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Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
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IF 5.240
5.768CiteScore
8.9SNIP 1.713
SJR 3.18
index 71h5-index 51
Abstracted/indexed
Abstracted/indexed
Volume 8, issue 8
Geosci. Model Dev., 8, 2465–2513, 2015
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Special issue: Nucleus for European Modelling of the Ocean - NEMO
Geosci. Model Dev., 8, 2465–2513, 2015
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-2465-2015
© Author(s) 2015. This work is distributed under
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 et al.
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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.
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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
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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
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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
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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.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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
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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
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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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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
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
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
Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
Marine biogeochemical cycling and oceanic CO2 uptake simulated by the NUIST Earth System Model version 3 (NESM v3)
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance
HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)
BPOP-v1 model: exploring the impact of changes in the biological pump on the shelf sea and ocean nutrient and redox state
P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production
HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 2: Phenology and water cycle
Dynamic upscaling of decomposition kinetics for carbon cycling models
CE-DYNAM (v1): a spatially explicit process-based carbon erosion scheme for use in Earth system models
FLiES-SIF ver. 1.0: Three-dimensional radiative transfer model for estimating solar induced fluorescence
A coupled pelagic–benthic–sympagic biogeochemical model for the Bering Sea: documentation and validation of the BESTNPZ model (v2019.08.23) within a high-resolution regional ocean model
The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage
FORests and HYdrology under Climate Change in Switzerland v1.0: a spatially distributed model combining hydrology and forest dynamics
ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 2: Model evaluation over the Lena River basin
Evaluation of CH4MODwetland and TEM models used to estimate global CH4 emissions from natural wetlands
Simulating stable carbon isotopes in the ocean component of the FAMOUS General Circulation Model with MOSES1 (XOAVI)
Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model (MIMICS-CN)
GLOBAL-FATE (version 1.0.0): A geographical information system (GIS)-based model for assessing contaminants fate in the global river network
A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?
Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data
Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE (trunk version, rev 4999): multi-scale evaluation of gross primary production
A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996)
Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED)
A lattice-automaton bioturbation simulator with coupled physics, chemistry, and biology in marine sediments (eLABS v0.2)
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)
Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH
Evaluation of leaf-level optical properties employed in land surface models
An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen, version 2 (FANv2)
ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of dissolved organic carbon from Arctic permafrost regions – Part 1: Rationale, model description, and simulation protocol
Short-term forecasting of regional biospheric CO2 fluxes in Europe using a light-use-efficiency model
Modelling northern peatland area and carbon dynamics since the Holocene with the ORCHIDEE-PEAT land surface model (SVN r5488)
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Description and validation of an intermediate complexity model for ecosystem photosynthesis and evapotranspiration: ACM-GPP-ETv1
The quasi-equilibrium framework revisited: analyzing long-term CO2 enrichment responses in plant–soil models
Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy
CO2 drawdown due to particle ballasting by glacial aeolian dust: an estimate based on the ocean carbon cycle model MPIOM/HAMOCC version 1.6.2p3
Towards end-to-end (E2E) modelling in a consistent NPZD-F modelling framework (ECOSMO E2E_v1.0): application to the North Sea and Baltic Sea
Evaluating the E3SM land model version 0 (ELMv0) at a temperate forest site using flux and soil water measurements
The [simple carbon project] model v1.0
MAgPIE 4 – a modular open-source framework for modeling global land systems
Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models
LPJ-GM 1.0: simulating migration efficiently in a dynamic vegetation model
A single-column ocean biogeochemistry model (GOTM–TOPAZ) version 1.0
Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5
Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)
Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations
A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: an example from the Amazon region
Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020, https://doi.org/10.5194/gmd-13-3299-2020, 2020
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Global fire–vegetation models are widely used, but there has been limited evaluation of how well they represent various aspects of fire regimes. Here we perform a systematic evaluation of simulations made by nine FireMIP models in order to quantify their ability to reproduce a range of fire and vegetation benchmarks. While some FireMIP models are better at representing certain aspects of the fire regime, no model clearly outperforms all other models across the full range of variables assessed.
