Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1709-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1709-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
now at: MARUM-Center for Marine Environmental Sciences, University of Bremen, 28334 Bremen, Germany
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
Christoph Völker
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
Özgür Gürses
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
Judith Hauck
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
Peter Köhler
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27515 Bremerhaven, Germany
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Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Peter Köhler
Clim. Past, 21, 1043–1060, https://doi.org/10.5194/cp-21-1043-2025, https://doi.org/10.5194/cp-21-1043-2025, 2025
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Using a carbon cycle model, I show that the 405 kyr periodicity found in marine δ13C during the last 5 million years and the offset in atmospheric δ13CO2 between the Last Glacial Maximum and the Penultimate Glacial Maximum are probably related to each other. They can be explained by variations in the δ13C signature of weathered carbonate rock or of volcanically degassed CO2, which vary mainly with obliquity (41 kyr), suggesting that Northern Hemispheric land ice sheets are their ultimate drivers.
Peter U. Clark, Jeremy D. Shakun, Yair Rosenthal, Chenyu Zhu, Patrick J. Bartlein, Jonathan M. Gregory, Peter Köhler, Zhengyu Liu, and Daniel P. Schrag
Clim. Past, 21, 973–1000, https://doi.org/10.5194/cp-21-973-2025, https://doi.org/10.5194/cp-21-973-2025, 2025
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We reconstruct changes in mean ocean temperature (ΔMOT) over the last 4.5 Myr. We find that the ratio of ΔMOT to changes in global mean sea surface temperature was around 0.5 before the Middle Pleistocene transition but was 1 thereafter. We subtract our ΔMOT reconstruction from the global δ18O record to derive the δ18O of seawater. Finally, we develop a theoretical understanding of why the ratio of ΔMOT / ΔGMSST changed over the Plio-Pleistocene.
Li-Qing Jiang, Amanda Fay, Jens Daniel Müller, Lydia Keppler, Dustin Carroll, Siv K. Lauvset, Tim DeVries, Judith Hauck, Christian Rödenbeck, Luke Gregor, Nicolas Metzl, Andrea J. Fassbender, Jean-Pierre Gattuso, Peter Landschützer, Rik Wanninkhof, Christopher Sabine, Simone R. Alin, Mario Hoppema, Are Olsen, Matthew P. Humphreys, Kumiko Azetsu-Scott, Dorothee C. E. Bakker, Leticia Barbero, Nicholas R. Bates, Nicole Besemer, Henry C. Bittig, Albert E. Boyd, Daniel Broullón, Wei-Jun Cai, Brendan R. Carter, Thi-Tuyet-Trang Chau, Chen-Tung Arthur Chen, Frédéric Cyr, John E. Dore, Ian Enochs, Richard A. Feely, Hernan E. Garcia, Marion Gehlen, Lucas Gloege, Melchor González-Dávila, Nicolas Gruber, Yosuke Iida, Masao Ishii, Esther Kennedy, Alex Kozyr, Nico Lange, Claire Lo Monaco, Derek P. Manzello, Galen A. McKinley, Natalie M. Monacci, Xose A. Padin, Ana M. Palacio-Castro, Fiz F. Pérez, Alizée Roobaert, J. Magdalena Santana-Casiano, Jonathan Sharp, Adrienne Sutton, Jim Swift, Toste Tanhua, Maciej Telszewski, Jens Terhaar, Ruben van Hooidonk, Anton Velo, Andrew J. Watson, Angelicque E. White, Zelun Wu, Hyelim Yoo, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-255, https://doi.org/10.5194/essd-2025-255, 2025
Preprint under review for ESSD
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This review article provides an overview of 60 existing ocean carbonate chemistry data products, encompassing a broad range of types, including compilations of cruise datasets, gap-filled observational products, model simulations, and more. It is designed to help researchers identify and access the data products that best support their scientific objectives, thereby facilitating progress in understanding the ocean's changing carbonate chemistry.
