Articles | Volume 5-opsr
https://doi.org/10.5194/sp-5-opsr-12-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/sp-5-opsr-12-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Numerical models for monitoring and forecasting ocean biogeochemistry: a short description of present status
Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Section of Oceanography, Trieste, Italy
Andrew Moore
Ocean Sciences Department, University of California Santa Cruz, Santa Cruz, CA, USA
Stefano Ciavatta
Mercator Ocean International, Toulouse, France
Katja Fennel
Department of Oceanography, Dalhousie University, Halifax, NS, Canada
Related authors
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary
Short summary
Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Anna Teruzzi, Ali Aydogdu, Carolina Amadio, Emanuela Clementi, Simone Colella, Valeria Di Biagio, Massimiliano Drudi, Claudia Fanelli, Laura Feudale, Alessandro Grandi, Pietro Miraglio, Andrea Pisano, Jenny Pistoia, Marco Reale, Stefano Salon, Gianluca Volpe, and Gianpiero Cossarini
State Planet, 4-osr8, 15, https://doi.org/10.5194/sp-4-osr8-15-2024, https://doi.org/10.5194/sp-4-osr8-15-2024, 2024
Short summary
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A noticeable cold spell occurred in Eastern Europe at the beginning of 2022 and was the main driver of intense deep-water formation and the associated transport of nutrients to the surface. Southeast of Crete, the availability of both light and nutrients in the surface layer stimulated an anomalous phytoplankton bloom. In the area, chlorophyll concentration (a proxy for bloom intensity) and primary production were considerably higher than usual, suggesting possible impacts on fishery catches.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Carolina Amadio, Anna Teruzzi, Gloria Pietropolli, Luca Manzoni, Gianluca Coidessa, and Gianpiero Cossarini
Ocean Sci., 20, 689–710, https://doi.org/10.5194/os-20-689-2024, https://doi.org/10.5194/os-20-689-2024, 2024
Short summary
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Forecasting of marine biogeochemistry can be improved via the assimilation of observations. Floating buoys provide multivariate information about the status of the ocean interior. Information on the ocean interior can be expanded/augmented by machine learning. In this work, we show the enhanced impact of assimilating new in situ variables (oxygen) and reconstructed variables (nitrate) in the operational forecast system (MedBFM) model of the Mediterranean Sea.
Eva Álvarez, Gianpiero Cossarini, Anna Teruzzi, Jorn Bruggeman, Karsten Bolding, Stefano Ciavatta, Vincenzo Vellucci, Fabrizio D'Ortenzio, David Antoine, and Paolo Lazzari
Biogeosciences, 20, 4591–4624, https://doi.org/10.5194/bg-20-4591-2023, https://doi.org/10.5194/bg-20-4591-2023, 2023
Short summary
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Chromophoric dissolved organic matter (CDOM) interacts with the ambient light and gives the waters of the Mediterranean Sea their colour. We propose a novel parameterization of the CDOM cycle, whose parameter values have been optimized by using the data of the monitoring site BOUSSOLE. Nutrient and light limitations for locally produced CDOM caused aCDOM(λ) to covary with chlorophyll, while the above-average CDOM concentrations observed at this site were maintained by allochthonous sources.
Simone Spada, Anna Teruzzi, Stefano Maset, Stefano Salon, Cosimo Solidoro, and Gianpiero Cossarini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-170, https://doi.org/10.5194/gmd-2023-170, 2023
Revised manuscript under review for GMD
Short summary
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In geosciences, data assimilation (DA) combines modeled dynamics and observations to reduce simulation uncertainties. Uncertainties can be dynamically and effectively estimated in ensemble DA methods. With respect to current techniques, the novel GHOSH ensemble DA scheme is designed to improve accuracy by reaching a higher approximation order, without increasing computational costs, as demonstrated in idealized Lorenz96 tests and in realistic simulations of the Mediterranean Sea biogeochemistry
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
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The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
Valeria Di Biagio, Riccardo Martellucci, Milena Menna, Anna Teruzzi, Carolina Amadio, Elena Mauri, and Gianpiero Cossarini
State Planet, 1-osr7, 10, https://doi.org/10.5194/sp-1-osr7-10-2023, https://doi.org/10.5194/sp-1-osr7-10-2023, 2023
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Oxygen is essential to all aerobic organisms, and its content in the marine environment is continuously under assessment. By integrating observations with a model, we describe the dissolved oxygen variability in a sensitive Mediterranean area in the period 1999–2021 and ascribe it to multiple acting physical and biological drivers. Moreover, the reduction recognized in 2021, apparently also due to other mechanisms, requires further monitoring in light of its possible impacts.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Alexandre Mignot, Hervé Claustre, Gianpiero Cossarini, Fabrizio D'Ortenzio, Elodie Gutknecht, Julien Lamouroux, Paolo Lazzari, Coralie Perruche, Stefano Salon, Raphaëlle Sauzède, Vincent Taillandier, and Anna Teruzzi
Biogeosciences, 20, 1405–1422, https://doi.org/10.5194/bg-20-1405-2023, https://doi.org/10.5194/bg-20-1405-2023, 2023
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Numerical models of ocean biogeochemistry are becoming a major tool to detect and predict the impact of climate change on marine resources and monitor ocean health. Here, we demonstrate the use of the global array of BGC-Argo floats for the assessment of biogeochemical models. We first detail the handling of the BGC-Argo data set for model assessment purposes. We then present 23 assessment metrics to quantify the consistency of BGC model simulations with respect to BGC-Argo data.
Valeria Di Biagio, Stefano Salon, Laura Feudale, and Gianpiero Cossarini
Biogeosciences, 19, 5553–5574, https://doi.org/10.5194/bg-19-5553-2022, https://doi.org/10.5194/bg-19-5553-2022, 2022
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The amount of dissolved oxygen in the ocean is the result of interacting physical and biological processes. Oxygen vertical profiles show a subsurface maximum in a large part of the ocean. We used a numerical model to map this subsurface maximum in the Mediterranean Sea and to link local differences in its properties to the driving processes. This emerging feature can help the marine ecosystem functioning to be better understood, also under the impacts of climate change.
Marco Reale, Gianpiero Cossarini, Paolo Lazzari, Tomas Lovato, Giorgio Bolzon, Simona Masina, Cosimo Solidoro, and Stefano Salon
Biogeosciences, 19, 4035–4065, https://doi.org/10.5194/bg-19-4035-2022, https://doi.org/10.5194/bg-19-4035-2022, 2022
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Future projections under the RCP8.5 and RCP4.5 emission scenarios of the Mediterranean Sea biogeochemistry at the end of the 21st century show different levels of decline in nutrients, oxygen and biomasses and an acidification of the water column. The signal intensity is stronger under RCP8.5 and in the eastern Mediterranean. Under RCP4.5, after the second half of the 21st century, biogeochemical variables show a recovery of the values observed at the beginning of the investigated period.
Anna Teruzzi, Giorgio Bolzon, Laura Feudale, and Gianpiero Cossarini
Biogeosciences, 18, 6147–6166, https://doi.org/10.5194/bg-18-6147-2021, https://doi.org/10.5194/bg-18-6147-2021, 2021
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During summer, maxima of phytoplankton chlorophyll concentration (DCM) occur in the subsurface of the Mediterranean Sea and can play a relevant role in carbon sequestration into the ocean interior. A numerical model based on in situ and satellite observations provides insights into the range of DCM conditions across the relatively small Mediterranean Sea and shows a western DCM that is 25 % shallower and with a higher phytoplankton chlorophyll concentration than in the eastern Mediterranean.
Valeria Di Biagio, Gianpiero Cossarini, Stefano Salon, and Cosimo Solidoro
Biogeosciences, 17, 5967–5988, https://doi.org/10.5194/bg-17-5967-2020, https://doi.org/10.5194/bg-17-5967-2020, 2020
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Events that influence the functioning of the Earth’s ecosystems are of interest in relation to a changing climate. We propose a method to identify and characterise
wavesof extreme events affecting marine ecosystems for multi-week periods over wide areas. Our method can be applied to suitable ecosystem variables and has been used to describe different kinds of extreme event waves of phytoplankton chlorophyll in the Mediterranean Sea, by analysing the output from a high-resolution model.