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020, https://doi.org/10.5194/gmd-13-3119-2020, 2020
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NESM v3 is one of the CMIP6 registered Earth system models. We evaluate its ocean carbon cycle component and present its present-day and future oceanic CO2 uptake based on the CMIP6 historical and SSP5–8.5 scenarios. We hope that this paper can serve as a documentation of the marine biogeochemical cycle in NESM v3. Also, the model defects found and their underlying causes analyzed in this paper could help users and further model development.
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, https://doi.org/10.5194/gmd-13-2825-2020, 2020
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We transitioned the CLASS-CTEM land surface model to an open-source community model format by modernizing the code base to make the model easier to use and understand, providing a complete software environment to run the model within, developing a benchmarking suite for model evaluation, and creating an infrastructure to support community involvement. The new model, the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC), is now available for the community to use and develop.
Giovanni Denaro, Daniela Salvagio Manta, Alessandro Borri, Maria Bonsignore, Davide Valenti, Enza Quinci, Andrea Cucco, Bernardo Spagnolo, Mario Sprovieri, and Andrea De Gaetano
Geosci. Model Dev., 13, 2073–2093, https://doi.org/10.5194/gmd-13-2073-2020, https://doi.org/10.5194/gmd-13-2073-2020, 2020
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The HR3DHG (high-resolution 3D mercury model) investigates the spatiotemporal behavior, in seawater and marine sediments, of three mercury species (elemental, inorganic, and organic mercury) in a highly polluted marine environment (Augusta Bay, southern Italy). The model shows fair agreement with the experimental data collected during six different oceanographic cruises and can possibly be used for a detailed exploration of the effects of climate change on mercury distribution.
Elisa Lovecchio and Timothy M. Lenton
Geosci. Model Dev., 13, 1865–1883, https://doi.org/10.5194/gmd-13-1865-2020, https://doi.org/10.5194/gmd-13-1865-2020, 2020
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We present here the newly developed BPOP box model. BPOP is aimed at studying the impact of large-scale changes in the biological pump, i.e. the cycle of production, export and remineralization of the marine organic matter, on the nutrient and oxygen concentrations in the shelf and open ocean. This model has been developed to investigate the global consequences of the evolution of larger and heavier phytoplankton cells but can be applied to a variety of past and future case studies.
Benjamin D. Stocker, Han Wang, Nicholas G. Smith, Sandy P. Harrison, Trevor F. Keenan, David Sandoval, Tyler Davis, and I. Colin Prentice
Geosci. Model Dev., 13, 1545–1581, https://doi.org/10.5194/gmd-13-1545-2020, https://doi.org/10.5194/gmd-13-1545-2020, 2020
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Estimating terrestrial photosynthesis relies on satellite data of vegetation cover and models simulating the efficiency by which light absorbed by vegetation is used for CO2 assimilation. This paper presents the P-model, a light use efficiency model derived from a carbon–water optimality principle, and evaluates its predictions of ecosystem-level photosynthesis against globally distributed observations. The model is implemented and openly accessible as an R package (rpmodel).
Louis de Wergifosse, Frédéric André, Nicolas Beudez, François de Coligny, Hugues Goosse, François Jonard, Quentin Ponette, Hugues Titeux, Caroline Vincke, and Mathieu Jonard
Geosci. Model Dev., 13, 1459–1498, https://doi.org/10.5194/gmd-13-1459-2020, https://doi.org/10.5194/gmd-13-1459-2020, 2020
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Given their key role in the simulation of climate impacts on tree growth, phenological and water balance processes must be integrated in models simulating forest dynamics under a changing environment. Here, we describe these processes integrated in HETEROFOR, a model accounting simultaneously for the functional, structural and spatial complexity to explore the forest response to forestry practices. The model evaluation using phenological and soil water content observations is quite promising.
Arjun Chakrawal, Anke M. Herrmann, John Koestel, Jerker Jarsjö, Naoise Nunan, Thomas Kätterer, and Stefano Manzoni
Geosci. Model Dev., 13, 1399–1429, https://doi.org/10.5194/gmd-13-1399-2020, https://doi.org/10.5194/gmd-13-1399-2020, 2020
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Soils are heterogeneous, which results in a nonuniform spatial distribution of substrates and the microorganisms feeding on them. Our results show that the variability in the spatial distribution of substrates and microorganisms at the pore scale is crucial because it affects how fast substrates are used by microorganisms and thus the decomposition rate observed at the soil core scale. This work provides a methodology to include microscale heterogeneity in soil carbon cycling models.
Victoria Naipal, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, and Yilong Wang
Geosci. Model Dev., 13, 1201–1222, https://doi.org/10.5194/gmd-13-1201-2020, https://doi.org/10.5194/gmd-13-1201-2020, 2020
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In this study we present the Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the soil carbon cycle along a cascade of hillslopes, floodplains, and rivers. The model can simulate the removal of soil and carbon from eroding areas and their destination at regional scale. We calibrated and validated the model for the Rhine catchment, and we show that soil erosion is a potential large net carbon sink over the period 1850–2005.
Yuma Sakai, Hideki Kobayashi, and Tomomichi Kato
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-19, https://doi.org/10.5194/gmd-2020-19, 2020
Revised manuscript accepted for GMD
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Chlorophyll fluorescence is one of the energy release pathways of excess incident lights in the photosynthetic process. The canopy scale sun-induced chlorophyll fluorescence (SIF), which potentially provides a direct pathway to link leaf-level photosynthesis to global GPP, can be observed from satellites. We develop the three-dimensional Monte Carlo plant canopy radiative transfer model to understand the biological and physical mechanisms behind the SIF emission from complex forest canopies.
Kelly Kearney, Albert Hermann, Wei Cheng, Ivonne Ortiz, and Kerim Aydin
Geosci. Model Dev., 13, 597–650, https://doi.org/10.5194/gmd-13-597-2020, https://doi.org/10.5194/gmd-13-597-2020, 2020
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We describe an ecosystem model for the Bering Sea. Biological components in the Bering Sea can be found in the water column, on and within the bottom sediments, and within the porous lower layer of seasonal sea ice. This model simulates the exchange of material between nutrients and plankton within all three environments. Here, we thoroughly document the model and assess its skill in capturing key biophysical features across the Bering Sea.
Femke Lutz, Stephen DelGrosso, Stephen Ogle, Stephen Williams, Sara Minoli, Susanne Rolinski, Jens Heinke, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-364, https://doi.org/10.5194/gmd-2019-364, 2020
Revised manuscript accepted for GMD
Matthias J. R. Speich, Massimiliano Zappa, Marc Scherstjanoi, and Heike Lischke
Geosci. Model Dev., 13, 537–564, https://doi.org/10.5194/gmd-13-537-2020, https://doi.org/10.5194/gmd-13-537-2020, 2020
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Climate change is expected to substantially affect natural processes, and simulation models are a valuable tool to anticipate these changes. In this study, we combine two existing models that each describe one aspect of the environment: forest dynamics and the terrestrial water cycle. The coupled model better described observed patterns in vegetation structure. We also found that including the effect of water availability on tree height and rooting depth improved the model.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Pierre Regnier, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 13, 507–520, https://doi.org/10.5194/gmd-13-507-2020, https://doi.org/10.5194/gmd-13-507-2020, 2020
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In this second part of the study, we performed simulations of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. We compare simulations using this model to existing data sources to show that it is capable of reproducing dissolved carbon fluxes of potentially great importance for the future of the global permafrost.
Tingting Li, Yanyu Lu, Lingfei Yu, Wenjuan Sun, Qing Zhang, Wen Zhang, Guocheng Wang, Lijun Yu, and Ran Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-367, https://doi.org/10.5194/gmd-2019-367, 2020
Revised manuscript accepted for GMD
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Reliable models are required to estimate global wetland CH4 emissions. In this study, we tested two process-based models, CH4MODwetlandand TEM, against the CH4 flux measurements of different continents and wetland types across the world and estimated the global CH4 emissions from 2000 to 2010 from natural wetlands. Each model shows good performance in different continents or wetland types. The estimated global CH4 emissions by the models would be 116.99–124.74 Tg yr−1 for the period 2000–2010.
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, and Laura F. Robinson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-250, https://doi.org/10.5194/gmd-2019-250, 2020
Revised manuscript accepted for GMD
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We have added a new tracer (13C) into the ocean of the FAMOUS climate model to study large-scale circulation and the marine carbon cycle. The model captures the large-scale spatial pattern of observations but the simulated values are consistently higher than observed. In the first instance, our new tracer is therefore useful for recalibrating the physical and biogeochemical components of the model.
Emily Kyker-Snowman, William R. Wieder, Serita Frey, and A. Stuart Grandy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-320, https://doi.org/10.5194/gmd-2019-320, 2019
Preprint under review for GMD
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Microbes drive carbon (C) and nitrogen (N) transformations in soil, and soil models have started to include explicit microbial physiology and functioning to try to reduce uncertainty in soil-climate feedbacks. Here, we add N cycling to a microbially-explicit soil C model and reproduce C and N dynamics in soil during litter decomposition across a range of sites. We discuss model-generated hypotheses about soil C and N cycling and highlight the need for landscape-scale model evaluation data.
Carme Font, Francesco Bregoli, Vicenç Acuña, Sergi Sabater, and Rafael Marcé
Geosci. Model Dev., 12, 5213–5228, https://doi.org/10.5194/gmd-12-5213-2019, https://doi.org/10.5194/gmd-12-5213-2019, 2019
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GLOBAL-FATE is an open-source, multiplatform, and flexible model that simulates the fate of pharmaceutical-like compounds in the global river network. The model considers the consumption of pharmaceuticals by humans, differentiates between pharmaceutical load treated in wastewater treatment plants from that directly delivered to streams and rivers, and integrates lakes and reservoirs in calculations. GLOBAL-FATE is a powerful tool for pollutant impact studies at the global scale.
Luke Gregor, Alice D. Lebehot, Schalk Kok, and Pedro M. Scheel Monteiro
Geosci. Model Dev., 12, 5113–5136, https://doi.org/10.5194/gmd-12-5113-2019, https://doi.org/10.5194/gmd-12-5113-2019, 2019
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The ocean plays a vital role in mitigating climate change by taking up atmospheric carbon dioxide (CO2). Historically sparse ship-based measurements of surface ocean CO2 make direct estimates of CO2 exchange changes unreliable. We introduce a machine-learning ensemble approach to fill these observational gaps. Our method performs incrementally better relative to past methods, leading to our hypothesis that we are perhaps reaching the limitation of machine-learning algorithms' capability.
Markus Drüke, Matthias Forkel, Werner von Bloh, Boris Sakschewski, Manoel Cardoso, Mercedes Bustamante, Jürgen Kurths, and Kirsten Thonicke
Geosci. Model Dev., 12, 5029–5054, https://doi.org/10.5194/gmd-12-5029-2019, https://doi.org/10.5194/gmd-12-5029-2019, 2019
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This work shows the successful application of a systematic model–data integration setup, as well as the implementation of a new fire danger formulation, in order to optimize a process-based fire-enabled dynamic global vegetation model. We have demonstrated a major improvement in the fire representation within LPJmL4-SPITFIRE in terms of the spatial pattern and the interannual variability of burned area in South America as well as in the modelling of biomass and the distribution of plant types.
Nicolas Vuichard, Palmira Messina, Sebastiaan Luyssaert, Bertrand Guenet, Sönke Zaehle, Josefine Ghattas, Vladislav Bastrikov, and Philippe Peylin
Geosci. Model Dev., 12, 4751–4779, https://doi.org/10.5194/gmd-12-4751-2019, https://doi.org/10.5194/gmd-12-4751-2019, 2019
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In this research, we present a new version of the global terrestrial ecosystem model ORCHIDEE in which carbon and nitrogen cycles are coupled. We evaluate its skills at simulating primary production at 78 sites and at a global scale. Based on a set of additional simulations in which carbon and nitrogen cycles are coupled and uncoupled, we show that the functional responses of the model with carbon–nitrogen interactions better agree with our current understanding of photosynthesis.
Tea Thum, Silvia Caldararu, Jan Engel, Melanie Kern, Marleen Pallandt, Reiner Schnur, Lin Yu, and Sönke Zaehle
Geosci. Model Dev., 12, 4781–4802, https://doi.org/10.5194/gmd-12-4781-2019, https://doi.org/10.5194/gmd-12-4781-2019, 2019
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To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
Dave van Wees and Guido R. van der Werf
Geosci. Model Dev., 12, 4681–4703, https://doi.org/10.5194/gmd-12-4681-2019, https://doi.org/10.5194/gmd-12-4681-2019, 2019
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For this paper, a novel high spatial-resolution fire emission model based on the Global Fire Emissions Database (GFED) modelling framework was developed and compared to a coarser-resolution version of the same model. Our findings highlight the importance of fine spatial resolution when modelling global-scale fire emissions, especially considering the comparison of model pixels to individual field measurements and the model representation of heterogeneity in the landscape.
Yoshiki Kanzaki, Bernard P. Boudreau, Sandra Kirtland Turner, and Andy Ridgwell
Geosci. Model Dev., 12, 4469–4496, https://doi.org/10.5194/gmd-12-4469-2019, https://doi.org/10.5194/gmd-12-4469-2019, 2019
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This paper provides eLABS, an extension of the lattice-automaton bioturbation simulator LABS. In our new model, the benthic animal behavior interacts and changes dynamically with oxygen and organic matter concentrations and the water flows caused by benthic animals themselves, in a 2-D marine-sediment grid. The model can address the mechanisms behind empirical observations of bioturbation based on the interactions between physical, chemical and biological aspects of marine sediment.
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019, https://doi.org/10.5194/gmd-12-4309-2019, 2019
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Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, https://doi.org/10.5194/gmd-12-4347-2019, 2019
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The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
Elias C. Massoud, Chonggang Xu, Rosie A. Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, and Jasper A. Vrugt
Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, https://doi.org/10.5194/gmd-12-4133-2019, 2019
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We conducted a comprehensive sensitivity analysis to understand behaviors of a demographic vegetation model within a land surface model. By running the model 5000 times with changing input parameter values, we found that (1) the photosynthetic capacity controls carbon fluxes, (2) the allometry is important for tree growth, and (3) the targeted carbon storage is important for tree survival. These results can provide guidance on improved model parameterization for a better fit to observations.
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019, https://doi.org/10.5194/gmd-12-4075-2019, 2019
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We assess the differences of six stomatal conductance formulations, embedded into a land–vegetation model JSBACH, on 10 boreal coniferous evergreen forest sites. We calibrate the model parameters using all six functions in a multi-year experiment, as well as for a separate drought event at one of the sites, using the adaptive population importance sampler. The analysis reveals weaknesses in the stomatal conductance formulation-dependent model behaviour that we are able to partially amend.
Titta Majasalmi and Ryan M. Bright
Geosci. Model Dev., 12, 3923–3938, https://doi.org/10.5194/gmd-12-3923-2019, https://doi.org/10.5194/gmd-12-3923-2019, 2019
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Many land surface models rely on solutions derived from two-stream approximations utilizing leaf-level optical properties, many of which have not been formally reviewed or published. Using plant functional type groupings of the Community Land Model (CLM), we found large deviations between measured and CLM default near-infrared optical properties, implying that the modeled shortwave radiation budget including surface albedo may be expected to change after updating the biased parameters.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-233, https://doi.org/10.5194/gmd-2019-233, 2019
Preprint under review for GMD
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Atmospheric emission of ammonia from fertilizers and livestock manure constitutes a significant pathway of nutrient transport from agricultural to natural ecosystems. This study evaluates a model for simulating ammonia emissions and their response to climate change. The model is first compared with empirical data, and then applied globally. The simulated emissions are similar to earlier estimates for Europe, North America and China, but differ for Africa, India and South America.
Simon P. K. Bowring, Ronny Lauerwald, Bertrand Guenet, Dan Zhu, Matthieu Guimberteau, Ardalan Tootchi, Agnès Ducharne, and Philippe Ciais
Geosci. Model Dev., 12, 3503–3521, https://doi.org/10.5194/gmd-12-3503-2019, https://doi.org/10.5194/gmd-12-3503-2019, 2019
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Few Earth system models represent permafrost soil biogeochemistry, contributing to uncertainty in estimating its response and that of the planet to warming. Because the permafrost contains over double the carbon in the present atmosphere, its fate as it is
unlockedby warming is globally significant. One way it can be mobilised is into rivers, the sea, or the atmosphere: a vector previously ignored in climate modelling. We present a model scheme for resolving this vector at a global scale.
Jinxuan Chen, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-173, https://doi.org/10.5194/gmd-2019-173, 2019
Revised manuscript accepted for GMD
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One of the essential challenge for atmospheric CO2 forecasting is predicting CO2 flux variation on sub-daily time scale. For CAMS CO2 forecast, a process-based vegetation model is used.
In this research we evaluate another type of model (i.e. the light-use-efficiency model VPRM), which is a data-driven approach and thus ideal for realistic estimation, on its flux prediction ability. Errors from different sources are assessed, and overall the model is capable of CO2 flux prediction.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Shushi Peng, Gerhard Krinner, Ardalan Tootchi, Agnès Ducharne, and Adam Hastie
Geosci. Model Dev., 12, 2961–2982, https://doi.org/10.5194/gmd-12-2961-2019, https://doi.org/10.5194/gmd-12-2961-2019, 2019
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We present a model that can simulate the dynamics of peatland area extent and the vertical buildup of peat. The model is validated across a range of northern peatland sites and over the Northern Hemisphere (> 30° N). It is able to reproduce the spatial extent of northern peatlands and peat carbon accumulation over the Holocene.
Femke Lutz, Tobias Herzfeld, Jens Heinke, Susanne Rolinski, Sibyll Schaphoff, Werner von Bloh, Jetse J. Stoorvogel, and Christoph Müller
Geosci. Model Dev., 12, 2419–2440, https://doi.org/10.5194/gmd-12-2419-2019, https://doi.org/10.5194/gmd-12-2419-2019, 2019
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Tillage practices are under-represented in global biogeochemical models so that assessments of agricultural greenhouse gas emissions and climate mitigation options are hampered. We describe the implementation of tillage modules into the model LPJmL5.0, including multiple feedbacks between soil water, nitrogen, and productivity. By comparing simulation results with observational data, we show that the model can reproduce reported tillage effects on carbon and water dynamics and crop yields.
Thomas Luke Smallman and Mathew Williams
Geosci. Model Dev., 12, 2227–2253, https://doi.org/10.5194/gmd-12-2227-2019, https://doi.org/10.5194/gmd-12-2227-2019, 2019
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Photosynthesis and evapotranspiration are processes with global significance for climate, carbon and water cycling. Process-orientated simulation of these processes and their interactions have till now come at high computational cost. Here we present a new coupled model of intermediate complexity operating at orders of magnitude greater speed. Independent evaluation at FLUXNET sites for a single, global parameterization shows good agreement, with a typical R2 value of ~ 0.60.
Mingkai Jiang, Sönke Zaehle, Martin G. De Kauwe, Anthony P. Walker, Silvia Caldararu, David S. Ellsworth, and Belinda E. Medlyn
Geosci. Model Dev., 12, 2069–2089, https://doi.org/10.5194/gmd-12-2069-2019, https://doi.org/10.5194/gmd-12-2069-2019, 2019
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Here we used a simple analytical framework developed by Comins and McMurtrie (1993) to investigate how different model assumptions affected plant responses to elevated CO2. This framework is useful in revealing both the consequences and the mechanisms through which different assumptions affect predictions. We therefore recommend the use of this framework to analyze the likely outcomes of new assumptions before introducing them to complex model structures.
Ahmed S. Elshall, Ming Ye, Guo-Yue Niu, and Greg A. Barron-Gafford
Geosci. Model Dev., 12, 2009–2032, https://doi.org/10.5194/gmd-12-2009-2019, https://doi.org/10.5194/gmd-12-2009-2019, 2019
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The assumptions that the residuals are independent, identically distributed, and have constant variance tend to simplify the underlying mathematics of data models for Bayesian inference. We relax these three assumptions step-wise, resulting in eight data models. Using three mechanistic soil respiration models with different levels of model discrepancy, we discuss the impacts of data models on parameter estimation and predictive performance, and provide recommendations for data model selection.
Malte Heinemann, Joachim Segschneider, and Birgit Schneider
Geosci. Model Dev., 12, 1869–1883, https://doi.org/10.5194/gmd-12-1869-2019, https://doi.org/10.5194/gmd-12-1869-2019, 2019
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Ocean CO2 uptake played a crucial role for the global cooling during ice ages. Dust formation, e.g. by ice scraping over bedrock, potentially contributed to this CO2 uptake because (1) the iron in the dust is a fertilizer and (2) the heavy dust particles can accelerate sinking organic matter (ballasting hypothesis). This study tests the glacial dust ballasting hypothesis for the first time, using an ocean model. It turns out, however, that the ballasting effect probably played a minor role.