Miriam Seifert, Christopher Danek, Christoph Völker, and Judith Hauck
EGUsphere, https://doi.org/10.5194/egusphere-2025-1495, https://doi.org/10.5194/egusphere-2025-1495, 2025
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Ocean alkalinity enhancement (OAE) can help to remove CO2 from the atmosphere. Yet, our study is the first that investigates the link between OAE and phytoplankton in an Earth System Model. We show that OAE can indirectly decrease primary production, and that biological feedbacks can modify the efficiency of OAE. Our study provides hints for ecological risks of OAE and the quantification of carbon drawdown, and can serve as a kick-start for other models to consider OAE-ecosystem interactions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
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Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Frauke Bunsen, Judith Hauck, Sinhué Torres-Valdés, and Lars Nerger
Ocean Sci., 21, 437–471, https://doi.org/10.5194/os-21-437-2025, https://doi.org/10.5194/os-21-437-2025, 2025
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Computer models are often used to estimate the ocean's CO2 uptake due to a lack of direct observations. Because such idealized models do not match precisely with the real world, we combine real-world observations of ocean temperature and salinity with a model and study the effect on the modeled air–sea CO2 flux (2010–2020). The corrections of temperature and salinity have their largest effect on regional CO2 fluxes in the Southern Ocean in winter and a small effect on the global CO2 uptake.
Peter Köhler and Stefan Mulitza
Clim. Past, 20, 991–1015, https://doi.org/10.5194/cp-20-991-2024, https://doi.org/10.5194/cp-20-991-2024, 2024
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We constructed 160 kyr long mono-specific stacks of δ13C and of δ18O from the wider tropics from the planktic foraminifera G. ruber and/or T. sacculifer and compared them with carbon cycle simulations using the BICYCLE-SE model. In our stacks and our model-based interpretation, we cannot detect a species-specific isotopic fractionation during hard-shell formation as a function of carbonate chemistry in the surrounding seawater, something which is called a carbonate ion effect.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Verena Haid, Ralph Timmermann, Özgür Gürses, and Hartmut H. Hellmer
Ocean Sci., 19, 1529–1544, https://doi.org/10.5194/os-19-1529-2023, https://doi.org/10.5194/os-19-1529-2023, 2023
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Recently, it was found that cold-to-warm changes in Antarctic shelf sea areas are possible and lead to higher ice shelf melt rates. In modelling experiments, we found that if the highest density in front of the ice shelf becomes lower than the density of the warmer water off-shelf at the deepest access to the shelf, the off-shelf water will flow onto the shelf. Our results also indicate that this change will offer some, although not much, resistance to reversal and constitutes a tipping point.
Luke Skinner, Francois Primeau, Aurich Jeltsch-Thömmes, Fortunat Joos, Peter Köhler, and Edouard Bard
Clim. Past, 19, 2177–2202, https://doi.org/10.5194/cp-19-2177-2023, https://doi.org/10.5194/cp-19-2177-2023, 2023
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Radiocarbon is best known as a dating tool, but it also allows us to track CO2 exchange between the ocean and atmosphere. Using decades of data and novel mapping methods, we have charted the ocean’s average radiocarbon ″age” since the last Ice Age. Combined with climate model simulations, these data quantify the ocean’s role in atmospheric CO2 rise since the last Ice Age while also revealing that Earth likely received far more cosmic radiation during the last Ice Age than hitherto believed.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
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For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Claudia Hinrichs, Peter Köhler, Christoph Völker, and Judith Hauck
Biogeosciences, 20, 3717–3735, https://doi.org/10.5194/bg-20-3717-2023, https://doi.org/10.5194/bg-20-3717-2023, 2023
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This study evaluated the alkalinity distribution in 14 climate models and found that most models underestimate alkalinity at the surface and overestimate it in the deeper ocean. It highlights the need for better understanding and quantification of processes driving alkalinity distribution and calcium carbonate dissolution and the importance of accounting for biases in model results when evaluating potential ocean alkalinity enhancement experiments.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Christian Rödenbeck, Tim DeVries, Judith Hauck, Corinne Le Quéré, and Ralph F. Keeling
Biogeosciences, 19, 2627–2652, https://doi.org/10.5194/bg-19-2627-2022, https://doi.org/10.5194/bg-19-2627-2022, 2022
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The ocean is an important part of the global carbon cycle, taking up about a quarter of the anthropogenic CO2 emitted by burning of fossil fuels and thus slowing down climate change. However, the CO2 uptake by the ocean is, in turn, affected by variability and trends in climate. Here we use carbon measurements in the surface ocean to quantify the response of the oceanic CO2 exchange to environmental conditions and discuss possible mechanisms underlying this response.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Stephan Krätschmer, Michèlle van der Does, Frank Lamy, Gerrit Lohmann, Christoph Völker, and Martin Werner
Clim. Past, 18, 67–87, https://doi.org/10.5194/cp-18-67-2022, https://doi.org/10.5194/cp-18-67-2022, 2022
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We use an atmospheric model coupled to an aerosol model to investigate the global mineral dust cycle with a focus on the Southern Hemisphere for warmer and colder climate states and compare our results to observational data. Our findings suggest that Australia is the predominant source of dust deposited over Antarctica during the last glacial maximum. In addition, we find that the southward transport of dust from all sources to Antarctica happens at lower altitudes in colder climates.