Stefano Salon, Gianpiero Cossarini, Giorgio Bolzon, Laura Feudale, Paolo Lazzari, Anna Teruzzi, Cosimo Solidoro, and Alessandro Crise
Ocean Sci., 15, 997–1022, https://doi.org/10.5194/os-15-997-2019, https://doi.org/10.5194/os-15-997-2019, 2019
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After 10 years of research and development, validated analysis and forecasts of the main parameters of the Mediterranean Sea biogeochemistry (e.g. phytoplankton, nutrients, oxygen, pH, carbon fluxes) at high spatial and temporal resolution are provided in the frame of the EU Copernicus Marine Environment Monitoring Service. Along with a traditional skill performance assessment, novel metrics exploiting the Biogeochemical Argo floats data are designed to estimate the forecasts uncertainty.
Gianpiero Cossarini, Stefano Querin, Cosimo Solidoro, Gianmaria Sannino, Paolo Lazzari, Valeria Di Biagio, and Giorgio Bolzon
Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017, https://doi.org/10.5194/gmd-10-1423-2017, 2017
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The BFMCOUPLER (v1.0) is a coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations. The online coupling is based on an open-source code characterizd by a modular structure. Modularity preserves the potentials of the two models, allowing for a sustainable programming effort to handle future evolutions in the two codes. The BFMCOUPLER code is released along with an idealized problem (a cyclonic gyre in a mid-latitude closed basin).
G. Cossarini, P. Lazzari, and C. Solidoro
Biogeosciences, 12, 1647–1658, https://doi.org/10.5194/bg-12-1647-2015, https://doi.org/10.5194/bg-12-1647-2015, 2015
Matthew J. Martin, Ibrahim Hoteit, Laurent Bertino, and Andrew M. Moore
State Planet, 5-opsr, 9, https://doi.org/10.5194/sp-5-opsr-9-2025, https://doi.org/10.5194/sp-5-opsr-9-2025, 2025
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Observations of the ocean from satellites and platforms in the ocean are combined with information from computer models to produce predictions of how the ocean temperature, salinity, and currents will evolve over the coming days and weeks and to describe how the ocean has evolved in the past. This paper summarises the methods used to produce these ocean forecasts at various centres around the world and outlines the practical considerations for implementing such forecasting systems.
Antonio Novellino, Pierre-Yves Le Traon, and Andy Moore
State Planet, 5-opsr, 8, https://doi.org/10.5194/sp-5-opsr-8-2025, https://doi.org/10.5194/sp-5-opsr-8-2025, 2025
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This paper discusses the vital role of observations in ocean predictions and forecasting, highlighting the need for effective access, management, and integration of data to improve models and decision-making. The paper also explores opportunities for standardizing protocols and the potential of citizen-based, cost-effective data collection methods.
Pierre-Yves Le Traon, Antonio Novellino, and Andrew M. Moore
State Planet, 5-opsr, 7, https://doi.org/10.5194/sp-5-opsr-7-2025, https://doi.org/10.5194/sp-5-opsr-7-2025, 2025
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Ocean prediction relies on the integration between models and satellite and in situ observations through data assimilation techniques. The authors discuss the role of observations in operational ocean forecasting systems, describing the state of the art of satellite and in situ observing networks and defining the paths for addressing multi-scale monitoring and forecasting.
Ieuan Higgs, Ross Bannister, Jozef Skákala, Alberto Carrassi, and Stefano Ciavatta
EGUsphere, https://doi.org/10.48550/arXiv.2504.05218, https://doi.org/10.48550/arXiv.2504.05218, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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We explored how machine learning can improve computer models that simulate ocean ecosystems. These models help us understand how the ocean works, but they often struggle due to limited observations and complex processes. Our approach uses machine learning to better connect the parts of the system we can observe with those we cannot. This leads to more accurate and efficient predictions, offering a promising way to improve future ocean monitoring and forecasting tools.
Gabriela Martinez-Balbontin, Julien Jouanno, Rachid Benshila, Julien Lamouroux, Coralie Perruche, and Stefano Ciavatta
EGUsphere, https://doi.org/10.5194/egusphere-2025-1246, https://doi.org/10.5194/egusphere-2025-1246, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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This study uses machine learning to predict chlorophyll-a levels, which are important for monitoring marine ecosystems and the carbon cycle. By using forecasts of sea surface temperature, salinity, height, and mixed layer depth, we can make global predictions up to six months ahead in just minutes. Our approach is as accurate or better than traditional methods, while being faster and more resource-efficient.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the ocean capture of atmospheric carbon dioxide, which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary
Short summary
Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Anna Teruzzi, Ali Aydogdu, Carolina Amadio, Emanuela Clementi, Simone Colella, Valeria Di Biagio, Massimiliano Drudi, Claudia Fanelli, Laura Feudale, Alessandro Grandi, Pietro Miraglio, Andrea Pisano, Jenny Pistoia, Marco Reale, Stefano Salon, Gianluca Volpe, and Gianpiero Cossarini
State Planet, 4-osr8, 15, https://doi.org/10.5194/sp-4-osr8-15-2024, https://doi.org/10.5194/sp-4-osr8-15-2024, 2024
Short summary
Short summary
A noticeable cold spell occurred in Eastern Europe at the beginning of 2022 and was the main driver of intense deep-water formation and the associated transport of nutrients to the surface. Southeast of Crete, the availability of both light and nutrients in the surface layer stimulated an anomalous phytoplankton bloom. In the area, chlorophyll concentration (a proxy for bloom intensity) and primary production were considerably higher than usual, suggesting possible impacts on fishery catches.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev., 17, 5619–5639, https://doi.org/10.5194/gmd-17-5619-2024, https://doi.org/10.5194/gmd-17-5619-2024, 2024
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Jozef Skakala, David Ford, Keith Haines, Amos Lawless, Matthew Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Mike Bell, Davi Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
EGUsphere, https://doi.org/10.5194/egusphere-2024-1737, https://doi.org/10.5194/egusphere-2024-1737, 2024
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In this paper we review marine data assimilation (MDA) in the UK, its stakeholders, needs, past and present developments in different areas of UK MDA, and offer a vision for their longer future. The specific areas covered are ocean physics and sea ice, marine biogeochemistry, coupled MDA, MDA informing observing network design and MDA theory. We also discuss future vision for MDA resources: observations, software, hardware and people skills.
Carolina Amadio, Anna Teruzzi, Gloria Pietropolli, Luca Manzoni, Gianluca Coidessa, and Gianpiero Cossarini
Ocean Sci., 20, 689–710, https://doi.org/10.5194/os-20-689-2024, https://doi.org/10.5194/os-20-689-2024, 2024
Short summary
Short summary
Forecasting of marine biogeochemistry can be improved via the assimilation of observations. Floating buoys provide multivariate information about the status of the ocean interior. Information on the ocean interior can be expanded/augmented by machine learning. In this work, we show the enhanced impact of assimilating new in situ variables (oxygen) and reconstructed variables (nitrate) in the operational forecast system (MedBFM) model of the Mediterranean Sea.
Ieuan Higgs, Jozef Skákala, Ross Bannister, Alberto Carrassi, and Stefano Ciavatta
Biogeosciences, 21, 731–746, https://doi.org/10.5194/bg-21-731-2024, https://doi.org/10.5194/bg-21-731-2024, 2024
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A complex network is a way of representing which parts of a system are connected to other parts. We have constructed a complex network based on an ecosystem–ocean model. From this, we can identify patterns in the structure and areas of similar behaviour. This can help to understand how natural, or human-made, changes will affect the shelf sea ecosystem, and it can be used in multiple future applications such as improving modelling, data assimilation, or machine learning.
Krysten Rutherford, Katja Fennel, Lina Garcia Suarez, and Jasmin G. John
Biogeosciences, 21, 301–314, https://doi.org/10.5194/bg-21-301-2024, https://doi.org/10.5194/bg-21-301-2024, 2024
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We downscaled two mid-century (~2075) ocean model projections to a high-resolution regional ocean model of the northwest North Atlantic (NA) shelf. In one projection, the NA shelf break current practically disappears; in the other it remains almost unchanged. This leads to a wide range of possible future shelf properties. More accurate projections of coastal circulation features would narrow the range of possible outcomes of biogeochemical projections for shelf regions.
Robert W. Izett, Katja Fennel, Adam C. Stoer, and David P. Nicholson
Biogeosciences, 21, 13–47, https://doi.org/10.5194/bg-21-13-2024, https://doi.org/10.5194/bg-21-13-2024, 2024
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This paper provides an overview of the capacity to expand the global coverage of marine primary production estimates using autonomous ocean-going instruments, called Biogeochemical-Argo floats. We review existing approaches to quantifying primary production using floats, provide examples of the current implementation of the methods, and offer insights into how they can be better exploited. This paper is timely, given the ongoing expansion of the Biogeochemical-Argo array.
