, J. Sediment Res., 66, 1050–1064,
https://doi.org/10.2110/jsr.66.1050, 1996. a
Korn, P.: Formulation of an unstructured grid model for global ocean dynamics,
J. Comput. Phys., 339, 525–552, https://doi.org/10.1016/j.jcp.2017.03.009, 2017. a, b
Le Hir, G., Donnadieu, Y., Goddéris, Y., Pierrehumbert, R. T., Halverson,
G. P., Macouin, M., Nédélec, A., and Ramstein, G.: The snowball Earth
aftermath: Exploring the limits of continental weathering processes, Earth
Planet. Sci. Lett., 277, 453–463, https://doi.org/10.1016/j.epsl.2008.11.010,
2008a. a, b, c
Le Hir, G., Goddéris, Y., Donnadieu, Y., and Ramstein, G.: A geochemical modelling study of the evolution of the chemical composition of seawater linked to a ”snowball” glaciation, Biogeosciences, 5, 253–267, https://doi.org/10.5194/bg-5-253-2008, 2008b. a
Le Hir, G., Ramstein, G., Donnadieu, Y., and Goddéris, Y.: Scenario for the
evolution of atmospheric pCO2 during a snowball Earth, Geology, 36, 47–50,
https://doi.org/10.1130/G24124A.1, 2008c. a, b, c
Lewis, J., Weaver, A., and Eby, M.: Deglaciating the snowball Earth:
Sensitivity to surface albedo, Geophys. Res. Lett., 33, L23604,
https://doi.org/10.1029/2006GL027774, 2006. a
Li, Z.-X., Evans, D. A., and Halverson, G. P.: Neoproterozoic glaciations in a
revised global palaeogeography from the breakup of Rodinia to the assembly of
Gondwanaland, Sediment. Geol., 294, 219–232,
https://doi.org/10.1016/j.sedgeo.2013.05.016, 2013. a, b, c
Liu, C., Wang, Z., Raub, T. D., Macdonald, F. A., and Evans, D. A.:
Neoproterozoic cap-dolostone deposition in stratified glacial meltwater
plume, Earth Planet. Sci. Lett., 404, 22–32,
https://doi.org/10.1016/j.epsl.2014.06.039, 2014. a, b
Marotzke, J. and Botzet, M.: Present-day and ice-covered equilibrium states in
a comprehensive climate model, Geophys. Res. Lett., 34, L16704,
https://doi.org/10.1029/2006GL028880, 2007. a
Mauritsen, T., Bader, J., Becker, T., et al.: Developments in the
MPI-M Earth System Model version 1.2 (MPI-ESM1. 2) and its response to
increasing CO2, J. Adv. Model. Earth. Sy., 11, 998–1038,
https://doi.org/10.1029/2018MS001400, 2019. a
McDougall, T. J.: Neutral surfaces, J. Phys. Oceanogr., 17, 1950–1964,
https://doi.org/10.1175/1520-0485(1987)017<1950:NS>2.0.CO;2, 1987. a
Merdith, A. S., Collins, A. S., Williams, S. E., Pisarevsky, S., Foden, J. D.,
Archibald, D. B., Blades, M. L., Alessio, B. L., Armistead, S., Plavsa, D.,
Clark, C., and Müller, R. D.: A full-plate global reconstruction of the Neoproterozoic, Gondwana
Res., 50, 84–134, https://doi.org/10.1016/j.gr.2017.04.001, 2017. a, b, c
Poulsen, C. and Jacob, R.: Factors that inhibit snowball Earth simulation,
Paleoceanography, 19, PA4021, https://doi.org/10.1029/2004PA001056, 2004. a
Prave, A. R., Condon, D. J., Hoffmann, K. H., Tapster, S., and Fallick, A. E.:
Duration and nature of the end-Cryogenian (Marinoan) glaciation, Geology, 44,
631–634, https://doi.org/10.1130/G38089.1, 2016. a
Ramme, L.: Publication data for “Ramme and Marotzke: Climate
and Ocean Circulation in the Aftermath of a Marinoan Snowball
Earth”, DOKU at DKRZ [code], https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=DKRZ_LTA_033_ds00013, last access: 5 April 2022. a
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys.
Oceanogr., 12, 1154–1158,
https://doi.org/10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2, 1982. a
Rothschild, L. J. and Mancinelli, R. L.: Life in extreme environments, Nature,
409, 1092–1101, https://doi.org/10.1038/35059215, 2001. a
Russell, J. L., Dixon, K. W., Gnanadesikan, A., Stouffer, R. J., and
Toggweiler, J.: The Southern Hemisphere westerlies in a warming world:
Propping open the door to the deep ocean, J. Climate, 19, 6382–6390,
https://doi.org/10.1175/JCLI3984.1, 2006. a
Semtner, A. J.: A model for the thermodynamic growth of sea ice in numerical
investigations of climate, J. Phys. Oceanogr., 6, 379–389,
https://doi.org/10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2, 1976. a
Shields, G. A.: Neoproterozoic cap carbonates: a critical appraisal of existing
models and the plumeworld hypothesis, Terra Nova, 17, 299–310,
https://doi.org/10.1111/j.1365-3121.2005.00638.x, 2005. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T.,
Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L.,
Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth system model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, Wiley Online Library, 2013. a
Thompson, D. W. and Solomon, S.: Interpretation of recent Southern Hemisphere
climate change, Science, 296, 895–899, https://doi.org/10.1126/science.1069270, 2002. a
Trindade, R., Font, E., D'Agrella-Filho, M., Nogueira, A., and Riccomini, C.:
Low-latitude and multiple geomagnetic reversals in the Neoproterozoic Puga
cap carbonate, Amazon craton, Terra Nova, 15, 441–446,
https://doi.org/10.1046/j.1365-3121.2003.00510.x, 2003.
a
Turner, E. C.: Possible poriferan body fossils in early Neoproterozoic
microbial reefs, Nature, 596, 1–5, https://doi.org/10.1038/s41586-021-03773-z, 2021. a
Tziperman, E., Abbot, D. S., Ashkenazy, Y., Gildor, H., Pollard, D., Schoof,
C. G., and Schrag, D. P.: Continental constriction and oceanic ice-cover
thickness in a Snowball-Earth scenario, J. Geophys. Res.-Oceans, 117, C05016,
https://doi.org/10.1029/2011JC007730, 2012. a
Voigt, A. and Marotzke, J.: The transition from the present-day climate to a
modern Snowball Earth, Clim. Dynam., 35, 887–905,
https://doi.org/10.1007/s00382-009-0633-5, 2010. a
Voigt, A., Abbot, D. S., Pierrehumbert, R. T., and Marotzke, J.: Initiation of a Marinoan Snowball Earth in a state-of-the-art atmosphere-ocean general circulation model, Clim. Past, 7, 249–263, https://doi.org/10.5194/cp-7-249-2011, 2011. a, b
Wolff, J.-O., Maier-Reimer, E., and Olbers, D. J.: Wind-driven flow over
topography in a zonal β-plane channel: A quasi-geostrophic model of the
Antarctic Circumpolar Current, J. Phys. Oceanogr., 21, 236–264,
https://doi.org/10.1175/1520-0485(1991)021<0236:WDFOTI>2.0.CO;2, 1991. a, b, c
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON
(ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M:
Description of the non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc.,
141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a
Short summary
After the Marinoan snowball Earth, the climate warmed rapidly due to enhanced greenhouse conditions, and the freshwater inflow of melting glaciers caused a strong stratification of the ocean. Our climate simulations reveal a potentially only moderate global temperature increase and a break-up of the stratification within just a few thousand years. The findings give insights into the environmental conditions relevant for the geological and biological evolution during that time.
After the Marinoan snowball Earth, the climate warmed rapidly due to enhanced greenhouse...