Tobias R. Vonnahme, Martial Leroy, Silke Thoms, Dick van Oevelen, H. Rodger Harvey, Svein Kristiansen, Rolf Gradinger, Ulrike Dietrich, and Christoph Völker
Biogeosciences, 18, 1719–1747, https://doi.org/10.5194/bg-18-1719-2021, https://doi.org/10.5194/bg-18-1719-2021, 2021
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Diatoms are crucial for Arctic coastal spring blooms, and their growth is controlled by nutrients and light. At the end of the bloom, inorganic nitrogen or silicon can be limiting, but nitrogen can be regenerated by bacteria, extending the algal growth phase. Modeling these multi-nutrient dynamics and the role of bacteria is challenging yet crucial for accurate modeling. We recreated spring bloom dynamics in a cultivation experiment and developed a representative dynamic model.
Christian B. Rodehacke, Madlene Pfeiffer, Tido Semmler, Özgür Gurses, and Thomas Kleiner
Earth Syst. Dynam., 11, 1153–1194, https://doi.org/10.5194/esd-11-1153-2020, https://doi.org/10.5194/esd-11-1153-2020, 2020
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In the warmer future, Antarctica's ice sheet will lose more ice due to enhanced iceberg calving and a warming ocean that melts more floating ice from below. However, the hydrological cycle is also stronger in a warmer world. Hence, more snowfall will precipitate on Antarctica and may balance the amplified ice loss. We have used future climate scenarios from various global climate models to perform numerous ice sheet simulations to show that precipitation may counteract mass loss.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Cited articles
Albani, S., Mahowald, N. M., Perry, A. T., Scanza, R. A., Zender, C. S. Heavens, N. G., Maggi, V., Kok, J. F., and Otto-Bliesner, B. L.: Improved dust representation in the Community Atmosphere Model, J. Adv. Model. Earth Sy., 6, 541–570, https://doi.org/10.1002/2013MS000279, 2014.
Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, R. A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 2: Salinity, Editor: Levitus, S., NOAA Atlas NESDIS 69, https://www.nodc.noaa.gov/OC5/WOA09/pubwoa09.html (last access: 20 February 2024), 2010.
Assonov, S., Groening, M., Fajgelj, A., Hélie, J.-F., and Hillaire-Marcel, C.: Preparation and characterisation of IAEA-603, a new primary reference material aimed at the VPDB scale realisation for δ13C and δ18O determination, Rapid Commun. Mass Sp., 34, e8867, https://doi.org/10.1002/rcm.8867, 2020.
Audi, G., Bersillon, O., Blachot, J., and Wapstra, A. H.: The Nubase evaluation of nuclear and decay properties, Nucl. Phys. A, 729, 3–128, https://doi.org/10.1016/j.nuclphysa.2003.11.001, 2003.
Aumont, O., Maier-Reimer, E., Blain, S., and Monfray, P.: An ecosystem model of the global ocean including Fe, Si, P colimitations, Global Biogeochem. Cycles, 17, 1060, https://doi.org/10.1029/2001GB001745, 2003.
Bé, M.-M. and Chechev, V. P.: 14C – Comments on evaluation of decay data, Laboratoire National Henri Becquerel, Gif-sur-Yvette, http://www.lnhb.fr/nuclides/C-14_com.pdf (last access: 20 February 2024), 2012.
Bidigare, R. R., Fluegge, A., Freeman, K. H., Hanson, K. L., Hayes, J. M., Hollander, D., Jasper, J. P., King, L. L., Laws, E. A., Milder, J., Millero, F. J., Pancost, R., Popp, B. N., Steinberg, P. A., and Wakeham, S. G.: Consistent fractionation of 13C in nature and in the laboratory: Growth-rate effects in some haptophyte algae, Global Biogeochem. Cycles, 11, 279–292, https://doi.org/10.1029/96GB03939, 1997.
Brandenburg, K. M., Rost, B., Van de Waal, D. B., Hoins, M., and Sluijs, A.: Physiological control on carbon isotope fractionation in marine phytoplankton, Biogeosciences, 19, 3305–3315, https://doi.org/10.5194/bg-19-3305-2022, 2022.
Broecker, W. S. and Maier-Reimer, E.: The influence of air and sea exchange on the carbon isotope distribution in the sea, Global Biogeochem. Cycles, 6, 315–320, https://doi.org/10.1029/92GB01672, 1992.