Li-Qing Jiang, Adam V. Subhas, Daniela Basso, Katja Fennel, and Jean-Pierre Gattuso
State Planet, 2-oae2023, 13, https://doi.org/10.5194/sp-2-oae2023-13-2023, https://doi.org/10.5194/sp-2-oae2023-13-2023, 2023
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This paper provides comprehensive guidelines for ocean alkalinity enhancement (OAE) researchers on archiving their metadata and data. It includes data standards for various OAE studies and a universal metadata template. Controlled vocabularies for terms like alkalinization methods are included. These guidelines also apply to ocean acidification data.
Katja Fennel, Matthew C. Long, Christopher Algar, Brendan Carter, David Keller, Arnaud Laurent, Jann Paul Mattern, Ruth Musgrave, Andreas Oschlies, Josiane Ostiguy, Jaime B. Palter, and Daniel B. Whitt
State Planet, 2-oae2023, 9, https://doi.org/10.5194/sp-2-oae2023-9-2023, https://doi.org/10.5194/sp-2-oae2023-9-2023, 2023
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This paper describes biogeochemical models and modelling techniques for applications related to ocean alkalinity enhancement (OAE) research. Many of the most pressing OAE-related research questions cannot be addressed by observation alone but will require a combination of skilful models and observations. We present illustrative examples with references to further information; describe limitations, caveats, and future research needs; and provide practical recommendations.
Eva Álvarez, Gianpiero Cossarini, Anna Teruzzi, Jorn Bruggeman, Karsten Bolding, Stefano Ciavatta, Vincenzo Vellucci, Fabrizio D'Ortenzio, David Antoine, and Paolo Lazzari
Biogeosciences, 20, 4591–4624, https://doi.org/10.5194/bg-20-4591-2023, https://doi.org/10.5194/bg-20-4591-2023, 2023
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Chromophoric dissolved organic matter (CDOM) interacts with the ambient light and gives the waters of the Mediterranean Sea their colour. We propose a novel parameterization of the CDOM cycle, whose parameter values have been optimized by using the data of the monitoring site BOUSSOLE. Nutrient and light limitations for locally produced CDOM caused aCDOM(λ) to covary with chlorophyll, while the above-average CDOM concentrations observed at this site were maintained by allochthonous sources.
Simone Spada, Anna Teruzzi, Stefano Maset, Stefano Salon, Cosimo Solidoro, and Gianpiero Cossarini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-170, https://doi.org/10.5194/gmd-2023-170, 2023
Revised manuscript under review for GMD
Short summary
Short summary
In geosciences, data assimilation (DA) combines modeled dynamics and observations to reduce simulation uncertainties. Uncertainties can be dynamically and effectively estimated in ensemble DA methods. With respect to current techniques, the novel GHOSH ensemble DA scheme is designed to improve accuracy by reaching a higher approximation order, without increasing computational costs, as demonstrated in idealized Lorenz96 tests and in realistic simulations of the Mediterranean Sea biogeochemistry
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
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The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
Valeria Di Biagio, Riccardo Martellucci, Milena Menna, Anna Teruzzi, Carolina Amadio, Elena Mauri, and Gianpiero Cossarini
State Planet, 1-osr7, 10, https://doi.org/10.5194/sp-1-osr7-10-2023, https://doi.org/10.5194/sp-1-osr7-10-2023, 2023
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Oxygen is essential to all aerobic organisms, and its content in the marine environment is continuously under assessment. By integrating observations with a model, we describe the dissolved oxygen variability in a sensitive Mediterranean area in the period 1999–2021 and ascribe it to multiple acting physical and biological drivers. Moreover, the reduction recognized in 2021, apparently also due to other mechanisms, requires further monitoring in light of its possible impacts.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Benjamin Richaud, Katja Fennel, Eric C. J. Oliver, Michael D. DeGrandpre, Timothée Bourgeois, Xianmin Hu, and Youyu Lu
The Cryosphere, 17, 2665–2680, https://doi.org/10.5194/tc-17-2665-2023, https://doi.org/10.5194/tc-17-2665-2023, 2023
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Sea ice is a dynamic carbon reservoir. Its seasonal growth and melt modify the carbonate chemistry in the upper ocean, with consequences for the Arctic Ocean carbon sink. Yet, the importance of this process is poorly quantified. Using two independent approaches, this study provides new methods to evaluate the error in air–sea carbon flux estimates due to the lack of biogeochemistry in ice in earth system models. Those errors range from 5 % to 30 %, depending on the model and climate projection.
Alexandre Mignot, Hervé Claustre, Gianpiero Cossarini, Fabrizio D'Ortenzio, Elodie Gutknecht, Julien Lamouroux, Paolo Lazzari, Coralie Perruche, Stefano Salon, Raphaëlle Sauzède, Vincent Taillandier, and Anna Teruzzi
Biogeosciences, 20, 1405–1422, https://doi.org/10.5194/bg-20-1405-2023, https://doi.org/10.5194/bg-20-1405-2023, 2023
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Numerical models of ocean biogeochemistry are becoming a major tool to detect and predict the impact of climate change on marine resources and monitor ocean health. Here, we demonstrate the use of the global array of BGC-Argo floats for the assessment of biogeochemical models. We first detail the handling of the BGC-Argo data set for model assessment purposes. We then present 23 assessment metrics to quantify the consistency of BGC model simulations with respect to BGC-Argo data.
Arnaud Laurent, Haiyan Zhang, and Katja Fennel
Biogeosciences, 19, 5893–5910, https://doi.org/10.5194/bg-19-5893-2022, https://doi.org/10.5194/bg-19-5893-2022, 2022
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The Changjiang is the main terrestrial source of nutrients to the East China Sea (ECS). Nutrient delivery to the ECS has been increasing since the 1960s, resulting in low oxygen (hypoxia) during phytoplankton decomposition in summer. River phosphorus (P) has increased less than nitrogen, and therefore, despite the large nutrient delivery, phytoplankton growth can be limited by the lack of P. Here, we investigate this link between P limitation, phytoplankton production/decomposition, and hypoxia.
Valeria Di Biagio, Stefano Salon, Laura Feudale, and Gianpiero Cossarini
Biogeosciences, 19, 5553–5574, https://doi.org/10.5194/bg-19-5553-2022, https://doi.org/10.5194/bg-19-5553-2022, 2022
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The amount of dissolved oxygen in the ocean is the result of interacting physical and biological processes. Oxygen vertical profiles show a subsurface maximum in a large part of the ocean. We used a numerical model to map this subsurface maximum in the Mediterranean Sea and to link local differences in its properties to the driving processes. This emerging feature can help the marine ecosystem functioning to be better understood, also under the impacts of climate change.
Marco Reale, Gianpiero Cossarini, Paolo Lazzari, Tomas Lovato, Giorgio Bolzon, Simona Masina, Cosimo Solidoro, and Stefano Salon
Biogeosciences, 19, 4035–4065, https://doi.org/10.5194/bg-19-4035-2022, https://doi.org/10.5194/bg-19-4035-2022, 2022
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Future projections under the RCP8.5 and RCP4.5 emission scenarios of the Mediterranean Sea biogeochemistry at the end of the 21st century show different levels of decline in nutrients, oxygen and biomasses and an acidification of the water column. The signal intensity is stronger under RCP8.5 and in the eastern Mediterranean. Under RCP4.5, after the second half of the 21st century, biogeochemical variables show a recovery of the values observed at the beginning of the investigated period.
Krysten Rutherford, Katja Fennel, Dariia Atamanchuk, Douglas Wallace, and Helmuth Thomas
Biogeosciences, 18, 6271–6286, https://doi.org/10.5194/bg-18-6271-2021, https://doi.org/10.5194/bg-18-6271-2021, 2021
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Using a regional model of the northwestern North Atlantic shelves in combination with a surface water time series and repeat transect observations, we investigate surface CO2 variability on the Scotian Shelf. The study highlights a strong seasonal cycle in shelf-wide pCO2 and spatial variability throughout the summer months driven by physical events. The simulated net flux of CO2 on the Scotian Shelf is out of the ocean, deviating from the global air–sea CO2 flux trend in continental shelves.
Anna Teruzzi, Giorgio Bolzon, Laura Feudale, and Gianpiero Cossarini
Biogeosciences, 18, 6147–6166, https://doi.org/10.5194/bg-18-6147-2021, https://doi.org/10.5194/bg-18-6147-2021, 2021
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During summer, maxima of phytoplankton chlorophyll concentration (DCM) occur in the subsurface of the Mediterranean Sea and can play a relevant role in carbon sequestration into the ocean interior. A numerical model based on in situ and satellite observations provides insights into the range of DCM conditions across the relatively small Mediterranean Sea and shows a western DCM that is 25 % shallower and with a higher phytoplankton chlorophyll concentration than in the eastern Mediterranean.
