Articles | Volume 13, issue 8
https://doi.org/10.5194/gmd-13-3529-2020
© Author(s) 2020. 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/gmd-13-3529-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Aug 2020
Development and technical paper |
| 07 Aug 2020
| 07 Aug 2020
Simulating stable carbon isotopes in the ocean component of the FAMOUS general circulation model with MOSES1 (XOAVI)
School of Earth and Environment, University of Leeds, Leeds, LS2
9JT, UK
Ruza F. Ivanovic
School of Earth and Environment, University of Leeds, Leeds, LS2
9JT, UK
Lauren J. Gregoire
School of Earth and Environment, University of Leeds, Leeds, LS2
9JT, UK
Julia C. Tindall
School of Earth and Environment, University of Leeds, Leeds, LS2
9JT, UK
Laura F. Robinson
School of Earth Sciences, University of Bristol, Bristol, BS8 1RJ, UK
Related authors
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, Laura F. Robinson, and Paul J. Valdes
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-365, https://doi.org/10.5194/bg-2019-365, 2019
Publication in BG not foreseen
Short summary
Short summary
We have added three new tracers (a dye tracer and two representations of radiocarbon, 14C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model performs well compared to modern 14C observations, both spatially and temporally. Proxy 14C records are interpreted in terms of water age, but comparing our dye tracer to our 14C tracer, we find that this is only valid in certain areas; elsewhere, the carbon cycle complicates the signal.
Takashi Obase, Laurie Menviel, Ayako Abe-Ouchi, Tristan Vadsaria, Ruza Ivanovic, Brooke Snoll, Sam Sherriff-Tadano, Paul J. Valdes, Lauren Gregoire, Marie-Luise Kapsch, Uwe Mikolajewicz, Nathaelle Bouttes, Didier Roche, Fanny Lhardy, Chengfei He, Bette Otto-Bliesner, Zhengyu Liu, and Wing-Le Chan
Clim. Past, 21, 1443–1463, https://doi.org/10.5194/cp-21-1443-2025, https://doi.org/10.5194/cp-21-1443-2025, 2025
Short summary
Short summary
This study analyses transient simulations of the last deglaciation performed by six climate models to understand the processes driving high-southern-latitude temperature changes. We find that atmospheric CO2 and AMOC (Atlantic Meridional Overturning Circulation) changes are the primary drivers of the warming and cooling during the middle stage of the deglaciation. The analysis highlights the model's sensitivity of CO2 and AMOC to meltwater and the meltwater history of temperature changes at high southern latitudes.
Elisa Ziegler, Nils Weitzel, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lauren Gregoire, Ruza Ivanovic, Paul J. Valdes, Christian Wirths, and Kira Rehfeld
Clim. Past, 21, 627–659, https://doi.org/10.5194/cp-21-627-2025, https://doi.org/10.5194/cp-21-627-2025, 2025
Short summary
Short summary
During the Last Deglaciation, global surface temperature rose by about 4–7 °C over several millennia. We show that changes in year-to-year up to century-to-century fluctuations of temperature and precipitation during the Deglaciation were mostly larger than during either the preceding or succeeding more stable periods in 15 climate model simulations. The analysis demonstrates how ice sheets, meltwater, and volcanism influence simulated variability to inform future simulation protocols.
Violet L. Patterson, Lauren J. Gregoire, Ruza F. Ivanovic, Niall Gandy, Stephen Cornford, Jonathan Owen, Sam Sherriff-Tadano, and Robin S. Smith
EGUsphere, https://doi.org/10.5194/egusphere-2024-3896, https://doi.org/10.5194/egusphere-2024-3896, 2025
Short summary
Short summary
Simulations of the last two glacial periods are ran using a computer model in which the atmosphere and ice sheets interact. The model is able to produce ice sheet volumes, extents and dynamics in good agreement with data. Sensitivity analysis is undertaken and shows the Northern Hemisphere ice sheet size is particularly sensitive to the albedo of the ice in the model but the different ice sheets display different sensitivities to other processes.
James F. O'Neill, Tamsin L. Edwards, Daniel F. Martin, Courtney Shafer, Stephen L. Cornford, Hélène L. Seroussi, Sophie Nowicki, Mira Adhikari, and Lauren J. Gregoire
The Cryosphere, 19, 541–563, https://doi.org/10.5194/tc-19-541-2025, https://doi.org/10.5194/tc-19-541-2025, 2025
Short summary
Short summary
We use an ice sheet model to simulate the Antarctic contribution to sea level over the 21st century under a range of future climates and varying how sensitive the ice sheet is to different processes. We find that ocean temperatures increase and more snow falls on the ice sheet under stronger warming scenarios. When the ice sheet is sensitive to ocean warming, ocean melt-driven loss exceeds snowfall-driven gains, meaning that the sea level contribution is greater with more climate warming.
Christopher L. Hancock, Michael P. Erb, Nicholas P. McKay, Sylvia G. Dee, and Ruza F. Ivanovic
Clim. Past, 20, 2663–2684, https://doi.org/10.5194/cp-20-2663-2024, https://doi.org/10.5194/cp-20-2663-2024, 2024
Short summary
Short summary
We reconstruct global hydroclimate anomalies for the past 21 000 years using a data assimilation methodology blending observations recorded in lake sediments with the climate dynamics simulated by climate models. The reconstruction resolves data–model disagreement in east Africa and North America, and we find that changing global temperatures and associated circulation patterns, as well as orbital forcing, are the dominant controls on global precipitation over this interval.
Violet L. Patterson, Lauren J. Gregoire, Ruza F. Ivanovic, Niall Gandy, Jonathan Owen, Robin S. Smith, Oliver G. Pollard, Lachlan C. Astfalck, and Paul J. Valdes
Clim. Past, 20, 2191–2218, https://doi.org/10.5194/cp-20-2191-2024, https://doi.org/10.5194/cp-20-2191-2024, 2024
Short summary
Short summary
Simulations of the last two glacial periods are run using a computer model in which the atmosphere and ice sheets interact. The results show that the initial conditions used in the simulations are the primary reason for the difference in simulated North American ice sheet volume between each period. Thus, the climate leading up to the glacial maxima and other factors, such as vegetation, are important contributors to the differences in the ice sheets at the Last and Penultimate glacial maxima.
Sam Sherriff-Tadano, Ruza Ivanovic, Lauren Gregoire, Charlotte Lang, Niall Gandy, Jonathan Gregory, Tamsin L. Edwards, Oliver Pollard, and Robin S. Smith
Clim. Past, 20, 1489–1512, https://doi.org/10.5194/cp-20-1489-2024, https://doi.org/10.5194/cp-20-1489-2024, 2024
Short summary
Short summary
Ensemble simulations of the climate and ice sheets of the Last Glacial Maximum (LGM) are performed with a new coupled climate–ice sheet model. Results show a strong sensitivity of the North American ice sheet to the albedo scheme, while the Greenland ice sheet appeared more sensitive to basal sliding schemes. Our result implies a potential connection between the North American ice sheet at the LGM and the future Greenland ice sheet through the albedo scheme.
Lauren E. Burton, Alan M. Haywood, Julia C. Tindall, Aisling M. Dolan, Daniel J. Hill, Erin L. McClymont, Sze Ling Ho, and Heather L. Ford
Clim. Past, 20, 1177–1194, https://doi.org/10.5194/cp-20-1177-2024, https://doi.org/10.5194/cp-20-1177-2024, 2024
Short summary
Short summary
The Pliocene (~ 3 million years ago) is of interest because its warm climate is similar to projections of the future. We explore the role of atmospheric carbon dioxide in forcing sea surface temperature during the Pliocene by combining climate model outputs with palaeoclimate proxy data. We investigate whether this role changes seasonally and also use our data to suggest a new estimate of Pliocene climate sensitivity. More data are needed to further explore the results presented.
