Articles | Volume 8, issue 8
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
13 Aug 2015
Model description paper |
| 13 Aug 2015
PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies
O. Aumont
CORRESPONDING AUTHOR
Laboratoire d'Océanographie et de Climatologie: Expérimentation et Approches Numériques, IPSL, 4 Place Jussieu, 75005 Paris, France
C. Ethé
Institut Pierre et Simon Laplace, 4 Place Jussieu, 75005 Paris, France
A. Tagliabue
Dept. of Earth, Ocean and Ecological Sciences, School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, Liverpool L69 3GP, UK
Laboratoire des Sciences du Climat et de l'Environement, IPSL, Orme des Merisiers, 91190 Gif-sur-Yvette, France
M. Gehlen
Laboratoire des Sciences du Climat et de l'Environement, IPSL, Orme des Merisiers, 91190 Gif-sur-Yvette, France
Related authors
Madhavan Girijakumari Keerthi, Olivier Aumont, Lester Kwiatkowski, and Marina Levy
Biogeosciences, 22, 2163–2180, https://doi.org/10.5194/bg-22-2163-2025, https://doi.org/10.5194/bg-22-2163-2025, 2025
Short summary
Short summary
We assessed how well climate models replicate sub-seasonal changes in ocean chlorophyll observed by satellites. Models struggle to capture these variations accurately. Some overestimate fluctuations and their impact on annual chlorophyll variability, while others underestimate them. The underestimation is likely due to limited model resolution, while the overestimation may come from internal model oscillations.
Lisa Di Matteo, Fabio Benedetti, Sakina-Dorothée Ayata, and Olivier Aumont
EGUsphere, https://doi.org/10.5194/egusphere-2025-1465, https://doi.org/10.5194/egusphere-2025-1465, 2025
Short summary
Short summary
Mesozooplankton gather small current-drifting animals. They are very diverse and play key roles in the functioning of marine ecosystem and ocean carbon cycle, especially through the production of rapidly sinking particles. Usually under-represented in marine biogeochemical models, we add 3 feeding strategies in the PISCES model and investigate their impact on carbon cycle at global scale. We find distinct distributions between mesozooplankton types with different contributions to carbon export.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
Short summary
Short summary
Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Corentin Clerc, Laurent Bopp, Fabio Benedetti, Meike Vogt, and Olivier Aumont
Biogeosciences, 20, 869–895, https://doi.org/10.5194/bg-20-869-2023, https://doi.org/10.5194/bg-20-869-2023, 2023
Short summary
Short summary
Gelatinous zooplankton play a key role in the ocean carbon cycle. In particular, pelagic tunicates, which feed on a wide size range of prey, produce rapidly sinking detritus. Thus, they efficiently transfer carbon from the surface to the depths. Consequently, we added these organisms to a marine biogeochemical model (PISCES-v2) and evaluated their impact on the global carbon cycle. We found that they contribute significantly to carbon export and that this contribution increases with depth.
Laurent Bopp, Olivier Aumont, Lester Kwiatkowski, Corentin Clerc, Léonard Dupont, Christian Ethé, Thomas Gorgues, Roland Séférian, and Alessandro Tagliabue
Biogeosciences, 19, 4267–4285, https://doi.org/10.5194/bg-19-4267-2022, https://doi.org/10.5194/bg-19-4267-2022, 2022
Short summary
Short summary
The impact of anthropogenic climate change on the biological production of phytoplankton in the ocean is a cause for concern because its evolution could affect the response of marine ecosystems to climate change. Here, we identify biological N fixation and its response to future climate change as a key process in shaping the future evolution of marine phytoplankton production. Our results show that further study of how this nitrogen fixation responds to environmental change is essential.
Martí Galí, Marcus Falls, Hervé Claustre, Olivier Aumont, and Raffaele Bernardello
Biogeosciences, 19, 1245–1275, https://doi.org/10.5194/bg-19-1245-2022, https://doi.org/10.5194/bg-19-1245-2022, 2022
Short summary
Short summary
Part of the organic matter produced by plankton in the upper ocean is exported to the deep ocean. This process, known as the biological carbon pump, is key for the regulation of atmospheric carbon dioxide and global climate. However, the dynamics of organic particles below the upper ocean layer are not well understood. Here we compared the measurements acquired by autonomous robots in the top 1000 m of the ocean to a numerical model, which can help improve future climate projections.
Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet
Geosci. Model Dev., 14, 4069–4086, https://doi.org/10.5194/gmd-14-4069-2021, https://doi.org/10.5194/gmd-14-4069-2021, 2021
Short summary
Short summary
The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
Short summary
Short summary
We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
Vincent Echevin, Manon Gévaudan, Dante Espinoza-Morriberón, Jorge Tam, Olivier Aumont, Dimitri Gutierrez, and François Colas
Biogeosciences, 17, 3317–3341, https://doi.org/10.5194/bg-17-3317-2020, https://doi.org/10.5194/bg-17-3317-2020, 2020
Short summary
Short summary
The coasts of Peru encompass the richest fisheries in the entire ocean. It is therefore very important for this country to understand how the nearshore marine ecosystem may evolve under climate change. Fine-scale numerical models are very useful because they can represent precisely the evolution of key parameters such as temperature, water oxygenation, and plankton biomass. Here we study the evolution of the Peruvian marine ecosystem in the 21st century under the worst-case climate scenario.
Marie-Hélène Radenac, Julien Jouanno, Christine Carine Tchamabi, Mesmin Awo, Bernard Bourlès, Sabine Arnault, and Olivier Aumont
Biogeosciences, 17, 529–545, https://doi.org/10.5194/bg-17-529-2020, https://doi.org/10.5194/bg-17-529-2020, 2020
Short summary
Short summary
Satellite data and a remarkable set of in situ measurements show a main bloom of microscopic seaweed, the phytoplankton, in summer and a secondary bloom in December in the central equatorial Atlantic. They are driven by a strong vertical supply of nitrate in May–July and a shorter and moderate supply in November. In between, transport of low-nitrate water from the west explains most nitrate losses in the sunlit layer. Horizontal eddy-induced processes also contribute to seasonal nitrate removal.
Renaud Person, Olivier Aumont, Gurvan Madec, Martin Vancoppenolle, Laurent Bopp, and Nacho Merino
Biogeosciences, 16, 3583–3603, https://doi.org/10.5194/bg-16-3583-2019, https://doi.org/10.5194/bg-16-3583-2019, 2019
Short summary
Short summary
The Antarctic Ice Sheet is considered a possibly important but largely overlooked source of iron (Fe). Here we explore its fertilization capacity by evaluating the response of marine biogeochemistry to Fe release from icebergs and ice shelves in a global ocean model. Large regional impacts are simulated, leading to only modest primary production and carbon export increases at the scale of the Southern Ocean. Large uncertainties are due to low observational constraints on modeling choices.
Cyril Dutheil, Olivier Aumont, Thomas Gorguès, Anne Lorrain, Sophie Bonnet, Martine Rodier, Cécile Dupouy, Takuhei Shiozaki, and Christophe Menkes
Biogeosciences, 15, 4333–4352, https://doi.org/10.5194/bg-15-4333-2018, https://doi.org/10.5194/bg-15-4333-2018, 2018
Short summary
Short summary
N2 fixation is recognized as one of the major sources of nitrogen in the ocean. Thus, N2 fixation sustains a significant part of the primary production (PP) by supplying the most common limiting nutrient for phytoplankton growth. From numerical simulations, the local maximums of Trichodesmium biomass in the Pacific are found around islands, explained by the iron fluxes from island sediments. We assessed that 15 % of the PP may be due to Trichodesmium in the low-nutrient, low-chlorophyll areas.
Madhavan Girijakumari Keerthi, Matthieu Lengaigne, Marina Levy, Jerome Vialard, Vallivattathillam Parvathi, Clément de Boyer Montégut, Christian Ethé, Olivier Aumont, Iyyappan Suresh, Valiya Parambil Akhil, and Pillathu Moolayil Muraleedharan
Biogeosciences, 14, 3615–3632, https://doi.org/10.5194/bg-14-3615-2017, https://doi.org/10.5194/bg-14-3615-2017, 2017
Short summary
Short summary
The northern Arabian Sea hosts a winter chlorophyll bloom, which exhibits strong interannual variability. The processes responsible for this interannual variation of the bloom are investigated using observations and a model. The interannual fluctuations of the winter bloom are largely related to the interannual mixed-layer depth (MLD) anomalies, which are driven by net heat flux anomalies. MLD controls the bloom amplitude through a modulation of nutrient turbulent fluxes into the mixed layer.
Guillaume Le Gland, Laurent Mémery, Olivier Aumont, and Laure Resplandy
Biogeosciences, 14, 3171–3189, https://doi.org/10.5194/bg-14-3171-2017, https://doi.org/10.5194/bg-14-3171-2017, 2017
Short summary
Short summary
In this study, we computed the fluxes of radium-228 from the continental shelf to the open ocean by fitting a numerical model to observations. After determining appropriate model parameters (cost function and number of source regions), we found a lower and more precise global flux than previous estimates: 8.01–8.49×1023 atoms yr−1. This result can be used to assess nutrient and trace element fluxes to the open ocean, but we cannot identify specific pathways like submarine groundwater discharge.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Olivier Aumont, Marco van Hulten, Matthieu Roy-Barman, Jean-Claude Dutay, Christian Éthé, and Marion Gehlen
Biogeosciences, 14, 2321–2341, https://doi.org/10.5194/bg-14-2321-2017, https://doi.org/10.5194/bg-14-2321-2017, 2017
Short summary
Short summary
The marine biological carbon pump is dominated by the vertical transfer of particulate organic carbon (POC) from the surface ocean to its interior. In this study, we explore the impacts of a variable composition of this organic matter using a global ocean biogeochemical model. We show that accounting for a variable lability of POC increases POC concentrations by up to 2 orders of magnitude in the ocean's interior. Furthermore, the amount of carbon that reaches the sediments is twice as large.
Parvathi Vallivattathillam, Suresh Iyyappan, Matthieu Lengaigne, Christian Ethé, Jérôme Vialard, Marina Levy, Neetu Suresh, Olivier Aumont, Laure Resplandy, Hema Naik, and Wajih Naqvi
Biogeosciences, 14, 1541–1559, https://doi.org/10.5194/bg-14-1541-2017, https://doi.org/10.5194/bg-14-1541-2017, 2017
Short summary
Short summary
During late boreal summer and fall, the west coast of India (WCI) experiences hypoxia, which turns into anoxia during some years. We analyze a coupled physical–biogeochemical simulation over the 1960–2012 period to investigate the physical processes influencing oxycline interannual variability off the WCI. We show that fall WCI oxycline fluctuations are strongly related to Indian Ocean Dipole (IOD), with positive IODs preventing anoxia, while negative IODs do not necessarily result in anoxia.
Pierre-Amaël Auger, Thomas Gorgues, Eric Machu, Olivier Aumont, and Patrice Brehmer
Biogeosciences, 13, 6419–6440, https://doi.org/10.5194/bg-13-6419-2016, https://doi.org/10.5194/bg-13-6419-2016, 2016
Short summary
Short summary
A box modeling approach reveals that horizontal currents drive the spatial distribution of phytoplankton biomass and primary production in the north-west African upwelling system. Alongshore (cross-shore) currents limit (enhance) cross-shore exchanges north (south) of Cape Blanc. Off Cape Blanc, a meridional convergence makes ambiguous the response of coastal nutrient upwelling to wind forcings, and high production is based upon nutrients and remineralized matter injected by horizontal currents.
Corinne Le Quéré, Erik T. Buitenhuis, Róisín Moriarty, Séverine Alvain, Olivier Aumont, Laurent Bopp, Sophie Chollet, Clare Enright, Daniel J. Franklin, Richard J. Geider, Sandy P. Harrison, Andrew G. Hirst, Stuart Larsen, Louis Legendre, Trevor Platt, I. Colin Prentice, Richard B. Rivkin, Sévrine Sailley, Shubha Sathyendranath, Nick Stephens, Meike Vogt, and Sergio M. Vallina
Biogeosciences, 13, 4111–4133, https://doi.org/10.5194/bg-13-4111-2016, https://doi.org/10.5194/bg-13-4111-2016, 2016
Short summary
Short summary
We present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types, and use the model to assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean. Our results suggest that observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community, despite iron limitation of phytoplankton growth.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary
Short summary
This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
Short summary
Short summary
This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
K. B. Rodgers, O. Aumont, S. E. Mikaloff Fletcher, Y. Plancherel, L. Bopp, C. de Boyer Montégut, D. Iudicone, R. F. Keeling, G. Madec, and R. Wanninkhof
Biogeosciences, 11, 4077–4098, https://doi.org/10.5194/bg-11-4077-2014, https://doi.org/10.5194/bg-11-4077-2014, 2014
I. Borrione, O. Aumont, M. C. Nielsdóttir, and R. Schlitzer
Biogeosciences, 11, 1981–2001, https://doi.org/10.5194/bg-11-1981-2014, https://doi.org/10.5194/bg-11-1981-2014, 2014
M. Ishii, R. A. Feely, K. B. Rodgers, G.-H. Park, R. Wanninkhof, D. Sasano, H. Sugimoto, C. E. Cosca, S. Nakaoka, M. Telszewski, Y. Nojiri, S. E. Mikaloff Fletcher, Y. Niwa, P. K. Patra, V. Valsala, H. Nakano, I. Lima, S. C. Doney, E. T. Buitenhuis, O. Aumont, J. P. Dunne, A. Lenton, and T. Takahashi
Biogeosciences, 11, 709–734, https://doi.org/10.5194/bg-11-709-2014, https://doi.org/10.5194/bg-11-709-2014, 2014
J. C. Currie, M. Lengaigne, J. Vialard, D. M. Kaplan, O. Aumont, S. W. A. Naqvi, and O. Maury
Biogeosciences, 10, 6677–6698, https://doi.org/10.5194/bg-10-6677-2013, https://doi.org/10.5194/bg-10-6677-2013, 2013
Nicolas Metzl, Claire Lo Monaco, Aline Tribollet, Jean-François Ternon, Frédéric Chevallier, and Marion Gehlen
EGUsphere, https://doi.org/10.5194/egusphere-2025-3469, https://doi.org/10.5194/egusphere-2025-3469, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
In the Mozambique Channel, observed acceleration of the ocean acidification in the recent decades is mainly driven by anthropogenic CO2 uptake. In this region the aragonite saturation state reached 3.2 in 2025 and could be as low as 3 in the next 10 years with potential impact on marine ecosystem including corals reefs areas.
Mathieu Delteil, Marina Lévy, and Laurent Bopp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2805, https://doi.org/10.5194/egusphere-2025-2805, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
The ocean is losing oxygen due to climate change, threatening ecosystems, especially in naturally low-oxygen areas called Oxygen Minimum Zones (OMZs). Using the IPSL-CM6A-LR Large Ensemble, this study identifies when climate-driven changes in OMZ volumes and regional deoxygenation emerge from natural variability. We highlight hemispheric asymmetries due to ocean ventilation and provide model-based estimates for the timing of detectable OMZ evolution.
Germain Bénard, Marion Gehlen, and Mathieu Vrac
Earth Syst. Dynam., 16, 1085–1102, https://doi.org/10.5194/esd-16-1085-2025, https://doi.org/10.5194/esd-16-1085-2025, 2025
Short summary
Short summary
We introduce a novel approach to compare Earth system model output using a causality-based approach. The analysis of interactions between atmospheric, oceanic and biogeochemical variables in the North Atlantic subpolar gyre highlights the dynamics of each model. This method reveals potential underlying causes of model differences, offering a tool for enhanced model evaluation and improved understanding of complex Earth system dynamics under past and future climates.
Alex Nalivaev, Francesco d'Ovidio, Laurent Bopp, Maristella Berta, Louise Rousselet, Clara Azarian, and Stéphane Blain
EGUsphere, https://doi.org/10.5194/egusphere-2025-2145, https://doi.org/10.5194/egusphere-2025-2145, 2025
Short summary
Short summary
The Kerguelen region hosts a phytoplankton bloom influenced by several iron sources. In particular, glaciers supply iron to the coastal waters. However, the importance of glacial iron for the bloom is not known. Here we calculate iron transport pathways from glaciers to the open ocean using in situ and satellite data, showing that one third of the offshore bloom is reached by glacial iron. These results are important in the context of the melting of the Kerguelen ice cap under climate change.
Travis Mellett, Justine Albers, Alyson Santoro, Pascal Salaun, Joseph Resing, Wenhao Wang, Alistar Lough, Alessandro Tagliabue, Maeve Lohan, Randelle Bundy, and Kristen Buck
EGUsphere, https://doi.org/10.5194/egusphere-2025-1798, https://doi.org/10.5194/egusphere-2025-1798, 2025
Short summary
Short summary
Hydrothermal plumes of iron have been observed to persist in the deep ocean, but the exact mechanisms that contribute to the long-range transport of iron is not well defined. We collected plume waters from three different vent systems along the mid-Atlantic Ridge and monitored the temporal evolution of the physical and chemical forms of iron and its interaction with organic matter over time to learn about the mechanisms that control its dispersion.
Li-Qing Jiang, Amanda Fay, Jens Daniel Müller, Lydia Keppler, Dustin Carroll, Siv K. Lauvset, Tim DeVries, Judith Hauck, Christian Rödenbeck, Luke Gregor, Nicolas Metzl, Andrea J. Fassbender, Jean-Pierre Gattuso, Peter Landschützer, Rik Wanninkhof, Christopher Sabine, Simone R. Alin, Mario Hoppema, Are Olsen, Matthew P. Humphreys, Kumiko Azetsu-Scott, Dorothee C. E. Bakker, Leticia Barbero, Nicholas R. Bates, Nicole Besemer, Henry C. Bittig, Albert E. Boyd, Daniel Broullón, Wei-Jun Cai, Brendan R. Carter, Thi-Tuyet-Trang Chau, Chen-Tung Arthur Chen, Frédéric Cyr, John E. Dore, Ian Enochs, Richard A. Feely, Hernan E. Garcia, Marion Gehlen, Lucas Gloege, Melchor González-Dávila, Nicolas Gruber, Yosuke Iida, Masao Ishii, Esther Kennedy, Alex Kozyr, Nico Lange, Claire Lo Monaco, Derek P. Manzello, Galen A. McKinley, Natalie M. Monacci, Xose A. Padin, Ana M. Palacio-Castro, Fiz F. Pérez, Alizée Roobaert, J. Magdalena Santana-Casiano, Jonathan Sharp, Adrienne Sutton, Jim Swift, Toste Tanhua, Maciej Telszewski, Jens Terhaar, Ruben van Hooidonk, Anton Velo, Andrew J. Watson, Angelicque E. White, Zelun Wu, Hyelim Yoo, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-255, https://doi.org/10.5194/essd-2025-255, 2025
Preprint under review for ESSD
Short summary
Short summary
This review article provides an overview of 60 existing ocean carbonate chemistry data products, encompassing a broad range of types, including compilations of cruise datasets, gap-filled observational products, model simulations, and more. It is designed to help researchers identify and access the data products that best support their scientific objectives, thereby facilitating progress in understanding the ocean's changing carbonate chemistry.
Madhavan Girijakumari Keerthi, Olivier Aumont, Lester Kwiatkowski, and Marina Levy
Biogeosciences, 22, 2163–2180, https://doi.org/10.5194/bg-22-2163-2025, https://doi.org/10.5194/bg-22-2163-2025, 2025
Short summary
Short summary
We assessed how well climate models replicate sub-seasonal changes in ocean chlorophyll observed by satellites. Models struggle to capture these variations accurately. Some overestimate fluctuations and their impact on annual chlorophyll variability, while others underestimate them. The underestimation is likely due to limited model resolution, while the overestimation may come from internal model oscillations.
Lisa Di Matteo, Fabio Benedetti, Sakina-Dorothée Ayata, and Olivier Aumont
EGUsphere, https://doi.org/10.5194/egusphere-2025-1465, https://doi.org/10.5194/egusphere-2025-1465, 2025
Short summary
Short summary
Mesozooplankton gather small current-drifting animals. They are very diverse and play key roles in the functioning of marine ecosystem and ocean carbon cycle, especially through the production of rapidly sinking particles. Usually under-represented in marine biogeochemical models, we add 3 feeding strategies in the PISCES model and investigate their impact on carbon cycle at global scale. We find distinct distributions between mesozooplankton types with different contributions to carbon export.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Noelle A. Held, Korrina Kunde, Clare E. Davis, Neil J. Wyatt, Elizabeth L. Mann, E. Malcolm S. Woodward, Matthew McIlvin, Alessandro Tagliabue, Benjamin S. Twining, Claire Mahaffey, Mak A. Saito, and Maeve C. Lohan
EGUsphere, https://doi.org/10.5194/egusphere-2024-3996, https://doi.org/10.5194/egusphere-2024-3996, 2025
Short summary
Short summary
Microbial enzymes are critical to marine biogeochemical cycles, but which microbes are producing those enzymes? We used a targeted proteomics method to quantify how much Prochlorococcus and Synechococcus contribute to surface ocean alkaline phosphatase activity. We find that alkaline phosphatase abundance is limited by the availability of iron, zinc and cobalt (which may substitute for zinc).
Alban Planchat, Laurent Bopp, and Lester Kwiatkowski
EGUsphere, https://doi.org/10.5194/egusphere-2025-523, https://doi.org/10.5194/egusphere-2025-523, 2025
Short summary
Short summary
Disparities in ocean carbon sink estimates derived from observations and models raise questions about our ability to accurately assess its magnitude and trend. Essential for isolating the anthropogenic component of the total air-sea carbon flux estimated from observations, the pre-industrial air-sea carbon flux is a key source of uncertainty. Thus, we take a fresh look at this flux using the alkalinity budget, alongside the carbon budget which had previously been considered alone.