Bin Wang, Katja Fennel, and Liuqian Yu
Ocean Sci., 17, 1141–1156, https://doi.org/10.5194/os-17-1141-2021, https://doi.org/10.5194/os-17-1141-2021, 2021
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We demonstrate that even sparse BGC-Argo profiles can substantially improve biogeochemical prediction via a priori model tuning. By assimilating satellite surface chlorophyll and physical observations, subsurface distributions of physical properties and nutrients were improved immediately. The improvement of subsurface chlorophyll was modest initially but was greatly enhanced after adjusting the parameterization for light attenuation through further a priori tuning.
Thomas S. Bianchi, Madhur Anand, Chris T. Bauch, Donald E. Canfield, Luc De Meester, Katja Fennel, Peter M. Groffman, Michael L. Pace, Mak Saito, and Myrna J. Simpson
Biogeosciences, 18, 3005–3013, https://doi.org/10.5194/bg-18-3005-2021, https://doi.org/10.5194/bg-18-3005-2021, 2021
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Better development of interdisciplinary ties between biology, geology, and chemistry advances biogeochemistry through (1) better integration of contemporary (or rapid) evolutionary adaptation to predict changing biogeochemical cycles and (2) universal integration of data from long-term monitoring sites in terrestrial, aquatic, and human systems that span broad geographical regions for use in modeling.
Arnaud Laurent, Katja Fennel, and Angela Kuhn
Biogeosciences, 18, 1803–1822, https://doi.org/10.5194/bg-18-1803-2021, https://doi.org/10.5194/bg-18-1803-2021, 2021
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CMIP5 and CMIP6 models, and a high-resolution regional model, were evaluated by comparing historical simulations with observations in the northwest North Atlantic, a climate-sensitive and biologically productive ocean margin region. Many of the CMIP models performed poorly for biological properties. There is no clear link between model resolution and skill in the global models, but there is an overall improvement in performance in CMIP6 from CMIP5. The regional model performed best.
Valeria Di Biagio, Gianpiero Cossarini, Stefano Salon, and Cosimo Solidoro
Biogeosciences, 17, 5967–5988, https://doi.org/10.5194/bg-17-5967-2020, https://doi.org/10.5194/bg-17-5967-2020, 2020
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Events that influence the functioning of the Earth’s ecosystems are of interest in relation to a changing climate. We propose a method to identify and characterise
wavesof extreme events affecting marine ecosystems for multi-week periods over wide areas. Our method can be applied to suitable ecosystem variables and has been used to describe different kinds of extreme event waves of phytoplankton chlorophyll in the Mediterranean Sea, by analysing the output from a high-resolution model.
Haiyan Zhang, Katja Fennel, Arnaud Laurent, and Changwei Bian
Biogeosciences, 17, 5745–5761, https://doi.org/10.5194/bg-17-5745-2020, https://doi.org/10.5194/bg-17-5745-2020, 2020
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In coastal seas, low oxygen, which is detrimental to coastal ecosystems, is increasingly caused by man-made nutrients from land. This is especially so near mouths of major rivers, including the Changjiang in the East China Sea. Here a simulation model is used to identify the main factors determining low-oxygen conditions in the region. High river discharge is identified as the prime cause, while wind and intrusions of open-ocean water modulate the severity and extent of low-oxygen conditions.
Christopher Gordon, Katja Fennel, Clark Richards, Lynn K. Shay, and Jodi K. Brewster
Biogeosciences, 17, 4119–4134, https://doi.org/10.5194/bg-17-4119-2020, https://doi.org/10.5194/bg-17-4119-2020, 2020
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We describe a method for correcting errors in oxygen optode measurements on autonomous platforms in the ocean. The errors result from the relatively slow response time of the sensor. The correction method includes an in situ determination of the effective response time and requires the time stamps of the individual measurements. It is highly relevant for the BGC-Argo program and also applicable to gliders. We also explore if diurnal changes in oxygen can be obtained from profiling floats.
Bin Wang, Katja Fennel, Liuqian Yu, and Christopher Gordon
Biogeosciences, 17, 4059–4074, https://doi.org/10.5194/bg-17-4059-2020, https://doi.org/10.5194/bg-17-4059-2020, 2020
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We assess trade-offs between different types of biological observations, specifically satellite ocean color and BGC-Argo profiles and the benefits of combining both for optimizing a biogeochemical model of the Gulf of Mexico. Using all available observations leads to significant improvements in observed and unobserved variables (including primary production and C export). Our results highlight the significant benefits of BGC-Argo measurements for biogeochemical model optimization and validation.
Fabian Große, Katja Fennel, Haiyan Zhang, and Arnaud Laurent
Biogeosciences, 17, 2701–2714, https://doi.org/10.5194/bg-17-2701-2020, https://doi.org/10.5194/bg-17-2701-2020, 2020
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In the East China Sea, hypoxia occurs frequently from spring to fall due to high primary production and subsequent decomposition of organic matter. Nitrogen inputs from the Changjiang and the open ocean have been suggested to contribute to hypoxia formation. We used a numerical modelling approach to quantify the relative contributions of these nitrogen sources. We found that the Changjiang dominates, which suggests that nitrogen management in the watershed would improve oxygen conditions.
Liuqian Yu, Katja Fennel, Bin Wang, Arnaud Laurent, Keith R. Thompson, and Lynn K. Shay
Ocean Sci., 15, 1801–1814, https://doi.org/10.5194/os-15-1801-2019, https://doi.org/10.5194/os-15-1801-2019, 2019
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We present a first direct comparison of nonidentical versus identical twin approaches for an ocean data assimilation system. We show that the identical twin approach overestimates the value of assimilating satellite observations and undervalues the benefit of assimilating temperature and salinity profiles. Misleading assessments such as undervaluing the impact of observational assets are problematic and can lead to misguided decisions on balancing investments among different observing assets.
Stefano Salon, Gianpiero Cossarini, Giorgio Bolzon, Laura Feudale, Paolo Lazzari, Anna Teruzzi, Cosimo Solidoro, and Alessandro Crise
Ocean Sci., 15, 997–1022, https://doi.org/10.5194/os-15-997-2019, https://doi.org/10.5194/os-15-997-2019, 2019
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After 10 years of research and development, validated analysis and forecasts of the main parameters of the Mediterranean Sea biogeochemistry (e.g. phytoplankton, nutrients, oxygen, pH, carbon fluxes) at high spatial and temporal resolution are provided in the frame of the EU Copernicus Marine Environment Monitoring Service. Along with a traditional skill performance assessment, novel metrics exploiting the Biogeochemical Argo floats data are designed to estimate the forecasts uncertainty.
Oriol Tintó Prims, Mario C. Acosta, Andrew M. Moore, Miguel Castrillo, Kim Serradell, Ana Cortés, and Francisco J. Doblas-Reyes
Geosci. Model Dev., 12, 3135–3148, https://doi.org/10.5194/gmd-12-3135-2019, https://doi.org/10.5194/gmd-12-3135-2019, 2019
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Mixed-precision approaches can provide substantial speed-ups for both computing- and memory-bound codes, requiring little effort. A novel method to enable modern and legacy codes to benefit from a reduction of precision without sacrificing accuracy is presented. Using a precision emulator and a divide-and-conquer algorithm it identifies the parts that cannot handle reduced precision and the ones that can. The method has been proved using two ocean models, NEMO and ROMS, with promising results.
Katja Fennel, Simone Alin, Leticia Barbero, Wiley Evans, Timothée Bourgeois, Sarah Cooley, John Dunne, Richard A. Feely, Jose Martin Hernandez-Ayon, Xinping Hu, Steven Lohrenz, Frank Muller-Karger, Raymond Najjar, Lisa Robbins, Elizabeth Shadwick, Samantha Siedlecki, Nadja Steiner, Adrienne Sutton, Daniela Turk, Penny Vlahos, and Zhaohui Aleck Wang
Biogeosciences, 16, 1281–1304, https://doi.org/10.5194/bg-16-1281-2019, https://doi.org/10.5194/bg-16-1281-2019, 2019
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We review and synthesize available information on coastal ocean carbon fluxes around North America (NA). There is overwhelming evidence, compiled and discussed here, that the NA coastal margins act as a sink. Our synthesis shows the great diversity in processes driving carbon fluxes in different coastal regions, highlights remaining gaps in observations and models, and discusses current and anticipated future trends with respect to carbon fluxes and acidification.