Ute Daewel, Corinna Schrum, and Jed I. Macdonald
Geosci. Model Dev., 12, 1765–1789, https://doi.org/10.5194/gmd-12-1765-2019, https://doi.org/10.5194/gmd-12-1765-2019, 2019
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Here we propose a novel modelling approach that includes an extended food web in a functional-group-type marine ecosystem model (ECOSMO E2E) by formulating new groups for macrobenthos and fish. This enables the estimation of the dynamics of the higher-trophic-level production potential and constitutes a more consistent closure term for the lower-trophic-level ecosystem. Thus, the model allows for the study of the control mechanisms for marine ecosystems at a high spatial and temporal resolution.
Junyi Liang, Gangsheng Wang, Daniel M. Ricciuto, Lianhong Gu, Paul J. Hanson, Jeffrey D. Wood, and Melanie A. Mayes
Geosci. Model Dev., 12, 1601–1612, https://doi.org/10.5194/gmd-12-1601-2019, https://doi.org/10.5194/gmd-12-1601-2019, 2019
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Soil respiration, the second largest carbon fluxes between the atmosphere and land, is not well represented in global land models. In this study, using long-term observations at a temperate forest, we identified a solution for using better soil water potential simulations to improve predictions of soil respiration in the E3SM land model. In addition, parameter calibration further improved model performance.
Cameron M. O'Neill, Andrew McC. Hogg, Michael J. Ellwood, Stephen M. Eggins, and Bradley N. Opdyke
Geosci. Model Dev., 12, 1541–1572, https://doi.org/10.5194/gmd-12-1541-2019, https://doi.org/10.5194/gmd-12-1541-2019, 2019
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The [simple carbon project] model v1.0 (SCP-M) was constructed for simulations of the paleo and modern carbon cycle. In this paper we show its application to the carbon cycle transition from the Last Glacial Maximum to the Holocene period. Our model–data experiment uses SCP-M's fast run time to cover a large range of possible inputs. The results highlight the role of varying the strength of ocean circulation to account for large fluctuations in atmospheric CO2 across the two periods.
Jan Philipp Dietrich, Benjamin Leon Bodirsky, Florian Humpenöder, Isabelle Weindl, Miodrag Stevanović, Kristine Karstens, Ulrich Kreidenweis, Xiaoxi Wang, Abhijeet Mishra, David Klein, Geanderson Ambrósio, Ewerton Araujo, Amsalu Woldie Yalew, Lavinia Baumstark, Stephen Wirth, Anastasis Giannousakis, Felicitas Beier, David Meng-Chuen Chen, Hermann Lotze-Campen, and Alexander Popp
Geosci. Model Dev., 12, 1299–1317, https://doi.org/10.5194/gmd-12-1299-2019, https://doi.org/10.5194/gmd-12-1299-2019, 2019
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We provides an overview on version 4 of the MAgPIE open-source framework for modeling global land systems. Among others, MAgPIE has been used to simulate marker scenarios of the Shared Socioeconomic Pathways (SSPs) and contributed substantially to multiple IPCC assessments. Its recent version marks the first open-source release of the framework and introduces several new features. Via its modularity and spatial flexibility it can serve as a tool for a broad range of land-related research topics.
Yuanyuan Huang, Mark Stacy, Jiang Jiang, Nilutpal Sundi, Shuang Ma, Volodymyr Saruta, Chang Gyo Jung, Zheng Shi, Jianyang Xia, Paul J. Hanson, Daniel Ricciuto, and Yiqi Luo
Geosci. Model Dev., 12, 1119–1137, https://doi.org/10.5194/gmd-12-1119-2019, https://doi.org/10.5194/gmd-12-1119-2019, 2019
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Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD) into models. EcoPAD also has the potential to become an interactive tool for resource management, stimulate citizen science in ecology, and transform environmental education.