Broecker, W. S. and McGee, D.: The 13C record for atmospheric CO2: What is it trying to tell us?, Earth Planet. Sc. Lett., 368, 175–182, https://doi.org/10.1016/j.epsl.2013.02.029, 2013.
Broecker, W. S. and Peng, T.-H.: Tracers in the Sea, Eldigio Press, New York, 690 pp., 1982.
Buchanan, P. J., Matear, R. J., Chase, Z., Phipps, S. J., and Bindoff, N. L.: Ocean carbon and nitrogen isotopes in CSIRO Mk3L-COAL version 1.0: a tool for palaeoceanographic research, Geosci. Model Dev., 12, 1491–1523, https://doi.org/10.5194/gmd-12-1491-2019, 2019.
Buckley, M. W. and Marshall, J.: Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review, Rev. Geophys., 54, 2015RG000493, https://doi.org/10.1002/2015RG000493, 2016.
Butzin, M.: FESOM2.1-REcoM3 source code with carbon isotopes (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.8169243, 2023.
Ciais, P., Tagliabue, A., Cuntz, M., Bopp, L., Scholze, M., Hoffmann, G., Lourantou, A., Harrison, S. P., Prentice, I. C., Kelley, D. I., Koven, C. D., and Piao, S.: Large inert carbon pool in the terrestrial biosphere during the Last Glacial Maximum, Nat. Geosci., 5, 74–79, https://doi.org/10.1038/ngeo1324, 2012.
Claret, M., Sonnerup, R. E., and Quay, P. D.: A Next Generation Ocean Carbon Isotope Model for Climate Studies I: Steady State Controls on Ocean 13C, Global Biogeochem. Cycles, 35, e2020GB006757, https://doi.org/10.1029/2020GB006757, 2021.
Craig, H.: Carbon 13 in plants and the relationships between carbon 13 and carbon 14 variations in nature, J. Geol., 62, 115–149, 1954.
Danilov, S., Sidorenko, D., Wang, Q., and Jung, T.: The Finite-volumE Sea ice–Ocean Model (FESOM2), Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, 2017.
Dentith, J. E., Ivanovic, R. F., Gregoire, L. J., Tindall, J. C., and Robinson, L. F.: Simulating stable carbon isotopes in the ocean component of the FAMOUS general circulation model with MOSES1 (XOAVI), Geosci. Model Dev., 13, 3529–3552, https://doi.org/10.5194/gmd-13-3529-2020, 2020.
Eide, M., Olsen, A., Ninnemann, U. S., and Eldevik, T.: A global estimate of the full oceanic 13C Suess effect since the preindustrial, Global Biogeochem. Cycles, 31, 2016GB005472, https://doi.org/10.1002/2016GB005472, 2017a.
Eide, M., Olsen, A., Ninnemann, U. S., and Johannessen, T.: A global ocean climatology of preindustrial and modern ocean δ13C, Global Biogeochem. Cycles, 31, 2016GB005473, https://doi.org/10.1002/2016GB005473, 2017b.
Fahrni, S. M., Southon, J. R., Santos, G. M., Palstra, S. W. L., Meijer, H. A. J., and Xu, X.: Reassessment of the and isotopic fractionation ratio and its impact on high-precision radiocarbon dating, Geochim. Cosmochim. Ac., 213, 330–345, https://doi.org/10.1016/j.gca.2017.05.038, 2017.
Fiadeiro, M. E.: Three-dimensional modeling of tracers in the deep Pacific Ocean, II. Radiocarbon and the circulation, J. Marine Res., 40, 537–550, 1982.
Freeman, K. H. and Hayes, J. M.: Fractionation of carbon isotopes by phytoplankton and estimates of ancient CO2 levels, Global Biogeochem. Cycles, 6, 185–198, https://doi.org/10.1029/92GB00190, 1992.
Frischknecht, T., Ekici, A., and Joos, F.: Radiocarbon in the land and ocean components of the Community Earth System Model, Global Biogeochem. Cycles, 36, e2021GB007042, https://doi.org/10.1029/2021GB007042, 2022.
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O. K., Zweng, M. M., Reagan, J. R., and Johnson, D. R.: World Ocean Atlas 2013, Volume 4: Dissolved Inorganic Nutrients (Phosphate, Nitrate, Silicate), edited by: Levitus, S. and Mishonov, A., NOAA Atlas NESDIS 76, https://doi.org/10.7289/V5J67DWD (last access: 20 February 2024), 2014.