Pearse J. Buchanan, Juan J. Pierella Karlusich, Robyn E. Tuerena, Roxana Shafiee, E. Malcolm S. Woodward, Chris Bowler, and Alessandro Tagliabue
EGUsphere, https://doi.org/10.5194/egusphere-2024-3639, https://doi.org/10.5194/egusphere-2024-3639, 2025
Short summary
Short summary
Ammonium is a form of nitrogen that may become more important for growth of marine primary producers (i.e., phytoplankton) in the future. Because some phytoplankton taxa have a greater affinity for ammonium than others, the relative increase in ammonium could cause shifts in community composition. We quantify ammonium enrichment, identify its drivers, and isolate the possible effect on phytoplankton community composition under a high emissions scenario.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernardello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
Earth Syst. Dynam., 15, 1591–1628, https://doi.org/10.5194/esd-15-1591-2024, https://doi.org/10.5194/esd-15-1591-2024, 2024
Short summary
Short summary
The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.
Colleen L. Hoffman, Patrick J. Monreal, Justine B. Albers, Alastair J. M. Lough, Alyson E. Santoro, Travis Mellett, Kristen N. Buck, Alessandro Tagliabue, Maeve C. Lohan, Joseph A. Resing, and Randelle M. Bundy
Biogeosciences, 21, 5233–5246, https://doi.org/10.5194/bg-21-5233-2024, https://doi.org/10.5194/bg-21-5233-2024, 2024
Short summary
Short summary
Hydrothermally derived iron can be transported kilometers away from deep-sea vents, representing a significant flux of vital micronutrients to the ocean. However, the mechanisms that support the stabilization of dissolved iron remain elusive. Using electrochemical, spectrometry, and genomic methods, we demonstrated that strong ligands exert an important control on iron in plumes, and high-affinity iron-binding siderophores were identified in several hydrothermal plume samples for the first time.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Timothée Bourgeois, Olivier Torres, Friederike Fröb, Aurich Jeltsch-Thömmes, Giang T. Tran, Jörg Schwinger, Thomas L. Frölicher, Jean Negrel, David Keller, Andreas Oschlies, Laurent Bopp, and Fortunat Joos
EGUsphere, https://doi.org/10.5194/egusphere-2024-2768, https://doi.org/10.5194/egusphere-2024-2768, 2024
Short summary
Short summary
Anthropogenic greenhouse gas emissions significantly impact ocean ecosystems through climate change and acidification, leading to either progressive or abrupt changes. This study maps the crossing of physical and ecological limits for various ocean impact metrics under three emission scenarios. Using Earth system models, we identify when these limits are exceeded, highlighting the urgent need for ambitious climate action to safeguard the world's oceans and ecosystems.
Nicolas Metzl, Claire Lo Monaco, Coraline Leseurre, Céline Ridame, Gilles Reverdin, Thi Tuyet Trang Chau, Frédéric Chevallier, and Marion Gehlen
Ocean Sci., 20, 725–758, https://doi.org/10.5194/os-20-725-2024, https://doi.org/10.5194/os-20-725-2024, 2024
Short summary
Short summary
In the southern Indian Ocean, south of the polar front, an observed increase of sea surface fCO2 and a decrease of pH over 1985–2021 are mainly driven by anthropogenic CO2 uptake, but in the last decade (2010–2020) fCO2 and pH were stable in summer, highlighting the competitive balance between anthropogenic CO2 and primary production. In the water column the increase of anthropogenic CO2 concentrations leads to migration of the aragonite saturation state from 600 m in 1985 up to 400 m in 2021.
Alban Planchat, Laurent Bopp, Lester Kwiatkowski, and Olivier Torres
Earth Syst. Dynam., 15, 565–588, https://doi.org/10.5194/esd-15-565-2024, https://doi.org/10.5194/esd-15-565-2024, 2024
Short summary
Short summary
Ocean acidification is likely to impact all stages of the ocean carbonate pump. We show divergent responses of CaCO3 export throughout this century in earth system models, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. While we confirm the limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification, we highlight a potentially abrupt shift in CaCO3 dissolution from deep to subsurface waters beyond 2100.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
Short summary
Short summary
Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Thi-Tuyet-Trang Chau, Marion Gehlen, Nicolas Metzl, and Frédéric Chevallier
Earth Syst. Sci. Data, 16, 121–160, https://doi.org/10.5194/essd-16-121-2024, https://doi.org/10.5194/essd-16-121-2024, 2024
Short summary
Short summary
CMEMS-LSCE leads as the first global observation-based reconstructions of six carbonate system variables for the years 1985–2021 at monthly and 0.25° resolutions. The high-resolution reconstructions outperform their 1° counterpart in reproducing horizontal and temporal gradients of observations over various oceanic regions to nearshore time series stations. New datasets can be exploited in numerous studies, including monitoring changes in ocean carbon uptake and ocean acidification.
Alizée Dale, Marion Gehlen, Douglas W. R. Wallace, Germain Bénard, Christian Éthé, and Elena Alekseenko
EGUsphere, https://doi.org/10.5194/egusphere-2023-2538, https://doi.org/10.5194/egusphere-2023-2538, 2023
Preprint archived
Short summary
Short summary
Diatom, which is at the base of a productive food chain that supports valuable fisheries, dominates the total primary production of the Labrador Sea (LS). The synthesis of biogenic silica frustules makes them peculiar among phytoplankton but also dependent on dissolved silicate (DSi). Regular oceanographic surveys show declining DSi concentrations since the mid-1990s. With a model-based approach, we show that weakening deep winter convection was the proximate cause of DSi decline in the LS.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
David T. Ho, Laurent Bopp, Jaime B. Palter, Matthew C. Long, Philip W. Boyd, Griet Neukermans, and Lennart T. Bach
State Planet, 2-oae2023, 12, https://doi.org/10.5194/sp-2-oae2023-12-2023, https://doi.org/10.5194/sp-2-oae2023-12-2023, 2023
Short summary
Short summary
Monitoring, reporting, and verification (MRV) refers to the multistep process to quantify the amount of carbon dioxide removed by a carbon dioxide removal (CDR) activity. Here, we make recommendations for MRV for Ocean Alkalinity Enhancement (OAE) research, arguing that it has an obligation for comprehensiveness, reproducibility, and transparency, as it may become the foundation for assessing large-scale deployment. Both observations and numerical simulations will be needed for MRV.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
Short summary
Short summary
For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Clément Haëck, Marina Lévy, Inès Mangolte, and Laurent Bopp
Biogeosciences, 20, 1741–1758, https://doi.org/10.5194/bg-20-1741-2023, https://doi.org/10.5194/bg-20-1741-2023, 2023
Short summary
Short summary
Phytoplankton vary in abundance in the ocean over large regions and with the seasons but also because of small-scale heterogeneities in surface temperature, called fronts. Here, using satellite imagery, we found that fronts enhance phytoplankton much more where it is already growing well, but despite large local increases the enhancement for the region is modest (5 %). We also found that blooms start 1 to 2 weeks earlier over fronts. These effects may have implications for ecosystems.
Sarah Berthet, Julien Jouanno, Roland Séférian, Marion Gehlen, and William Llovel
Earth Syst. Dynam., 14, 399–412, https://doi.org/10.5194/esd-14-399-2023, https://doi.org/10.5194/esd-14-399-2023, 2023
Short summary
Short summary
Phytoplankton absorbs the solar radiation entering the ocean surface and contributes to keeping the associated energy in surface waters. This natural effect is either not represented in the ocean component of climate models or its representation is simplified. An incomplete representation of this biophysical interaction affects the way climate models simulate ocean warming, which leads to uncertainties in projections of oceanic emissions of an important greenhouse gas (nitrous oxide).
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
Short summary
Short summary
Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Corentin Clerc, Laurent Bopp, Fabio Benedetti, Meike Vogt, and Olivier Aumont
Biogeosciences, 20, 869–895, https://doi.org/10.5194/bg-20-869-2023, https://doi.org/10.5194/bg-20-869-2023, 2023
Short summary
Short summary
Gelatinous zooplankton play a key role in the ocean carbon cycle. In particular, pelagic tunicates, which feed on a wide size range of prey, produce rapidly sinking detritus. Thus, they efficiently transfer carbon from the surface to the depths. Consequently, we added these organisms to a marine biogeochemical model (PISCES-v2) and evaluated their impact on the global carbon cycle. We found that they contribute significantly to carbon export and that this contribution increases with depth.
Alastair J. M. Lough, Alessandro Tagliabue, Clément Demasy, Joseph A. Resing, Travis Mellett, Neil J. Wyatt, and Maeve C. Lohan
Biogeosciences, 20, 405–420, https://doi.org/10.5194/bg-20-405-2023, https://doi.org/10.5194/bg-20-405-2023, 2023
Short summary
Short summary
Iron is a key nutrient for ocean primary productivity. Hydrothermal vents are a source of iron to the oceans, but the size of this source is poorly understood. This study examines the variability in iron inputs between hydrothermal vents in different geological settings. The vents studied release different amounts of Fe, resulting in plumes with similar dissolved iron concentrations but different particulate concentrations. This will help to refine modelling of iron-limited ocean productivity.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Laurent Bopp, Olivier Aumont, Lester Kwiatkowski, Corentin Clerc, Léonard Dupont, Christian Ethé, Thomas Gorgues, Roland Séférian, and Alessandro Tagliabue
Biogeosciences, 19, 4267–4285, https://doi.org/10.5194/bg-19-4267-2022, https://doi.org/10.5194/bg-19-4267-2022, 2022
Short summary
Short summary
The impact of anthropogenic climate change on the biological production of phytoplankton in the ocean is a cause for concern because its evolution could affect the response of marine ecosystems to climate change. Here, we identify biological N fixation and its response to future climate change as a key process in shaping the future evolution of marine phytoplankton production. Our results show that further study of how this nitrogen fixation responds to environmental change is essential.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
Short summary
Short summary
The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Rebecca Chmiel, Nathan Lanning, Allison Laubach, Jong-Mi Lee, Jessica Fitzsimmons, Mariko Hatta, William Jenkins, Phoebe Lam, Matthew McIlvin, Alessandro Tagliabue, and Mak Saito
Biogeosciences, 19, 2365–2395, https://doi.org/10.5194/bg-19-2365-2022, https://doi.org/10.5194/bg-19-2365-2022, 2022
Short summary
Short summary
Dissolved cobalt is present in trace amounts in seawater and is a necessary nutrient for marine microbes. On a transect from the Alaskan coast to Tahiti, we measured seawater concentrations of dissolved cobalt. Here, we describe several interesting features of the Pacific cobalt cycle including cobalt sources along the Alaskan coast and Hawaiian vents, deep-ocean particle formation, cobalt activity in low-oxygen regions, and how our samples compare to a global biogeochemical model’s predictions.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Nicolas Metzl, Claire Lo Monaco, Coraline Leseurre, Céline Ridame, Jonathan Fin, Claude Mignon, Marion Gehlen, and Thi Tuyet Trang Chau
Biogeosciences, 19, 1451–1468, https://doi.org/10.5194/bg-19-1451-2022, https://doi.org/10.5194/bg-19-1451-2022, 2022
Short summary
Short summary
During an oceanographic cruise conducted in January 2020 in the south-western Indian Ocean, we observed very low CO2 concentrations associated with a strong phytoplankton bloom that occurred south-east of Madagascar. This biological event led to a strong regional CO2 ocean sink not previously observed.
Martí Galí, Marcus Falls, Hervé Claustre, Olivier Aumont, and Raffaele Bernardello
Biogeosciences, 19, 1245–1275, https://doi.org/10.5194/bg-19-1245-2022, https://doi.org/10.5194/bg-19-1245-2022, 2022
Short summary
Short summary
Part of the organic matter produced by plankton in the upper ocean is exported to the deep ocean. This process, known as the biological carbon pump, is key for the regulation of atmospheric carbon dioxide and global climate. However, the dynamics of organic particles below the upper ocean layer are not well understood. Here we compared the measurements acquired by autonomous robots in the top 1000 m of the ocean to a numerical model, which can help improve future climate projections.
Thi Tuyet Trang Chau, Marion Gehlen, and Frédéric Chevallier
Biogeosciences, 19, 1087–1109, https://doi.org/10.5194/bg-19-1087-2022, https://doi.org/10.5194/bg-19-1087-2022, 2022
Short summary
Short summary
Air–sea CO2 fluxes and associated uncertainty over the open ocean to coastal shelves are estimated with a new ensemble-based reconstruction of pCO2 trained on observation-based data. The regional distribution and seasonality of CO2 sources and sinks are consistent with those suggested in previous studies as well as mechanisms discussed therein. The ensemble-based uncertainty field allows identifying critical regions where improvements in pCO2 and air–sea CO2 flux estimates should be a priority.
Amanda R. Fay, Luke Gregor, Peter Landschützer, Galen A. McKinley, Nicolas Gruber, Marion Gehlen, Yosuke Iida, Goulven G. Laruelle, Christian Rödenbeck, Alizée Roobaert, and Jiye Zeng
Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, https://doi.org/10.5194/essd-13-4693-2021, 2021
Short summary
Short summary
The movement of carbon dioxide from the atmosphere to the ocean is estimated using surface ocean carbon (pCO2) measurements and an equation including variables such as temperature and wind speed; the choices of these variables lead to uncertainties. We introduce the SeaFlux ensemble which provides carbon flux maps calculated in a consistent manner, thus reducing uncertainty by using common choices for wind speed and a set definition of "global" coverage.
Anna Denvil-Sommer, Marion Gehlen, and Mathieu Vrac
Ocean Sci., 17, 1011–1030, https://doi.org/10.5194/os-17-1011-2021, https://doi.org/10.5194/os-17-1011-2021, 2021
Short summary
Short summary
In this work we explored design options for a future Atlantic-scale observational network enabling the release of carbon system estimates by combining data streams from various platforms. We used outputs of a physical–biogeochemical global ocean model at sites of real-world observations to reconstruct surface ocean pCO2 by applying a non-linear feed-forward neural network. The results provide important information for future BGC-Argo deployment, i.e. important regions and the number of floats.
Damien Couespel, Marina Lévy, and Laurent Bopp
Biogeosciences, 18, 4321–4349, https://doi.org/10.5194/bg-18-4321-2021, https://doi.org/10.5194/bg-18-4321-2021, 2021
Short summary
Short summary
An alarming consequence of climate change is the oceanic primary production decline projected by Earth system models. These coarse-resolution models parameterize oceanic eddies. Here, idealized simulations of global warming with increasing resolution show that the decline in primary production in the eddy-resolved simulations is half as large as in the eddy-parameterized simulations. This stems from the high sensitivity of the subsurface nutrient transport to model resolution.
Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet
Geosci. Model Dev., 14, 4069–4086, https://doi.org/10.5194/gmd-14-4069-2021, https://doi.org/10.5194/gmd-14-4069-2021, 2021
Short summary
Short summary
The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
Short summary
Short summary
The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Randelle M. Bundy, Alessandro Tagliabue, Nicholas J. Hawco, Peter L. Morton, Benjamin S. Twining, Mariko Hatta, Abigail E. Noble, Mattias R. Cape, Seth G. John, Jay T. Cullen, and Mak A. Saito
Biogeosciences, 17, 4745–4767, https://doi.org/10.5194/bg-17-4745-2020, https://doi.org/10.5194/bg-17-4745-2020, 2020
Short summary
Short summary
Cobalt (Co) is an essential nutrient for ocean microbes and is scarce in most areas of the ocean. This study measured Co concentrations in the Arctic Ocean for the first time and found that Co levels are extremely high in the surface waters of the Canadian Arctic. Although the Co primarily originates from the shelf, the high concentrations persist throughout the central Arctic. Co in the Arctic appears to be increasing over time and might be a source of Co to the North Atlantic.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
Short summary
Short summary
Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, Victor Estella-Perez, Christian Ethé, Frédéric Fluteau, Marie-Alice Foujols, Guillaume Gastineau, Josefine Ghattas, Didier Hauglustaine, Frédéric Hourdin, Masa Kageyama, Myriam Khodri, Olivier Marti, Yann Meurdesoif, Juliette Mignot, Anta-Clarisse Sarr, Jérôme Servonnat, Didier Swingedouw, Sophie Szopa, and Delphine Tardif
Geosci. Model Dev., 13, 3011–3053, https://doi.org/10.5194/gmd-13-3011-2020, https://doi.org/10.5194/gmd-13-3011-2020, 2020
Short summary
Short summary
Our paper describes IPSL-CM5A2, an Earth system model that can be integrated for long (several thousands of years) climate simulations. We describe the technical aspects, assess the model computing performance and evaluate the strengths and weaknesses of the model, by comparing pre-industrial and historical runs to the previous-generation model simulations and to observations. We also present a Cretaceous simulation as a case study to show how the model simulates deep-time paleoclimates.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
Short summary
Short summary
We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
Vincent Echevin, Manon Gévaudan, Dante Espinoza-Morriberón, Jorge Tam, Olivier Aumont, Dimitri Gutierrez, and François Colas
Biogeosciences, 17, 3317–3341, https://doi.org/10.5194/bg-17-3317-2020, https://doi.org/10.5194/bg-17-3317-2020, 2020
Short summary
Short summary
The coasts of Peru encompass the richest fisheries in the entire ocean. It is therefore very important for this country to understand how the nearshore marine ecosystem may evolve under climate change. Fine-scale numerical models are very useful because they can represent precisely the evolution of key parameters such as temperature, water oxygenation, and plankton biomass. Here we study the evolution of the Peruvian marine ecosystem in the 21st century under the worst-case climate scenario.
Marie Laugié, Yannick Donnadieu, Jean-Baptiste Ladant, J. A. Mattias Green, Laurent Bopp, and François Raisson
Clim. Past, 16, 953–971, https://doi.org/10.5194/cp-16-953-2020, https://doi.org/10.5194/cp-16-953-2020, 2020
Short summary
Short summary
To quantify the impact of major climate forcings on the Cretaceous climate, we use Earth system modelling to progressively reconstruct the Cretaceous state by changing boundary conditions one by one. Between the preindustrial and the Cretaceous simulations, the model simulates a global warming of more than 11°C. The study confirms the primary control exerted by atmospheric CO2 on atmospheric temperatures. Palaeogeographic changes represent the second major contributor to the warming.
Marie-Hélène Radenac, Julien Jouanno, Christine Carine Tchamabi, Mesmin Awo, Bernard Bourlès, Sabine Arnault, and Olivier Aumont
Biogeosciences, 17, 529–545, https://doi.org/10.5194/bg-17-529-2020, https://doi.org/10.5194/bg-17-529-2020, 2020
Short summary
Short summary
Satellite data and a remarkable set of in situ measurements show a main bloom of microscopic seaweed, the phytoplankton, in summer and a secondary bloom in December in the central equatorial Atlantic. They are driven by a strong vertical supply of nitrate in May–July and a shorter and moderate supply in November. In between, transport of low-nitrate water from the west explains most nitrate losses in the sunlit layer. Horizontal eddy-induced processes also contribute to seasonal nitrate removal.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Judith Hauck, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Dorothee C. E. Bakker, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Peter Anthoni, Leticia Barbero, Ana Bastos, Vladislav Bastrikov, Meike Becker, Laurent Bopp, Erik Buitenhuis, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Kim I. Currie, Richard A. Feely, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Daniel S. Goll, Nicolas Gruber, Sören Gutekunst, Ian Harris, Vanessa Haverd, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Jed O. Kaplan, Etsushi Kato, Kees Klein Goldewijk, Jan Ivar Korsbakken, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Gregg Marland, Patrick C. McGuire, Joe R. Melton, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Craig Neill, Abdirahman M. Omar, Tsuneo Ono, Anna Peregon, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Roland Séférian, Jörg Schwinger, Naomi Smith, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Guido R. van der Werf, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 11, 1783–1838, https://doi.org/10.5194/essd-11-1783-2019, https://doi.org/10.5194/essd-11-1783-2019, 2019
Short summary
Short summary
The Global Carbon Budget 2019 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Renaud Person, Olivier Aumont, Gurvan Madec, Martin Vancoppenolle, Laurent Bopp, and Nacho Merino
Biogeosciences, 16, 3583–3603, https://doi.org/10.5194/bg-16-3583-2019, https://doi.org/10.5194/bg-16-3583-2019, 2019
Short summary
Short summary
The Antarctic Ice Sheet is considered a possibly important but largely overlooked source of iron (Fe). Here we explore its fertilization capacity by evaluating the response of marine biogeochemistry to Fe release from icebergs and ice shelves in a global ocean model. Large regional impacts are simulated, leading to only modest primary production and carbon export increases at the scale of the Southern Ocean. Large uncertainties are due to low observational constraints on modeling choices.
Jens Terhaar, James C. Orr, Marion Gehlen, Christian Ethé, and Laurent Bopp
Biogeosciences, 16, 2343–2367, https://doi.org/10.5194/bg-16-2343-2019, https://doi.org/10.5194/bg-16-2343-2019, 2019
Short summary
Short summary
A budget of anthropogenic carbon in the Arctic Ocean, the main driver of open-ocean acidification, was constructed for the first time using a high-resolution ocean model. The budget reveals that anthropogenic carbon enters the Arctic Ocean mainly by lateral transport; the air–sea flux plays a minor role. Coarser-resolution versions of the same model, typical of earth system models, store less anthropogenic carbon in the Arctic Ocean and thus underestimate ocean acidification in the Arctic Ocean.