Angela M. Kuhn, Katja Fennel, and Ilana Berman-Frank
Biogeosciences, 15, 7379–7401, https://doi.org/10.5194/bg-15-7379-2018, https://doi.org/10.5194/bg-15-7379-2018, 2018
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Recent studies demonstrate that marine N2 fixation can be carried out without light. However, direct measurements of N2 fixation in dark environments are relatively scarce. This study uses a model that represents biogeochemical cycles at a deep-ocean location in the Gulf of Aqaba (Red Sea). Different model versions are used to test assumptions about N2 fixers. Relaxing light limitation for marine N2 fixers improved the similarity between model results and observations of deep nitrate and oxygen.
Krysten Rutherford and Katja Fennel
Ocean Sci., 14, 1207–1221, https://doi.org/10.5194/os-14-1207-2018, https://doi.org/10.5194/os-14-1207-2018, 2018
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Using a regional model of the northwestern North Atlantic shelves, we calculate transport timescales and pathways in order to understand the transport processes that underlie the rapid oxygen loss, air–sea CO2 flux, and supply of plankton seed populations on the Scotian Shelf. Study results highlight the limited connectivity between the Scotian Shelf and adjacent slope waters; instead, the dominant southwestward currents bring Grand Banks and Gulf of St. Lawrence waters to the Scotian Shelf.
Katja Fennel and Arnaud Laurent
Biogeosciences, 15, 3121–3131, https://doi.org/10.5194/bg-15-3121-2018, https://doi.org/10.5194/bg-15-3121-2018, 2018
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Increasing human-derived nutrient inputs to coastal oceans lead to spreading dead zones around the world. Here a biogeochemical model for the northern Gulf of Mexico, where nutrients from the Mississippi River create the largest dead zone in North American coastal waters, is used for the first time to show the effects of single and dual nutrient reductions of nitrogen (N) and phosphorus (P). Significant reductions in N or N&P load would be required to significantly reduce hypoxia in this system.
Jonathan Lemay, Helmuth Thomas, Susanne E. Craig, William J. Burt, Katja Fennel, and Blair J. W. Greenan
Biogeosciences, 15, 2111–2123, https://doi.org/10.5194/bg-15-2111-2018, https://doi.org/10.5194/bg-15-2111-2018, 2018
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We report a detailed mechanistic investigation of the impact of Hurricane Arthur on the CO2 cycling on the Scotian Shelf. We can show that in contrast to common thinking, the deepening of the surface during the summer months can lead to increased CO2 uptake as carbon-poor waters from subsurface water are brought up to the surface. Only during prolonged storm events is the deepening of the mixed layer strong enough to bring the (expected) carbon-rich water to the surface.
Julia M. Moriarty, Courtney K. Harris, Katja Fennel, Marjorie A. M. Friedrichs, Kehui Xu, and Christophe Rabouille
Biogeosciences, 14, 1919–1946, https://doi.org/10.5194/bg-14-1919-2017, https://doi.org/10.5194/bg-14-1919-2017, 2017
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In coastal aquatic environments, resuspension of sediment and organic material from the seabed into the overlying water can impact biogeochemistry. Here, we used a novel modeling approach to quantify this impact for the Rhône River delta. In the model, resuspension increased oxygen consumption during individual resuspension events, and when results were averaged over 2 months. This implies that observations and models that only represent calm conditions may underestimate net oxygen consumption.
Gianpiero Cossarini, Stefano Querin, Cosimo Solidoro, Gianmaria Sannino, Paolo Lazzari, Valeria Di Biagio, and Giorgio Bolzon
Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017, https://doi.org/10.5194/gmd-10-1423-2017, 2017
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The BFMCOUPLER (v1.0) is a coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations. The online coupling is based on an open-source code characterizd by a modular structure. Modularity preserves the potentials of the two models, allowing for a sustainable programming effort to handle future evolutions in the two codes. The BFMCOUPLER code is released along with an idealized problem (a cyclonic gyre in a mid-latitude closed basin).
William J. Crawford, Polly J. Smith, Ralph F. Milliff, Jerome Fiechter, Christopher K. Wikle, Christopher A. Edwards, and Andrew M. Moore
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 171–192, https://doi.org/10.5194/ascmo-2-171-2016, https://doi.org/10.5194/ascmo-2-171-2016, 2016
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We present a method for estimating intrinsic model error in a model of the California Current System. The estimated model error covariance matrix is used in the weak constraint formulation of the Regional Ocean Modeling System, four-dimensional variational data assimilation system, and comparison of the circulation estimates computed in this way show demonstrable improvement to those computed in the strong constraint formulation, where intrinsic model error is not taken into account.
Zuo Xue, Ruoying He, Katja Fennel, Wei-Jun Cai, Steven Lohrenz, Wei-Jen Huang, Hanqin Tian, Wei Ren, and Zhengchen Zang
Biogeosciences, 13, 4359–4377, https://doi.org/10.5194/bg-13-4359-2016, https://doi.org/10.5194/bg-13-4359-2016, 2016
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In this study we used a state-of-the-science coupled physical–biogeochemical model to simulate and examine temporal and spatial variability of sea surface CO2 concentration in the Gulf of Mexico. Our model revealed the Gulf was a net CO2 sink with a flux of 1.11 ± 0.84 × 1012 mol C yr−1. We also found that biological uptake was the primary driver making the Gulf an overall CO2 sink and that the carbon flux in the northern Gulf was very susceptible to changes in river inputs.
Momme Butenschön, James Clark, John N. Aldridge, Julian Icarus Allen, Yuri Artioli, Jeremy Blackford, Jorn Bruggeman, Pierre Cazenave, Stefano Ciavatta, Susan Kay, Gennadi Lessin, Sonja van Leeuwen, Johan van der Molen, Lee de Mora, Luca Polimene, Sevrine Sailley, Nicholas Stephens, and Ricardo Torres
Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, https://doi.org/10.5194/gmd-9-1293-2016, 2016
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ERSEM 15.06 is a model for marine biogeochemistry and the lower trophic levels of the marine food web. It comprises a pelagic and benthic sub-model including the microbial food web and the major biogeochemical cycles of carbon, nitrogen, phosphorus, silicate, and iron using dynamic stochiometry. Further features include modules for the carbonate system and calcification. We present full mathematical descriptions of all elements along with examples at various scales up to 3-D applications.
A. Laurent, K. Fennel, R. Wilson, J. Lehrter, and R. Devereux
Biogeosciences, 13, 77–94, https://doi.org/10.5194/bg-13-77-2016, https://doi.org/10.5194/bg-13-77-2016, 2016
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In low oxygen environments, the lack of oxygen influences sediment biogeochemistry and in turn sediment-water fluxes. These nonlinear interactions are often missing from biogeochemical circulation models because sediment models are computationally expensive. A method for parameterizing realistic sediment-water fluxes is presented and applied to the Mississippi River Dead Zone where high primary production, stimulated by excess nutrient loads, promotes low bottom water conditions in summer.
L. Yu, K. Fennel, A. Laurent, M. C. Murrell, and J. C. Lehrter
Biogeosciences, 12, 2063–2076, https://doi.org/10.5194/bg-12-2063-2015, https://doi.org/10.5194/bg-12-2063-2015, 2015
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Our study suggests that a combination of physical processes and sediment oxygen consumption determine the spatial extent and temporal dynamics of hypoxia on the Louisiana shelf. In summer, stratification isolates oxygen-rich surface waters from hypoxic bottom waters; oxygen outgasses to the atmosphere at this time. A large fraction of primary production occurs below the pycnocline in summer, but this primary production does not strongly affect the spatial extent of hypoxic bottom waters.
G. Cossarini, P. Lazzari, and C. Solidoro
Biogeosciences, 12, 1647–1658, https://doi.org/10.5194/bg-12-1647-2015, https://doi.org/10.5194/bg-12-1647-2015, 2015
K.-K. Liu, C.-K. Kang, T. Kobari, H. Liu, C. Rabouille, and K. Fennel
Biogeosciences, 11, 7061–7075, https://doi.org/10.5194/bg-11-7061-2014, https://doi.org/10.5194/bg-11-7061-2014, 2014
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This paper provides background info on the East China Sea, Japan/East Sea and South China Sea and highlights major findings in the special issue on their biogeochemical conditions and ecosystem functions. The three seas are subject to strong impacts from human activities and/or climate forcing. Because these continental margins sustain arguably some of the most productive marine ecosystems in the world, changes in these stressed ecosystems may threaten the livelihood of a large human population.