Garcia, H. E., Weathers, K., Paver, C. R., Smolyar, I., Boyer, T. P., Locarnini, R. A., Zweng, M. M., Mishonov, A. V., Baranova, O. K., Seidov, D., and Reagan, J. R.: World Ocean Atlas 2018, Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation, edited by: Mishonov, A., NOAA Atlas NESDIS 83, https://www.ncei.noaa.gov/access/world-ocean-atlas-2018/ (last access: 20 February 2024), 2019.
Graven, H., Lamb, E., Blake, D., and Khatiwala, S.: Future Changes in δ13C of Dissolved Inorganic Carbon in the Ocean, Earth's Future, 9, e2021EF002173, https://doi.org/10.1029/2021EF002173, 2021.
Griffies, S. M., Winton, M., Samuels, B., Danabasoglu, G., Yeager, S., Marsland, S., Drange., H., and Bentsen, M.: Datasets and protocol for the CLIVAR WGOMD Coordinated Ocean-sea ice Reference Experiments (COREs), WCRP Report No. 21/2012, https://eprints.soton.ac.uk/350257 (last access: 20 February 2024), 2012.
Gürses, Ö., Oziel, L., Karakuş, O., Sidorenko, D., Völker, C., Ye, Y., Zeising, M., Butzin, M., and Hauck, J.: Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3, Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, 2023.
Heaton, T. J., Bard, E., Bronk Ramsey, C., Butzin, M., Köhler, P., Muscheler, R., Reimer, P. J., and Wacker, L.: Radiocarbon: A key tracer for studying Earth's dynamo, climate system, carbon cycle, and Sun, Science, 374, eabd7096, https://doi.org/10.1126/science.abd7096, 2021.
Hesse, T., Butzin, M., Bickert, T., and Lohmann, G.: A model-data comparison of δ13C in the glacial Atlantic Ocean, Paleoceanography, 26, PA3220, https://doi.org/10.1029/2010PA002085, 2011.
Holden, P. B., Edwards, N. R., Müller, S. A., Oliver, K. I. C., Death, R. M., and Ridgwell, A.: Controls on the spatial distribution of oceanic δ13CDIC, Biogeosciences, 10, 1815–1833, https://doi.org/10.5194/bg-10-1815-2013, 2013.
Jahn, A., Lindsay, K., Giraud, X., Gruber, N., Otto-Bliesner, B. L., Liu, Z., and Brady, E. C.: Carbon isotopes in the ocean model of the Community Earth System Model (CESM1), Geosci. Model Dev., 8, 2419–2434, https://doi.org/10.5194/gmd-8-2419-2015, 2015.
Jeltsch-Thömmes, A., Battaglia, G., Cartapanis, O., Jaccard, S. L., and Joos, F.: Low terrestrial carbon storage at the Last Glacial Maximum: constraints from multi-proxy data, Clim. Past, 15, 849–879, https://doi.org/10.5194/cp-15-849-2019, 2019.
Keeling, C. D.: The Suess effect: 13Carbon-14Carbon interrelations, Environ. Int., 2, 229–300, https://doi.org/10.1016/0160-4120(79)90005-9, 1979.
Keller, K. and Morel, F. M. M.: A model of carbon isotopic fractionation and active carbon uptake in phytoplankton, Marine Ecol. Prog. Ser., 182, 295–298, https://doi.org/10.3354/meps182295, 1999.
Key, R. M., Kozyr, A., Sabine, C. L., Lee, K., Wanninkhof, R., Bullister, J. L., Feely, R. A., Millero, F. J., Mordy, C., and Peng, T.-H.: A global ocean carbon climatology: Results from Global Data Analysis Project (GLODAP), Global Biogeochem. Cycles, 18, GB4031, https://doi.org/10.1029/2004GB002247, 2004.
Key, R. M., Olsen, A., Van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterstrom, S., Steinfeldt, R., Jeansson, E., Ishi, M., Perez, F. F., and Suzuki, T.: Global Ocean Data Analysis Project, Version 2 (GLODAPv2), ORNL/CDIAC-162, ND-P093, https://doi.org/10.3334/CDIAC/OTG.NDP093_GLODAPv2, 2015.
Köhler, P., Fischer, H., Schmitt, J., and Munhoven, G.: On the application and interpretation of Keeling plots in paleo climate research – deciphering δ13C of atmospheric CO2 measured in ice cores, Biogeosciences, 3, 539–556, https://doi.org/10.5194/bg-3-539-2006, 2006.
Köhler, P.: Using the Suess effect on the stable carbon isotope to distinguish the future from the past in radiocarbon, Environ. Res. Lett., 11, 124016, https://doi.org/10.1088/1748-9326/11/12/124016, 2016.