Veiko Lehsten, Michael Mischurow, Erik Lindström, Dörte Lehsten, and Heike Lischke
Geosci. Model Dev., 12, 893–908, https://doi.org/10.5194/gmd-12-893-2019, https://doi.org/10.5194/gmd-12-893-2019, 2019
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To assess the effect of climate on vegetation, dynamic vegetation models simulate their response e.g. to climate change. Most currently used dynamic vegetation models ignore the fact that for colonization of a new area not only do the climatic conditions have to be suitable, but seeds also need to arrive at the site to allow the species to migrate there. In this paper we are developing a novel method which allows us to simulate migration within dynamic vegetation models even at large scale.
Hyun-Chae Jung, Byung-Kwon Moon, Jieun Wie, Hyei-Sun Park, Johan Lee, and Young-Hwa Byun
Geosci. Model Dev., 12, 699–722, https://doi.org/10.5194/gmd-12-699-2019, https://doi.org/10.5194/gmd-12-699-2019, 2019
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We developed the GOTM–TOPAZ, a single-column ocean biogeochemistry model, which simulates the biogeochemical processes including carbon and nutrient cycles. The model contains the bio–physical feedback by incorporating the oceanic heating due to chlorophyll absorption of solar radiation. We evaluate the model performance against available observations and a global ocean simulation, and this shows that our model reproduces the magnitude of and variability in biogeochemical variables well.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 12, 457–472, https://doi.org/10.5194/gmd-12-457-2019, https://doi.org/10.5194/gmd-12-457-2019, 2019
Chantelle Burton, Richard Betts, Manoel Cardoso, Ted R. Feldpausch, Anna Harper, Chris D. Jones, Douglas I. Kelley, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 12, 179–193, https://doi.org/10.5194/gmd-12-179-2019, https://doi.org/10.5194/gmd-12-179-2019, 2019
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Fire and land-use change are important disturbances within the Earth system, and their inclusion in models is critical to enable the correct simulation of vegetation cover. Here we describe developments to the land surface model JULES to represent explicit land-use change and fire and to assess the effects of each process on present day vegetation compared to observations. Using historical land-use data and the fire model INFERNO, overall model results are improved by the developments.
Sergey Venevsky, Yannick Le Page, José M. C. Pereira, and Chao Wu
Geosci. Model Dev., 12, 89–110, https://doi.org/10.5194/gmd-12-89-2019, https://doi.org/10.5194/gmd-12-89-2019, 2019
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We present SEVER-FIRE (v1.0), incorporated into the SEVER DGVM. One of the major focuses of SEVER-FIRE is an implementation of the pyrogenic behavior of humans (timing of their activities and their willingness and necessity to ignite or suppress fire), related to socioeconomic and demographic conditions in a geographical domain of the model application. Unlike other DGVM- and ESM-based global fire models, we do not use any satellite-derived assumptions in equations of fire model development.
Anja Rammig, Jens Heinke, Florian Hofhansl, Hans Verbeeck, Timothy R. Baker, Bradley Christoffersen, Philippe Ciais, Hannes De Deurwaerder, Katrin Fleischer, David Galbraith, Matthieu Guimberteau, Andreas Huth, Michelle Johnson, Bart Krujit, Fanny Langerwisch, Patrick Meir, Phillip Papastefanou, Gilvan Sampaio, Kirsten Thonicke, Celso von Randow, Christian Zang, and Edna Rödig
Geosci. Model Dev., 11, 5203–5215, https://doi.org/10.5194/gmd-11-5203-2018, https://doi.org/10.5194/gmd-11-5203-2018, 2018
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We propose a generic approach for a pixel-to-point comparison applicable for evaluation of models and remote-sensing products. We provide statistical measures accounting for the uncertainty in ecosystem variables. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest.
Vladislav Bastrikov, Natasha MacBean, Cédric Bacour, Diego Santaren, Sylvain Kuppel, and Philippe Peylin
Geosci. Model Dev., 11, 4739–4754, https://doi.org/10.5194/gmd-11-4739-2018, https://doi.org/10.5194/gmd-11-4739-2018, 2018
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In this study, we compare different methods for optimising parameters of the ORCHIDEE land surface model (LSM) using in situ observations. We use two minimisation methods - local gradient-based and global random search - applied either at each individual site or a group of sites characterised by one plant functional type. We demonstrate the advantages and challenges of different techniques and provide some advice on using it for the LSM parameters optimisation.
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.
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