Z. Xue, R. He, K. Fennel, W.-J. Cai, S. Lohrenz, and C. Hopkinson
Biogeosciences, 10, 7219–7234, https://doi.org/10.5194/bg-10-7219-2013, https://doi.org/10.5194/bg-10-7219-2013, 2013
W. J. Burt, H. Thomas, K. Fennel, and E. Horne
Biogeosciences, 10, 53–66, https://doi.org/10.5194/bg-10-53-2013, https://doi.org/10.5194/bg-10-53-2013, 2013
Cited articles
Álvarez, E., Lazzari, P., and Cossarini, G.: Phytoplankton diversity emerging from chromatic adaptation and competition for light, Prog. Oceanogr., 204, 102789, https://doi.org/10.1016/j.pocean.2022.102789, 2022.
Alvarez-Fanjul, E., Ciliberti, S., and Bahurel, P.: Implementing Operational Ocean Monitoring and Forecasting Systems. IOC-UNESCO, GOOS-275, https://doi.org/10.48670/ETOOFS, 2022.
Alvarez-Fanjul, E., Ciliberti, S., Pearlman, J., Wilmer-Becker, K., Bahurel, P., Ardhuin, F., Arnaud, A., Azizzadenesheli, K., Aznar, R., Bell, M., Bertino, L., Behera, S., Brassington, G., Calewaert, J. B., Capet, A., Chassignet, E., Ciavatta, S., Cirano, M., Clementi, E., Cornacchia, L., Cossarini, G., Coro, G., Corney, S., Davidson, F., Drevillon, M., Drillet, Y., Dussurget, R., El Serafy, G., Fearon, G., Fennel, K., Ford, D., Le Galloudec, O., Huang, X., Lellouche, J. M., Heimbach, P., Hernandez, F., Hogan, P., Hoteit, I., Joseph, S., Josey, S., Le Traon, P.-Y., Libralato, S., Mancini, M., Martin, M., Matte, P., McConnell, T., Melet, A., Miyazawa, Y., Moore, A. M., Novellino, A., O'Donncha, F., Porter, A., Qiao, F., Regan, H., Robert-Jones, J., Sanikommu, S., Schiller, A., Siddorn, J., Sotillo, M. G., Staneva, J., Thomas-Courcoux, C., Thupaki, P., Tonani, M., Garcia Valdecasas, J. M., Veitch, J., von Schuckmann, K., Wan, L., Wilkin, J., Zhong, A., and Zufic, R.: Promoting best practices in ocean forecasting through an Operational Readiness Level, Front. Mar. Sci., 11, 1443284, https://doi.org/10.3389/fmars.2024.1443284, 2024.
Amadio, C., Teruzzi, A., Pietropolli, G., Manzoni, L., Coidessa, G., and Cossarini, G.: Combining neural networks and data assimilation to enhance the spatial impact of Argo floats in the Copernicus Mediterranean biogeochemical model, Ocean Sci., 20, 689–710, https://doi.org/10.5194/os-20-689-2024, 2024.
Anderson, T. R., Christian, J. R., and Flynn, K. J.: Chapter 15 – Modeling DOM Biogeochemistry, Biogeochemistry of Marine Dissolved Organic Matter (Second Edition), edited by: Hansell, D. A. and Carlson, C. A., Academic Press, 635–667, https://doi.org/10.1016/B978-0-12-405940-5.00015-7, 2015.
Artioli, Y., Blackford, J. C., Butenschön, M., Holt, J. T., Wakelin, S. L., Thomas, H., Borges, A. V., and Allen, J. I.: The carbonate system in the North Sea: Sensitivity and model validation, J. Marine Syst., 102, 1–13, https://doi.org/10.1016/j.jmarsys.2012.04.006, 2012.
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015.
Baird, D., Christian, R. R., Peterson, C. H., and Johnson, G. A.: Consequences of hypoxia on estuarine ecosystem function: energy diversion from consumers to microbes, Ecol. Appl., 14, 805–822, https://doi.org/10.1890/02-5094, 2004.
Baird, M. E., Cherukuru, N., Jones, E., Margvelashvili, N., Mongin, M., Oubelkheir, K., and Wild-Allen, K. A.: Remote-sensing reflectance and true colour produced by a coupled hydrodynamic, optical, sediment, biogeochemical model of the Great Barrier Reef, Australia: comparison with satellite data. Environ. Model. Softw., 78, 79–96, https://doi.org/10.1016/j.envsoft.2015.11.025, 2016.
Baird, M. E., Wild-Allen, K. A., Parslow, J., Mongin, M., Robson, B., Skerratt, J., Rizwi, F., Soja-Woźniak, M., Jones, E., Herzfeld, M., Margvelashvili, N., Andrewartha, J., Langlais, C., Adams, M. P., Cherukuru, N., Gustafsson, M., Hadley, S., Ralph, P. J., Rosebrock, U., Schroeder, T., Laiolo, L., Harrison, D., and Steven, A. D. L.: CSIRO Environmental Modelling Suite (EMS): scientific description of the optical and biogeochemical models (vB3p0), Geosci. Model Dev., 13, 4503–4553, https://doi.org/10.5194/gmd-13-4503-2020, 2020.
Baretta, J. W., Ebenhöh, W., and Ruardij, P.: The European regional seas ecosystem model, a complex marine ecosystem model, Neth. J. Sea Res., 33, 233–246, https://doi.org/10.1016/0077-7579(95)90047-0, 1995.
Bell, M. J., Schiller, A., and Ciliberti, S.: Numerical Models for Simulating Ocean Physics, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 10, https://doi.org/10.5194/sp-5-opsr-10-2025, 2025.
Bieser, J., Amptmeijer, D. J., Daewel, U., Kuss, J., Soerensen, A. L., and Schrum, C.: The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish, Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, 2023.
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.
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, https://doi.org/10.5670/oceanog.2009.80, 2009.
Bruggeman, J. and Bolding, K.: A general framework for aquatic biogeochemical models, Environ. Model. Softw., 61, 249–265, https://doi.org/10.1016/j.envsoft.2014.04.002, 2014.
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y., Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin, G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley, S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels, Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, 2016.
Capet, A., Meysman, F. J. R., Akoumianaki, I., Soetaert, K., and Grégoire, M.: Integrating sediment biogeochemistry into 3D oceanic models: A study of benthic-pelagic coupling in the Black Sea, Ocean Model., 101, 83–100, https://doi.org/10.1016/j.ocemod.2016.03.006, 2016.
Ciavatta, S., Torres, R., Saux-Picart, S., and Allen, J. I.: Can ocean color assimilation improve biogeochemical hindcasts in shelf seas?, J. Geophys. Res.-Oceans, 116, C12043, https://doi.org/10.1029/2011JC007219, 2011.
Ciavatta, S., Torres, R., Martinez-Vicente, V., Smyth, T., Dall'Olmo, G., Polimene, L., and Allen, J. I.: Assimilation of remotely-sensed optical properties to improve marine biogeochemistry modelling, Prog. Oceanogr., 127, 74–95, 2014.
Ciavatta, S., Kay, S., Saux-Picard, S., Butenschön, M., and Allen, J. I.: Decadal reanalysis of biogeochemical indicators and fluxes in the North West European shelf-sea ecosystem, J. Geophys. Res.-Oceans, 121, 1824–1845, https://doi.org/10.1002/2015JC011496, 2016.
Ciavatta, S., Brewin, R. J. W., Skákala, J., Polimene, L., de Mora, L., Artioli, Y., and Allen, J. I.: Assimilation of ocean-color plankton functional types to improve marine ecosystem simulations, J. Geophys. Res.-Oceans, 123, 834–854, 2018.
Ciliberti, S. A., Grégoire, M., Staneva, J., Palazov, A., Coppini, G., Lecci, R., Peneva, E., Matreata, M., Marinova, V., Masina, S., and Pinardi, N.: Monitoring and Forecasting the Ocean State and Biogeochemical Processes in the Black Sea: Recent Developments in the Copernicus Marine Service, J. Mar. Sci. Eng., 9, 1146, https://doi.org/10.3390/jmse9101146, 2022.
Cossarini, G., Querin, S., and Solidoro, C.: The continental shelf carbon pump in the northern Adriatic Sea (Mediterranean Sea): Influence of wintertime variability, Ecol. Model., 314, 118–134, https://doi.org/10.1016/j.ecolmodel.2015.07.024, 2015a.
Cossarini, G., Lazzari, P., and Solidoro, C.: Spatiotemporal variability of alkalinity in the Mediterranean Sea, Biogeosciences, 12, 1647–1658, https://doi.org/10.5194/bg-12-1647-2015, 2015b.