Kutschera, W.: Applications of accelerator mass spectrometry, Int. J. Mass Sp., 349–350, 203–218, https://doi.org/10.1016/j.ijms.2013.05.023, 2013.
Kwon, E. Y., Timmermann, A., Tipple, B. J., and Schmittner, A.: Projected reversal of oceanic stable carbon isotope ratio depth gradient with continued anthropogenic carbon emissions, Commun. Earth Environ., 3, 1–12, https://doi.org/10.1038/s43247-022-00388-8, 2022.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air–sea flux data set, Clim. Dyn., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2009 (data available at: https://data1.gfdl.noaa.gov/nomads/forms/core/COREv2/CNYF_v2.html, last access: 29 June 2021).
Lauvset, S. K., Key, R. M., Olsen, A., van Heuven, S., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., Suzuki, T., and Watelet, S.: A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2, Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016, 2016.
Laws, E. A., Popp, B. N., Bidigare, R. R., Kennicutt, M. C., and Macko, S. A.: Dependence of phytoplankton carbon isotopic composition on growth rate and [CO2]aq: Theoretical considerations and experimental results, Geochim. Cosmochim. Ac., 59, 1131–1138, https://doi.org/10.1016/0016-7037(95)00030-4, 1995.
Laws, E. A., Bidigare, R. R., and Popp, B. N.: Effect of growth rate and CO2 concentration on carbon isotopic fractionation by the marine diatom Phaeodactylum tricornutum, Limnol. Oceanogr., 42, 1552–1560, https://doi.org/10.4319/lo.1997.42.7.1552, 1997.
Liu, B., Six, K. D., and Ilyina, T.: Incorporating the stable carbon isotope 13C in the ocean biogeochemical component of the Max Planck Institute Earth System Model, Biogeosciences, 18, 4389–4429, https://doi.org/10.5194/bg-18-4389-2021, 2021.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 1: Temperature, edited by: Levitus, S., NOAA Atlas NESDIS 68, https://www.nodc.noaa.gov/OC5/WOA09/pubwoa09.html (last access: 20 February 2024), 2010.
Lohmann, G., Butzin, M., Eissner, N., Shi, X., and Stepanek, C.: Abrupt Climate and Weather Changes Across Time Scales, Paleoceanogr. Paleocl., 35, e2019PA003782, https://doi.org/10.1029/2019PA003782, 2020.
Lorrain, A., Pethybridge, H., Cassar, N., Receveur, A., Allain, V., Bodin, N., Bopp, L., Choy, C. A., Duffy, L., Fry, B., Goni, N., Graham, B. S., Hobday, A. J., Logan, J. M., Ménard, F., Menkes, C. E., Olson, R. J., Pagendam, D. E., Point, D., Revill, A. T., Somes, C. J., and Young, J. W.: Trends in tuna carbon isotopes suggest global changes in pelagic phytoplankton communities, Global Change Biol., 26, 458–470, https://doi.org/10.1111/gcb.14858, 2020.
Lynch-Stieglitz, J., Adkins, J. F., Curry, W. B., Dokken, T., Hall, I. R., Herguera, J. C., Hirschi, J. J.-M., Ivanova, E. V., Kissel, C., Marchal, O., Marchitto, T. M., McCave, I. N., McManus, J. F., Mulitza, S., Ninnemann, U., Peeters, F., Yu, E.-F., and Zahn, R.: Atlantic Meridional Overturning Circulation During the Last Glacial Maximum, Science, 316, 66–69, https://doi.org/10.1126/science.1137127, 2007.
Matsumoto, K., Sarmiento, J. L., Key, R. M., Aumont, O., Bullister, J. L., Caldeira, K., Campin, J.-M., Doney, S. C., Drange, H., Dutay, J.-C., Follows, M., Gao, Y., Gnanadesikan, A., Gruber, N., Ishida, A., Joos, F., Lindsay, K., Maier-Reimer, E., Marshall, J. C., Matear, R. J., Monfray, P., Mouchet, A., Najjar, R., Plattner, G.-K., Schlitzer, R., Slater, R., Swathi, P. S., Totterdell, I. J., Weirig, M.-F., Yamanaka, Y., Yool, A., and Orr, J. C.: Evaluation of ocean carbon cycle models with data-based metrics, Geophys. Res. Lett., 31, L07303, https://doi.org/10.1029/2003GL018970, 2004.