Anna Denvil-Sommer, Marion Gehlen, Mathieu Vrac, and Carlos Mejia
Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, https://doi.org/10.5194/gmd-12-2091-2019, 2019
Short summary
Short summary
This work is dedicated to a new model that reconstructs the surface ocean partial pressure of carbon dioxide (pCO2) over the global ocean on a monthly 1°×1° grid. The model is based on a feed-forward neural network and represents the nonlinear relationships between pCO2 and the ocean drivers. Reconstructed pCO2 has a satisfying accuracy compared to independent observational data and shows a good agreement in seasonal and interannual variability with three existing mapping methods.
Ludivine Conte, Sophie Szopa, Roland Séférian, and Laurent Bopp
Biogeosciences, 16, 881–902, https://doi.org/10.5194/bg-16-881-2019, https://doi.org/10.5194/bg-16-881-2019, 2019
Short summary
Short summary
The ocean is a source of atmospheric carbon monoxide, a key component for the oxidizing capacity of the atmosphere. We use a global ocean biogeochemistry model to dynamically assess the oceanic CO budget and its emission to the atmosphere at the global scale. The total emissions of CO to the atmosphere are 4.0 Tg C yr−1. The oceanic CO emission maps produced are relevant for use by atmospheric chemical models, especially to study the oxidizing capacity of the atmosphere above the remote ocean.
Camille Richon, Jean-Claude Dutay, Laurent Bopp, Briac Le Vu, James C. Orr, Samuel Somot, and François Dulac
Biogeosciences, 16, 135–165, https://doi.org/10.5194/bg-16-135-2019, https://doi.org/10.5194/bg-16-135-2019, 2019
Short summary
Short summary
We evaluate the effects of climate change and biogeochemical forcing evolution on the nutrient and plankton cycles of the Mediterranean Sea for the first time. We use a high-resolution coupled physical and biogeochemical model and perform 120-year transient simulations. The results indicate that changes in external nutrient fluxes and climate change may have synergistic or antagonistic effects on nutrient concentrations, depending on the region and the scenario.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Judith Hauck, Julia Pongratz, Penelope A. Pickers, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Almut Arneth, Vivek K. Arora, Leticia Barbero, Ana Bastos, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Scott C. Doney, Thanos Gkritzalis, Daniel S. Goll, Ian Harris, Vanessa Haverd, Forrest M. Hoffman, Mario Hoppema, Richard A. Houghton, George Hurtt, Tatiana Ilyina, Atul K. Jain, Truls Johannessen, Chris D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Peter Landschützer, Nathalie Lefèvre, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Craig Neill, Are Olsen, Tsueno Ono, Prabir Patra, Anna Peregon, Wouter Peters, Philippe Peylin, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Matthias Rocher, Christian Rödenbeck, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Tobias Steinhoff, Adrienne Sutton, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, Rebecca Wright, Sönke Zaehle, and Bo Zheng
Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, https://doi.org/10.5194/essd-10-2141-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2018 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Julien Palmiéri, Jean-Claude Dutay, Fabrizio D'Ortenzio, Loïc Houpert, Nicolas Mayot, and Laurent Bopp
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-423, https://doi.org/10.5194/bg-2018-423, 2018
Manuscript not accepted for further review
Short summary
Short summary
In this model study, we highlight the importance of the subsurface phytoplankton dynamic in the Mediterranean sea. Comparing surface chlorophyll annual cycle to vertically integrated one, we show how important the subsurface phytoplankton community is, throughout the Mediterranean. It shows that surface chlorophyll is incomplete and cannot alone be considered a good proxy of the total phytoplankton biomass. Then, we decrypt some deep chlorophyll maximum mechanisms in the low production area.
Virginie Racapé, Patricia Zunino, Herlé Mercier, Pascale Lherminier, Laurent Bopp, Fiz F. Pérèz, and Marion Gehlen
Biogeosciences, 15, 4661–4682, https://doi.org/10.5194/bg-15-4661-2018, https://doi.org/10.5194/bg-15-4661-2018, 2018
Short summary
Short summary
This study of a model–data comparison investigates the relationship between transport, air–sea flux and storage rate of Cant in the North Atlantic Subpolar Ocean over the past 53 years. It reveals the key role played by Central Water for storing Cant in the subtropical region and for supplying Cant into the deep ocean. The Cant transfer to the deep ocean occurred mainly north of the OVIDE section, and just a small fraction was exported to the subtropical gyre within the lower MOC.
Cyril Dutheil, Olivier Aumont, Thomas Gorguès, Anne Lorrain, Sophie Bonnet, Martine Rodier, Cécile Dupouy, Takuhei Shiozaki, and Christophe Menkes
Biogeosciences, 15, 4333–4352, https://doi.org/10.5194/bg-15-4333-2018, https://doi.org/10.5194/bg-15-4333-2018, 2018
Short summary
Short summary
N2 fixation is recognized as one of the major sources of nitrogen in the ocean. Thus, N2 fixation sustains a significant part of the primary production (PP) by supplying the most common limiting nutrient for phytoplankton growth. From numerical simulations, the local maximums of Trichodesmium biomass in the Pacific are found around islands, explained by the iron fluxes from island sediments. We assessed that 15 % of the PP may be due to Trichodesmium in the low-nutrient, low-chlorophyll areas.
Christoph Heinze, Tatiana Ilyina, and Marion Gehlen
Biogeosciences, 15, 3521–3539, https://doi.org/10.5194/bg-15-3521-2018, https://doi.org/10.5194/bg-15-3521-2018, 2018
Short summary
Short summary
The ocean becomes increasingly acidified through uptake of additional man-made CO2 from the atmosphere. This is impacting ecosystems. In order to find out whether reduced biological production of calcium carbonate shell material of biota is occurring at a large scale, we carried out a model study simulating the changes in oceanic 230Th concentrations with reduced availability of calcium carbonate particles in the water. 230Th can serve as a useful magnifying glass for acidification impacts.
Derek P. Tittensor, Tyler D. Eddy, Heike K. Lotze, Eric D. Galbraith, William Cheung, Manuel Barange, Julia L. Blanchard, Laurent Bopp, Andrea Bryndum-Buchholz, Matthias Büchner, Catherine Bulman, David A. Carozza, Villy Christensen, Marta Coll, John P. Dunne, Jose A. Fernandes, Elizabeth A. Fulton, Alistair J. Hobday, Veronika Huber, Simon Jennings, Miranda Jones, Patrick Lehodey, Jason S. Link, Steve Mackinson, Olivier Maury, Susa Niiranen, Ricardo Oliveros-Ramos, Tilla Roy, Jacob Schewe, Yunne-Jai Shin, Tiago Silva, Charles A. Stock, Jeroen Steenbeek, Philip J. Underwood, Jan Volkholz, James R. Watson, and Nicola D. Walker
Geosci. Model Dev., 11, 1421–1442, https://doi.org/10.5194/gmd-11-1421-2018, https://doi.org/10.5194/gmd-11-1421-2018, 2018
Short summary
Short summary
Model intercomparison studies in the climate and Earth sciences communities have been crucial for strengthening future projections. Given the speed and magnitude of anthropogenic change in the marine environment, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. We describe the Fisheries and Marine Ecosystem Model Intercomparison Project, which brings together the marine ecosystem modelling community to inform long-term projections of marine ecosystems.
Corinne Le Quéré, Robbie M. Andrew, Pierre Friedlingstein, Stephen Sitch, Julia Pongratz, Andrew C. Manning, Jan Ivar Korsbakken, Glen P. Peters, Josep G. Canadell, Robert B. Jackson, Thomas A. Boden, Pieter P. Tans, Oliver D. Andrews, Vivek K. Arora, Dorothee C. E. Bakker, Leticia Barbero, Meike Becker, Richard A. Betts, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Catherine E. Cosca, Jessica Cross, Kim Currie, Thomas Gasser, Ian Harris, Judith Hauck, Vanessa Haverd, Richard A. Houghton, Christopher W. Hunt, George Hurtt, Tatiana Ilyina, Atul K. Jain, Etsushi Kato, Markus Kautz, Ralph F. Keeling, Kees Klein Goldewijk, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Ivan Lima, Danica Lombardozzi, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Yukihiro Nojiri, X. Antonio Padin, Anna Peregon, Benjamin Pfeil, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Janet Reimer, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Hanqin Tian, Bronte Tilbrook, Francesco N. Tubiello, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Steven van Heuven, Nicolas Viovy, Nicolas Vuichard, Anthony P. Walker, Andrew J. Watson, Andrew J. Wiltshire, Sönke Zaehle, and Dan Zhu
Earth Syst. Sci. Data, 10, 405–448, https://doi.org/10.5194/essd-10-405-2018, https://doi.org/10.5194/essd-10-405-2018, 2018
Short summary
Short summary
The Global Carbon Budget 2017 describes data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. It is the 12th annual update and the 6th published in this journal.
Madhavan Girijakumari Keerthi, Matthieu Lengaigne, Marina Levy, Jerome Vialard, Vallivattathillam Parvathi, Clément de Boyer Montégut, Christian Ethé, Olivier Aumont, Iyyappan Suresh, Valiya Parambil Akhil, and Pillathu Moolayil Muraleedharan
Biogeosciences, 14, 3615–3632, https://doi.org/10.5194/bg-14-3615-2017, https://doi.org/10.5194/bg-14-3615-2017, 2017
Short summary
Short summary
The northern Arabian Sea hosts a winter chlorophyll bloom, which exhibits strong interannual variability. The processes responsible for this interannual variation of the bloom are investigated using observations and a model. The interannual fluctuations of the winter bloom are largely related to the interannual mixed-layer depth (MLD) anomalies, which are driven by net heat flux anomalies. MLD controls the bloom amplitude through a modulation of nutrient turbulent fluxes into the mixed layer.
Priscilla Le Mézo, Luc Beaufort, Laurent Bopp, Pascale Braconnot, and Masa Kageyama
Clim. Past, 13, 759–778, https://doi.org/10.5194/cp-13-759-2017, https://doi.org/10.5194/cp-13-759-2017, 2017
Short summary
Short summary
This paper focuses on the relationship between Arabian Sea biological productivity and the Indian summer monsoon in climates of the last 72 kyr. A general circulation model coupled to a biogeochemistry model simulates the changes in productivity and monsoon intensity and pattern. The paradigm stating that a stronger summer monsoon enhances productivity is not always verified in our simulations. This work highlights the importance of considering the monsoon pattern in addition to its intensity.
Guillaume Le Gland, Laurent Mémery, Olivier Aumont, and Laure Resplandy
Biogeosciences, 14, 3171–3189, https://doi.org/10.5194/bg-14-3171-2017, https://doi.org/10.5194/bg-14-3171-2017, 2017
Short summary
Short summary
In this study, we computed the fluxes of radium-228 from the continental shelf to the open ocean by fitting a numerical model to observations. After determining appropriate model parameters (cost function and number of source regions), we found a lower and more precise global flux than previous estimates: 8.01–8.49×1023 atoms yr−1. This result can be used to assess nutrient and trace element fluxes to the open ocean, but we cannot identify specific pathways like submarine groundwater discharge.
James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin, Keith Lindsay, Richard J. Matear, Galen A. McKinley, Anne Mouchet, Andreas Oschlies, Anastasia Romanou, Reiner Schlitzer, Alessandro Tagliabue, Toste Tanhua, and Andrew Yool
Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, https://doi.org/10.5194/gmd-10-2169-2017, 2017
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.
Olivier Aumont, Marco van Hulten, Matthieu Roy-Barman, Jean-Claude Dutay, Christian Éthé, and Marion Gehlen
Biogeosciences, 14, 2321–2341, https://doi.org/10.5194/bg-14-2321-2017, https://doi.org/10.5194/bg-14-2321-2017, 2017
Short summary
Short summary
The marine biological carbon pump is dominated by the vertical transfer of particulate organic carbon (POC) from the surface ocean to its interior. In this study, we explore the impacts of a variable composition of this organic matter using a global ocean biogeochemical model. We show that accounting for a variable lability of POC increases POC concentrations by up to 2 orders of magnitude in the ocean's interior. Furthermore, the amount of carbon that reaches the sediments is twice as large.
Parvathi Vallivattathillam, Suresh Iyyappan, Matthieu Lengaigne, Christian Ethé, Jérôme Vialard, Marina Levy, Neetu Suresh, Olivier Aumont, Laure Resplandy, Hema Naik, and Wajih Naqvi
Biogeosciences, 14, 1541–1559, https://doi.org/10.5194/bg-14-1541-2017, https://doi.org/10.5194/bg-14-1541-2017, 2017
Short summary
Short summary
During late boreal summer and fall, the west coast of India (WCI) experiences hypoxia, which turns into anoxia during some years. We analyze a coupled physical–biogeochemical simulation over the 1960–2012 period to investigate the physical processes influencing oxycline interannual variability off the WCI. We show that fall WCI oxycline fluctuations are strongly related to Indian Ocean Dipole (IOD), with positive IODs preventing anoxia, while negative IODs do not necessarily result in anoxia.
Marco van Hulten, Rob Middag, Jean-Claude Dutay, Hein de Baar, Matthieu Roy-Barman, Marion Gehlen, Alessandro Tagliabue, and Andreas Sterl
Biogeosciences, 14, 1123–1152, https://doi.org/10.5194/bg-14-1123-2017, https://doi.org/10.5194/bg-14-1123-2017, 2017
Short summary
Short summary
We ran a global ocean model to understand manganese (Mn), a biologically essential element. Our model shows that (i) in the deep ocean, dissolved [Mn] is mostly homogeneous ~0.10—0.15 nM. The model reproduces this with a threshold on MnO2 of 25 pM, suggesting a minimal particle concentration is needed before aggregation and removal become efficient.
(ii) The observed distinct hydrothermal signals are produced by assuming both a strong source and a strong removal of Mn near hydrothermal vents.
Thomas Gasser, Philippe Ciais, Olivier Boucher, Yann Quilcaille, Maxime Tortora, Laurent Bopp, and Didier Hauglustaine
Geosci. Model Dev., 10, 271–319, https://doi.org/10.5194/gmd-10-271-2017, https://doi.org/10.5194/gmd-10-271-2017, 2017
Short summary
Short summary
Simple models of the Earth system are useful, especially because of their high computing efficiency. This work describes the OSCAR model: a new simple Earth system model calibrated on state-of-the-art complex models. It will add to the pool of the few simple models currently used by the community, and it will therefore improve the robustness of future studies. Its source code is available upon request.
Pierre-Amaël Auger, Thomas Gorgues, Eric Machu, Olivier Aumont, and Patrice Brehmer
Biogeosciences, 13, 6419–6440, https://doi.org/10.5194/bg-13-6419-2016, https://doi.org/10.5194/bg-13-6419-2016, 2016
Short summary
Short summary
A box modeling approach reveals that horizontal currents drive the spatial distribution of phytoplankton biomass and primary production in the north-west African upwelling system. Alongshore (cross-shore) currents limit (enhance) cross-shore exchanges north (south) of Cape Blanc. Off Cape Blanc, a meridional convergence makes ambiguous the response of coastal nutrient upwelling to wind forcings, and high production is based upon nutrients and remineralized matter injected by horizontal currents.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
Short summary
Short summary
The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Ana Bastos, Philippe Ciais, Jonathan Barichivich, Laurent Bopp, Victor Brovkin, Thomas Gasser, Shushi Peng, Julia Pongratz, Nicolas Viovy, and Cathy M. Trudinger
Biogeosciences, 13, 4877–4897, https://doi.org/10.5194/bg-13-4877-2016, https://doi.org/10.5194/bg-13-4877-2016, 2016
Short summary
Short summary
The ice-core record shows a stabilisation of atmospheric CO2 in the 1940s, despite continued emissions from fossil fuel burning and land-use change (LUC). We use up-to-date reconstructions of the CO2 sources and sinks over the 20th century to evaluate whether these capture the CO2 plateau and to test the previously proposed hypothesis. Both strong terrestrial sink, possibly due to LUC not fully accounted for in the records, and enhanced oceanic uptake are necessary to explain this stall.
Chris D. Jones, Vivek Arora, Pierre Friedlingstein, Laurent Bopp, Victor Brovkin, John Dunne, Heather Graven, Forrest Hoffman, Tatiana Ilyina, Jasmin G. John, Martin Jung, Michio Kawamiya, Charlie Koven, Julia Pongratz, Thomas Raddatz, James T. Randerson, and Sönke Zaehle
Geosci. Model Dev., 9, 2853–2880, https://doi.org/10.5194/gmd-9-2853-2016, https://doi.org/10.5194/gmd-9-2853-2016, 2016
Short summary
Short summary
How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD Special Issue.
Timothée Bourgeois, James C. Orr, Laure Resplandy, Jens Terhaar, Christian Ethé, Marion Gehlen, and Laurent Bopp
Biogeosciences, 13, 4167–4185, https://doi.org/10.5194/bg-13-4167-2016, https://doi.org/10.5194/bg-13-4167-2016, 2016
Short summary
Short summary
The global coastal ocean took up 0.1 Pg C yr−1 of anthropogenic carbon during 1993–2012 based on new biogeochemical simulations with an eddying 3-D global model. That is about half of the most recent estimate, an extrapolation based on surface areas. It should not be confused with the continental shelf pump, perhaps 10 times larger, which includes natural as well as anthropogenic carbon. Coastal uptake of anthropogenic carbon is limited by its offshore transport.
Corinne Le Quéré, Erik T. Buitenhuis, Róisín Moriarty, Séverine Alvain, Olivier Aumont, Laurent Bopp, Sophie Chollet, Clare Enright, Daniel J. Franklin, Richard J. Geider, Sandy P. Harrison, Andrew G. Hirst, Stuart Larsen, Louis Legendre, Trevor Platt, I. Colin Prentice, Richard B. Rivkin, Sévrine Sailley, Shubha Sathyendranath, Nick Stephens, Meike Vogt, and Sergio M. Vallina
Biogeosciences, 13, 4111–4133, https://doi.org/10.5194/bg-13-4111-2016, https://doi.org/10.5194/bg-13-4111-2016, 2016
Short summary
Short summary
We present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types, and use the model to assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean. Our results suggest that observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community, despite iron limitation of phytoplankton growth.
Charlotte Laufkötter, Meike Vogt, Nicolas Gruber, Olivier Aumont, Laurent Bopp, Scott C. Doney, John P. Dunne, Judith Hauck, Jasmin G. John, Ivan D. Lima, Roland Seferian, and Christoph Völker
Biogeosciences, 13, 4023–4047, https://doi.org/10.5194/bg-13-4023-2016, https://doi.org/10.5194/bg-13-4023-2016, 2016
Short summary
Short summary
We compare future projections in marine export production, generated by four ecosystem models under IPCC's high-emission scenario RCP8.5. While all models project decreases in export, they differ strongly regarding the drivers. The formation of sinking particles of organic matter is the most uncertain process with models not agreeing on either magnitude or the direction of change. Changes in diatom concentration are a strong driver for export in some models but of low significance in others.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary
Short summary
This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
Elodie Gutknecht, Guillaume Reffray, Marion Gehlen, Iis Triyulianti, Dessy Berlianty, and Philippe Gaspar
Geosci. Model Dev., 9, 1523–1543, https://doi.org/10.5194/gmd-9-1523-2016, https://doi.org/10.5194/gmd-9-1523-2016, 2016
Short summary
Short summary
An operational ocean forecasting system was developed to monitor the state of the Indonesian seas in terms of circulation, biogeochemistry and fisheries (INDESO project). Here we describe the skill assessment of the physical-biogeochemical coupled model configuration. Model results reproduce the main characteristics of biogeochemical tracer distributions in space and time: phasing of chlorophyll bloom, nutrient and oxygen distributions, water mass transformation across the archipelago.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
Short summary
Short summary
This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
C. Laufkötter, M. Vogt, N. Gruber, M. Aita-Noguchi, O. Aumont, L. Bopp, E. Buitenhuis, S. C. Doney, J. Dunne, T. Hashioka, J. Hauck, T. Hirata, J. John, C. Le Quéré, I. D. Lima, H. Nakano, R. Seferian, I. Totterdell, M. Vichi, and C. Völker
Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, https://doi.org/10.5194/bg-12-6955-2015, 2015
Short summary
Short summary
We analyze changes in marine net primary production (NPP) and its drivers for the 21st century in 9 marine ecosystem models under the RCP8.5 scenario. NPP decreases in 5 models and increases in 1 model; 3 models show no significant trend. The main drivers include stronger nutrient limitation, but in many models warming-induced increases in phytoplankton growth outbalance the nutrient effect. Temperature-driven increases in grazing and other loss processes cause a net decrease in biomass and NPP.
C. Le Quéré, R. Moriarty, R. M. Andrew, J. G. Canadell, S. Sitch, J. I. Korsbakken, P. Friedlingstein, G. P. Peters, R. J. Andres, T. A. Boden, R. A. Houghton, J. I. House, R. F. Keeling, P. Tans, A. Arneth, D. C. E. Bakker, L. Barbero, L. Bopp, J. Chang, F. Chevallier, L. P. Chini, P. Ciais, M. Fader, R. A. Feely, T. Gkritzalis, I. Harris, J. Hauck, T. Ilyina, A. K. Jain, E. Kato, V. Kitidis, K. Klein Goldewijk, C. Koven, P. Landschützer, S. K. Lauvset, N. Lefèvre, A. Lenton, I. D. Lima, N. Metzl, F. Millero, D. R. Munro, A. Murata, J. E. M. S. Nabel, S. Nakaoka, Y. Nojiri, K. O'Brien, A. Olsen, T. Ono, F. F. Pérez, B. Pfeil, D. Pierrot, B. Poulter, G. Rehder, C. Rödenbeck, S. Saito, U. Schuster, J. Schwinger, R. Séférian, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, I. T. van der Laan-Luijkx, G. R. van der Werf, S. van Heuven, D. Vandemark, N. Viovy, A. Wiltshire, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, https://doi.org/10.5194/essd-7-349-2015, 2015
Short summary
Short summary
Accurate assessment of anthropogenic carbon dioxide emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to understand the global carbon cycle, support the development of climate policies, and project future climate change. We describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on a range of data and models and their interpretation by a broad scientific community.