Cossarini, G., Querin, S., Solidoro, C., Sannino, G., Lazzari, P., Di Biagio, V., and Bolzon, G.: Development of BFMCOUPLER (v1.0), the coupling scheme that links the MITgcm and BFM models for ocean biogeochemistry simulations, Geosci. Model Dev., 10, 1423–1445, https://doi.org/10.5194/gmd-10-1423-2017, 2017.
Cossarini, G., Mariotti, L., Feudale, L., Mignot, A., Salon, S., Taillandier, V., Teruzzi, A., and D'Ortenzio, F.: Towards operational 3D-Var assimilation of chlorophyll Biogeochemical-Argo float data into a biogeochemical model of the Mediterranean Sea, Ocean Model., 133, 112–128, https://doi.org/10.1016/j.ocemod.2018.11.005, 2019.
Cossarini G., Feudale, L., Teruzzi, A., Bolzon, G., Coidessa, G., Solidoro, C., Di Biagio, V., Amadio, C., Lazzari, P., Brosich, A., and Salon, S.: High-Resolution Reanalysis of the Mediterranean Sea Biogeochemistry (1999–2019), Front. Mar. Sci., 8, 1–21, https://doi.org/10.3389/fmars.2021.741486, 2021.
Daewel, U. and Schrum, C.: Simulating long-term dynamics of the coupled North Sea and Baltic Sea ecosystem with ECOSMO II: Model description and validation. J. Marine Syst., 119–120, 30–49, https://doi.org/10.1016/j.jmarsys.2013.03.008, 2013.
Dutkiewicz, S., Follows, M. J., and Bragg, J. G.: Modeling the coupling of ocean ecology and biogeochemistry, Global Biogeochem. Cy., 23, 1–15, 2009.
Eilola, K., Meier, H. E. M., and Almroth, E.: On the dynamics of oxygen, phosphorus and cyanobacteria in the Baltic Sea: a model study, J. Marine Syst., 75, 163–184, https://doi.org/10.1016/j.jmarsys.2008.08.009, 2009.
Falls, M., Bernardello, R., Castrillo, M., Acosta, M., Llort, J., and Galí, M.: Use of genetic algorithms for ocean model parameter optimisation: a case study using PISCES-v2_RC for North Atlantic particulate organic carbon, Geosci. Model Dev., 15, 5713–5737, https://doi.org/10.5194/gmd-15-5713-2022, 2022.
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, https://elischolar.library.yale.edu/journal_of_marine_research/1981 (last access: 18 April 2025), 1990.
Feng, Y., Friedrichs, M. A. M., Wilkin, J., Tian, H., Yang, Q., Hofmann, E. E., Wiggert, J. D., and Hood, R. R.: Chesapeake Bay nitrogen fluxes derived from a land-estuarine-ocean biogeochemical modeling system: model description, evaluation and nitrogen budgets, J. Geophys. Res.-Biogeo., 120, 1666–1695, https://doi.org/10.1002/2015JG002931, 2015.
Fennel, K., Hetland, R., Feng, Y., and DiMarco, S.: A coupled physical-biological model of the Northern Gulf of Mexico shelf: model description, validation and analysis of phytoplankton variability, Biogeosciences, 8, 1881–1899, https://doi.org/10.5194/bg-8-1881-2011, 2011.
Fennel, K., Gehlen, M., Brasseur, P., Brown, C. W., Ciavatta, S., Cossarini, G., Crise, A., Edwards, C. A., Ford, D., Friedrichs, M. A., and Gregoire, M.: Advancing marine biogeochemical and ecosystem reanalyses and forecasts as tools for monitoring and managing ecosystem health, Front. Mar. Sci., 6, 89, https://doi.org/10.3389/fmars.2019.00089, 2019.
Fennel, K., Mattern, J. P., Doney, S. C., Bopp, L., Moore, A. M., Wang, B., and Yu, L.: Ocean biogeochemical modelling, Nature Reviews Methods Primers, 2, 76, https://doi.org/10.1038/s43586-022-00154-2, 2022.
Fennel, K., Long, M. C., Algar, C., Carter, B., Keller, D., Laurent, A., Mattern, J. P., Musgrave, R., Oschlies, A., Ostiguy, J., Palter, J. B., and Whitt, D. B.: Modelling considerations for research on ocean alkalinity enhancement (OAE), in: Guide to Best Practices in Ocean Alkalinity Enhancement Research, edited by: Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gattuso, J.-P., Copernicus Publications, State Planet, 2-oae2023, 9, https://doi.org/10.5194/sp-2-oae2023-9-2023, 2023.
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.
Follows, M. J., Dutkiewicz, S. Grant, S., and Chisholm, S.W.: Emergent biogeography of microbial communities in a model ocean, Science, 315, 1843–1846, https://doi.org/10.1126/science.1138544, 2007.
Fontana, C., Brasseur, P., and Brankart, J.-M.: Toward a multivariate reanalysis of the North Atlantic Ocean biogeochemistry during 1998–2006 based on the assimilation of SeaWiFS chlorophyll data, Ocean Sci., 9, 37–56, https://doi.org/10.5194/os-9-37-2013, 2013.
Ford, D. and Barciela, R.: Global marine biogeochemical reanalyses assimilating two different sets ofmerged ocean colour products, Remote Sens. Environ., 203, 40–54, https://doi.org/10.1016/j.rse.2017.03.040, 2017.
Ford, D., Key, S., McEwan, R., Totterdell, I., and Gehlen, M.: Marine biogeochemical modelling and data assimilation for operational forecasting, reanalysis, and climate research, in: New Frontiers in Operational Oceanography, edited by: Chassignet, E., Pascual, A., Tintoré, J., and Verron, J., GODAE OceanView, 625–652, https://doi.org/10.17125/gov2018.ch22, 2018.
Ford, D. A., Grossberg, S., Rinaldi, G., Menon, P. P., Palmer, M. R., Skakala, J., Smyth, T., Williams, C. A. J., Lopez, A. L., and Ciavatta, S.: A solution for autonomous, adaptive monitoring of coastal ocean ecosystems: Integrating ocean robots and operational forecasts, Front. Mar. Sci., 9, 1067174, https://doi.org/10.3389/fmars.2022.1067174, 2022.
Gehlen, M., Barciela, R., Bertino, L., Brasseur, P., Butenschön, M., Chai, F., and Simon, E.: Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments, J. Oper. Oceanogr., 8, s168–s187, https://doi.org/10.1080/1755876X.2015.1022350, 2015.
Geider, R. J., MacIntyre, H. L., and Kana, T. M.: Dynamic model of phytoplankton growth and acclimation: responses of the balanced growth rate and the chlorophyll a: carbon ratio to light, nutrient-limitation and temperature, Mar. Ecol. Prog. Ser., 148, 187–200, http://www.jstor.org/stale/24857483 (last access: 18 April 2025), 1997.
Glibert, P. M. and Mitra, A.: From webs, loops, shunts, and pumps to microbial multitasking: Evolving concepts of marine microbial ecology, the mixoplankton paradigm, and implications for a future ocean, Limnol. Oceanogr., 67, 585–597, https://doi.org/10.1002/lno.12018, 2022.
Grégoire, M. and Soetaert, K.: Carbon, nitrogen, oxygen and sulfide budgets in the Black Sea: A biogeochemical model of the whole water column coupling the oxic and anoxic parts, Ecol. Model., 221, 2287–2301, https://doi.org/10.1016/j.ecolmodel.2010.06.007, 2010.
Grégoire, M., Raick, C., and Soetaert, K.: Numerical modeling of the deep Black Sea ecosystem functioning during the late 80's (eutrophication phase), Prog. Oceanogr., 76, 286–333, https://doi.org/10.1016/j.pocean.2008.01.002, 2008.
Grégoire, M., Garçon, V., Garcia, H., Breitburg, D., Isensee, K., Oschlies, A., Telszewski, M., Barth, A., Bittig, H.C., Carstensen, J., and Carval, T.: A global ocean oxygen database and atlas for assessing and predicting deoxygenation and ocean health in the open and coastal ocean. Front. Mar. Sci., 8, 724913, https://doi.org/10.3389/fmars.2021.724913, 2021.
Gutknecht, E., Reffray, G., Mignot, A., Dabrowski, T., and Sotillo, M. G.: Modelling the marine ecosystem of Iberia–Biscay–Ireland (IBI) European waters for CMEMS operational applications, Ocean Sci., 15, 1489–1516, https://doi.org/10.5194/os-15-1489-2019, 2019.