Menking, J. A., Shackleton, S. A., Bauska, T. K., Buffen, A. M., Brook, E. J., Barker, S., Severinghaus, J. P., Dyonisius, M. N., and Petrenko, V. V.: Multiple carbon cycle mechanisms associated with the glaciation of Marine Isotope Stage 4, Nat. Commun., 13, 5443, https://doi.org/10.1038/s41467-022-33166-3, 2022.
Menviel, L., Mouchet, A., Meissner, K. J., Joos, F., and England, M. H.: Impact of oceanic circulation changes on atmospheric δ13CO2, Global Biogeochem. Cycles, 29, 1944–1961, https://doi.org/10.1002/2015GB005207, 2015.
Morée, A. L., Schwinger, J., Ninnemann, U. S., Jeltsch-Thömmes, A., Bethke, I., and Heinze, C.: Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using δ13C, Clim. Past, 17, 753–774, https://doi.org/10.5194/cp-17-753-2021, 2021.
Mouchet, A., The ocean bomb radiocarbon inventory revisited, Radiocarbon, 55, 1580–1594, https://doi.org/10.1017/S0033822200048505, 2013.
Munhoven, G.: Model of Early Diagenesis in the Upper Sediment with Adaptable complexity – MEDUSA (v. 2): a time-dependent biogeochemical sediment module for Earth system models, process analysis and teaching, Geosci. Model Dev., 14, 3603–3631, https://doi.org/10.5194/gmd-14-3603-2021, 2021.
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L., Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H., Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R. J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R., Tagliabue, A., Tanhua, T., and Yool, A.: Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, 2017.
Popp, B. N., Laws, E. A., Bidigare, R. R., Dore, J. E., Hanson, K. L., and Wakeham, S. G.: Effect of Phytoplankton Cell Geometry on Carbon Isotopic Fractionation, Geochim. Cosmochim. Ac., 62, 69–77, https://doi.org/10.1016/S0016-7037(97)00333-5, 1998.
Quay, P. D., Tilbrook, B., and Wong, C. S.: Oceanic Uptake of Fossil Fuel CO2: Carbon-13 Evidence, 256, 74–79, https://doi.org/10.1126/science.256.5053.74, 1992.
Rafter, P. A., Gray, W. R., Hines, S. K. V., Burke, A., Costa, K. M., Gottschalk, J., Hain, M. P., Rae, J. W. B., Southon, J. R., Walczak, M. H., Yu, J., Adkins, J. F., and DeVries, T.: Global reorganization of deep-sea circulation and carbon storage after the last ice age, Sci. Adv., 8, eabq5434, https://doi.org/10.1126/sciadv.abq5434, 2022.
Rau, G. H., Riebesell, U., and Wolf-Gladrow, D.: A model of photosynthetic 13C fractionation by marine phytoplankton based on diffusive molecular CO2 uptake, Marine Ecol. Prog. Ser., 133, 275–285, https://doi.org/10.3354/meps133275, 1996.
Rau, G. H., Riebesell, U., and Wolf-Gladrow, D.: CO2aq-dependent photosynthetic 13C fractionation in the ocean: A model versus measurements, Global Biogeochem. Cycles, 11, 267–278, https://doi.org/10.1029/97GB00328, 1997.
Šavrič, B., Patterson, T., and Jenny, B.: The Equal Earth map projection, Int. J. Geogr. Inf. Sci., 33, 454–465, https://doi.org/10.1080/13658816.2018.1504949, 2019.
Schmittner, A., Gruber, N., Mix, A. C., Key, R. M., Tagliabue, A., and Westberry, T. K.: Biology and air–sea gas exchange controls on the distribution of carbon isotope ratios (δ13C) in the ocean, Biogeosciences, 10, 5793–5816, https://doi.org/10.5194/bg-10-5793-2013, 2013.
Schmittner, A., Bostock, H. C., Cartapanis, O., Curry, W. B., Filipsson, H. L., Galbraith, E. D., Gottschalk, J., Herguera, J. C., Hoogakker, B., Jaccard, S. L., Lisiecki, L. E., Lund, D. C., Martínez-Méndez, G., Lynch-Stieglitz, J., Mackensen, A., Michel, E., Mix, A. C., Oppo, D. W., Peterson, C. D., Repschläger, J., Sikes, E. L., Spero, H. J., and Waelbroeck, C.: Calibration of the carbon isotope composition (δ13C) of benthic foraminifera, Paleoceanography, 32, 512–530, https://doi.org/10.1002/2016PA003072, 2017.
Scholz, P., Sidorenko, D., Gurses, O., Danilov, S., Koldunov, N., Wang, Q., Sein, D., Smolentseva, M., Rakowsky, N., and Jung, T.: Assessment of the Finite-volumE Sea ice-Ocean Model (FESOM2.0) – Part 1: Description of selected key model elements and comparison to its predecessor version, Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, 2019.