J. Martinez-Rey, L. Bopp, M. Gehlen, A. Tagliabue, and N. Gruber
Biogeosciences, 12, 4133–4148, https://doi.org/10.5194/bg-12-4133-2015, https://doi.org/10.5194/bg-12-4133-2015, 2015
R. Wang, Y. Balkanski, O. Boucher, L. Bopp, A. Chappell, P. Ciais, D. Hauglustaine, J. Peñuelas, and S. Tao
Atmos. Chem. Phys., 15, 6247–6270, https://doi.org/10.5194/acp-15-6247-2015, https://doi.org/10.5194/acp-15-6247-2015, 2015
Short summary
Short summary
This study makes a first attempt to estimate the temporal trend of Fe emissions from anthropogenic and natural combustion sources from 1960 to 2007 and the emissions of Fe from mineral dust based on a recent mineralogical database. The new emission inventory is introduced into a global aerosol model. The simulated total Fe and soluble Fe concentrations in surface air as well as the deposition of total Fe are evaluated by observations over major continental and oceanic regions globally.
N. Bouttes, D. M. Roche, V. Mariotti, and L. Bopp
Geosci. Model Dev., 8, 1563–1576, https://doi.org/10.5194/gmd-8-1563-2015, https://doi.org/10.5194/gmd-8-1563-2015, 2015
Short summary
Short summary
We describe the development of a relatively simple climate model to include a model of the carbon cycle in the ocean. The carbon cycle consists of the exchange of carbon between the atmosphere, land vegetation and ocean. In the ocean, carbon exists in organic form, such as plankton which grows and dies, and inorganic forms, such as dissolved CO2. With this we will be able to explore long-standing questions such as why the atmospheric CO2 has changed over time during the last million years.
T. Roy, F. Lombard, L. Bopp, and M. Gehlen
Biogeosciences, 12, 2873–2889, https://doi.org/10.5194/bg-12-2873-2015, https://doi.org/10.5194/bg-12-2873-2015, 2015
C. Le Quéré, R. Moriarty, R. M. Andrew, G. P. Peters, P. Ciais, P. Friedlingstein, S. D. Jones, S. Sitch, P. Tans, A. Arneth, T. A. Boden, L. Bopp, Y. Bozec, J. G. Canadell, L. P. Chini, F. Chevallier, C. E. Cosca, I. Harris, M. Hoppema, R. A. Houghton, J. I. House, A. K. Jain, T. Johannessen, E. Kato, R. F. Keeling, V. Kitidis, K. Klein Goldewijk, C. Koven, C. S. Landa, P. Landschützer, A. Lenton, I. D. Lima, G. Marland, J. T. Mathis, N. Metzl, Y. Nojiri, A. Olsen, T. Ono, S. Peng, W. Peters, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. E. Salisbury, U. Schuster, J. Schwinger, R. Séférian, J. Segschneider, T. Steinhoff, B. D. Stocker, A. J. Sutton, T. Takahashi, B. Tilbrook, G. R. van der Werf, N. Viovy, Y.-P. Wang, R. Wanninkhof, A. Wiltshire, and N. Zeng
Earth Syst. Sci. Data, 7, 47–85, https://doi.org/10.5194/essd-7-47-2015, https://doi.org/10.5194/essd-7-47-2015, 2015
Short summary
Short summary
Carbon dioxide (CO2) emissions from human activities (burning fossil fuels and cement production, deforestation and other land-use change) are set to rise again in 2014.
This study (updated yearly) makes an accurate assessment of anthropogenic CO2 emissions and their redistribution between the atmosphere, ocean, and terrestrial biosphere in order to better understand the global carbon cycle, support the development of climate policies, and project future climate change.
T. Launois, S. Belviso, L. Bopp, C. G. Fichot, and P. Peylin
Atmos. Chem. Phys., 15, 2295–2312, https://doi.org/10.5194/acp-15-2295-2015, https://doi.org/10.5194/acp-15-2295-2015, 2015
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
C. D. Nevison, M. Manizza, R. F. Keeling, M. Kahru, L. Bopp, J. Dunne, J. Tiputra, T. Ilyina, and B. G. Mitchell
Biogeosciences, 12, 193–208, https://doi.org/10.5194/bg-12-193-2015, https://doi.org/10.5194/bg-12-193-2015, 2015
Short summary
Short summary
The observed seasonal cycles in atmospheric potential oxygen (APO) at five surface monitoring sites are compared to those inferred from the air-sea O2 fluxes of six ocean biogeochemistry models. The simulated air-sea fluxes are translated into APO seasonal cycles using a matrix method that takes into account atmospheric transport model (ATM) uncertainty among 13 different ATMs. Net primary production (NPP), estimated from satellite ocean color data, is also compared to model output.
M. Gehlen, R. Séférian, D. O. B. Jones, T. Roy, R. Roth, J. Barry, L. Bopp, S. C. Doney, J. P. Dunne, C. Heinze, F. Joos, J. C. Orr, L. Resplandy, J. Segschneider, and J. Tjiputra
Biogeosciences, 11, 6955–6967, https://doi.org/10.5194/bg-11-6955-2014, https://doi.org/10.5194/bg-11-6955-2014, 2014
Short summary
Short summary
This study evaluates potential impacts of pH reductions on North Atlantic deep-sea ecosystems in response to latest IPCC scenarios.Multi-model projections of pH changes over the seafloor are analysed with reference to a critical threshold based on palaeo-oceanographic studies, contemporary observations and model results. By 2100 under the most severe IPCC CO2 scenario, pH reductions occur over ~23% of deep-sea canyons and ~8% of seamounts – including seamounts proposed as marine protected areas.
K. B. Rodgers, O. Aumont, S. E. Mikaloff Fletcher, Y. Plancherel, L. Bopp, C. de Boyer Montégut, D. Iudicone, R. F. Keeling, G. Madec, and R. Wanninkhof
Biogeosciences, 11, 4077–4098, https://doi.org/10.5194/bg-11-4077-2014, https://doi.org/10.5194/bg-11-4077-2014, 2014
M. M. P. van Hulten, A. Sterl, R. Middag, H. J. W. de Baar, M. Gehlen, J.-C. Dutay, and A. Tagliabue
Biogeosciences, 11, 3757–3779, https://doi.org/10.5194/bg-11-3757-2014, https://doi.org/10.5194/bg-11-3757-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
C. Le Quéré, G. P. Peters, R. J. Andres, R. M. Andrew, T. A. Boden, P. Ciais, P. Friedlingstein, R. A. Houghton, G. Marland, R. Moriarty, S. Sitch, P. Tans, A. Arneth, A. Arvanitis, D. C. E. Bakker, L. Bopp, J. G. Canadell, L. P. Chini, S. C. Doney, A. Harper, I. Harris, J. I. House, A. K. Jain, S. D. Jones, E. Kato, R. F. Keeling, K. Klein Goldewijk, A. Körtzinger, C. Koven, N. Lefèvre, F. Maignan, A. Omar, T. Ono, G.-H. Park, B. Pfeil, B. Poulter, M. R. Raupach, P. Regnier, C. Rödenbeck, S. Saito, J. Schwinger, J. Segschneider, B. D. Stocker, T. Takahashi, B. Tilbrook, S. van Heuven, N. Viovy, R. Wanninkhof, A. Wiltshire, and S. Zaehle
Earth Syst. Sci. Data, 6, 235–263, https://doi.org/10.5194/essd-6-235-2014, https://doi.org/10.5194/essd-6-235-2014, 2014
I. Borrione, O. Aumont, M. C. Nielsdóttir, and R. Schlitzer
Biogeosciences, 11, 1981–2001, https://doi.org/10.5194/bg-11-1981-2014, https://doi.org/10.5194/bg-11-1981-2014, 2014
W. R. Joubert, S. Swart, A. Tagliabue, S. J. Thomalla, and P. M. S. Monteiro
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-4335-2014, https://doi.org/10.5194/bgd-11-4335-2014, 2014
Revised manuscript not accepted
M. Ishii, R. A. Feely, K. B. Rodgers, G.-H. Park, R. Wanninkhof, D. Sasano, H. Sugimoto, C. E. Cosca, S. Nakaoka, M. Telszewski, Y. Nojiri, S. E. Mikaloff Fletcher, Y. Niwa, P. K. Patra, V. Valsala, H. Nakano, I. Lima, S. C. Doney, E. T. Buitenhuis, O. Aumont, J. P. Dunne, A. Lenton, and T. Takahashi
Biogeosciences, 11, 709–734, https://doi.org/10.5194/bg-11-709-2014, https://doi.org/10.5194/bg-11-709-2014, 2014
J. Holt, C. Schrum, H. Cannaby, U. Daewel, I. Allen, Y. Artioli, L. Bopp, M. Butenschon, B. A. Fach, J. Harle, D. Pushpadas, B. Salihoglu, and S. Wakelin
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-1909-2014, https://doi.org/10.5194/bgd-11-1909-2014, 2014
Revised manuscript not accepted
A. M. Foley, D. Dalmonech, A. D. Friend, F. Aires, A. T. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. R. Edwards, G. Feulner, P. Friedlingstein, S. P. Harrison, P. O. Hopcroft, C. D. Jones, J. Kolassa, J. G. Levine, I. C. Prentice, J. Pyle, N. Vázquez Riveiros, E. W. Wolff, and S. Zaehle
Biogeosciences, 10, 8305–8328, https://doi.org/10.5194/bg-10-8305-2013, https://doi.org/10.5194/bg-10-8305-2013, 2013
M. Vogt, T. Hashioka, M. R. Payne, E. T. Buitenhuis, C. Le Quéré, S. Alvain, M. N. Aita, L. Bopp, S. C. Doney, T. Hirata, I. Lima, S. Sailley, and Y. Yamanaka
Biogeosciences Discuss., https://doi.org/10.5194/bgd-10-17193-2013, https://doi.org/10.5194/bgd-10-17193-2013, 2013
Revised manuscript has not been submitted
T. Hashioka, M. Vogt, Y. Yamanaka, C. Le Quéré, E. T. Buitenhuis, M. N. Aita, S. Alvain, L. Bopp, T. Hirata, I. Lima, S. Sailley, and S. C. Doney
Biogeosciences, 10, 6833–6850, https://doi.org/10.5194/bg-10-6833-2013, https://doi.org/10.5194/bg-10-6833-2013, 2013
J. C. Currie, M. Lengaigne, J. Vialard, D. M. Kaplan, O. Aumont, S. W. A. Naqvi, and O. Maury
Biogeosciences, 10, 6677–6698, https://doi.org/10.5194/bg-10-6677-2013, https://doi.org/10.5194/bg-10-6677-2013, 2013
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
A. Schmittner, N. Gruber, A. C. Mix, R. M. Key, A. Tagliabue, and T. K. Westberry
Biogeosciences, 10, 5793–5816, https://doi.org/10.5194/bg-10-5793-2013, https://doi.org/10.5194/bg-10-5793-2013, 2013
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
C. Beaulieu, S. A. Henson, Jorge L. Sarmiento, J. P. Dunne, S. C. Doney, R. R. Rykaczewski, and L. Bopp
Biogeosciences, 10, 2711–2724, https://doi.org/10.5194/bg-10-2711-2013, https://doi.org/10.5194/bg-10-2711-2013, 2013
R. Séférian, L. Bopp, D. Swingedouw, and J. Servonnat
Earth Syst. Dynam., 4, 109–127, https://doi.org/10.5194/esd-4-109-2013, https://doi.org/10.5194/esd-4-109-2013, 2013
V. Cocco, F. Joos, M. Steinacher, T. L. Frölicher, L. Bopp, J. Dunne, M. Gehlen, C. Heinze, J. Orr, A. Oschlies, B. Schneider, J. Segschneider, and J. Tjiputra
Biogeosciences, 10, 1849–1868, https://doi.org/10.5194/bg-10-1849-2013, https://doi.org/10.5194/bg-10-1849-2013, 2013
V. Krumins, M. Gehlen, S. Arndt, P. Van Cappellen, and P. Regnier
Biogeosciences, 10, 371–398, https://doi.org/10.5194/bg-10-371-2013, https://doi.org/10.5194/bg-10-371-2013, 2013
Related subject area
Biogeosciences
Simulating the drought response of European tree species with the dynamic vegetation model LPJ-GUESS (v4.1, 97c552c5)
pyVPRM: a next-generation vegetation photosynthesis and respiration model for the post-MODIS era
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Development and assessment of the physical–biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
China Wildfire Emission Dataset (ChinaWED v1) for the period 2012–2022
Process-based modeling of solar-induced chlorophyll fluorescence with VISIT-SIF version 1.0
Implementing a process-based representation of soil water movement in a second-generation dynamic vegetation model: application to dryland ecosystems (LPJ-GUESS-RE v1.0)
Including the phosphorus cycle into the LPJ-GUESS dynamic global vegetation model (v4.1, r10994) – global patterns and temporal trends of N and P primary production limitation
A comprehensive land-surface vegetation model for multi-stream data assimilation, D&B v1.0
Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements
CROMES v1.0: A flexible CROp Model Emulator Suite for climate impact assessment
Spatially varying parameters improve carbon cycle modeling in the Amazon rainforest with ORCHIDEE r8849
The unicellular NUM v.0.91: a trait-based plankton model evaluated in two contrasting biogeographic provinces
FESOM2.1-REcoM3-MEDUSA2: an ocean–sea ice–biogeochemistry model coupled to a sediment model
Satellite-based modeling of wetland methane emissions on a global scale (SatWetCH4 1.0)
Representing high-latitude deep carbon in the pre-industrial state of the ORCHIDEE-MICT land surface model (r8704)
Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe
Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling
A trait-based model to describe plant community dynamics in managed grasslands (GrasslandTraitSim.jl v1.0.0)
An improved model for air–sea exchange of elemental mercury in MITgcm-ECCOv4-Hg: the role of surfactants and waves
BOATSv2: new ecological and economic features improve simulations of high seas catch and effort
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 1: Land module for simulating emissions from synthetic fertilizer use
Data-Informed Inversion Model (DIIM): a framework to retrieve marine optical constituents in the BOUSSOLE site using a three-stream irradiance model
Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
BIOPERIANT12: a mesoscale resolving coupled physics-biogeochemical model for the Southern Ocean
Learning from conceptual models – a study of the emergence of cooperation towards resource protection in a social–ecological system
TROLL 4.0: representing water and carbon fluxes, leaf phenology and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 1: Model description
The biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of the carbon cycle in central European beech forests
TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluation for two Amazonian sites
Sunburned plankton: Ultraviolet radiation inhibition of phytoplankton photosynthesis in the Community Earth System Model version 2
DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology
Impacts of land-use change on biospheric carbon: an oriented benchmark using the ORCHIDEE land surface model
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Assimilation of carbonyl sulfide (COS) fluxes within the adjoint-based data assimilation system – Nanjing University Carbon Assimilation System (NUCAS v1.0)
Quantifying the role of ozone-caused damage to vegetation in the Earth system: a new parameterization scheme for photosynthetic and stomatal responses
Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models
Exploring the potential of history matching for land surface model calibration
EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters
Using deep learning to integrate paleoclimate and global biogeochemistry over the Phanerozoic Eon
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
In silico calculation of soil pH by SCEPTER v1.0
Benjamin F. Meyer, João P. Darela-Filho, Konstantin Gregor, Allan Buras, Qiao-Lin Gu, Andreas Krause, Daijun Liu, Phillip Papastefanou, Sijeh Asuk, Thorsten E. E. Grams, Christian S. Zang, and Anja Rammig
Geosci. Model Dev., 18, 4643–4666, https://doi.org/10.5194/gmd-18-4643-2025, https://doi.org/10.5194/gmd-18-4643-2025, 2025
Short summary
Short summary
Climate change has increased the likelihood of drought events across Europe, potentially threatening the European forest carbon sink. Dynamic vegetation models with mechanistic plant hydraulic architecture are needed to model these developments. We evaluate the plant hydraulic architecture version of LPJ-GUESS and show its ability to capture species-specific evapotranspiration responses to drought and to reproduce flux observations of both gross primary production and evapotranspiration.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Carolina Natel, David Martín Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
Geosci. Model Dev., 18, 4317–4333, https://doi.org/10.5194/gmd-18-4317-2025, https://doi.org/10.5194/gmd-18-4317-2025, 2025
Short summary
Short summary
We developed fast machine learning models to predict forest regrowth and carbon dynamics under climate change. These models mimic the outputs of a complex vegetation model but run 95 % faster, enabling global analyses and supporting climate solutions in large modeling frameworks such as LandSyMM.
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025, https://doi.org/10.5194/gmd-18-4103-2025, 2025
Short summary
Short summary
This study integrates machine learning with a land surface model to improve wildfire predictions in North America. Traditional models struggle with accurately simulating burned areas due to simplified processes. By combining the predictive power of machine learning with a land model, our hybrid framework better captures fire dynamics. This approach enhances our understanding of wildfire behavior and aids in developing more effective climate and fire management strategies.
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
Geosci. Model Dev., 18, 3941–3964, https://doi.org/10.5194/gmd-18-3941-2025, https://doi.org/10.5194/gmd-18-3941-2025, 2025
Short summary
Short summary
Physical–biogeochemical ocean global models are required to analyze difficult oceanic environmental systems. To accurately understand the physical–biogeochemical processes at the regional scale, physical and biogeochemical models were coupled at a high resolution. The results successfully simulated the seasonal variations of chlorophyll and nutrients, particularly in the marginal seas, which were not captured by global models. The developed model is an important tool for studying physical–biogeochemical processes.
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025, https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Short summary
This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025, https://doi.org/10.5194/gmd-18-3241-2025, 2025
Short summary
Short summary
Developing scientific software and making sure it functions properly requires a significant effort. As we advance our understanding of natural systems, however, there is the need to develop yet more complex models and codes. In this work, we present a piece of software that facilitates this work, specifically with regard to reactive processes. Existing tried-and-true codes are made available via this new interface, freeing up resources to focus on the new aspects of the problems at hand.
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025, https://doi.org/10.5194/gmd-18-3131-2025, 2025
Short summary
Short summary
Nitrous oxide (N2O) is a powerful greenhouse gas mainly released from natural and agricultural soils. This study examines how global soil N2O emissions changed from 1961 to 2020 and identifies key factors driving these changes using an ecological model. The findings highlight croplands as the largest source, with factors like fertilizer use and climate change enhancing emissions. Rising CO2 levels, however, can partially mitigate N2O emissions through increased plant nitrogen uptake.
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025, https://doi.org/10.5194/gmd-18-2961-2025, 2025
Short summary
Short summary
Parameterization is key in modeling to reproduce observations well but is often done manually. This study presents a particle-swarm-optimizer-based toolbox for marine ecosystem models, compatible with the Framework for Aquatic Biogeochemical Models, thus enhancing its reusability. Applied to the Sylt ecosystem, the toolbox effectively (1) identified multiple parameter sets that matched observations well, providing different insights into ecosystem dynamics, and (2) optimized model complexity.
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025, https://doi.org/10.5194/gmd-18-2921-2025, 2025
Short summary
Short summary
We use an innovative approach to studying the Earth's water cycle by integrating advanced machine learning techniques with a traditional water cycle model. Our model is designed to learn from observational data, with a particular emphasis on understanding the influence of vegetation on water movement. By closely aligning with real-world observations, our model offers new possibilities for enhancing our understanding of the water cycle and its interactions with vegetation.
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025, https://doi.org/10.5194/gmd-18-2521-2025, 2025
Short summary
Short summary
Our research uses deep learning to predict organic carbon stocks in ocean sediments, which is crucial for understanding their role in the global carbon cycle. By analysing over 22 000 samples and various seafloor characteristics, our model gives more accurate results than traditional methods. We estimate that the top 10 cm of ocean sediments hold about 156 Pg of carbon. This work enhances carbon stock estimates and helps plan future sampling strategies to better understand oceanic carbon burial.
Zhengyang Lin, Ling Huang, Hanqin Tian, Anping Chen, and Xuhui Wang
Geosci. Model Dev., 18, 2509–2520, https://doi.org/10.5194/gmd-18-2509-2025, https://doi.org/10.5194/gmd-18-2509-2025, 2025
Short summary
Short summary
The China Wildfire Emission Dataset (ChinaWED v1) estimated wildfire emissions in China during 2012–2022 as 78.13 Tg CO2, 279.47 Gg CH4, and 6.26 Gg N2O annually. Agricultural fires dominated emissions, while forest and grassland emissions decreased. Seasonal peaks occurred in late spring, with hotspots in northeast, southwest, and east China. The model emphasizes the importance of using localized emission factors and high-resolution fire estimates for accurate assessments.
Tatsuya Miyauchi, Makoto Saito, Hibiki M. Noda, Akihiko Ito, Tomomichi Kato, and Tsuneo Matsunaga
Geosci. Model Dev., 18, 2329–2347, https://doi.org/10.5194/gmd-18-2329-2025, https://doi.org/10.5194/gmd-18-2329-2025, 2025
Short summary
Short summary
Solar-induced chlorophyll fluorescence (SIF) is an effective indicator for monitoring photosynthetic activity. This paper introduces VISIT-SIF, a biogeochemical model developed based on the Vegetation Integrative Simulator for Trace gases (VISIT) to represent satellite-observed SIF. Our simulations reproduced the global distribution and seasonal variations in observed SIF. VISIT-SIF helps to improve photosynthetic processes through a combination of biogeochemical modeling and observed SIF.
Wim Verbruggen, David Wårlind, Stéphanie Horion, Félicien Meunier, Hans Verbeeck, and Guy Schurgers
EGUsphere, https://doi.org/10.5194/egusphere-2025-1259, https://doi.org/10.5194/egusphere-2025-1259, 2025
Short summary
Short summary
We improved the representation of soil water movement in a state-of-the-art dynamic vegetation model. This is especially important for dry ecosystems, as they are often driven by changes in soil water availability. We showed that this update resulted in a generally better match with observations, and that the updated model is more sensitive to soil texture. This updated model will help scientists to better understand the future of dry ecosystems under climate change.
Mateus Dantas de Paula, Matthew Forrest, David Warlind, João Paulo Darela Filho, Katrin Fleischer, Anja Rammig, and Thomas Hickler
Geosci. Model Dev., 18, 2249–2274, https://doi.org/10.5194/gmd-18-2249-2025, https://doi.org/10.5194/gmd-18-2249-2025, 2025
Short summary
Short summary
Our study maps global nitrogen (N) and phosphorus (P) availability and how they changed from 1901 to 2018. We find that tropical regions are mostly P-limited, while temperate and boreal areas face N limitations. Over time, P limitation increased, especially in the tropics, while N limitation decreased. These shifts are key to understanding global plant growth and carbon storage, highlighting the importance of including P dynamics in ecosystem models.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
Short summary
Short summary
When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Luke Oberhagemann, Maik Billing, Werner von Bloh, Markus Drüke, Matthew Forrest, Simon P. K. Bowring, Jessica Hetzer, Jaime Ribalaygua Batalla, and Kirsten Thonicke
Geosci. Model Dev., 18, 2021–2050, https://doi.org/10.5194/gmd-18-2021-2025, https://doi.org/10.5194/gmd-18-2021-2025, 2025
Short summary
Short summary
Under climate change, the conditions necessary for wildfires to form are occurring more frequently in many parts of the world. To help predict how wildfires will change in future, global fire models are being developed. We analyze and further develop one such model, SPITFIRE. Our work identifies and corrects sources of substantial bias in the model that are important to the global fire modelling field. With this analysis and these developments, we help to provide a basis for future improvements.
Christian Folberth, Artem Baklanov, Nikolay Khabarov, Thomas Oberleitner, Juraj Balkovič, and Rastislav Skalský
EGUsphere, https://doi.org/10.5194/egusphere-2025-862, https://doi.org/10.5194/egusphere-2025-862, 2025
Short summary
Short summary
Global gridded crop models (GGCMs) are important tools in agricultural climate impact assessments but computationally costly. An emergent approach to derive crop productivity estimates similar to those from GGCMs are emulators that mimic the original model, but typically with considerable bias. Here we present a modelling package that trains emulators with very high accuracy and high computational gain, providing a basis for more comprehensive scenario assessments.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
Short summary
Short summary
This study enhances the accuracy of modeling the carbon dynamics of Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to refine global carbon cycle models.
Trine Frisbæk Hansen, Donald Eugene Canfield, Ken Haste Andersen, and Christian Jannik Bjerrum
Geosci. Model Dev., 18, 1895–1916, https://doi.org/10.5194/gmd-18-1895-2025, https://doi.org/10.5194/gmd-18-1895-2025, 2025
Short summary
Short summary
We describe and test the size-based Nutrient-Unicellular-Multicellular model, which defines unicellular plankton using a single set of parameters, on a eutrophic and oligotrophic ecosystem. The results demonstrate that both sites can be modeled with similar parameters and robust performance over a wide range of parameters. The study shows that the model is useful for non-experts and applicable for modeling ecosystems with limited data. It holds promise for evolutionary and deep-time climate models.
Ying Ye, Guy Munhoven, Peter Köhler, Martin Butzin, Judith Hauck, Özgür Gürses, and Christoph Völker
Geosci. Model Dev., 18, 977–1000, https://doi.org/10.5194/gmd-18-977-2025, https://doi.org/10.5194/gmd-18-977-2025, 2025
Short summary
Short summary
Many biogeochemistry models assume all material reaching the seafloor is remineralized and returned to solution, which is sufficient for studies on short-term climate change. Under long-term climate change, the carbon storage in sediments slows down carbon cycling and influences feedbacks in the atmosphere–ocean–sediment system. This paper describes the coupling of a sediment model to an ocean biogeochemistry model and presents results under the pre-industrial climate and under CO2 perturbation.
Juliette Bernard, Elodie Salmon, Marielle Saunois, Shushi Peng, Penélope Serrano-Ortiz, Antoine Berchet, Palingamoorthy Gnanamoorthy, Joachim Jansen, and Philippe Ciais
Geosci. Model Dev., 18, 863–883, https://doi.org/10.5194/gmd-18-863-2025, https://doi.org/10.5194/gmd-18-863-2025, 2025
Short summary
Short summary
Despite their importance, uncertainties remain in the evaluation of the drivers of temporal variability of methane emissions from wetlands on a global scale. Here, a simplified global model is developed, taking advantage of advances in remote-sensing data and in situ observations. The model reproduces the large spatial and temporal patterns of emissions, albeit with limitations in the tropics due to data scarcity. This model, while simple, can provide valuable insights into sensitivity analyses.
Yi Xi, Philippe Ciais, Dan Zhu, Chunjing Qiu, Yuan Zhang, Shushi Peng, Gustaf Hugelius, Simon P. K. Bowring, Daniel S. Goll, and Ying-Ping Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-206, https://doi.org/10.5194/gmd-2024-206, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
Including high-latitude deep carbon is critical for projecting future soil carbon emissions, yet it’s absent in most land surface models. Here we propose a new carbon accumulation protocol by integrating deep carbon from Yedoma deposits and representing the observed history of peat carbon formation in ORCHIDEE-MICT. Our results show an additional 157 PgC in present-day Yedoma deposits and a 1–5 m shallower peat depth, 43 % less passive soil carbon in peatlands against the convention protocol.
Christian Poppe Terán, Bibi S. Naz, Harry Vereecken, Roland Baatz, Rosie A. Fisher, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 18, 287–317, https://doi.org/10.5194/gmd-18-287-2025, https://doi.org/10.5194/gmd-18-287-2025, 2025
Short summary
Short summary
Carbon and water exchanges between the atmosphere and the land surface contribute to water resource availability and climate change mitigation. Land surface models, like the Community Land Model version 5 (CLM5), simulate these. This study finds that CLM5 and other data sets underestimate the magnitudes of and variability in carbon and water exchanges for the most abundant plant functional types compared to observations. It provides essential insights for further research into these processes.
Katherine A. Muller, Peishi Jiang, Glenn Hammond, Tasneem Ahmadullah, Hyun-Seob Song, Ravi Kukkadapu, Nicholas Ward, Madison Bowe, Rosalie K. Chu, Qian Zhao, Vanessa A. Garayburu-Caruso, Alan Roebuck, and Xingyuan Chen
Geosci. Model Dev., 17, 8955–8968, https://doi.org/10.5194/gmd-17-8955-2024, https://doi.org/10.5194/gmd-17-8955-2024, 2024
Short summary
Short summary
The new Lambda-PFLOTRAN workflow incorporates organic matter chemistry into reaction networks to simulate aerobic respiration and biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow in a Jupyter notebook interface that digests raw organic matter chemistry data via Fourier transform ion cyclotron resonance mass spectrometry, develops a representative reaction network, and completes a biogeochemical simulation with the open-source, parallel-reactive-flow, and transport code PFLOTRAN.
Felix Nößler, Thibault Moulin, Oksana Buzhdygan, Britta Tietjen, and Felix May
EGUsphere, https://doi.org/10.5194/egusphere-2024-3798, https://doi.org/10.5194/egusphere-2024-3798, 2024
Short summary
Short summary
To predict the response of grassland plant communities to management and climate change, we developed the computer model GrasslandTraitSim.jl. Unlike other models, it uses measurable plant traits such as height, leaf thinness, and root structure as inputs, rather than hard-to-measure species data. This allows realistic simulation of many species. The model tracks daily changes in above- and below-ground biomass, plant height, and soil water, linking plant community composition to biomass supply.
Ling Li, Peipei Wu, Peng Zhang, Shaojian Huang, and Yanxu Zhang
Geosci. Model Dev., 17, 8683–8695, https://doi.org/10.5194/gmd-17-8683-2024, https://doi.org/10.5194/gmd-17-8683-2024, 2024
Short summary
Short summary
In this study, we incorporate sea surfactants and wave-breaking processes into MITgcm-ECCOv4-Hg. The updated model shows increased fluxes in high-wind-speed and high-wave regions and vice versa, enhancing spatial heterogeneity. It shows that elemental mercury (Hg0) transfer velocity is more sensitive to wind speed. These findings may elucidate the discrepancies in previous estimations and offer insights into global Hg cycling.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev., 17, 8421–8454, https://doi.org/10.5194/gmd-17-8421-2024, https://doi.org/10.5194/gmd-17-8421-2024, 2024
Short summary
Short summary
The BiOeconomic mArine Trophic Size-spectrum (BOATSv2) model dynamically simulates global commercial fish populations and their coupling with fishing activity, as emerging from environmental and economic drivers. New features, including separate pelagic and demersal populations, iron limitation, and spatial variation of fishing costs and management, improve the accuracy of high seas fisheries. The updated model code is available to simulate both historical and future scenarios.
Jize Jiang, David S. Stevenson, and Mark A. Sutton
Geosci. Model Dev., 17, 8181–8222, https://doi.org/10.5194/gmd-17-8181-2024, https://doi.org/10.5194/gmd-17-8181-2024, 2024
Short summary
Short summary
A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from fertilizer use and also taking into account how the environment influences these NH3 emissions. It is estimated that about 17 % of applied N in fertilizers was lost due to NH3 emissions. Hot and dry conditions and regions with high-pH soils can expect higher NH3 emissions.
Carlos Enmanuel Soto López, Fabio Anselmi, Mirna Gharbi Dit Kacem, and Paolo Lazzari
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-174, https://doi.org/10.5194/gmd-2024-174, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Our goal was to use an analytical expression to estimate the density of optical constituents, allowing us to have an interpretable formulation consistent with the laws of physics. We focused on a probabilistic approach, optimizing the model and retrieving quantities with their respective uncertainty. Considering future application to Big Data, we also explored a Neural Network based method, retrieving computationally efficient estimates, maintaining consistency with the analytical expression.
Guillaume Marie, Jina Jeong, Hervé Jactel, Gunnar Petter, Maxime Cailleret, Matthew J. McGrath, Vladislav Bastrikov, Josefine Ghattas, Bertrand Guenet, Anne Sofie Lansø, Kim Naudts, Aude Valade, Chao Yue, and Sebastiaan Luyssaert
Geosci. Model Dev., 17, 8023–8047, https://doi.org/10.5194/gmd-17-8023-2024, https://doi.org/10.5194/gmd-17-8023-2024, 2024
Short summary
Short summary
This research looks at how climate change influences forests, and particularly how altered wind and insect activities could make forests emit instead of absorb carbon. We have updated a land surface model called ORCHIDEE to better examine the effect of bark beetles on forest health. Our findings suggest that sudden events, such as insect outbreaks, can dramatically affect carbon storage, offering crucial insights into tackling climate change.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
Short summary
Short summary
We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Nicolette Chang, Sarah-Anne Nicholson, Marcel du Plessis, Alice D. Lebehot, Thulwaneng Mashifane, Tumelo C. Moalusi, N. Precious Mongwe, and Pedro M. S. Monteiro
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-182, https://doi.org/10.5194/gmd-2024-182, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Mesoscale features (10's to 100's of km) in the Southern Ocean (SO) are crucial for global heat and carbon transport, but often unresolved in models due to high computational costs. To address this source of uncertainty, we use a regional, NEMO model of the SO at 8 km resolution with coupled ocean, ice, and biogeochemistry, BIOPERIANT12. This serves as an experimental platform to explore physical-biogeochemical interactions, model parameters/formulations, and configuring future models.
Saeed Harati-Asl, Liliana Perez, and Roberto Molowny-Horas
Geosci. Model Dev., 17, 7423–7443, https://doi.org/10.5194/gmd-17-7423-2024, https://doi.org/10.5194/gmd-17-7423-2024, 2024
Short summary
Short summary
Social–ecological systems are the subject of many sustainability problems. Because of the complexity of these systems, we must be careful when intervening in them; otherwise we may cause irreversible damage. Using computer models, we can gain insight about these complex systems without harming them. In this paper we describe how we connected an ecological model of forest insect infestation with a social model of cooperation and simulated an intervention measure to save a forest from infestation.
Isabelle Maréchaux, Fabian Jörg Fischer, Sylvain Schmitt, and Jérôme Chave
EGUsphere, https://doi.org/10.5194/egusphere-2024-3104, https://doi.org/10.5194/egusphere-2024-3104, 2024
Short summary
Short summary
We describe TROLL 4.0, a simulator of forest dynamics that represents trees in a virtual space at one-meter resolution. Tree birth, growth, death and the underlying physiological processes such as carbon assimilation, water transpiration and leaf phenology depend on plant traits that are measured in the field for many individuals and species. The model is thus capable of jointly simulating forest structure, diversity and ecosystem functioning, a major challenge in modelling vegetation dynamics.
Katarína Merganičová, Ján Merganič, Laura Dobor, Roland Hollós, Zoltán Barcza, Dóra Hidy, Zuzana Sitková, Pavel Pavlenda, Hrvoje Marjanovic, Daniel Kurjak, Michal Bošel'a, Doroteja Bitunjac, Maša Zorana Ostrogović Sever, Jiří Novák, Peter Fleischer, and Tomáš Hlásny
Geosci. Model Dev., 17, 7317–7346, https://doi.org/10.5194/gmd-17-7317-2024, https://doi.org/10.5194/gmd-17-7317-2024, 2024
Short summary
Short summary
We developed a multi-objective calibration approach leading to robust parameter values aiming to strike a balance between their local precision and broad applicability. Using the Biome-BGCMuSo model, we tested the calibrated parameter sets for simulating European beech forest dynamics across large environmental gradients. Leveraging data from 87 plots and five European countries, the results demonstrated reasonable local accuracy and plausible large-scale productivity responses.
Sylvain Schmitt, Fabian Fischer, James Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
EGUsphere, https://doi.org/10.5194/egusphere-2024-3106, https://doi.org/10.5194/egusphere-2024-3106, 2024
Short summary
Short summary
We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote-sensing products. The model realistically predicts the structure and composition, and the seasonality of carbon and water fluxes at both sites.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-94, https://doi.org/10.5194/gmd-2024-94, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We develop a new feature in the atmosphere and ocean components of the Community Earth System Model version 2. We have implemented ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation. The new feature will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Guohua Liu, Mirco Migliavacca, Christian Reimers, Basil Kraft, Markus Reichstein, Andrew D. Richardson, Lisa Wingate, Nicolas Delpierre, Hui Yang, and Alexander J. Winkler
Geosci. Model Dev., 17, 6683–6701, https://doi.org/10.5194/gmd-17-6683-2024, https://doi.org/10.5194/gmd-17-6683-2024, 2024
Short summary
Short summary
Our study employs long short-term memory (LSTM) networks to model canopy greenness and phenology, integrating meteorological memory effects. The LSTM model outperforms traditional methods, enhancing accuracy in predicting greenness dynamics and phenological transitions across plant functional types. Highlighting the importance of multi-variate meteorological memory effects, our research pioneers unlock the secrets of vegetation phenology responses to climate change with deep learning techniques.
Thi Lan Anh Dinh, Daniel Goll, Philippe Ciais, and Ronny Lauerwald
Geosci. Model Dev., 17, 6725–6744, https://doi.org/10.5194/gmd-17-6725-2024, https://doi.org/10.5194/gmd-17-6725-2024, 2024
Short summary
Short summary
The study assesses the performance of the dynamic global vegetation model (DGVM) ORCHIDEE in capturing the impact of land-use change on carbon stocks across Europe. Comparisons with observations reveal that the model accurately represents carbon fluxes and stocks. Despite the underestimations in certain land-use conversions, the model describes general trends in soil carbon response to land-use change, aligning with the site observations.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Short summary
Short summary
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Huajie Zhu, Mousong Wu, Fei Jiang, Michael Vossbeck, Thomas Kaminski, Xiuli Xing, Jun Wang, Weimin Ju, and Jing M. Chen
Geosci. Model Dev., 17, 6337–6363, https://doi.org/10.5194/gmd-17-6337-2024, https://doi.org/10.5194/gmd-17-6337-2024, 2024
Short summary
Short summary
In this work, we developed the Nanjing University Carbon Assimilation System (NUCAS v1.0). Data assimilation experiments were conducted to demonstrate the robustness and investigate the feasibility and applicability of NUCAS. The assimilation of ecosystem carbonyl sulfide (COS) fluxes improved the model performance in gross primary productivity, evapotranspiration, and sensible heat, showing that COS provides constraints on parameters relevant to carbon-, water-, and energy-related processes.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
Short summary
Short summary
A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven
Geosci. Model Dev., 17, 5961–5985, https://doi.org/10.5194/gmd-17-5961-2024, https://doi.org/10.5194/gmd-17-5961-2024, 2024
Short summary
Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems to the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.
Nina Raoult, Simon Beylat, James M. Salter, Frédéric Hourdin, Vladislav Bastrikov, Catherine Ottlé, and Philippe Peylin
Geosci. Model Dev., 17, 5779–5801, https://doi.org/10.5194/gmd-17-5779-2024, https://doi.org/10.5194/gmd-17-5779-2024, 2024
Short summary
Short summary
We use computer models to predict how the land surface will respond to climate change. However, these complex models do not always simulate what we observe in real life, limiting their effectiveness. To improve their accuracy, we use sophisticated statistical and computational techniques. We test a technique called history matching against more common approaches. This method adapts well to these models, helping us better understand how they work and therefore how to make them more realistic.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
Short summary
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Dongyu Zheng, Andrew S. Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev., 17, 5413–5429, https://doi.org/10.5194/gmd-17-5413-2024, https://doi.org/10.5194/gmd-17-5413-2024, 2024
Short summary
Short summary
This study uses a deep learning method to upscale the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model to more accurately predict climate shifts. The method may be critical in developing new fully continuous methods that are able to be applied over a moving continental surface in deep time with high resolution at reasonable computational expense.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
Geosci. Model Dev., 17, 5349–5367, https://doi.org/10.5194/gmd-17-5349-2024, https://doi.org/10.5194/gmd-17-5349-2024, 2024
Short summary
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, https://doi.org/10.5194/gmd-17-4643-2024, 2024
Short summary
Short summary
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
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.
Cited articles
Albert, A., Echevin, V., Lévy, M., and Aumont, O.: Impact of nearshore wind stress curl on coastal circulation and primary productivity in the Peru upwelling system, J. Geophys. Res., 115, C12033, https://doi.org/10.1029/2010JC006569, 2010.
Allen, J. I., Somerfield, P. J., and Gilbert, F. J.: Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models, J. Marine Syst., 64, 3–14, 2007.
Alvain, S., Moulin, C., Dandonneau, Y., and Bréon, F.-M.: Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery, Deep-Sea Res. Pt. I, 52, 1989–2004, 2005.
Anderson, T. R.: Plankton functional type modelling: running before we can walk?, J. Plankton Res., 27, 1073–1081, 2005.
Anderson, T. R.: Progress in marine ecosystem modelling and the "unreasonable effectiveness of mathematics", J. Marine Syst., 81, 4–11, 2010.
Anderson, T. R. and Williams, P. J. B.: A one dimensional model of dissolved organic carbon cycling in the water column incorporating combined biological-photochemical decomposition, Global Biogeochem. Cy., 13, 337–349, 1999.
Anderson, T. R., Hessen, D. O., Mitra, A., Mayor, D. J., and Yool, A.: Sensitivity of secondary production and export flux to choice of trophic transfer formulation in marine ecosystem models, J. Marine Syst., 125, 41–53, https://doi.org/10.1016/j.jmarsys.2012.09.008, 2013.
Antoine, D., André, J. M., and Morel, A.: Oceanic primary production 2. Estimation at global scale from satellite (coastal zone color scanner) chlorophyll, Global Biogeochem. Cy., 10, 57–69, 1996.
Archer, D. E.: An atlas of the distribution of calcium carbonate in sediments of the deep sea, Global Biogeochem. Cy., 10, 159–174, 1996.
Aristegui, J., Gasol, J. M., Duarte, C. M., and Herndl, G. J.: Microbial oceanography of the dark oceans's pelagic realm, Limnol. Oceanogr., 54, 1501–1529, 2009.
Armstrong, R. A.: Grazing limitation and nutrient limitation in marine ecosystems: steady-state solutions of an ecosystem model with multiple food chains, Limnol. Oceanogr., 39, 597–608, 1994.
Armstrong, R. A., Lee, C., Hedges, J. I., Honjo, S., and Wakeham, S. G.: A new, mechanistic model for organic carbon fluxes in the ocean based on the quantitative association of POC with ballast minarals, Deep-Sea Res. Pt. II, 49, 219–236, 2002.
Arsouze, T., Dutay, J.-C., Kageyama, M., Lacan, F., Alkama, R., Marti, O., and Jeandel, C.: A modeling sensitivity study of the influence of the Atlantic meridional overturning circulation on neodymium isotopic composition at the Last Glacial Maximum, Clim. Past, 4, 191–203, https://doi.org/10.5194/cp-4-191-2008, 2008.
Arsouze, T., Dutay, J.-C., Lacan, F., and Jeandel, C.: Reconstructing the Nd oceanic cycle using a coupled dynamical – biogeochemical model, Biogeosciences, 6, 2829–2846, https://doi.org/10.5194/bg-6-2829-2009, 2009.
Aumont, O.: Etude du cycle naturel du carbone dans un modèle 3D de l'océan mondial, PhD thesis, Univ. Paris VI, Paris, 1998.
Aumont, O. and Bopp, L.: Globalizing results from ocean in-situ iron fertilization studies, Global Biogeochem. Cy., 20, GB2017, https://doi.org/10.1029/2005GB002591, 2006.
Aumont, O., Belviso, S., and Monfray, P.: Dimethylsulfoniopropionate (DMSP) and dimethylsulfide (DMS) sea surface distributions simulated from a global 3-D ocean carbon cycle model, J. Geophys. Res., 107, 4.1–4.19, https://doi.org/10.1029/1999JC000111, 2002.
Aumont, O., Maier-Reimer, E., Blain, S., and Monfray, P.: An ecosystem model of the global ocean including Fe, Si, P co-limitation, Global Biogeochem. Cy., 17, 1060, https://doi.org/10.1029/2001GB001745, 2003.
Ayata, S. D., Lévy, M., Aumont, O., Sciandra, A., Sainte-Marie, J., Tagliabue, A., and Bernard, O.: Phytoplankton growth formulation in marine ecosystem models: should we take into account photo-acclimation and variable stoichiometry in oligotrophic areas?, J. Marine Syst., 125, 29–40, https://doi.org/10.1016/j.jmarsys.2012.12.010, 2013.
Bacastow, R. and Maier-Reimer, E.: Ocean-circulation model of the carbon cycle, Clim. Dynam., 4, 95–125, 1990.
Baines, S. B., Twining, B. S., Brzezinski, M. A., Nelson, D. M., and Fisher, N. S.: Causes and biogeochemical implications of regional differences in silicification of marine diatoms, Global Biogeochem. Cy., 24, GB4031, https://doi.org/10.1029/2010GB003856, 2010.
Balch, W. M., Drapeau, D. T., Bowler, B. C., and Booth, E.: Prediction of pelagic calcification rates using satellite-measurements, Deep-Sea Res. Pt. II, 54, 478–495, 2007.
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Tréguier, A.-M., le Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J., and Cuevas, B. D.: Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution, Ocean Dynam., 56, 543–567, https://doi.org/10.1007/s10236-006-0082-1, 2006.
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20, 1997.
Behrenfeld, M. J., Boss, E., Siegel, D. A., and Shea, D. M.: Carbon-based ocean productivity and phytoplankton physiology from space, Global Biogeochem. Cy., 19, GB1006, https://doi.org/10.1029/2004GB002299, 2005.
Bennett, S. A., Achterberg, E. P., Connelly, D. P., Statham, P. J., Fones, G. R., and German, C. R.: The distribution and stabilisation of dissolved Fe in deep-sea hydrothermal plumes, Earth Planet. Sc. Lett., 270, 157–167, 2008.
Berelson, W. M.: Particle settling rates increase with depth in the ocean, Deep-Sea Res. Pt. II, 49, 237–251, 2002.
Berelson, W. M., Balch, W. M., Najjar, R., Feely, R. A., Sabine, C., and Lee, K.: Relating estimates of CaCO3 production, export, and dissolution in the water column to measurements of CaCO3 rain into sediment traps and dissolution on the sea floor: a revised global carbonate budget, Global Biogeochem. Cy., 21, GB1024, https://doi.org/10.1029/2006GB002803, 2007.
Blain, S., Quéguiner, B., Armand, L., Belviso, S., Bombled, B., Bopp, L., Bowie, A., Brunet, C., Brussaard, C., Carlotti, F., Christaki, U., Corbière, A., Durand, I., Ebersbach, F., Fuda, J.-L., Garcia, N., Gerringa, L., Griffiths, B., Guigue, C., Guillerm, C., Jacquet, S., Jeandel, C., Laan, P., Lefèvre, D., Monaco, C. L., Malits, A., Mosseri, J., Obernosterer, I., Park, Y.-H., Picheral, M., Pondaven, P., Remenyi, T., Sandroni, V., Sarthou, G., Savoye, N., Scouarnec, L., Souhaut, M., Thuiller, D., Timmermans, K., Trull, T., Uitz, J., van Beek, P., Veldhuis, M., Vincent, D., Viollier, E., Vong, L., and Wagener, T.: Effect of natural iron fertilization on carbon sequestration in the Southern Ocean, Nature, 446, 1070–1074, 2007.
Bonnet, S. and Guieu, C.: Dissolution of atmospheric iron in seawater, Geophys. Res. Lett., 31, L03303, https://doi.org/10.1029/2003GL018423, 2004.
Bopp, L., Kohfeld, K. E., Quéré, C. L., and Aumont, O.: Dust impact on marine biota and atmospheric pCO2 during glacial periods, Paleoceanography, 18, 1046, https://doi.org/10.1029/2002PA000810, 2003.
Bopp, L., Aumont, O., Cadule, P., Alvain, S., and Gehlen, M.: Response of diatoms distribution to global warming and potential implications: a global model study, Geophys. Res. Lett., 32, L19606, https://doi.org/10.1029/2005GL023653, 2005.
Bopp, L., Aumont, O., Belviso, S., and Blain, S.: Modelling the effect of iron fertilization on dimethylsulphide emissions in the Southern Ocean, Deep-Sea Res. Pt. II, 55, 901–912, https://doi.org/10.1016/j.dsr2.2007.12.002, 2008.
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013.
Boyd, P. W. and Ellwood, M. J.: The biogeochemical cycle of iron in the ocean, Nat. Geosci., 3, 675–682, 2010.
Boyé, M., van den Berg, C. M. G., de Jong, J. T. M., Leach, H., Croot, P., and de Baar, H. J. W.: Organic complexation of iron in the Southern Ocean, Deep-Sea Res. Pt. I, 48, 1477–1497, 2001.
Boyé, M., Aldrich, A. P., van den Berg, C. M. G., de Jong, J. T. M., Veldhuis, M., and de Baar, H. J. W: Horizontal gradient of the chemical speciation of iron in surface waters of the northeast Atlantic Ocean, Mar. Chem., 80, 129–143, 2003.
Boyle, E. A. and Jenkins, W. J.: Hydrothermal iron in the deep western South Pacific, Geochim. Cosmochim. Ac., 72, A107, 2008.
Boyle, E. A., Bergquist, B. A., Kayser, R. A., and Mahowald, N.: Iron, manganese, and lead at Hwawaii Ocean Time-series station ALOHA: temporal variability and an intermediate water hydrothermal plume, Geochim. Cosmochim. Acta, 69, 933–952, 2005.
Brasseur, P., Gruber, N., Barciela, R., Brander, K., Doron, M., El Moussaoui, A., Hobday, A. J., Huret, M., Kremeur, A.-S., Lehodey, P., Matear, R., Moulin, C., Murtugudde, R., Senina, I., and Svendsen, E.: Integrating biogeochemistry and ecology into ocean data assimilation systems, Oceanography, 22, 206–215, 2009.
Brewin, R. J. W., Sathyendranath, S., Hirata, T., Lavender, S., Baraciela, R. M., and Hardman-Mountford, N.: A three-component model of phytoplankton size class for the Atlantic ocean, Ecol. Model., 221, 1472–1483, 2010.
Brewin, R. J. W., Hardman-Mountford, N., Lavender, S. J., Raitsos, D., Hirata, T., Uitz, J., Devred, E., Bricaud, A., Ciotti, A., and Gentili, B.: An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing, Remote Sens. Environ., 115, 325–339, 2011.
Bricaud, A., Babin, M., Morel, A., and Claustre, H.: Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: analysis and parameterization, J. Geophys. Res., 100, 13321–13332, 1995.
Bruland, K. W., Rue, E. L., Smith, G. J., and DiTullio, G. R.: Iron, macronutrients and diatom blooms in the Peru upwelling regime: brown and blue waters of Peru, Mar. Chem., 93, 81–103, 2005.
Brzezinski, M. A.: The Si : C : N ratio of marine diatoms: interspecific variability and the effect of some environmental variables, J. Phycol., 21, 347–357, 1985.
Buitenhuis, E. T. and Geider, R. J.: A model of phytoplankton acclimation to iron-light colimitation, Limnol. Oceanogr., 55, 714–724, 2010.
Buitenhuis, E., Le Quéré, C., Aumont, O., Bunker, A., Hirst, A., Ikeda, T., O'Brien, T., Pontkiovski, S., and Straile, D.: Biogeochemical fluxes through mesozooplankton, Global Biogeochem. Cy., 20, GB2003, https://doi.org/10.1029/2009GB003601, 2005.
Buitenhuis, E. T., Rivkin, R. B., Sailley, S., and Le Quéré, C.: Biogeochemical fluxes through microzooplankton, Global Biogeochem. Cy., 24, GB4015, https://doi.org/10.1029/2005GB002511, 2010.
Calbet, A.: Mesozooplankton grazing effect on primary production: a global comparative analysis in marine ecosystems, Limnol. Oceanogr., 46, 1824–1830, 2001.
Capone, D. G., Zehr, J. P., Paerl, H. W., Berman, B., and Carpenter, E. J.: Trichodesmium, a globally significant marine cyanobacterium, Science, 276, 1221–1229, 1997.
Carlson, C. A., Ducklow, H. W., and Michaels, A. F.: Annual flux of dissolved organic carbon from the euphotic zone in the northwestern Sargasso Sea, Nature, 371, 405–408, 1994.
Chen, M. and Wang, W.-X.: Bioavailability of natural colloidal-bound iron to marine phytoplankton: influences of colloidal size and aging, Limnol. Oceanogr., 46, 1956–1967, 2001.
Chen, M., Dei, R. C. H., Wang, W.-X., and Guo, L.: Marine diatom uptake of iron bound with natural colloids of different origins, Mar. Chem., 81, 177–189, 2003.
Chester, R.: Marine Geochemistry, Unwin Hyman, London, 698 pp., 1990.
Claquin, P., Martin-Jézéquel, V., Kromkamp, J. C., Veldhuis, M., and Kraay, G.: Uncoupling of silicon compared to carbon and nitrogen metabolism, and the role of the cell cycle, in continuous cultures of Thalassiosira Pseudonana (Bacillariophyceae), under light, nitrogen, and phosphorus control, J. Phycol., 38, 922–930, 2002.
Codispoti, L. A., Brandes, J. A., Christensen, J. P., Devol, A. H., Naqvi, S. W. A., Pearl, H. W., and Yoshinari, T.: The oceanic fixed nitrogen and nitrous oxide budgets: moving targets as we enter the anthropocene?, Sci. Mar., 65, 85–105, 2001.
Collos, Y., Vaquer, A., and Souchu, P.: Acclimation of nitrate uptake by phytoplankton to high substrate levels, J. Phycol., 41, 466–478, 1980.
Conkright, M. E., Locarnini, R. A., Garcia, H. E., O'Brien, T. D., Boyer, T. P., Stephens, C., and Antononov, J.: World Ocean Atlas 2001: Objective Analyses, Data Statistics and Figures, CD-ROM Documentation, Tech. rep., National Oceanographic Data Centre, Silver Spring, MD, USA, 2002.
Darchambeau, F. and Thys, I.: In situ filtration responses of Daphnia galeata to changes in food quality, J. Plankton Res., 27, 227–236, 2005.
de Baar, H. J. W. and de Jong, J. T. M.: Distributions, sources and sinks of iron in seawater, in: The Biogeochemistry of Iron in Seawater, edited by: Turner, D. and Hunter, K., John Wiley, Hoboken, NJ, 85–121, 2001.
de Boyer-Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Iudicone, D.: Mixed layer depth over the global ocean: an examination of profile data and a profile-based climatology, J. Geophys. Res., 109, C12003, https://doi.org/10.1029/2004JC002378, 2004.
Debreu, L., Marchesiello, P., Penven, P., and Cambon, G.: Two-way nesting in split-explicit ocean models: algorithms, implementation and validation, Ocean Model., 49–50, 1–21, 2011.
Decho, A. W.: Microbial exopolymer secretions in ocean environments: their role(s) in food web and marine processes, Oceanogr. Mar. Biol., 28, 73–153, 1990.
Deutsch, C., Sarmiento, J. L., SIgman, D. M., Gruber, N., and Dunne, J. P.: Spatial coupling of nitrogen inputs and losses in the ocean, Nature, 445, 163–167, https://doi.org/10.1038/nature05392, 2007.
Dierssen, H. M. and Smith, R. C.: Bio-optical properties and remote sensing ocean color algorithms for Antarctic Peninsula waters, J. Geophys. Res., 105, 26301–26312, https://doi.org/10.1029/1999JC000296, 2000.
Dilling, L. and Alldredge, A. L.: Fragmentation of marine snow by swimming macrozooplankton: a new process impacting carbon cycling in the sea, Deep-Sea Res. Pt. I, 47, 1227–1245, 2000.
Donald, K. M., Scanlan, D. J., Carr, N. G., Mann, N. H., and Joint, I.: Comparative phosphorus nutrition of the marine cyanobacterium Synechococus WH7803 and the marine diatom Thalassiosira Weissflogii, J. Plankton Res., 19, 1793–1814, 1997.
Doney, S. C.: Major challenges confronting marine biogeochemical modeling, Global Biogeochem. Cy., 13, 705–714, 1999.
Doney, S. C., Lima, I., Moore, J. K., Lindsay, K., Behrenfeld, M. J., Westberry, T. K., Mahowald, N., GLover, D. M., and Takahashi, T.: Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data, J. Marine Syst., 76, 95–112, 2009.
Doucette, G. J. and Harrison, P. J.: Aspects of iron and nitrogen nutrition in the red tide dinoflagellate Gymnodinium sanguineum, Mar. Biol., 110, 175–182, 1991.
Droop, M. R.: 25 years of algal growth kinetics, Bot. Mar., 26, 99–112, 1983.
Dufresne, J. L., Friedlingstein, P., Berthelot, M., Bopp, L., Ciais, P., Fairhead, L., LeTreut, H., and Monfray, P.: Effects of climate change due to CO2 increase on land and ocean carbon uptake, Geophys. Res. Lett., 29, 1405, https://doi.org/10.1029/2001GL013777, 2002.
Dunne, J. P., Sarmiento, J. L., and Gnanadesikan, A.: A synthesis of global particle export from the surface ocean and cycling through the ocean interior and on the seafloor, Global Biogeochem. Cy., 21, GB4006, https://doi.org/10.1029/2006GB002907, 2007.
Dutay, J.-C., Jean-Baptiste, P., Campin, J.-M., Ishida, A., Maier-Reimer, E., Matear, R. J., Mouchet, A., Totterdell, I. J., Yamanaka, Y., Rodgers, K., Madec, G., and Orr, J. C.: Evaluation of OCMIP-2 ocean models' deep circulation with mantle helium-3, J. Marine Syst., 48, 15–36, 2004.
Dutay, J.-C., Lacan, F., Roy-Barman, M., and Bopp, L.: Influence of particle size and type on 231Pa and 230Th simulation with a global coupled biogeochemical-ocean general circulation model: a first approach, Geochem. Geophys. Geosyst., 10, Q01011, https://doi.org/10.1029/2008GC002291, 2009.
Dutkiewicz, S., Follows, M. J., and Parekh, P.: Interactions of the iron and phosphorus cycles: a three-dimensional model study, Global Biogeochem. Cy., 19, GB1021, https://doi.org/10.1029/2004GB002342, 2005.
Dutz, J., Koski, M., and Jonasdóttir, S.: Copepod reproduction is unaffected by diatom aldehydes or lipid composition, Limnol. Oceanogr., 53, 225–235, https://doi.org/10.4319/lo.2008.53.1.0225, 2008.
Echevin, V., Aumont, O., Ledesma, J., and Flores, G.: The seasonal cycle of surface chlorophyll in the Peruvian upwelling system: a modelling study, Prog. Oceanogr., 79, 167–176, 2008.
Edwards, K. F., Thomas, M. K., Klausmeier, C. A., and Litchman, E.: Allometric scaling and taxonomic variation in nutrient utilization traits and maximum growth rate of phytoplankton, Limnol. Oceanogr., 57, 554–566, 2012.
Elrod, V. A., Berelson, W. M., Coale, K. H., and Johnson, K. S.: The flux of iron from continental shelf sediments: a missing source for global budgets, Geophys. Res. Lett., 31, L12307, https://doi.org/10.1029/2004GL020216, 2004.
Engel, A., Szlosek, J., Abramson, L., Liu, Z., and Lee, C.: Investigating the effect of ballasting by CaCO3 in Emiliania huxleyi: I. Formation, settling velocities and physical properties of aggregates, Deep-Sea Res. Pt. II, 56, 1396–1407, https://doi.org/10.1016/j.dsr2.2008.11.027, 2009.
Eppley, R. W.: Temperature and phytoplankton growth in the sea, Fish. Bull., 70, 1063–1085, 1972.
Eppley, R. W. and Peterson, B. J.: Particulate organic matter flux and planktonic new production in the deep ocean, Nature, 282, 677–680, 1979.
Eppley, R. W., Rogers, J. N., and McCarthy, J. J.: Half-saturation constants for uptake of nitrate and ammonium by marine phytoplankton, Limnol. Oceanogr., 14, 912–920, 1969.
Farley, K. A., Maier-Reimer, E., Schlosser, P., and Broecker, W. S.: Constraints on mantle 3He fluxes and deep-sea circulation from an oceanic general circulation model, J. Geophys. Res.-Sol. Eaarth, 100, 3829–3839, 1995.
Fasham, M. J. R., Ducklow, H. W., and McKelvie, S. M.: A nitrogen-based model of plankton dynamics in the oceanic mixed layer, J. Mar. Res., 48, 591–639, 1990.
Fernández I, C., Raimbault, P., Garcia, N., Rimmelin, P., and Caniaux, G.: An estimation of annual new production and carbon fluxes in the northeast Atlantic Ocean during 2001, J. Geophys. Res.-Oceans, 110, C07S13, https://doi.org/10.1029/2004JC002616, 2005.
Flynn, K. J.: Ecological modelling in a sea of variable stoichiometry: dysfunctionality and the legacy of Redfield and Monod, Prog. Oceanogr., 84, 52–65, https://doi.org/10.1016/j.pocean.2009.09.006, 2010.
Flynn, K. J. and Davidson, K.: Predator–prey interactions between Isochrysis galbana and Oxyrrhis marina, I I. Release of non-protein amines and faeces during predation of Isochrysis, J. Plankton Res., 15, 893–905, 1993.
Flynn, K. J. and Hipkin, C. R.: Interactions between iron, light, ammonium and nitrate: insights from the construction of a dynamic model of algal physiology, J. Phycol., 35, 1171–1190, 1999.
Flynn, K. J., Stoecker, D. K., Mitra, A., Raven, J. A., Glibert, P. M., Hansen, P. J., Granéli, E., and Burkholder, J. M.: Misuse of the phytoplankton–zooplankton dichotomy: the need to assign organisms as mixotrophs within plankton functional types, J. Plankton Res., 35, 3–11, https://doi.org/10.1093/plankt/fbs062, 2013.
Franck, V. M., Brzezinski, M. A., Coale, K. H., and Nelson, D. M.: Iron and silicic acid concentrations regulate Si uptake north and south of the Polar Frontal Zone in the Pacific Sector of the Southern Ocean, Deep-Sea Res. Pt. II, 47, 3315–3338, 2000.
Galloway, J. N., Dentener, F. J., Capone, D. G., Boyer, E. W., Howarth, R. W., Setzinger, S. P., Asner, G. P., Cleveland, C. C., Green, P. A., Holland, E. A., Karl, D. M., Michaels, A. F., and Porter, J. H.: Nitrogen cycles: past, present, future, Biogeochemistry, 70, 153–226, 2004.
Garcia, C. A. E., Garcia, V. M. T., and McClain, C. R.: Evaluation of SeaWiFS chlorophyll algorithms in the Southwestern Atlantic and Southern Oceans, Remote Sens. Environ., 95, 125–137, 2005.
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 4: Nutrients (Phosphate, Nitrate, Silicate), US Government Printing Office, Washington, DC, noaa atlas nesdis 71st Edn., 398 pp., 2010.
Gaspar, P., Gregoris, Y., and Lefevre, J. M.: A simple eddy kinetic energy model for simulations of the ocean vertical mixing: tests at station Papa and Long-Term Upper Ocean Study Site site, J. Geophys. Res., 95, 16179–16193, 1990.
Gehlen, M., Bopp, L., Emprin, N., Aumont, O., Heinze, C., and Ragueneau, O.: Reconciling surface ocean productivity, export fluxes and sediment composition in a global biogeochemical ocean model, Biogeosciences, 3, 521–537, https://doi.org/10.5194/bg-3-521-2006, 2006.
Gehlen, M., Gangstø, R., Schneider, B., Bopp, L., Aumont, O., and Ethe, C.: The fate of pelagic CaCO3 production in a high CO2 ocean: a model study, Biogeosciences, 4, 505–519, https://doi.org/10.5194/bg-4-505-2007, 2007.
Geider, R. J., MacIntyre, H. L., and Kana, T. M.: A dynamic model of photoadaptation in phytoplankton, Limnol. Oceanogr., 41, 1–15, 1996.
Geider, R. J., MacIntyre, H. L., and Kana, T. M.: A dynamic model of phytoplankton growth and acclimation: responses of the balanced growth and Chlorophyll a : carbon ratio to light, nutrient-limitation and temperature, Mar. Ecol.-Prog. Ser., 148, 187–200, 1997.
Gent, P. R. and McWilliams, J. C.: Isopycnal mixing in ocean circulation models, J. Phys. Oceanogr., 20, 150–155, 1990.
Gentleman, W., Leising, A., Frost, B., Strom, S., and Murray, J.: Functional responses for zooplankton feeding on multiple resources: a review of assumptions and biological dynamics, Deep-Sea Res. Pt. II, 50, 2847–2875, 2003.
Gilstad, M. and Sakshaug, E.: Growth rates of ten diatoms species from the Barents Seas at different irradiance and day lengths, Mar. Ecol.-Prog. Ser., 64, 169–173, 1990.
Geldhill, M. and Buck, K. N. : The organic complexation of iron in the marine environment: a review, Frontiers in Microbiology, 3, https://doi.org/10.3389/fmicb.2012.00069, 2012.
Gnanadesikan, A., Slater, R. J., Gruber, N., and Sarmiento, J. L.: Oceanic vertical exchange and new production: a comparison between models and observations, Deep-Sea Res. Pt. II, 49, 363–401, 2002.
Goldman, J. C. and Dennett, M. R.: Ammonium regeneration and carbon utilization by marine bacteria grown on mixed sbstrates, Mar. Biol., 109, 369–378, 1991.
Goose, H.: Modelling the large-scale behaviour of the coupled ocean-sea-ice system, PhD thesis, Université catholique de Louvain, Louvain-La-Neuve, Belgium, 231 pp., 1997.
Gorgues, T., Menkes, C., Aumont, O., Vialard, J., Dandonneau, Y., and Bopp, L.: Biogeochemical impact of tropical instability waves in the Equatorial Pacific, Geophys. Res. Lett., 32, L24615, https://doi.org/10.1029/2005GL024110, 2005.
Griffies, S. M., Biastoch, A., Böning, C., Bryan, F., Danabasoglu, G., Chassignet, E. P., England, M. H., Gerdes, R., Haak, H., Hallberg, R. W., Hazeleger, W., Jungclaus, J., Large, W. G., Madec, G., Pirani, A., Samuels, B. L., Scheinert, M., Gupta, A. S., Severijns, C. A., Tr\'guier, H. L. S. A.-M., Winton, M., Yeager, S., and Yin, J.: Coordinated Ocean-ice Reference Experiments (COREs), Ocean Model., 26, 1–46, 2009.
Gruber, N.: The dynamics of the marine nitrogen cycle and atmospheric CO2, in: Carbon Climate Interactions, edited by: Oguz, T. and Follows, M., Kluwer, Dordrecht, 97–148, 2004.
Hansard, S. P., Landing, W. M., Measures, C. I., and Voelker, B. M.: Dissolved iron(II) in the PacificOcean: measurements from the PO2 and P16N CLIVAR/CO2 repeat hydrography expeditions, Deep-Sea Res. Pt. I, 56, 1117–1129, 2009.
Harrison, P. J. and Morel, F. M. M.: Response of the marine diatom Thalassiosira weissflogii to iron stress, Limnol. Oceanogr., 31, 989–997, 1986.
Harvey, H. R., Tuttle, J. H., and Bell, J. T.: Kinetics of phytoplankton decay during simulated sedimentation: changes in biochemical composition and microbial activity under oxic and anoxic conditions, Geochim. Cosmochim. Acta, 59, 3367–3377, 1995.
Haygood, M. G., Holt, P. D., and Butler, A.: Aerobactin production by a planktonic marine Vibrio sp., Limnol. Oceanogr., 38, 1091–1097, 1993.
Heinze, C., Maier-Reimer, E., Winguth, A. M. E., and Archer, D.: A global oceanic sediment model for long-term climate studies, Global Biogeochem. Cy., 13, 221–250, 1999.
Hernández-León, S. and Ikeda, T.: A global assessment of mesozooplankton respiration in the ocean, J. Plankton Res., 27, 153–158, 2005.
Hirata, T., Aiken, J., Hardman-Mountford, N., Smyth, T. J., and Barlow, R.: An absorption model to determine phytoplankton size classes from satellite ocean colour, Remote Sens. Environ., 112, 3153–3159, 2008.
Hirata, T., Hardman-Mountford, N. J., Brewin, R. J. W., Aiken, J., Barlow, R., Suzuki, K., Isada, T., Howell, E., Hashioka, T., Noguchi-Aita, M., and Yamanaka, Y.: Synoptic relationships between surface Chlorophyll-a and diagnostic pigments specific to phytoplankton functional types, Biogeosciences, 8, 311–327, https://doi.org/10.5194/bg-8-311-2011, 2011.
Honeyman, B., Balistrieri, L., and Murray, J.: Oceanic trace metal scavenging and the importance of particule concentration, Deep-Sea Res. Pt. I, 35, 227–246, 1988.
Honjo, S.: Fluxes of particles to the interior of the open oceans, in: Particle Flux to the Ocean, edited by: Ittekkot, V., Schäfer, P., Honjo, S., and Depetris, P. J., Vol. 57 of SCOPE, Wiley, New York, 91–254, 1996.
Hood, R. R., Kohler, K. E., McCreary, J. P., and Smith, S. L.: A four-dimensional validation of a coupled physical-biological model of the Arabian Sea, Deep-Sea Res. Pt. II, 50, 2917–2945, 2003.
Hood, R. R., Laws, E. A., Armstrong, R. A., Bates, N. R., Brown, C. W., Carlson, C. A., Chai, F., Doney, S. C., Falkowski, P. G., Feely, R. A., Friedrichs, M. A. M., Landry, M. R., Keith Moore, J., Nelson, D. M., Richardson, T. L., Salihoglu, B., Schartau, M., Toole, D. A., and Wiggert, J. D.: Pelagic functional group modeling: progress, challenges and prospects, Deep-Sea Res. Pt. II, 53, 459–512, https://doi.org/10.1016/j.dsr2.2006.01.025, 2006.
Horrigan, S. G., Carlucci, A. F., and Williams, P. M.: Light inhibition of nitrification in sea-surface waters, J. Mar. Res., 39, 557–565, 1981.
Hunter, K. A. and Boyd, P. W.: Iron-binding ligands and their role in the ocean biogeochemistry of iron, Environ. Chem., 4, 221–232, 2007.
Hurtt, G. C. and Armstrong, R. A.: A pelagic ecosystem model calibrated with BATS data, Deep-Sea Res., 43, 653–683, 1996.
Hutchins, D. A. and Bruland, K. W.: Iron-limited diatom growth and Si : N uptake ratios in a coastal upwelling regime, Nature, 393, 561–564, 1998.
Ibisanmi, E., Sander, S. G., Boyd, P. W., Bowie, A. R., and Hunter, K. A.: Vertical distributions of iron-(III) complexing ligands in the Southern Ocean, Deep-Sea Res. Pt. II, 58, 2113–2125, 2011.
Jackson, G. A.: A model of the formation of marine algal flocs by physical coagulation processes, Deep-Sea Res., 37, 1197–1211, 1990.
Jansen, H. and Wolf-Gladrow, D. A.: Carbonate dissolution in copepod guts: a numerical model, Mar. Ecol.-Prog. Ser., 221, 199–207, 2001.
Jickells, T. D. and Spokes, L. J.: Atmospheric iron inputs to the oceans, in: The Biogeochemistry of Iron in Seawater, edited by: Turner, D. and Hunter, K., John Wiley, Hoboken, NJ, 85–121, 2001.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., laRoche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., and Torres, R.: Global iron connections between desert dust, ocean biogeochemistry, and climate, Nature, 308, 67–71, https://doi.org/10.1126/science.1105959, 2005.
Johnson, K. S., Gordon, R. M., and Coale, K. H.: What controls dissolved iron concentrations in the world ocean?, Mar. Chem., 57, 137–161, 1997.
Johnson, K. S., Chavez, F. P., and Friederich, G. E.: Continental-shelf sediment as a primary source of iron for coastal phytoplankton, Nature, 398, 697–700, 1999.
Kahru, M. and Mitchell, B. G.: Blending of ocean colour algorithms applied to the Southern Ocean, Remote Sens. Lett., 1, 119–124, 2010.
Kalnay, E. C., 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., Letmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR Reanalysis project, B. Am. Meteorol. Soc., 77, 437–471, 1996.
Kamatani, A., Riley, J. P., and Shirrow, G.: The dissolution of opaline silica of diatom tests in sea water, J. Oceanogr. Soc. Jpn., 36, 201–208, 1980.
Kawamiya, M.: Mechanism of offshore nutrient supply in the Western Arabian Sea, J. Mar. Res., 59, 675–696, 2001.
Key, R. M., Kozyr, A., Sabine, C. L., Lee, K., Wanninkhof, R., Bullister, J., Feely, R. A., Millero, F., Mordy, C., and Peng, T.-H.: A global ocean carbon climatology: results from GLODAP, Global Biogeochem. Cy., 18, GB4031, https://doi.org/10.1029/2004GB002247, 2004.
Klaas, C. and Archer, D. E.: Association of sinking organic matter with various types of mineral ballast in the deep sea: implications for the rain ratio, Global Biogeochem. Cy., 16, 1116, https://doi.org/10.1029/2001GB001765, 2002.
Koné, V., Aumont, O., Lévy, M., and Resplandy, L.: Physical and biogeochemical controls of the phytoplankton seasonal cycle in the Indian Ocean: a modeling study, Geophys. Monogr., 185, 147–166, 2009.
Korb, R. E., Whitehouse, M. J., and Ward, P.: SeaWiFS in the southern ocean: spatial and temporal variability in phytoplankton biomass around South Georgia, Deep-Sea Res. Pt. II, 51, 99–116, 2004.
Korb, R. E., Whitehouse, M. J., Atkinson, A., and Thorpe, S. E.: Magnitude and maintenance of the phytoplankton bloom at South Georgia: a naturally iron-replete environment, Mar. Ecol.-Prog. Ser., 368, 75–91, 2008.
Kortzinger, A., Hedges, J. I., and Quay, P. D.: Redfield ratios revisited: removing the biasing effect of anthropogenic CO2, Limnol. Oceanogr., 46, 964–970, 2001.
Kriest, I.: Different parameterizations of marine snow in a 1-D model and their influence on representation of marine snow, nitrogen budget and sedimentation, Deep-Sea Res. Pt. I, 49, 2133–2162, 2002.
Kriest, I. and Evans, G. T.: Representing phytoplankton aggregates in biogeochemical models, Deep-Sea Res. Pt. I, 46, 1841–1859, 1999.
Kriest, I. and Evans, G.: A vertically resolved model for phytoplankton aggregation, Proceedings of the Indian Academy of Science, Earth Planet. Sci., 109, 453–469, 2000.
Lam, P. J., Bishop, J. K. B., Henning, C. C., Marcus, M. A., Waychunas, G. A., and Fung, I. Y.: Wintertime phytoplankton bloom in the subarctic Pacific supported by continental margin iron, Global Biogeochem. Cy., 20, GB1006, https://doi.org/10.1029/2005GB002557, 2006.
Lancelot, C., de Montety, A., Goosse, H., Becquevort, S., Schoemann, V., Pasquer, B., and Vancoppenolle, M.: Spatial distribution of the iron supply to phytoplankton in the Southern Ocean: a model study, Biogeosciences, 6, 2861–2878, https://doi.org/10.5194/bg-6-2861-2009, 2009.
Lannuzel, D., Schoemann, V., de Jong, J. T. M., Tison, J., and Chou, L.: Distribution and biogeochemical behaviour of iron in the East Antarctic sea ice, Mar. Chem., 106, 18–32, 2007.
Lannuzel, D., Schoemann, V., de Jong, J. T. M., Chou, L., Delille, B., Becquevort, S., and Tison, J.-L.: Iron study during a time series in the western Weddell pack ice, Mar. Chem., 108, 85–95, 2008.
Lee, C., Peterson, M. L., Wakeman, S. G., Armstrong, R. A., Cochran, J. K., Miquel, J. M., Fowler, S. W., Hirschberg, D., Beck, A., and Xue, J.: Particulate organic matter and ballast fluxes measured using time-series and settling velocity sediment traps in the northwestern Mediterranean Sea, Deep-Sea Res. Pt. II, 56, 1420–1436, 2009.
Lee, C. M., Jones, B. H., Brink, K. H., and Fischer, A. S.: The upper-ocean response to monsoonal forcing in the Arabian Sea: seasonal and spatial variability, Deep-Sea Res. Pt. II, 47, 1177–1226, 2000.
Lee, K.: Global net community production estimated from the annual cycle of surface water total dissolved inorganic carbon, Limnol. Oceanogr., 46, 1287–1297, 2001.
Lee, K., Tong, L. T., Millero, F. J., Sabine, C. L., Dickson, A. G., Goyet, C., Park, G.-H., Wanninkhof, R., Feely, R. A., and Key, R. M.: Global relationships of total alkalinity with salinity and temperature in surface waters of the world's oceans, Geophys. Res. Lett., 33, L19605, https://doi.org/10.1029/2006GL027207, 2006.
Lengaigne, M., Madec, G., Menkes, C., and Alory, G.: Effect of isopycnal diffusion in the tropical Pacific Ocean, J. Geophys. Res., 108, 3345, https://doi.org/10.1029/2002JC001704, 2003.
Lengaigne, M., Menkes, C., Aumont, O., Gorgues, T., Bopp, L., André, J.-M., and Madec, G.: Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model, Clim. Dynam., 28, 503–516, https://doi.org/10.1007/s00382-006-0200-2, 2007.
Lévy, M., Klein, P., and Tréguier, A.-M.: Impact of sub-mesoscale physics on production and subduction of phytoplankton in an oligotrophic regime, J. Mar. Res., 59, 535–565, 2001.
Lévy, M., Lehahn, Y., André, J.-M., Mémery, L., Loisel, H., and Heifetz, E.: Production regimes in the northeast Atlantic: a study based on Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll and ocean general circulation model mixed layer depth, J. Geophys. Res.-Oceans, 110, C07S10, https://doi.org/10.1029/2004JC002771, 2005.
Lipschultz, F., Wofsy, S., Ward, B., Codispoti, L., Friederich, G., and Elkins, J.: Bacterial transformations of inorganic nitrogen in the oxygen-deficient waters of the eastern tropical South Pacific Ocean, Deep-Sea Res. Pt. I, 37, 1513–1541, 1990.
Litchman, E., Klausmeier, C. A., Schofield, O. M., and Falkowski, P. G.: The role of functional traits and trade-offs in structuring phytoplankton communities: scaling from cellular to ecosystem level, Ecol. Lett., 10, 1170–1181, https://doi.org/10.1111/j.1461-0248.2007.01117.x, 2007.
Liu, X. and Millero, F. J.: The solubility of iron in seawater, Mar. Chem., 77, 43–54, 2002.
Longhurst, A., Sathyendranath, S., Platt, T., and Caverhill, C.: An estimate of global primary production in the ocean from satellite radiometer data, J. Plankton Res., 17, 1245–1271, 1995.
Loucaides, S., Van Cappellen, P., Roubeix, V., Moriceau, B., and Ragueneau, O.: Controls on the recycling and preservation of biogenic silica from biomineralization to burial, Silicon, 4, 7–22, 2012.
Ludwig, W., Probst, J. L., and Kempe, S.: Predicting the oceanic input of organic carbon by continental erosion, Global Biogeochem. Cy., 10, 23–41, 1996.
Luo, C., Mahowald, N., Meskhidze, N., Chen, Y., Siefert, R., Baker, A., and Johansen, A.: Estimation of iron solubility from observations and a global aerosol model, J. Geophys. Res., 110, D23307, https://doi.org/10.1029/2005JD006059, 2005.
Mackey, D. J., O'Sullivan, J. E., and Watson, R. J.: Iron in the western Pacific: a riverine or hydrothermal source for iron in the equatorial undercurrent?, Deep-Sea Res. Pt. I, 49, 877–893, 2002.
Madec, G.: "NEMO Ocean Engine", Note du Pôle de Modélisation 27, Institut Pierre-Simon Laplace (IPSL), France, 2008.
Madec, G., Delecluse, P., Imbard, M., and Lévy, C.: OPA8.1 Ocean General Circulation Model Reference Manual, Notes du pôle de modélisation, IPSL, 1998.
Mahowald, N., Jickells, T. D., Baker, A. R., Artaxo, P., Benitez-Nelson, C. R., Bergametti, G., Bond, T. C., Chen, Y., Cohen, D. D., Herut, B., Kubilay, N., Losno, R., Luo, C., Maenhaut, W., McGee, K. A., Okin, G. S., Siefert, R. L., and Tsukuda, S.: Global distribution of atmospheric phosphorus sources, concentrations and deposition rates, and anthropogenic impacts, Global Biogeochem. Cy., 22, GB4026, https://doi.org/10.1029/2008GB003240, 2008.
Maier-Reimer, E., Mikolajewicz, U., and Hasselmann, K.: Mean circulation of the Hamburg LSG OGCM and its sensitivity to the thermohaline surface forcing, J. Phys. Oceanogr., 23, 731–757, 1993.
Martin, J. H., Knauer, G. A., Karl, D. M., and Broenkow, W. W.: VERTEX: carbon cycling in the northeast Pacific, Deep-Sea Res., 34, 267–285, 1987.
Martinez, J. S., Zhang, G. P., Holt, P. D., Jung, H.-T., Carrano, C. J., Haygood, M. G., and Butler, A.: Self-assembling amphiphilic siderophores from marine bacteria, Science, 287, 1245–1247, https://doi.org/10.1126/science.287.5456.1245, 2000.
Martin-Jézéquel, V., Hildebrand, M., and Brzezinski, M.: Silicon metabolism in diatoms: implications for growth, J. Phycol., 36, 1–20, 2000.
Martinez-Rey, J., Bopp, L., Gehlen, M., Tagliabue, A., and Gruber, N.: Projections of oceanic N2O emissions in the 21st century using the IPSL Earth system model, Biogeosciences, 12, 4133–4148, https://doi.org/10.5194/bg-12-4133-2015, 2015.
Masotti, I., Ruiz-Pino, D., and Le Bouteiller, A.: Photsynthetic characteristics of Trichodesmium in the southwest Pacific Ocean: importance and significance, Mar. Ecol.-Prog. Ser., 338, 47–59, 2007.
Maury, O., Faugeras, B., Shin, Y.-J., Poggiale, J.-C., Ben Ari, T., and Marsac, F.: Modeling environmental effects on the size-structured energy flow through marine ecosystems. Part 1: The model, Prog. Oceanogr., 74, 479–499, 2007.
Mayorga, E., Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H. W., Bowman, A. F., Fekete, B. M., Kroeze, C., and Van Drecht, G.: Global Nutrient Export from WaterSheds 2 (NEWS 2): model development and implementation, Journal of Environ. Modell. Softw., 25, 837–853, 2010.
McCarthy, J. J.: The kinetics of nutrient utilization, Can. B. Fish. Aquat. Sci., 210, 211–233, 1980.
McGillicuddy, O. J., Robinson, A. R., Siegel, D. A., Jannasch, H. W., Johnson, R., Dickey, T. D., McNell, H., Michaels, A. F., and Knap, A. H.: Influence of mesoscale eddies on new production in the Sargasso Sea, Nature, 394, 263–266, 1998.
Menkes, C., Boulanger, J.-P., Busalacchi, A. J., J. Vialard, J., Delecluse, P., McPhaden, M. J., Hackert, E., and Grima, N.: Impact of TAO vs. ERS wind stresses onto simulations of the tropical Pacific Ocean during the 1993–1998 period by the OPA OGCM, in: Climatic Impact of Scale Interactions for the Tropical Ocean-Atmosphere System, EuroClivar Workshop Report, 46–48, 1998.
Merico, A., Bruggeman, J., and Wirtz, K.: A trait-based approach for downscaling complexity in plankton ecosystem models, Ecol. Model., 220, 3001–3010, https://doi.org/10.1016/j.ecolmodel.2009.05.005, 2009.
Middelburg, J. J., Soetaert, K., Herman, P. M. J., and Heip, C.: Denitrification in marine sediments: a model study, Global Biogeochem. Cy., 10, 661–673, 1996.
Milliman, J. D., Troy, P. J., Balsch, W. M., Adams, A. K., Li, Y.-H., and Mackenzie, F. T.: Biologically mediated dissolution of calcium carbonate above the chemical lysocline?, Deep-Sea Res. Pt. I, 46, 1653–1669, 1999.
Mills, M. M., Ridame, C., Davey, M., La Roche, J., and Geider, R. J.: Iron and phosphorus co-limit nitrogen fixation in the eastern tropical North Atlantic, Nature, 429, 292–294, 2004.
Misumi, K., Tsumune, D., Yoshida, Y., Uchimoto, K., Nakamura, T., Nishioka, J., Mitsudera, H., Bryan, F. O., Lindsay, K., Moore, J. K., and Doney, S. C.: Mechanisms controlling dissolved iron distribution in the North Pacific: a model study, J. Geophys. Res., 116, G03005, https://doi.org/10.1029/2010JG001541, 2011.
Mitra, A. and Flynn, K. J.: Predator–prey interactions: is "ecological stoichiometry" sufficient when good food goes bad?, J. Plankton Res., 27, 393–399, 2005.
Mitra, A., Flynn, K. J., and Fasham, M. J. R.: Accounting for grazing dynamics in nitrogen-phytoplankton-zooplankton models, Limnol. Oceanogr., 52, 649–661, 2007.
Mitra, A., Castellani, C., Gentleman, W. C., Jónasdóttir, S. H., Flynn, K. J., Bode, A., Halsband, C., Kuhn, P., Licandro, P., Agersted, M. D., Cakbet, A., Lindeque, P. K., Koppelmann, R., Møller, E. F., Gislason, A., Nielsen, T. G., and St. John, M.: Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link, Prog. Oceanogr., 129, 176–199, 2014.
Monod, J.: Recherches sur la Croissance des Cultures Bactériennes, Hermann, Paris, 1942.
Moore, J. K. and Braucher, O.: Sedimentary and mineral dust sources of dissolved iron to the world ocean, Biogeosciences, 5, 631–656, https://doi.org/10.5194/bg-5-631-2008, 2008.
Moore, J. K., Doney, S. C., Glover, D. M., and Fung, I. Y.: Iron cycling and nutrient limitation patterns in surface waters of the world ocean, Deep-Sea Res. Pt. II, 49, 463–507, 2002a.
Moore, J. K., Doney, S. C., Kleypas, J. A., Glover, D. M., and Fung, I. Y.: An intermediate complexity marine ecosystem model for the global domain, Deep-Sea Res. Pt. II, 49, 403–462, 2002b.
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model, Global Biogeochem. Cy., 18, GB4028, https://doi.org/10.1029/2004GB002220, 2004.
Mooy, B. A. S. V., Keil, R. G., and Devol, A. H.: Impact of suboxia on sinking particulateorganic carbon: enhanced carbon flux and preferential degradation of amino acids via denitrification, Geochim. Cosmochim. Acta, 3, 457–465, 2002.
Morel, A.: Optical modeling of the upper ocean in relation to its biogenous matter content, J. Geophys. Res., 93, 709–722, 1988.
Morel, A. and Maritorena, S.: Bio-optical properties of oceanic waters: a reappraisal, J. Geophys. Res.-Oceans, 106, 7163–7180, https://doi.org/10.1029/2000JC000319, 2001.
Morel, F. M. M.: Kinetics of nutrient uptake and growth in phytoplankton, J. Phycol., 23, 137–150, 1987.
Moriceau, B., Goutx, M., Guigue, C., Lee, C., Armstrong, R. A., Duflos, M., Tamburini, C., Charrière, B., and Ragueneau, O.: Si-C interactions during degradation of the diatom Skeletonema marinoi, Deep-Sea Res. Pt. II, 56, 1381–1395, https://doi.org/10.1016/j.dsr2.2008.11.026, 2009.
Murnane, R. J., Sarmiento, J. L., and Le Quéré, C.: Spatial distribution of air-sea CO2 fluxes and the interhemispheric transport of carbon by the oceans, Global Biogeochem. Cy., 13, 287–305, 1999.
Nelson, D. M., Tréguer, P., Brzezinski, M. A., Leynaert, A., and Quéguigner, B.: Production and dissolution of biogenic silica in the ocean: revised global estimates, comparison with regional data and relationship to biogenic sedimentation, Global Biogeochem. Cy., 9, 359–372, 1995.
Nishioka, J. and Takeda, S.: Change in the concentrations of iron in different size-fractions during growth of the oceanic diatom Chaetoceros sp.: importance of small colloidal iron, Mar. Biol., 137, 231–238, 2000.
O'Neill, R. V., Angelis, D. L., Pastor, J. J., Jackson, B. J., and Post, W. M.: Multiple nutrient limitation in ecological models, Ecol. Model., 46, 147–163, 1989.
Orr, J. C.: On ocean carbon-cycle model comparison, Tellus B, 51, 509–510, 1999.
Orr, J. C., Fabry, V. J., Aumont, O., Bopp, L., Doney, S. C., Feely, R. A., Gnanadesikan, A., Gruber, N., Ishida, A., Joos, F., Key, R. M., Lindsay, K., Maier-Reimer, E., Matear, R., Monfray, P., Mouchet, A., Najjar, R. G., Plattner, G.-K., Rodgers, K. B., Sabine, C. L., Sarmiento, J. L., Schlitzer, R., Slater, R. D., Totterdell, I. J., Weirig, M.-F., Yamanaka, T., and Yool, A.: Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms, Nature, 437, 681–686, 2005.
Oschlies, A. and Garçon, V.: Eddy-induced enhancement of primary production in a model of the North Atlantic Ocean, Nature, 394, 266–269, 1998.
Parekh, P., Follows, M. J., and Boyle, E. A.: Decoupling of iron and phosphate in the global ocean, Global Biogeochem. Cy., 19, GB002280, https://doi.org/10.1029/2004GB002280, 2004.
Paulmier, A., Kriest, I., and Oschlies, A.: Stoichiometries of remineralisation and denitrification in global biogeochemical ocean models, Biogeosciences, 6, 923–935, https://doi.org/10.5194/bg-6-923-2009, 2009.
Penduff, T., Le Sommer, J., Barnier, B., Treguier, A.-M., Molines, J.-M., and Madec, G.: Influence of numerical schemes on current-topography interactions in 1/4° global ocean simulations, Ocean Sci., 3, 509–524, https://doi.org/10.5194/os-3-509-2007, 2007.
Penven, P., Debreu, L., Marchesiello, P., and McWilliams, J. C.: Evaluation and application of the ROMS 1-way embedding procedure to the central California upwelling system, Ocean Model., 12, 157–187, 2006.
Perry, M. J.: Phosphate utilization by an oceanic diatom in phosphorus-limited chemostat culture and in the oligotrophic waters of the central north Pacific, Limnol. Oceanogr., 21, 88–107, 1976.
Plath, K. and Boersma, M.: Mineral limitation of zooplankton: stoichiometric constraints and optimal foraging, Ecology, 82, 1260–1269, 2001.
Pollard, R., Sanders, R., Lucas, M., and Statham, P.: The Crozet Natural Iron Bloom and Export Experiment (CROZEX), Deep-Sea Res. Pt. II, 54, 1905–1914, 2007.
Pondaven, P., Fravalo, C., Ruiz-Pino, D., Tréguer, P., Quéguiner, B., and Jeandel, C.: Modelling the silica pump in the permanently open ocean zone of the Southern Ocean, J. Marine Syst., 17, 587–619, 1998.
Pullin, M. J. and Cabaniss, S. E.: The effects of pH, ionicx strength, and iron-fulvic acid interactions on the kinetics of non-photochemical iron transformations II: the kinetics of thermal reduction, Geochim. Cosmochim. Ac., 67, 4079–4089, 2003.
Quéré, C. L., Harrison, S. P., Prentice, I. C., Buitenhuis, E. T., Aumont, O., Bopp, L., Cotrim Da Cunha, L., Geider, R., Giraud, X., Klaas, C., Kohfeld, K. E., Legendre, L., Manizza, M., Platt, T., Rivkin, R. B., Sathyendranath, S., Watson, J. U. A. J., and Wolf-Gladrow, D.: Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models, Glob. Change Biol., 11, 2016–2040, 2005.
Raimbault, P., Rodier, M., and Taupier-Letage, I.: Size-fraction of phytoplankton in the Ligurian Sea and the Algerian Basin (Mediterranean Sea): size distribution versus total concentration, Marine Microbial Food Web, 3, 1–7, 1988.
Raiswell, R. and Anderson, T. F.: Reactive iron enrichment in sediments deposited beneath euxinic bottom waters: constraints on supply by shelf recycling, Geol. Soc. Spec. Publ., 248, 179–194, 2005.
Raynaud, S., Orr, J. C., Aumont, O., Rodgers, K. B., and Yiou, P.: Interannual-to-decadal variability of North Atlantic air-sea CO2 fluxes, Ocean Sci., 2, 43–60, https://doi.org/10.5194/os-2-43-2006, 2006.
Resplandy, L., Vialard, J., Lévy, M., Aumont, O., and Dandonneau, Y.: Seasonal and intraseasonal biogeochemical variability in the thermocline ridge of the southern tropical Indian Ocean, J. Geophys. Res., 114, C07024, https://doi.org/10.1029/2008JC005246, 2009.
Resplandy, L., Lévy, M., Bopp, L., Echevin, V., Pous, S., Sarma, V. V. S. S., and Kumar, D.: Controlling factors of the oxygen balance in the Arabian Sea's OMZ, Biogeosciences, 9, 5095–5109, https://doi.org/10.5194/bg-9-5095-2012, 2012.
Ridame, C. and Guieu, C.: Saharan input of phosphate to the oligotrophic water of the open western Mediterranean Sea, Limnol. Oceanogr., 47, 856–869, 2002.
Ridgwell, A. J., Watson, A. J., and Archer, D. E.: Modelling the response of the oceanic Si inventory to perturbations and consequences for atmospheric CO2, Global Biogeochem. Cy., 16, 1071, https://doi.org/10.1029/2002GB001877, 2002.
Rodgers, K. B., Aumont, O., Menkes, C., and Gorgues, T.: Decadal variations in equatorial Pacific ecosystems and ferrocline/pycnocline decoupling, Global Biogeochem. Cy., 22, GB2019, https://doi.org/10.1029/2006GB002919, 2008.
Rossow, W. B. and Schiffer, R. A.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2288, 1999.
Sabine, C. L., Feely, R. A., Gruber, N., Key, R. M., Lee, K., Bullister, J. L., Wanninkhof, R., Wong, C., Wallace, D. W., Tilbrook, B., Millero, F. J., Peng, T.-H., Kozyr, A., Ono, T., and Aida, F. R.: The oceanic sink for anthropogenic CO2, Science, 305, 367–371, 2004.
Sarthou, G., Timmermans, K., Blain, S., and Treguer, P.: Growth physiology and fate of diatoms in the ocean: a review, J. Sea Res., 53, 25–42, 2005.
Schlitzer, R.: Applying the adjoint method for biogeochemical modeling: export of particulate organic matter in the World Ocean, in: Inverse Methods in Biogeochemical Cycles, edited by: Kasibhata, P., Vol. 114 of AGU Monograph, American Geophysical Union, 107–124, 2000.
Sedwick, P. N. and Di Tullio, G. R.: Regulation of algal blooms in Antarctic shelf waters by the release of iron from melting sea ice, Geophys. Res. Lett., 24, 2515–2518, 1997.
Séférian, R., Bopp, L., Gehlen, M., Orr, J. C., Ethé, C., Cadule, P., Aumont, O., Mélia, D. S. y., Voldoire, A., and Madec, G.: Skill assessment of three earth system models with common marine biogeochemistry, Clim. Dynam., 40, 2549–2573, https://doi.org/10.1007/s00382-012-1362-8, 2013.
Severmann, S., MacManus, J., Berelson, W. M., and Hammond, D. E.: The continental shelf benthic iron flux and its isotope composition, Geochim. Cosmochim. Acta, 74, 3984–4004, 2010.
Six, K. D. and Maier-Reimer, E.: Effects of plankton dynamics on seasonal carbon fluxes in an ocean general circulation model, Global Biogeochem. Cy., 10, 559–583, 1996.
Smetacek, V.: Role of sinking in diatom life-history cycles: ecological, evolutionary and geological significance, Mar. Biol., 84, 239–251, 1985.
Smith, G. C., Haines, K., Kanzow, T., and Cunningham, S.: Impact of hydrographic data assimilation on the modelled Atlantic meridional overturning circulation, Ocean Sci., 6, 761–774, https://doi.org/10.5194/os-6-761-2010, 2010.
Smith, S. L., Yamanaka, Y., Pahlow, M., and Oschlies, A.: Optimal uptake kinetics: physiological acclimation explains the pattern of nitrate uptake by phytoplankton in the ocean, Mar. Ecol.-Prog. Ser., 384, 1–12, https://doi.org/10.3354/meps08022, 2009.
Smith, S. L., Pahlow, M., Merico, A., and Wirtz, K. W.: Optimality-based modeling of planktonic organisms, Limnol. Oceanogr., 56, 2080–2094, https://doi.org/10.4319/lo.2011.56.6.2080, 2011.
Smith, S. V. and Hollibaugh, J. T.: Coastal Metabolism and the oceanic organic carbon balance, Rev. Geophys., 31, 75–89, 1993.
Smith, W. O. S. and Nelson, D. M.: Phytoplankton bloom produced by a receding ice-edge in the Ross Sea: spatial coherence with the density field, Science, 227, 163–166, 1985.
Soetaert, K., Middelburg, J. J., Herman, P. M. J., and Buis, K.: On the coupling of benthic and pelagic biogeochemical models, Earth-Sci. Rev., 51, 173–201, 2000.
Sommer, U.: Nitrate and silicate competition among antarctic phytoplankton, Mar. Biol., 91, 345–351, 1986.
Steinacher, M., Joos, F., Frölicher, T. L., Bopp, L., Cadule, P., Cocco, V., Doney, S. C., Gehlen, M., Lindsay, K., Moore, J. K., Schneider, B., and Segschneider, J.: Projected 21st century decrease in marine productivity: a multi-model analysis, Biogeosciences, 7, 979–1005, https://doi.org/10.5194/bg-7-979-2010, 2010.
Stemmann, L., Jackson, G. A., and Gorsky, G.: A vertical model of particle size distributions and fluxes in the mid-water column that includes biological and physical processes-Part II Application to a three year survey in the NW Mediterranean Sea, Deep-Sea Res. Pt. I, 51, 885–908, 2004.
Stoecker, D. K.: Conceptual models of mixotrophy in planktonic protists and some ecological and evolutionary implications, Eur. J. Protistol., 34, 281–290, https://doi.org/10.1016/S0932-4739(98)80055-2, 1998.
Sunda, W. G. and Huntsman, S. A.: Iron uptake and growth limitation in oceanic and coastal phytoplankton, Mar. Chem., 50, 189–206, 1995.
Sunda, W. G. and Huntsman, S. A.: Interrelated influence of iron, light and cell size on marine phytoplankton growth, Nature, 390, 389–392, 1997.
Tagliabue, A. and Arrigo, K. R.: Processes governing the supply of iron to phytoplankton in stratified seas, J. Geophys. Res., 111, C06019, https://doi.org/10.1029/2005JC003363, 2006.
Tagliabue, A. and Völker, C.: Towards accounting for dissolved iron speciation in global ocean models, Biogeosciences, 8, 3025–3039, https://doi.org/10.5194/bg-8-3025-2011, 2011.
Tagliabue, A., Bopp, L., Aumont, O., and Arrigo, K.: Influence of light and temperature on the marine iron cycle: from theoretical to global modeling, Global Biogeochem. Cy., 23, C06019, https://doi.org/10.1029/2005JC003363, 2009a.
Tagliabue, A., Bopp, L., Roche, D. M., Bouttes, N., Dutay, J.-C., Alkama, R., Kageyama, M., Michel, E., and Paillard, D.: Quantifying the roles of ocean circulation and biogeochemistry in governing ocean carbon-13 and atmospheric carbon dioxide at the last glacial maximum, Clim. Past, 5, 695–706, https://doi.org/10.5194/cp-5-695-2009, 2009b.
Tagliabue, A., Bopp, L., Dutay, J.-C., Bowie, A. R., Chever, F., Jean-Baptiste, P., Bucciarelli, E., Lannuzel, D., Sarthou, G., Aumont, O., Gehlen, M., and Jeandel, C.: Hydrothermal contribution to the oceanic dissolved iron inventory, Nat. Geosci., 3, 252–256, https://doi.org/10.1038/ngeo818, 2010.
Tagliabue, A., Mtshali, T., Aumont, O., Bowie, A. R., Klunder, M. B., Roychoudhury, A. N., and Swart, S.: A global compilation of dissolved iron measurements: focus on distributions and processes in the Southern Ocean, Biogeosciences, 9, 2333–2349, https://doi.org/10.5194/bg-9-2333-2012, 2012.
Takahashi, T., Broecker, W. S., and Langer, S.: Redfield ratio based on chemical data from isopycnal surfaces, J. Geophys. Res., 90, 6907–6924, 1985.
Takeda, S.: Influence of iron availability on nutrient consumption ratio of diatoms in oceanic waters, Nature, 393, 774–777, 1998.
Taylor, K. E.: Summarizing multiple aspects of model performance in single diagram, J. Geophys. Res., 106, 7183–7193, 2001.
Taylor, S. R. and McLennan, S. M.: The Continental Crust: Its Composition and Evolution, Blackwell, Malden, Mass, 1985.
Thingstad, T. F. and Lignell, R.: Theoretical models for the control of bacterial growth rate, abundance diversity and carbon demand, Aquat. Microb. Ecol., 13, 19–27, 1997.
Thompson, P.: The response of growth and biogeochemical composition to variations in daylength, temperature and irradiance in the marine diatom Thalassiosira Pseudonana (Bacillariophyceae), J. Phycol., 35, 1215–1223, 1999.
Timmermann, R., Goose, H., Madec, G., Fichefet, T., Ethé, C., and Dulière, V.: On representation of high latitude processes in the ORCALIM global coupled sea ice-ocean model, Ocean Model., 8, 175–201, 2005.
Tirelli, V. and Mayzaud, P.: Relationship between functional response and gut transit time in the calanoid copepod Acartia clausi: role of food quantity and quality, J. Plankton Res., 27, 557–568, https://doi.org/10.1093/plankt/fbi031, 2005.
Toner, B. M., Fakra, S. C., Manganini, S. J., Santelli, C. M., Marcus, M. A., Moffett, J. W., Rouxel, O., German, C. R., and Edwards, K. J.: Preservation of iron(II) by organic-rich matrices in a hydrothermal plume, Nat. Geosci., 2, 197–201, https://doi.org/10.1038/ngeo433, 2009.
Tortell, P. D., Maldonado, M. T., and Price, N. M.: The role of heterotrophic bacteria in iron-limited ocean ecosystems, Nature, 383, 330–332, https://doi.org/10.1038/383330a0, 1996.
Tortell, P. D., Maldonado, M. T., Granger, J., and Price, N. M.: Marine bacteria and biogeochemical cycling of iron in the oceans, FEMS Microbiol. Ecol., 29, 1–11, 1999.
Tréguer, P., and De La Rocha, C. L.: The World Ocean Silica Cycle, Ann. Rev. Marine Sci., 5, 477–501, https://doi.org/10.1146/annurev-marine-121211-172346, 2012.
Trenberth, K. E., Olson, J. G., and Large, W. G.: A Global Ocean Wind Stress Climatology Based on the ECMWF Analyses, NCAR/TN-338+STR NCAR/TN-338+STR, National Center for Atmospheric Research, Boulder, USA, 1989.
Uitz, J., Claustre, H., Morel, A., and Hooker, S. B.: Vertical distribution of phytoplankton communities in open ocean, An assessment based on surface chlorophyll, J. Geophys. Res., 111, GB3016, https://doi.org/10.1029/2005JC003207, 2006.
Uitz, J., CLaustre, H., Gentili, B., and Stramski, D.: Phytoplankton class-specific primary production in the world's oceans: seasonal and interannual variability from satellite observations, Global Biogeochem. Cy., 24, GB3016, https://doi.org/10.1029/2009GB003680, 2010.
Van Capellen, P., Dixit, S., and Van Beusekom, J. E. E.: Biogenic silica dissolution in the oceans: reconciling experimental and field-based dissolution rates, Global Biogeochem. Cy., 16, 1075, https://doi.org/10.1029/2001GB001431, 2002.
Vichi, M. and Masina, S.: Skill assessment of the PELAGOS global ocean biogeochemistry model over the period 1980–2000, Biogeosciences, 6, 2333–2353, https://doi.org/10.5194/bg-6-2333-2009, 2009.
Wagener, T., Guieu, C., and Leblond, N.: Effects of dust deposition on iron cycle in the surface Mediterranean Sea: results from a mesocosm seeding experiment, Biogeosciences, 7, 3769–3781, https://doi.org/10.5194/bg-7-3769-2010, 2010.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean, J. Geophys. Res., 97, 7373–7382, 1992.
Wu, J. and Luther, G. W.: Complexation of Fe(III) by natural organic ligands in the Northwest Atlantic Ocean by a competitive ligand equilibration method and a kinetic approach, Mar. Chem., 50, 159–177, 1995.
Wu, J., Boyle, E., Sunda, W., and Wen, L. S.: Soluble and colloidal iron in the oligotrophic North Atlantic and North Pacific, Science, 293, 847–849, 2001.
Wu, K. and Boyle, E.: Iron in the Sargasso Sea: implications for the processes controlling dissolved Fe distribution in the ocean, Global Biogeochem. Cy., 16, GB1086, https://doi.org/10.1029/2001GB001453, 2002.
Xin, P. and Arkin, P. A.: Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimations, and numerical model inputs, B. Am. Meteorol. Soc., 78, 2539–2558, 1997.
Ye, Y., Völker, C., and Wolf-Gladrow, D. A.: A model of Fe speciation and biogeochemistry at the Tropical Eastern North Atlantic Time-Series Observatory site, Biogeosciences, 6, 2041–2061, https://doi.org/10.5194/bg-6-2041-2009, 2009.
Ye, Y., Wagener, T., Völker, C., Guieu, C., and Wolf-Gladrow, D. A.: Dust deposition: iron source or sink? a case study, Biogeosciences, 8, 2107–2124, https://doi.org/10.5194/bg-8-2107-2011, 2011.
Yool, A., Popova, E. E., and Anderson, T. R.: Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain, Geosci. Model Dev., 4, 381–417, https://doi.org/10.5194/gmd-4-381-2011, 2011.
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies, Geosci. Model Dev., 6, 1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, 2013.
Yoshioka, Y. and Saijo, Y.: Photoinhibition and recovery of NH4+-oxidizing bacteria and NO2-oxidinzing bacteria, J. Gen. Appl. Microbiol., 30, 151–166, 1984.
Zehr, J. P.: Nitrogen fixation by marine cyanobacteria, Trends Microbiol., 19, 162–173, 2011.
Zondervan, I.: The effects of light, macronutrients, trace metals and CO2 on the production of calcium carbonate and organic carbon in coccolithophores? A review, Deep-Sea Res. Pt. II, 54, 521–537, 2007.
Special issue