Julia E. Weiffenbach, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Wing-Le Chan, Deepak Chandan, Ran Feng, Alan M. Haywood, Stephen J. Hunter, Xiangyu Li, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, Ning Tan, Julia C. Tindall, and Zhongshi Zhang
Clim. Past, 20, 1067–1086, https://doi.org/10.5194/cp-20-1067-2024, https://doi.org/10.5194/cp-20-1067-2024, 2024
Short summary
Short summary
Elevated atmospheric CO2 concentrations and a smaller Antarctic Ice Sheet during the mid-Pliocene (~ 3 million years ago) cause the Southern Ocean surface to become fresher and warmer, which affects the global ocean circulation. The CO2 concentration and the smaller Antarctic Ice Sheet both have a similar and approximately equal impact on the Southern Ocean. The conditions of the Southern Ocean in the mid-Pliocene could therefore be analogous to those in a future climate with smaller ice sheets.
Brooke Snoll, Ruza Ivanovic, Lauren Gregoire, Sam Sherriff-Tadano, Laurie Menviel, Takashi Obase, Ayako Abe-Ouchi, Nathaelle Bouttes, Chengfei He, Feng He, Marie Kapsch, Uwe Mikolajewicz, Juan Muglia, and Paul Valdes
Clim. Past, 20, 789–815, https://doi.org/10.5194/cp-20-789-2024, https://doi.org/10.5194/cp-20-789-2024, 2024
Short summary
Short summary
Geological records show rapid climate change throughout the recent deglaciation. The drivers of these changes are still misunderstood but are often attributed to shifts in the Atlantic Ocean circulation from meltwater input. A cumulative effort to understand these processes prompted numerous simulations of this period. We use these to explain the chain of events and our collective ability to simulate them. The results demonstrate the importance of the meltwater amount used in the simulation.
Oliver G. Pollard, Natasha L. M. Barlow, Lauren J. Gregoire, Natalya Gomez, Víctor Cartelle, Jeremy C. Ely, and Lachlan C. Astfalck
The Cryosphere, 17, 4751–4777, https://doi.org/10.5194/tc-17-4751-2023, https://doi.org/10.5194/tc-17-4751-2023, 2023
Short summary
Short summary
We use advanced statistical techniques and a simple ice-sheet model to produce an ensemble of plausible 3D shapes of the ice sheet that once stretched across northern Europe during the previous glacial maximum (140,000 years ago). This new reconstruction, equivalent in volume to 48 ± 8 m of global mean sea-level rise, will improve the interpretation of high sea levels recorded from the Last Interglacial period (120 000 years ago) that provide a useful perspective on the future.
Xin Ren, Daniel J. Lunt, Erica Hendy, Anna von der Heydt, Ayako Abe-Ouchi, Bette Otto-Bliesner, Charles J. R. Williams, Christian Stepanek, Chuncheng Guo, Deepak Chandan, Gerrit Lohmann, Julia C. Tindall, Linda E. Sohl, Mark A. Chandler, Masa Kageyama, Michiel L. J. Baatsen, Ning Tan, Qiong Zhang, Ran Feng, Stephen Hunter, Wing-Le Chan, W. Richard Peltier, Xiangyu Li, Youichi Kamae, Zhongshi Zhang, and Alan M. Haywood
Clim. Past, 19, 2053–2077, https://doi.org/10.5194/cp-19-2053-2023, https://doi.org/10.5194/cp-19-2053-2023, 2023
Short summary
Short summary
We investigate the Maritime Continent climate in the mid-Piacenzian warm period and find it is warmer and wetter and the sea surface salinity is lower compared with preindustrial period. Besides, the fresh and warm water transfer through the Maritime Continent was stronger. In order to avoid undue influence from closely related models in the multimodel results, we introduce a new metric, the multi-cluster mean, which could reveal spatial signals that are not captured by the multimodel mean.
Xiaofang Huang, Shiling Yang, Alan Haywood, Julia Tindall, Dabang Jiang, Yongda Wang, Minmin Sun, and Shihao Zhang
Clim. Past, 19, 731–745, https://doi.org/10.5194/cp-19-731-2023, https://doi.org/10.5194/cp-19-731-2023, 2023
Short summary
Short summary
The sensitivity of climate to the height changes of the East Antarctic ice sheet (EAIS) during the mid-Pliocene has been assessed using the HadCM3 model. The results show that the height reduction of the EAIS leads to a warmer and wetter East Antarctica. However, unintuitively, both the surface air temperature and the sea surface temperature decrease over the rest of the globe. These findings could provide insights into future changes caused by warming-induced decay of the Antarctic ice sheet.
Lauren E. Burton, Alan M. Haywood, Julia C. Tindall, Aisling M. Dolan, Daniel J. Hill, Ayako Abe-Ouchi, Wing-Le Chan, Deepak Chandan, Ran Feng, Stephen J. Hunter, Xiangyu Li, W. Richard Peltier, Ning Tan, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 19, 747–764, https://doi.org/10.5194/cp-19-747-2023, https://doi.org/10.5194/cp-19-747-2023, 2023
Short summary
Short summary
Warm climates of the Pliocene (~ 3 million years ago) are similar to projections of the near future. We find elevated concentrations of atmospheric carbon dioxide to be the most important forcing for driving changes in Pliocene surface air temperature, sea surface temperature, and precipitation. However, changes caused by the nature of Pliocene ice sheets and orography are also important, affecting the extent to which we can use the Pliocene as an analogue for our warmer future.
Suzanne Robinson, Ruza F. Ivanovic, Lauren J. Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul J. Valdes
Geosci. Model Dev., 16, 1231–1264, https://doi.org/10.5194/gmd-16-1231-2023, https://doi.org/10.5194/gmd-16-1231-2023, 2023
Short summary
Short summary
We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (Nd v1.0). Nd fluxes from seafloor sediment and incorporation of Nd onto sinking particles represent the major global sources and sinks, respectively. However, model–data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Julia E. Weiffenbach, Michiel L. J. Baatsen, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Zixuan Han, Alan M. Haywood, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Julia C. Tindall, Charles J. R. Williams, Qiong Zhang, and Zhongshi Zhang
Clim. Past, 19, 61–85, https://doi.org/10.5194/cp-19-61-2023, https://doi.org/10.5194/cp-19-61-2023, 2023
Short summary
Short summary
We study the behavior of the Atlantic Meridional Overturning Circulation (AMOC) in the mid-Pliocene. The mid-Pliocene was about 3 million years ago and had a similar CO2 concentration to today. We show that the stronger AMOC during this period relates to changes in geography and that this has a significant influence on ocean temperatures and heat transported northwards by the Atlantic Ocean. Understanding the behavior of the mid-Pliocene AMOC can help us to learn more about our future climate.
Michael P. Erb, Nicholas P. McKay, Nathan Steiger, Sylvia Dee, Chris Hancock, Ruza F. Ivanovic, Lauren J. Gregoire, and Paul Valdes
Clim. Past, 18, 2599–2629, https://doi.org/10.5194/cp-18-2599-2022, https://doi.org/10.5194/cp-18-2599-2022, 2022
Short summary
Short summary
To look at climate over the past 12 000 years, we reconstruct spatial temperature using natural climate archives and information from model simulations. Our results show mild global mean warmth around 6000 years ago, which differs somewhat from past reconstructions. Undiagnosed seasonal biases in the data could explain some of the observed temperature change, but this still would not explain the large difference between many reconstructions and climate models over this period.
Benjamin J. Stoker, Martin Margold, John C. Gosse, Alan J. Hidy, Alistair J. Monteath, Joseph M. Young, Niall Gandy, Lauren J. Gregoire, Sophie L. Norris, and Duane Froese
The Cryosphere, 16, 4865–4886, https://doi.org/10.5194/tc-16-4865-2022, https://doi.org/10.5194/tc-16-4865-2022, 2022
Short summary
Short summary
The Laurentide Ice Sheet was the largest ice sheet to grow and disappear in the Northern Hemisphere during the last glaciation. In northwestern Canada, it covered the Mackenzie Valley, blocking the migration of fauna and early humans between North America and Beringia and altering the drainage systems. We reconstruct the timing of ice sheet retreat in this region and the implications for the migration of early humans into North America, the drainage of glacial lakes, and past sea level rise.
Suzanne Robinson, Ruza Ivanovic, Lauren Gregoire, Lachlan Astfalck, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, and Kazuyo Tachikawa
EGUsphere, https://doi.org/10.5194/egusphere-2022-937, https://doi.org/10.5194/egusphere-2022-937, 2022
Preprint archived
Short summary
Short summary
The neodymium (Nd) isotope (εNd) scheme in the ocean model of FAMOUS is used to explore a benthic Nd flux to seawater. Our results demonstrate that sluggish modern Pacific waters are sensitive to benthic flux alterations, whereas the well-ventilated North Atlantic displays a much weaker response. In closing, there are distinct regional differences in how seawater acquires its εNd signal, in part relating to the complex interactions of Nd addition and water advection.
Zixuan Han, Qiong Zhang, Qiang Li, Ran Feng, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Bette L. Otto-Bliesner, Esther C. Brady, Nan Rosenbloom, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Charles J. R. Williams, Daniel J. Lunt, Jianbo Cheng, Qin Wen, and Natalie J. Burls
Clim. Past, 17, 2537–2558, https://doi.org/10.5194/cp-17-2537-2021, https://doi.org/10.5194/cp-17-2537-2021, 2021
Short summary
Short summary
Understanding the potential processes responsible for large-scale hydrological cycle changes in a warmer climate is of great importance. Our study implies that an imbalance in interhemispheric atmospheric energy during the mid-Pliocene could have led to changes in the dynamic effect, offsetting the thermodynamic effect and, hence, altering mid-Pliocene hydroclimate cycling. Moreover, a robust westward shift in the Pacific Walker circulation can moisten the northern Indian Ocean.
Arthur M. Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Henk A. Dijkstra, Julia C. Tindall, Ayako Abe-Ouchi, Alice R. Booth, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Alan M. Haywood, Stephen J. Hunter, Youichi Kamae, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gabriel M. Pontes, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Qiong Zhang, Zhongshi Zhang, Ilana Wainer, and Charles J. R. Williams
Clim. Past, 17, 2427–2450, https://doi.org/10.5194/cp-17-2427-2021, https://doi.org/10.5194/cp-17-2427-2021, 2021
Short summary
Short summary
In this work, we have studied the behaviour of El Niño events in the mid-Pliocene, a period of around 3 million years ago, using a collection of 17 climate models. It is an interesting period to study, as it saw similar atmospheric carbon dioxide levels to the present day. We find that the El Niño events were less strong in the mid-Pliocene simulations, when compared to pre-industrial climate. Our results could help to interpret El Niño behaviour in future climate projections.
Charles J. R. Williams, Alistair A. Sellar, Xin Ren, Alan M. Haywood, Peter Hopcroft, Stephen J. Hunter, William H. G. Roberts, Robin S. Smith, Emma J. Stone, Julia C. Tindall, and Daniel J. Lunt
Clim. Past, 17, 2139–2163, https://doi.org/10.5194/cp-17-2139-2021, https://doi.org/10.5194/cp-17-2139-2021, 2021
Short summary
Short summary
Computer simulations of the geological past are an important tool to improve our understanding of climate change. We present results from a simulation of the mid-Pliocene (approximately 3 million years ago) using the latest version of the UK’s climate model. The simulation reproduces temperatures as expected and shows some improvement relative to previous versions of the same model. The simulation is, however, arguably too warm when compared to other models and available observations.
Ellen Berntell, Qiong Zhang, Qiang Li, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, William Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, Charles J. R. Williams, Daniel J. Lunt, Ran Feng, Bette L. Otto-Bliesner, and Esther C. Brady
Clim. Past, 17, 1777–1794, https://doi.org/10.5194/cp-17-1777-2021, https://doi.org/10.5194/cp-17-1777-2021, 2021
Short summary
Short summary
The mid-Pliocene Warm Period (~ 3.2 Ma) is often considered an analogue for near-future climate projections, and model results from the PlioMIP2 ensemble show an increase of rainfall over West Africa and the Sahara region compared to pre-industrial conditions. Though previous studies of future projections show a west–east drying–wetting contrast over the Sahel, these results indicate a uniform rainfall increase over the Sahel in warm climates characterized by increased greenhouse gas forcing.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
Short summary
Short summary
The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Odd Helge Otterå, Kerim H. Nisancioglu, Ning Tan, Camille Contoux, Gilles Ramstein, Ran Feng, Bette L. Otto-Bliesner, Esther Brady, Deepak Chandan, W. Richard Peltier, Michiel L. J. Baatsen, Anna S. von der Heydt, Julia E. Weiffenbach, Christian Stepanek, Gerrit Lohmann, Qiong Zhang, Qiang Li, Mark A. Chandler, Linda E. Sohl, Alan M. Haywood, Stephen J. Hunter, Julia C. Tindall, Charles Williams, Daniel J. Lunt, Wing-Le Chan, and Ayako Abe-Ouchi
Clim. Past, 17, 529–543, https://doi.org/10.5194/cp-17-529-2021, https://doi.org/10.5194/cp-17-529-2021, 2021
Short summary
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is an important topic in the Pliocene Model Intercomparison Project. Previous studies have suggested a much stronger AMOC during the Pliocene than today. However, our current multi-model intercomparison shows large model spreads and model–data discrepancies, which can not support the previous hypothesis. Our study shows good consistency with future projections of the AMOC.
Irene Malmierca-Vallet, Louise C. Sime, Paul J. Valdes, and Julia C. Tindall
Clim. Past, 16, 2485–2508, https://doi.org/10.5194/cp-16-2485-2020, https://doi.org/10.5194/cp-16-2485-2020, 2020
Wesley de Nooijer, Qiong Zhang, Qiang Li, Qiang Zhang, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Harry J. Dowsett, Christian Stepanek, Gerrit Lohmann, Bette L. Otto-Bliesner, Ran Feng, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, and Chris M. Brierley
Clim. Past, 16, 2325–2341, https://doi.org/10.5194/cp-16-2325-2020, https://doi.org/10.5194/cp-16-2325-2020, 2020
Short summary
Short summary
The simulations for the past climate can inform us about the performance of climate models in different climate scenarios. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), when the CO2 level was comparable to today. The results highlight the importance of slow feedbacks in the model simulations and imply that we must be careful when using simulations of the mPWP as an analogue for future climate change.
Andy R. Emery, David M. Hodgson, Natasha L. M. Barlow, Jonathan L. Carrivick, Carol J. Cotterill, Janet C. Richardson, Ruza F. Ivanovic, and Claire L. Mellett
Earth Surf. Dynam., 8, 869–891, https://doi.org/10.5194/esurf-8-869-2020, https://doi.org/10.5194/esurf-8-869-2020, 2020
Short summary
Short summary
During the last ice age, sea level was lower, and the North Sea was land. The margin of a large ice sheet was at Dogger Bank in the North Sea. This ice sheet formed large rivers. After the ice sheet retreated down from the high point of Dogger Bank, the rivers had no water supply and dried out. Increased precipitation during the 15 000 years of land exposure at Dogger Bank formed a new drainage network. This study shows how glaciation and climate changes can control how drainage networks evolve.
Ilkka S. O. Matero, Lauren J. Gregoire, and Ruza F. Ivanovic
Geosci. Model Dev., 13, 4555–4577, https://doi.org/10.5194/gmd-13-4555-2020, https://doi.org/10.5194/gmd-13-4555-2020, 2020
Short summary
Short summary
The Northern Hemisphere cooled by several degrees for a century 8000 years ago due to the collapse of an ice sheet in North America that released large amounts of meltwater into the North Atlantic and slowed down its circulation. We numerically model the ice sheet to understand its evolution during this event. Our results match data thanks to good ice dynamics but depend mostly on surface melt and snowfall. Further work will help us understand how past and future ice melt affects climate.
Erin L. McClymont, Heather L. Ford, Sze Ling Ho, Julia C. Tindall, Alan M. Haywood, Montserrat Alonso-Garcia, Ian Bailey, Melissa A. Berke, Kate Littler, Molly O. Patterson, Benjamin Petrick, Francien Peterse, A. Christina Ravelo, Bjørg Risebrobakken, Stijn De Schepper, George E. A. Swann, Kaustubh Thirumalai, Jessica E. Tierney, Carolien van der Weijst, Sarah White, Ayako Abe-Ouchi, Michiel L. J. Baatsen, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Ran Feng, Chuncheng Guo, Anna S. von der Heydt, Stephen Hunter, Xiangyi Li, Gerrit Lohmann, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 16, 1599–1615, https://doi.org/10.5194/cp-16-1599-2020, https://doi.org/10.5194/cp-16-1599-2020, 2020
Short summary
Short summary
We examine the sea-surface temperature response to an interval of climate ~ 3.2 million years ago, when CO2 concentrations were similar to today and the near future. Our geological data and climate models show that global mean sea-surface temperatures were 2.3 to 3.2 ºC warmer than pre-industrial climate, that the mid-latitudes and high latitudes warmed more than the tropics, and that the warming was particularly enhanced in the North Atlantic Ocean.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, Laura F. Robinson, and Paul J. Valdes
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-365, https://doi.org/10.5194/bg-2019-365, 2019
Publication in BG not foreseen
Short summary
Short summary
We have added three new tracers (a dye tracer and two representations of radiocarbon, 14C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model performs well compared to modern 14C observations, both spatially and temporally. Proxy 14C records are interpreted in terms of water age, but comparing our dye tracer to our 14C tracer, we find that this is only valid in certain areas; elsewhere, the carbon cycle complicates the signal.
Stephen J. Hunter, Alan M. Haywood, Aisling M. Dolan, and Julia C. Tindall
Clim. Past, 15, 1691–1713, https://doi.org/10.5194/cp-15-1691-2019, https://doi.org/10.5194/cp-15-1691-2019, 2019
Short summary
Short summary
In this paper, we model climate of the mid-Piacenzian warm period (mPWP; ~3 million years ago), a geological analogue for contemporary climate. Using the HadCM3 climate model, we show how changes in CO2 and geography contributed to mPWP climate. We find mPWP warmth focussed in the high latitudes, geography-driven precipitation changes, complex changes in sea surface temperature and intensified overturning in the North Atlantic (AMOC).
Laurie Menviel, Emilie Capron, Aline Govin, Andrea Dutton, Lev Tarasov, Ayako Abe-Ouchi, Russell N. Drysdale, Philip L. Gibbard, Lauren Gregoire, Feng He, Ruza F. Ivanovic, Masa Kageyama, Kenji Kawamura, Amaelle Landais, Bette L. Otto-Bliesner, Ikumi Oyabu, Polychronis C. Tzedakis, Eric Wolff, and Xu Zhang
Geosci. Model Dev., 12, 3649–3685, https://doi.org/10.5194/gmd-12-3649-2019, https://doi.org/10.5194/gmd-12-3649-2019, 2019
Short summary
Short summary
As part of the Past Global Changes (PAGES) working group on Quaternary Interglacials, we propose a protocol to perform transient simulations of the penultimate deglaciation for the Paleoclimate Modelling Intercomparison Project (PMIP4). This design includes time-varying changes in orbital forcing, greenhouse gas concentrations, continental ice sheets as well as freshwater input from the disintegration of continental ice sheets. Key paleo-records for model-data comparison are also included.
Niall Gandy, Lauren J. Gregoire, Jeremy C. Ely, Christopher D. Clark, David M. Hodgson, Victoria Lee, Tom Bradwell, and Ruza F. Ivanovic
The Cryosphere, 12, 3635–3651, https://doi.org/10.5194/tc-12-3635-2018, https://doi.org/10.5194/tc-12-3635-2018, 2018
Short summary
Short summary
We use the deglaciation of the last British–Irish Ice Sheet as a valuable case to examine the processes of contemporary ice sheet change, using an ice sheet model to simulate the Minch Ice Stream. We find that ice shelves were a control on retreat and that the Minch Ice Stream was vulnerable to the same marine mechanisms which threaten the future of the West Antarctic Ice Sheet. This demonstrates the importance of marine processes when projecting the future of our contemporary ice sheets.
Laurie Menviel, Emilie Capron, Aline Govin, Andrea Dutton, Lev Tarasov, Ayako Abe-Ouchi, Russell Drysdale, Philip Gibbard, Lauren Gregoire, Feng He, Ruza Ivanovic, Masa Kageyama, Kenji Kawamura, Amaelle Landais, Bette L. Otto-Bliesner, Ikumi Oyabu, Polychronis Tzedakis, Eric Wolff, and Xu Zhang
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-106, https://doi.org/10.5194/cp-2018-106, 2018
Preprint withdrawn
Short summary
Short summary
The penultimate deglaciation (~ 138–128 ka), which represents the transition into the Last Interglacial period, provides a framework to investigate the climate and environmental response to large changes in boundary conditions. Here, as part of the PAGES-PMIP working group on Quaternary Interglacials, we propose a protocol to perform transient simulations of the penultimate deglaciation as well as a selection of paleo records for upcoming model-data comparisons.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, https://doi.org/10.5194/gmd-11-1033-2018, 2018
Short summary
Short summary
The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, https://doi.org/10.5194/gmd-10-4035-2017, 2017
Short summary
Short summary
The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes, Andrea Burke, Rosemarie Drummond, W. Richard Peltier, and Lev Tarasov
Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, https://doi.org/10.5194/gmd-9-2563-2016, 2016
Short summary
Short summary
This manuscript presents the experiment design for the PMIP4 Last Deglaciation Core experiment: a transient simulation of the last deglaciation, 21–9 ka. Specified model boundary conditions include time-varying orbital parameters, greenhouse gases, ice sheets, ice meltwater fluxes and other geographical changes (provided for 26–0 ka). The context of the experiment and the choices for the boundary conditions are explained, along with the future direction of the working group.
R. F. Ivanovic, P. J. Valdes, R. Flecker, and M. Gutjahr
Clim. Past, 10, 607–622, https://doi.org/10.5194/cp-10-607-2014, https://doi.org/10.5194/cp-10-607-2014, 2014
M. J. Pound, J. Tindall, S. J. Pickering, A. M. Haywood, H. J. Dowsett, and U. Salzmann
Clim. Past, 10, 167–180, https://doi.org/10.5194/cp-10-167-2014, https://doi.org/10.5194/cp-10-167-2014, 2014
P. J. Irvine, L. J. Gregoire, D. J. Lunt, and P. J. Valdes
Geosci. Model Dev., 6, 1447–1462, https://doi.org/10.5194/gmd-6-1447-2013, https://doi.org/10.5194/gmd-6-1447-2013, 2013
T. Russon, A. W. Tudhope, G. C. Hegerl, M. Collins, and J. Tindall
Clim. Past, 9, 1543–1557, https://doi.org/10.5194/cp-9-1543-2013, https://doi.org/10.5194/cp-9-1543-2013, 2013
Related subject area
Biogeosciences
Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849
Simulating the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5)
pyVPRM: a next-generation vegetation photosynthesis and respiration model for the post-MODIS era
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Development and assessment of the physical–biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Implementing a process-based representation of soil water movement in a second-generation dynamic vegetation model: application to dryland ecosystems (LPJ-GUESS-RE v1.0)
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
CROMES v1.0: A flexible CROp Model Emulator Suite for climate impact assessment
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Simple Eulerian-Lagrangian approach to solve equations for sinking particulate organic matter in the ocean
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Representing high-latitude deep carbon in the pre-industrial state of the ORCHIDEE-MICT land surface model (r8704)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
A trait-based model to describe plant community dynamics in managed grasslands (GrasslandTraitSim.jl v1.0.0)
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Data-Informed Inversion Model (DIIM): a framework to retrieve marine optical constituents in the BOUSSOLE site using a three-stream irradiance model
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Sunburned plankton: Ultraviolet radiation inhibition of phytoplankton photosynthesis in the Community Earth System Model version 2
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
Geosci. Model Dev., 18, 4915–4933, https://doi.org/10.5194/gmd-18-4915-2025, https://doi.org/10.5194/gmd-18-4915-2025, 2025
Short summary
Short summary
This study enhances the accuracy of modeling the carbon dynamics of the Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to use in refining global carbon cycle models.
Benjamin F. Meyer, João P. Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
Geosci. Model Dev., 18, 4643–4666, https://doi.org/10.5194/gmd-18-4643-2025, https://doi.org/10.5194/gmd-18-4643-2025, 2025
Short summary
Short summary
Climate change has increased the likelihood of drought events across Europe, potentially threatening the European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show its ability to capture species-specific evapotranspiration responses to drought and to reproduce flux observations of both gross primary production and evapotranspiration.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Carolina Natel, David Martín Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
Geosci. Model Dev., 18, 4317–4333, https://doi.org/10.5194/gmd-18-4317-2025, https://doi.org/10.5194/gmd-18-4317-2025, 2025
Short summary
Short summary
We developed fast machine learning models to predict forest regrowth and carbon dynamics under climate change. These models mimic the outputs of a complex vegetation model but run 95 % faster, enabling global analyses and supporting climate solutions in large modeling frameworks such as LandSyMM.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025, https://doi.org/10.5194/gmd-18-4103-2025, 2025
Short summary
Short summary
This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
Geosci. Model Dev., 18, 3941–3964, https://doi.org/10.5194/gmd-18-3941-2025, https://doi.org/10.5194/gmd-18-3941-2025, 2025
Short summary
Short summary
Physical–biogeochemical ocean global models are required to analyze difficult oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The developed model is an important tool for studying physical–biogeochemical processes.
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025, https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Short summary
This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025, https://doi.org/10.5194/gmd-18-3241-2025, 2025
Short summary
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
Short summary
Short summary
Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
Short summary
Short summary
Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
Short summary
Short summary
We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
Short summary
Short summary
The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Wim Verbruggen, David Wårlind, Stéphanie Horion, Félicien Meunier, Hans Verbeeck, and Guy Schurgers
EGUsphere, https://doi.org/10.5194/egusphere-2025-1259, https://doi.org/10.5194/egusphere-2025-1259, 2025
Short summary
Short summary
We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
Short summary
Short summary
Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Christian Folberth, Artem Baklanov, Nikolay Khabarov, Thomas Oberleitner, Juraj Balkovič, and Rastislav Skalský
EGUsphere, https://doi.org/10.5194/egusphere-2025-862, https://doi.org/10.5194/egusphere-2025-862, 2025
Short summary
Short summary
Global gridded crop models (GGCMs) are important tools in agricultural climate impact assessments but computationally costly. An emergent approach to derive crop productivity estimates similar to those from GGCMs are emulators that mimic the original model, but typically with considerable bias. Here we present a modelling package that trains emulators with very high accuracy and high computational gain, providing a basis for more comprehensive scenario assessments.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
Short summary
Short summary
We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
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
Short summary
Short summary
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.
Vladimir Maderich, Igor Brovchenko, Kateryna Kovalets, Seongbong Seo, and Kyeong Ok Kim
EGUsphere, https://doi.org/10.5194/egusphere-2025-491, https://doi.org/10.5194/egusphere-2025-491, 2025
Short summary
Short summary
We have developed a new simple Eulerian-Lagrangian approach to solve equations for sinking particulate organic matter in the ocean. We rely on the known parameterizations, but our approach to solving the problem differs, allowing the algorithm to be incorporated into biogeochemical global ocean models with relative ease. New analytical and numerical solutions confirmed that feedback between degradation rate and sinking velocity significantly changes particulate matter fluxes.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
Short summary
Short summary
Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Yi Xi, Philippe Ciais, Dan Zhu, Chunjing Qiu, Yuan Zhang, Shushi Peng, Gustaf Hugelius, Simon P. K. Bowring, Daniel S. Goll, and Ying-Ping Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-206, https://doi.org/10.5194/gmd-2024-206, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
Including high-latitude deep carbon is critical for projecting future soil carbon emissions, yet it’s absent in most land surface models. Here we propose a new carbon accumulation protocol by integrating deep carbon from Yedoma deposits and representing the observed history of peat carbon formation in ORCHIDEE-MICT. Our results show an additional 157 PgC in present-day Yedoma deposits and a 1–5 m shallower peat depth, 43 % less passive soil carbon in peatlands against the convention protocol.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
Short summary
Short summary
The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Felix Nößler, Thibault Moulin, Oksana Buzhdygan, Britta Tietjen, and Felix May
EGUsphere, https://doi.org/10.5194/egusphere-2024-3798, https://doi.org/10.5194/egusphere-2024-3798, 2024
Short summary
Short summary
To predict the response of grassland plant communities to management and climate change, we developed the computer model GrasslandTraitSim.jl. Unlike other models, it uses measurable plant traits such as height, leaf thinness, and root structure as inputs, rather than hard-to-measure species data. This allows realistic simulation of many species. The model tracks daily changes in above- and below-ground biomass, plant height, and soil water, linking plant community composition to biomass supply.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Carlos Enmanuel Soto López, Fabio Anselmi, Mirna Gharbi Dit Kacem, and Paolo Lazzari
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-174, https://doi.org/10.5194/gmd-2024-174, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Our goal was to use an analytical expression to estimate the density of optical constituents, allowing us to have an interpretable formulation consistent with the laws of physics. We focused on a probabilistic approach, optimizing the model and retrieving quantities with their respective uncertainty. Considering future application to Big Data, we also explored a Neural Network based method, retrieving computationally efficient estimates, maintaining consistency with the analytical expression.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, Tumelo C. Moalusi, N. Precious Mongwe, and Pedro M. S. Monteiro
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-182, https://doi.org/10.5194/gmd-2024-182, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Mesoscale features (10's to 100's of km) in the Southern Ocean (SO) are crucial for global heat and carbon transport, but often unresolved in models due to high computational costs. To address this source of uncertainty, we use a regional, NEMO model of the SO at 8 km resolution with coupled ocean, ice, and biogeochemistry, BIOPERIANT12. This serves as an experimental platform to explore physical-biogeochemical interactions, model parameters/formulations, and configuring future models.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
Short summary
Short summary
We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
Short summary
Short summary
We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-94, https://doi.org/10.5194/gmd-2024-94, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We develop a new feature in the atmosphere and ocean components of the Community Earth System Model version 2. We have implemented ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation. The new feature will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Cited articles
Andres, R., Boden, T., and Marland, G.: Annual Fossil-Fuel CO2 Emissions:
Global Stable Carbon Isotopic Signature, CDIAC,
https://doi.org/10.3334/CDIAC/FFE.DB1013.2017, 1996.
Andres, R. J., Marland, G., Boden, T., and Bischof, S.: Carbon dioxide
emissions from fossil fuel consumption and cement manufacture, 1751–1991;
and an estimate of their isotopic composition and latitudinal distribution,
Oak Ridge National Lab., TN (United States), Oak Ridge Inst. for Science and
Education, TN (United States), available at:
https://www.osti.gov/biblio/10185357 (last access:29 October 2018), 1994.
Bardin, A., Primeau, F., and Lindsay, K.: An offline implicit solver for
simulating prebomb radiocarbon, Ocean Model., 73, 45–58,
https://doi.org/10.1016/j.ocemod.2013.09.008, 2014.