Scholz, P., Sidorenko, D., Danilov, S., Wang, Q., Koldunov, N., Sein, D., and Jung, T.: Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix, Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, 2022.
Skinner, L. C. and Bard, E.: Radiocarbon as a Dating Tool and Tracer in Paleoceanography, Rev. Geophys., 60, e2020RG000720, https://doi.org/10.1029/2020RG000720, 2022.
Skinner, L., Primeau, F., Jeltsch-Thömmes, A., Joos, F., Köhler, P., and Bard, E.: Rejuvenating the ocean: mean ocean radiocarbon, CO2 release, and radiocarbon budget closure across the last deglaciation, Clim. Past, 19, 2177–2202, https://doi.org/10.5194/cp-19-2177-2023, 2023.
Steele, M., Morley, R., and Ermold, W.: PHC: A Global Ocean Hydrography with a High-Quality Arctic Ocean, J. Climate, 14, 2079–2087, https://doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2, 2001.
Stuiver, M. and Polach, H. A.: Discussion; reporting of C-14 data, Radiocarbon, 19, 355–363, 1977.
Suess, H. E.: Radiocarbon Concentration in Modern Wood, Science, 122, 415–417, https://doi.org/10.1126/science.122.3166.415-a, 1955.
Tagliabue, A. and Bopp, L.: Towards understanding global variability in ocean carbon-13, Global Biogeochem. Cycles, 22, GB1025, https://doi.org/10.1029/2007GB003037, 2008.
Tagliabue, A., Mtshali, T., Aumont, O., Bowie, A. R., Klunder, M. B., Roychoudhury, A. N., and Swart, S.: A global compilation of dissolved iron measurements: focus on distributions and processes in the Southern Ocean, Biogeosciences, 9, 2333–2349, https://doi.org/10.5194/bg-9-2333-2012, 2012.
Tjiputra, J. F., Schwinger, J., Bentsen, M., Morée, A. L., Gao, S., Bethke, I., Heinze, C., Goris, N., Gupta, A., He, Y.-C., Olivié, D., Seland, Ø., and Schulz, M.: Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2), Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, 2020.
Toggweiler, J. R., Dixon, K., and Bryan, K.: Simulations of radiocarbon in a coarse-resolution world ocean model: 1. Steady state prebomb distributions, J. Geophys. Res., 94, 8217–8242, https://doi.org/10.1029/JC094iC06p08217, 1989.
Tschumi, T., Joos, F., Gehlen, M., and Heinze, C.: Deep ocean ventilation, carbon isotopes, marine sedimentation and the deglacial CO2 rise, Clim. Past, 7, 771–800, https://doi.org/10.5194/cp-7-771-2011, 2011.
Verwega, M.-T., Somes, C. J., Schartau, M., Tuerena, R. E., Lorrain, A., Oschlies, A., and Slawig, T.: Description of a global marine particulate organic carbon-13 isotope data set, Earth Syst. Sci. Data, 13, 4861–4880, https://doi.org/10.5194/essd-13-4861-2021, 2021.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean revisited: Gas exchange and wind speed over the ocean, Limnol. Oceanogr.-Methods, 12, 351–362, https://doi.org/10.4319/lom.2014.12.351, 2014.
Ye, Y., Munhoven, G., Köhler, P., Butzin, M., Hauck, J., Gürses, Ö., and Völker, C.: FESOM2.1-REcoM3-MEDUSA2: an ocean-sea ice-biogeochemistry model coupled to a sediment model, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-181, in review, 2023.
Young, J. N., Bruggeman, J., Rickaby, R. E. M., Erez, J., and Conte, M.: Evidence for changes in carbon isotopic fractionation by phytoplankton between 1960 and 2010, Global Biogeochem. Cycles, 27, 505–515, https://doi.org/10.1002/gbc.20045, 2013.
Zhang, J., Quay, P. D., and Wilbur, D. O.: Carbon isotope fractionation during gas-water exchange and dissolution of CO2, Geochim. Cosmochim. Ac., 59, 107–114, https://doi.org/10.1016/0016-7037(95)91550-D, 1995.
Ziveri, P., Stoll, H., Probert, I., Klaas, C., Geisen, M., Ganssen, G., and Young, J.: Stable isotope `vital effects' in coccolith calcite, Earth Planet. Sc. Lett., 210, 137–149, https://doi.org/10.1016/S0012-821X(03)00101-8, 2003.
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine...