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.
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.
Elisa Ziegler, Nils Weitzel, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lauren Gregoire, Ruza Ivanovic, Paul J. Valdes, Christian Wirths, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-1396, https://doi.org/10.5194/egusphere-2024-1396, 2024
Short summary
Short summary
During the Last Deglaciation global surface temperature rose by about 4–7 degrees over several millennia. We show that changes of 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 fifteen climate model simulations. The analysis demonstrates how ice sheets, meltwater and volcanism influence simulated variability to inform future simulation protocols.
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.
Takashi Obase, Laurie Menviel, Ayako Abe-Ouchi, Tristan Vadsaria, Ruza Ivanovic, Brooke Snoll, Sam Sherriff-Tadano, Paul 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 Discuss., https://doi.org/10.5194/cp-2023-86, https://doi.org/10.5194/cp-2023-86, 2023
Revised manuscript under review for CP
Short summary
Short summary
This study analyses transient simulations of the last deglaciation performed by six climate models to understand the processes driving southern high latitude temperature changes. We find that atmospheric CO2 changes and AMOC changes are the primary drivers of the major warming and cooling during the middle stage of the deglaciation. The multi-model analysis highlights the model’s sensitivity of CO2, AMOC to meltwater, and the meltwater history on temperature changes in southern high latitudes.
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
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
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
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
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
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Lambda-PFLOTRAN 1.0: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
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.
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.
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.
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.
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.
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
Short summary
Short summary
Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
Short summary
Short summary
Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
Short summary
Short summary
Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
Short summary
Short summary
We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie Fisher, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2024-978, https://doi.org/10.5194/egusphere-2024-978, 2024
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 and variability of carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research on 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. Discuss., https://doi.org/10.5194/gmd-2024-34, https://doi.org/10.5194/gmd-2024-34, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The newly developed Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate respiration and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow via a Jupyter Notebook interface, that digests raw organic matter chemistry data via FTICR-MS, develops the representative reaction network, and completes a biogeochemical simulation with the open source, parallel reactive flow and transport code PFLOTRAN.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
Short summary
Short summary
We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
Short summary
Short summary
By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
Short summary
Short summary
Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
Short summary
Short summary
Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
Short summary
Short summary
Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
Short summary
Short summary
By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
Short summary
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
Short summary
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
Short summary
Short summary
To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
Short summary
Short summary
Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
Short summary
Short summary
This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
Short summary
Short summary
Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
Short summary
Short summary
We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
Short summary
Short summary
Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
Short summary
Short summary
The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
Short summary
Short summary
We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
Short summary
Short summary
Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
Short summary
Short summary
We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
Short summary
Short summary
Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
Short summary
Short summary
In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
Short summary
Short summary
Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
Short summary
Short summary
This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
Short summary
Short summary
Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
Short summary
Short summary
Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
Short summary
Short summary
Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
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