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from
satellite-based chlorophyll concentration, Limnol. Oceanogr.,
42, 1–20, https://doi.org/10.4319/lo.1997.42.1.0001, 1997.
Bouttes, N., Roche, D. M., Mariotti, V., and Bopp, L.: Including an ocean carbon cycle model into iLOVECLIM (v1.0), Geosci. Model Dev., 8, 1563–1576, https://doi.org/10.5194/gmd-8-1563-2015, 2015.
Brovkin, V., Bendtsen, J., Claussen, M., Ganopolski, A., Kubatzki, C.,
Petoukhov, V., and Andreev, A.: Carbon cycle, vegetation, and climate
dynamics in the Holocene: Experiments with the CLIMBER-2 model, Global
Biogeochem. Cy., 16, 86-1–86-20, https://doi.org/10.1029/2001GB001662, 2002.
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.
Burkhardt, S., Riebesell, U., and Zondervan, I.: Effects of growth rate, CO2
concentration, and cell size on the stable carbon isotope fractionation in
marine phytoplankton, Geochim. Cosmochim. Ac., 63, 3729–3741,
https://doi.org/10.1016/S0016-7037(99)00217-3, 1999.
Campos, M. C., Chiessi, C. M., Voigt, I., Piola, A. R., Kuhnert, H., and Mulitza, S.: δ13C decreases in the upper western South Atlantic during Heinrich Stadials 3 and 2, Clim. Past, 13, 345–358, https://doi.org/10.5194/cp-13-345-2017, 2017.
Cox, P. M., Betts, R. A., Bunton, C. B., Essery, R. L. H., Rowntree, P. R.,
and Smith, J.: The impact of new land surface physics on the GCM simulation
of climate and climate sensitivity, Clim. Dynam., 15, 183–203,
https://doi.org/10.1007/s003820050276, 1999.
Craig, H.: Isotopic standards for carbon and oxygen and correction factors
for mass-spectrometric analysis of carbon dioxide, Geochim.
Cosmochim. Ac., 12, 133–149, 1957.
Crucifix, M.: Distribution of carbon isotopes in the glacial ocean: A model
study, Paleoceanography, 20, PA4020, https://doi.org/10.1029/2005PA001131, 2005.
Curry, W. B. and Oppo, D. W.: Glacial water mass geometry and the
distribution of δ13C of ΣCO2 in the western Atlantic Ocean,
Paleoceanography, 20, PA1017, https://doi.org/10.1029/2004PA001021, 2005.
de la Fuente, M., Calvo, E., Skinner, L., Pelejero, C., Evans, D.,
Müller, W., Povea, P., and Cacho, I.: The Evolution of Deep Ocean
Chemistry and Respired Carbon in the Eastern Equatorial Pacific Over the
Last Deglaciation, Paleoceanography, 32, 2017PA003155,
https://doi.org/10.1002/2017PA003155, 2017.
Dentith, J. E.: Supplementary material for the thesis “Modelling carbon
isotopes to examine ocean circulation and the marine carbon cycle”,
University of Leeds, https://doi.org/10.5518/621, 2019.
Dentith, J. E., Ivanovic, R. F., Gregoire, L. J., Tindall, J. C., Robinson, L. F., and Valdes, P. J.: Simulating oceanic radiocarbon with the FAMOUS GCM: implications for its use as a proxy for ventilation and carbon uptake, Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-365, in review, 2019a.
Dentith, J. E., Ivanovic, R. F., Gregoire, L. J., Tindall, J. C., and Smith,
R. S.: Ocean circulation drifts in multi-millennial climate simulations: the
role of salinity corrections and climate feedbacks, Clim Dynam., 52,
1761–1781, https://doi.org/10.1007/s00382-018-4243-y, 2019b.
Doney, S. C.: Major challenges confronting marine biogeochemical modeling,
Global Biogeochem. Cycles, 13, 705–714, https://doi.org/10.1029/1999GB900039, 1999.
Doney, S. C., Lindsay, K., Caldeira, K., Campin, J.-M., Drange, H., Dutay,
J.-C., Follows, M., Gao, Y., Gnanadesikan, A., Gruber, N., Ishida, A., Joos,
F., Madec, G., Maier-Reimer, E., Marshall, J. C., Matear, R. J., Monfray,
P., Mouchet, A., Najjar, R., Orr, J. C., Plattner, G.-K., Sarmiento, J.,
Schlitzer, R., Slater, R., Totterdell, I. J., Weirig, M.-F., Yamanaka, Y.,
and Yool, A.: Evaluating global ocean carbon models: The importance of
realistic physics, Global Biogeochem. Cycles, 18, GB3017,
https://doi.org/10.1029/2003GB002150, 2004.
Eide, M., Olsen, A., Ninnemann, U. S., and Johannessen, T.: A global ocean
climatology of preindustrial and modern ocean δ13C, Global
Biogeochem. Cycles, 31, 515–534, https://doi.org/10.1002/2016GB005473, 2017.
Emrich, K., Ehhalt, D. H., and Vogel, J. C.: Carbon isotope fractionation
during the precipitation of calcium carbonate, Earth Planet. Sc.
Lett., 8, 363–371, https://doi.org/10.1016/0012-821X(70)90109-3, 1970.
England, M. H.: The Age of Water and Ventilation Timescales in a Global
Ocean Model, J. Phys. Oceanogr., 25, 2756–2777, 1995.
Essery, R. L. H., Best, M. J., and Cox, P. M.: MOSES2.2 Technical
Documentation, Hadley Centre Tech. Note 30, Met Office, Bracknell, United
Kingdom, 30 pp., available at:
http://jules.jchmr.org/sites/default/files/HCTN_30.pdf (last access: 1 August 2020), 2001.
Essery, R. L. H., Best, M. J., Betts, R. A., Cox, P. M., and Taylor, C. M.:
Explicit Representation of Subgrid Heterogeneity in a GCM Land Surface
Scheme, J. Hydrometeor., 4, 530–543,
https://doi.org/10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2,
2003.
Falkowski, P., Scholes, R. J., Boyle, E., Canadell, J., Canfield, D., Elser,
J., Gruber, N., Hibbard, K., Högberg, P., Linder, S., Mackenzie, F. T.,
Iii, B. M., Pedersen, T., Rosenthal, Y., Seitzinger, S., Smetacek, V., and
Steffen, W.: The Global Carbon Cycle: A Test of Our Knowledge of Earth as a
System, Science, 290, 291–296, https://doi.org/10.1126/science.290.5490.291,
2000.
Francey, R. J., Allison, C. E., Etheridge, D. M., Trudinger, C. M., Enting,
I. G., Leuenberger, M., Langenfelds, R. L., Michel, E., and Steele, L. P.: A
1000-year high precision record of δ13C in atmospheric CO2, Tellus
B, 51, 170–193, 1999.
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, 1992.
Goericke, R. and Fry, B.: Variations of marine plankton δ13C with
latitude, temperature, and dissolved CO2 in the world ocean, Global
Biogeochem. Cycles, 8, 85–90, https://doi.org/10.1029/93GB03272, 1994.
Gordon, C., Cooper, C., Senior, C. A., Banks, H., Gregory, J. M., Johns, T.
C., Mitchell, J. F. B., and Wood, R. A.: The simulation of SST, sea ice
extents and ocean heat transports in a version of the Hadley Centre coupled
model without flux adjustments, Clim. Dynam., 16, 147–168,
https://doi.org/10.1007/s003820050010, 2000.
Gregoire, L. J., Valdes, P. J., Payne, A. J., and Kahana, R.: Optimal tuning
of a GCM using modern and glacial constraints, Clim. Dynam., 37,
705–719, https://doi.org/10.1007/s00382-010-0934-8, 2011.
Gregoire, L. J., Payne, A. J., and Valdes, P. J.: Deglacial rapid sea level
rises caused by ice-sheet saddle collapses, Nature, 487, 219–222,
https://doi.org/10.1038/nature11257, 2012.
Gregoire, L. J., Valdes, P. J., and Payne, A. J.: The relative contribution
of orbital forcing and greenhouse gases to the North American deglaciation,
Geophys. Res. Lett., 42, 2015GL066005, https://doi.org/10.1002/2015GL066005, 2015.
Gruber, N. and Keeling, C. D.: An improved estimate of the isotopic air-sea
disequilibrium of CO2: Implications for the oceanic uptake of anthropogenic
CO2, Geophys. Res. Lett., 28, 555–558,
https://doi.org/10.1029/2000GL011853, 2001.
Guilderson, T. P., McCarthy, M. D., Dunbar, R. B., Englebrecht, A., and Roark, E. B.: Late Holocene variations in Pacific surface circulation and biogeochemistry inferred from proteinaceous deep-sea corals, Biogeosciences, 10, 6019–6028, https://doi.org/10.5194/bg-10-6019-2013, 2013.
Hofmann, M., Wolf-Gladrow, D. A., Takahashi, T., Sutherland, S. C., Six, K.
D., and Maier-Reimer, E.: Stable carbon isotope distribution of particulate
organic matter in the ocean: a model study, Marine Chem., 72,
131–150, https://doi.org/10.1016/S0304-4203(00)00078-5, 2000.
Hollander, D. J. and McKenzie, J. A.: CO2 control on carbon-isotope
fractionation during aqueous photosynthesis: A paleo-pCO2 barometer,
Geology, 19, 929–932, https://doi.org/10.1130/0091-7613(1991)019<0929:CCOCIF>2.3.CO;2, 1991.
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.
Jasper, J. P. and Hayes, J. M.: A carbon isotope record of CO2 levels during
the late Quaternary, Nature, 347, 462–464, 1990.
Jasper, J. P., Hayes, J. M., Mix, A. C., and Prahl, F. G.: Photosynthetic
fractionation of 13C and concentrations of dissolved CO2 in the central equatorial
Pacific during the last 255,000 years, Paleoceanography, 9, 781–798, 1994.
Jones, C., Gregory, J., Thorpe, R., Cox, P., Murphy, J., Sexton, D., and
Valdes, P.: Systematic optimisation and climate simulation of FAMOUS, a fast
version of HadCM3, Clim. Dynam., 25, 189–204,
https://doi.org/10.1007/s00382-005-0027-2, 2005.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-Year Reanalyis Project, B. Am. Meteorol. Soc.,
77, 437–470, 1996.
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, Mar. Ecol. Prog. Ser., 182,
295–298, 1999.
Key, R. M.: Radiocarbon, Encyclopedia of Ocean Sciences, Academic Press, available at: https://www.gfdl.noaa.gov/bibliography/related_files/rmk0101.pdf (last access: 1 August 2020),
2001.
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., Tanhua, T., Olsen, A., Hoppema, M., Jutterström, S., Schirnick, C., van Heuven, S., Kozyr, A., Lin, X., Velo, A., Wallace, D. W. R., and Mintrop, L.: The CARINA data synthesis project: introduction and overview, Earth Syst. Sci. Data, 2, 105–121, https://doi.org/10.5194/essd-2-105-2010, 2010.
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.
Koltermann, K. P., Gouretski, V., and Jancke, K.:Hydrographic Atlas of the World Ocean Circulation Experiment (WOCE), Volume 3: Atlantic Ocean, edited by: Sparrow, M., Chapman, P., and Gould, J., International WOCE Project Office, Southampton, UK, ISBN 090417557X, 2011.
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, 1997.
Leonard, B. P., Macvean, M. K., and Lock, A. P.: Positivity-preserving
numerical schemes for multidimensional advection, NASA, Washington, D.C.,
20546-0001, available at:
https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19930017902.pdf (last access: 23 May 2019), 1993.
Lindsay, K.: A Newton–Krylov solver for fast spin-up of online ocean
tracers, Ocean Model., 109, 33–43, https://doi.org/10.1016/j.ocemod.2016.12.001,
2017.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H.
E., Baranova, O. K., Zweng, M. M., Reagan, J. R., Johnson, D. R., Hamilton,
M., and Seidov, D.: World Ocean Atlas 2013, Volume 1: Temperature, edited by:
Levitus, S. and Mishonov, A., NOAA Atlas NESDIS 73, 2013.
Lynch-Stieglitz, J., Stocker, T. F., Broecker, W. S., and Fairbanks, R. G.:
The influence of air-sea exchange on the isotopic composition of oceanic
carbon: Observations and modeling, Global Biogeochem. Cycles, 9,
653–665, https://doi.org/10.1029/95GB02574, 1995.
Maier-Reimer, E.: Geochemical cycles in an ocean general circulation model.
Preindustrial tracer distributions, Global Biogeochem. Cycles, 7,
645–677, https://doi.org/10.1029/93GB01355, 1993.
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.
Menviel, L., Yu, J., Joos, F., Mouchet, A., Meissner, K. J., and England, M.
H.: Poorly ventilated deep ocean at the Last Glacial Maximum inferred from
carbon isotopes: A data-model comparison study, Paleoceanography, 32,
2–17, https://doi.org/10.1002/2016PA003024, 2017.
Mook, W. G.: 13C in atmospheric CO2, Netherlands Journal of Sea Research,
20, 211–223, https://doi.org/10.1016/0077-7579(86)90043-8, 1986.
Mouchet, A.: A 3D model of ocean biogeochemical cycles and ocean ventilation
studies, Université de Liège, Lìege, Belgium, available at: http://hdl.handle.net/2268/98995 (last access: 10 May 2020), 2011.
Murnane, R. J. and Sarmiento, J. L.: Roles of biology and gas exchange in
determining the δ13C distribution in the ocean and the preindustrial
gradient in atmospheric δ13C, Global Biogeochem. Cycles, 14,
389–405, https://doi.org/10.1029/1998GB001071, 2000.
Najjar, R. G., Jin, X., Louanchi, F., Aumont, O., Caldeira, K., Doney, S.
C., Dutay, J.-C., Follows, M., Gruber, N., Joos, F., Lindsay, K.,
Maier-Reimer, E., Matear, R. J., Matsumoto, K., Monfray, P., Mouchet, A.,
Orr, J. C., Plattner, G.-K., Sarmiento, J. L., Schlitzer, R., Slater, R. D.,
Weirig, M.-F., Yamanaka, Y., and Yool, A.: Impact of circulation on export
production, dissolved organic matter, and dissolved oxygen in the ocean:
Results from Phase II of the Ocean Carbon-cycle Model Intercomparison
Project (OCMIP-2), Global Biogeochem. Cycles, 21, GB3007,
https://doi.org/10.1029/2006GB002857, 2007.
Oliver, K. I. C., Hoogakker, B. A. A., Crowhurst, S., Henderson, G. M., Rickaby, R. E. M., Edwards, N. R., and Elderfield, H.: A synthesis of marine sediment core δ13C data over the last 150 000 years, Clim. Past, 6, 645–673, https://doi.org/10.5194/cp-6-645-2010, 2010.
Olsen, A., Key, R. M., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Pérez, F. F., and Suzuki, T.: The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean, Earth Syst. Sci. Data, 8, 297–323, https://doi.org/10.5194/essd-8-297-2016, 2016.
Orr, J., Najjar, R., Sabine, C. L., and Joos, F.: Abiotic-HOWTO. Technical
report, Revision: 1.16, available at:
http://ocmip5.ipsl.jussieu.fr/documentation/OCMIP/phase2/simulations/Abiotic/HOWTO-Abiotic.html (last access: 23 December 2019),
2000.
Orr, J. C.: Ocean Carbon-Cycle Model Intercomparison Project (OCMIP): Phase
1 (1995–1997), GAIM Report 7, available at: http://ocmip5.ipsl.jussieu.fr/OCMIP/phase1/reports/final/phase1.html (last access: 1 August 2020), 1999.
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.
Orsi, A. H. and Whitworth III, T.: Hydrographic Atlas of the World Ocean Circulation Experiment (WOCE), Volume 1: Southern Ocean, edited by: Sparrow, M., Chapman, P., and Gould, J., International WOCE Project Office, Southampton, U.K., ISBN 0-904175-49-9, 2005.
Palmer, J. R.: The Ocean Carbon Cycle in the Unified Model, available at: http://cms.ncas.ac.uk/documents/vn4.5/p053.pdf (last access: 1 August 2020), 1998.
Palmer, J. R. and Totterdell, I. J.: Production and export in a global ocean
ecosystem model, Deep-Sea Res. Pt. I,
48, 1169–1198, https://doi.org/10.1016/S0967-0637(00)00080-7, 2001.
Pope, V. D., Gallani, M. L., Rowntree, P. R., and Stratton, R. A.: The impact
of new physical parametrizations in the Hadley Centre climate model: HadAM3,
Clim. Dynam., 16, 123–146, https://doi.org/10.1007/s003820050009, 2000.
Popp, B. N., Takigiku, R., Hayes, J. M., Louda, J. W., and Baker, E. W.: The
post-Paleozoic chronology and mechanism of 13C depletion in primary marine
organic matter, Am. J. Sci., 289, 436–454, 1989.
Quay, P., Sonnerup, R., Westby, T., Stutsman, J., and McNichol, A.: Changes
in the 13C∕12C of dissolved inorganic carbon in the ocean as a tracer of
anthropogenic CO2 uptake, Global Biogeochem. Cy., 17, 4-1–4-20,
https://doi.org/10.1029/2001GB001817, 2003.
Quay, P. D., Tilbrook, B., and Wong, C. S.: Oceanic Uptake of Fossil Fuel
CO2: Carbon-13 Evidence, Science, 256, 74–79,
https://doi.org/10.1126/science.256.5053.74, 1992.
Rau, G. H., Takahashi, T., and Des Marais, D. J.: Latitudinal variations in
plankton δ13C: implications for CO2 and productivity in past oceans,
Nature, 341, 516–518, 1989.
Rau, G. H., Riebesell, U., and Wolf-Gladrow, D.: A model of photosynthetic 13C fractionation by marine phytoplankton based on diffusive molecular CO2
uptake, Mar. Ecol. Prog. Ser., 133, 275–285, 1996.
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007.
Ridgwell, A. J.: Glacial-interglacial perturbations in the global carbon
cycle, PhD thesis, University of East Anglia at Norwich, UK, available at: http://www.seao2.info/pubs/ridgwell_2001.pdf (last access: 10 May 2020),
2001.
Rubino, M., Etheridge, D. M., Trudinger, C. M., Allison, C. E., Battle, M.
O., Langenfelds, R. L., Steele, L. P., Curran, M., Bender, M., White, J. W.
C., Jenk, T. M., Blunier, T., and Francey, R. J.: A revised 1000 year
atmospheric δ13C-CO2 record from Law Dome and South Pole,
Antarctica, J. Geophys. Res.-Atmos., 118,
8482–8499, https://doi.org/10.1002/jgrd.50668, 2013.
Sackett, W. M., Eckelmann, W. R., Bender, M. L., and Bé, A. W. H.:
Temperature Dependence of Carbon Isotope Composition in Marine Plankton and
Sediments, Science, 148, 235–237, https://doi.org/10.1126/science.148.3667.235,
1965.
Sagoo, N., Valdes, P., Flecker, R., and Gregoire, L. J.: The Early Eocene
equable climate problem: can perturbations of climate model parameters
identify possible solutions?, Philos. Trans. A Math. Phys. Eng. Sci., 371,
20130123, https://doi.org/10.1098/rsta.2013.0123, 2013.
Sarmiento, J. and Gruber, N.: Ocean Biogeochemical Dynamics, Princeton
University Press, Princeton, New Jersey, Oxfordshire, UK, 2006.
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.
Smith, R. S.: The FAMOUS climate model (versions XFXWB and XFHCC): description update to version XDBUA, Geosci. Model Dev., 5, 269–276, https://doi.org/10.5194/gmd-5-269-2012, 2012.
Smith, R. S. and Gregory, J.: The last glacial cycle: transient simulations
with an AOGCM, Clim. Dynam., 38, 1545–1559,
https://doi.org/10.1007/s00382-011-1283-y, 2012.
Smith, R. S., Gregory, J. M., and Osprey, A.: A description of the FAMOUS (version XDBUA) climate model and control run, Geosci. Model Dev., 1, 53–68, https://doi.org/10.5194/gmd-1-53-2008, 2008.
Spero, H. J. and Lea, D. W.: The Cause of Carbon Isotope Minimum Events on
Glacial Terminations, Science, 296, 522–525,
https://doi.org/10.1126/science.1069401, 2002.
Suess, H. E.: Radiocarbon Concentration in Modern Wood, Science, 122,
415–417, 1955.
Suzuki, T., Ishii, M., Aoyama, M., Christian, J. R., Enyo, K., Kawano, T.,
Key, R. M., Kosugi, N., Kozyr, A., Miller, L., Murata, A., Nakano, T., Ono,
T., Saino, T., Sasaki, K.-I., Sasano, D., Takatani, Y., Wakita, M., and
Sabine, C.: PACIFICA data synthesis project, Carbon Dioxide Information
Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy,
Oak Ridge, Tennessee, 2013.
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.
Talley, L. D.: Hydrographic Atlas of the World Ocean Circulation Experiment (WOCE), Volume 2: Pacific Ocean, edited by: Sparrow, M., Chapman, P., and Gould, J., International WOCE Project Office, Southampton, UK, ISBN 0-904175-54-5, 2007.
Talley, L. D.: Hydrographic Atlas of the World Ocean Circulation Experiment (WOCE), Volume 4: Indian Ocean, edited by: Sparrow, M., Chapman, P., and Gould, J., International WOCE Project Office, Southampton, UK, ISBN 0904175588, 2013.
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.
Turner, J. V.: Kinetic fractionation of carbon-13 during calcium carbonate
precipitation, Geochim. Cosmochim. Ac., 46, 1183–1191,
https://doi.org/10.1016/0016-7037(82)90004-7, 1982.
Valdes, P. J., Armstrong, E., Badger, M. P. S., Bradshaw, C. D., Bragg, F., Crucifix, M., Davies-Barnard, T., Day, J. J., Farnsworth, A., Gordon, C., Hopcroft, P. O., Kennedy, A. T., Lord, N. S., Lunt, D. J., Marzocchi, A., Parry, L. M., Pope, V., Roberts, W. H. G., Stone, E. J., Tourte, G. J. L., and Williams, J. H. T.: The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0, Geosci. Model Dev., 10, 3715–3743, https://doi.org/10.5194/gmd-10-3715-2017, 2017.
Williams, J. H. T., Smith, R. S., Valdes, P. J., Booth, B. B. B., and Osprey, A.: Optimising the FAMOUS climate model: inclusion of global carbon cycling, Geosci. Model Dev., 6, 141–160, https://doi.org/10.5194/gmd-6-141-2013, 2013.
Williams, J. H. T., Totterdell, I. J., Halloran, P. R., and Valdes, P. J.: Numerical simulations of oceanic oxygen cycling in the FAMOUS Earth-System model: FAMOUS-ES, version 1.0, Geosci. Model Dev., 7, 1419–1431, https://doi.org/10.5194/gmd-7-1419-2014, 2014.
Wong, W. W. and Sackett, W. M.: Fractionation of stable carbon isotopes by
marine phytoplankton, Geochim. Cosmochim. Ac., 42, 1809–1815,
https://doi.org/10.1016/0016-7037(78)90236-3, 1978.
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
We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model captures the large-scale spatial pattern of observations but the simulated values are consistently higher than observed. In the first instance, our new tracer is therefore useful for recalibrating the physical and biogeochemical components of the model.
We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale...
Special issue