Gutknecht, E., Bertino, L., Brasseur, P., Ciavatta, S., Cossarini, G., Fennel, K., Ford, D., Grégoire M., Lavoie D., and Lehodey, P.: Biogeochemical Modelling, in: Implementing Operational Ocean Monitoring and Forecasting Systems, edited by: Alvarez-Franjul, E., Ciliberti, S., and Bahurel, P., IOC-UNESCO, GOOS-275, https://doi.org/10.48670/ETOOFS, 2022.
Heinze, C. and Gehlen, M.: Chapter 26: Modelling ocean biogeochemical processes and resulting tracer distributions, Int. Geophys., 103, 667–694, https://doi.org/10.1016/B978-0-12-391851-2.00026-X, 2013.
Hernandez, F., Smith, G., Baetens, K., Cossarini, G., Garcia-Hermosa, I., Drévillon, M., Maksymczuk, J., Melet, A., Régnier, C., and Schuckmann, K. V.: Measuring performances, skill and accuracy in operational oceanography: new challenges and approaches, in: New Frontiers in Operational Oceanography, edited by: Chassignet, E., Pascual, A., Tintoré, J., and Verron, J., GODAE OceanView, 759–796, https://doi.org/10.17125/gov2018.ch29, 2018.
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., and Friedrichs, M. A.: 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.
Irby, I. D. and Friedrichs, M. A. M.: Evaluating confidence in the impact of regulatory nutrient reduction on Chesapeake Bay water quality, Estuar. Coasts, 42, 16–32, https://www.jstor.org/stable/48703007 (last access: 18 April 2025), 2019.
Irby, I. D., Friedrichs, M. A. M., Da, F., and Hinson, K. E.: The competing impacts of climate change and nutrient reductions on dissolved oxygen in Chesapeake Bay, Biogeosciences, 15, 2649–2668, https://doi.org/10.5194/bg-15-2649-2018, 2018.
Jones, E. M., Baird, M. E., Mongin, M., Parslow, J., Skerratt, J., Lovell, J., Margvelashvili, N., Matear, R. J., Wild-Allen, K., Robson, B., Rizwi, F., Oke, P., King, E., Schroeder, T., Steven, A., and Taylor, J.: Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef, Biogeosciences, 13, 6441–6469, https://doi.org/10.5194/bg-13-6441-2016, 2016.
Kishi, M. J., Kashiwai, M., Ware, D. M., Megrey, B. A., Eslinger, D. L., and Werner, F. E.: NEMURO A lower trophic level model for the north pacific marine ecosystem, Ecol. Model., 202, 12–25, https://doi.org/10.1016/j.ecolmodel.2006.08.021, 2007.
Kishi, M. J., Ito, S. I., Megrey, B. A., Rose, K. A., and Werner, F. E.: A review of the NEMURO and NEMURO.FISH models and their application to marine ecosystem investigations, J. Oceanogr., 67, 3–16, https://doi.org/10.1007/s10872-011-0009-4, 2011.
Klausmeier, C. A., Litchman, E., and Levin, S. A.: Phytoplankton growth and stoichiometry under multiple nutrient limitation, Limnol. Oceanogr., 49, 1463–1470, https://doi.org/10.4319/lo.2004.49.4_part_2.1463, 2004.
Kwiatkowski, L., Yool, A., Allen, J. I., Anderson, T. R., Barciela, R., Buitenhuis, E. T., Butenschön, M., Enright, C., Halloran, P. R., Le Quéré, C., de Mora, L., Racault, M.-F., Sinha, B., Totterdell, I. J., and Cox, P. M.: iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework, Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, 2014.
Kwiatkowski, L., Aumont, O., Bopp, L., and Ciais, P.: The impact of variable phytoplankton stoichiometry on projections of primary production, food quality, and carbon uptake in the global ocean, Global Biogeochem. Cy., 32, 516–528, 2018.
Laurent, A., Fennel, K., Cai, W.-J. Huang, W.-J, Barbero, L., and Wanninkhof, R.: Eutrophication induced acidification of coastal waters in the northern Gulf of Mexico: Insights into origin and processes from a coupled physical-biogeochemical model, Geophys. Res. Lett., 44, 946–956, https://doi.org/10.1002/2016GL071881, 2017.
Lazzari, P., Salon, S., Terzić, E., Gregg, W. W., D'Ortenzio, F., Vellucci, V., Organelli, E., and Antoine, D.: Assessment of the spectral downward irradiance at the surface of the Mediterranean Sea using the radiative Ocean-Atmosphere Spectral Irradiance Model (OASIM), Ocean Sci., 17, 675–697, https://doi.org/10.5194/os-17-675-2021, 2021.
Legendre, L. and Rassoulzadegan, F.: Plankton and nutrient dynamics in marine water, Ophelia, 41, 153–172, https://doi.org/10.1080/00785236.1995.10422042, 1995.
Lenton, T. M. and Watson, A. J.: Redfield revisited: 1. Regulation of nitrate, phosphate, and oxygen in the ocean, Global Biogeochem. Cy., 14, 225–248, https://doi.org/10.1029/1999GB900065, 2000.
Le Traon, P.-Y., Reppucci, A., Alvarez Fanjul, E., Aouf, L., Behrens, A., Belmonte, M., Bentamy, A., Bertino, L., Brando, V. E., Kreiner, M. B., Benkiran, M., Carval, T., Ciliberti, S. A., Claustre, H., Clementi, E., Coppini, G., Cossarini, G., De Alfonso Alonso-Muñoyerro, M., Delamarche, A., Dibarboure, G., Dinessen, F., Drevillon, M., Drillet, Y., Faugere, Y., Fernández, V., Fleming, A., Garcia-Hermosa, M. I., Sotillo, M. G., Garric, G., Gasparin, F., Giordan,C., Gehlen, M., Gregoire, M. L., Guinehut, S., Hamon, M., Harris, C., Hernandez, F., Hinkler, J. B., Hoyer, J., Karvonen, J., Kay, S., King, R., Lavergne, T., Lemieux-Dudon, B., Lima, L., Mao, C., Martin, M. J., Masina, S., Melet, A., Buongiorno Nardelli, B., Nolan, G., Pascual, A., Pistoia, J., Palazov, A., Piolle, J. F., Pujol, M. I., Pequignet, A. C., Peneva, E., Pérez Gómez, B., Petit de la Villeon, L., Pinardi, N., Pisano, A., Pouliquen, S., Reid, R., Remy, E., Santoleri, R., Siddorn, J., She, J., Staneva, J., Stoffelen, A., Tonani, M., Vandenbulcke, L., von Schuckmann, K., Volpe, G., Wettre, C., and Zacharioudaki, A.: From Observation to Information and Users: The Copernicus Marine Service Perspective, Front. Mar. Sci., 6, 1–22, https://doi.org/10.3389/fmars.2019.00234, 2019.
Libralato, S.: Numerical Models for Monitoring and Forecasting Ocean Ecosystems: a short description of present status, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 13, https://doi.org/10.5194/sp-5-opsr-13-2025, 2025.
Litchman, E. and Klausmeier, C. A.: Trait-based community ecology of phytoplankton, Annu. Rev. Ecol. Evol. S., 39, 615–639, https://doi.org/10.1146/annurev.ecolsys.39.110707.173549, 2008.
Liu, Y., Meier, H. E. M., and Eilola, K.: Nutrient transports in the Baltic Sea – results from a 30-year physical–biogeochemical reanalysis, Biogeosciences, 14, 2113–2131, https://doi.org/10.5194/bg-14-2113-2017, 2017.
Melaku Canu, D., Rosati, G., Solidoro, C., Heimbürger, L.-E., and Acquavita, A.: A comprehensive assessment of the mercury budget in the Marano–Grado Lagoon (Adriatic Sea) using a combined observational modeling approach, Mar. Chem., 177, 742–752, https://doi.org/10.1016/j.marchem.2015.10.013, 2015.
Mignot, A., Claustre, H., Cossarini, G., D'Ortenzio, F., Gutknecht, E., Lamouroux, J., Lazzari, P., Perruche, C., Salon, S., Sauzède, R., Taillandier, V., and Teruzzi, A.: Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design, Biogeosciences, 20, 1405–1422, https://doi.org/10.5194/bg-20-1405-2023, 2023.
Mitra, A., Castellani, C., Gentleman, W. C., Jónasdóttir, S. H., Flynn, K. J., Bode, A., Halsband, C., Kuhn, P., Licandro, P., Agersted, M.D., and Calbet, A.: Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link, Prog. Oceanogr., 129, 176–199, https://doi.org/10.1016/j.pocean.2014.04.025, 2014.
Mongin, M., Baird, M. E., Tilbrook, B., Matear, R. J., Lenton, A., Herzfeld, M., Wild-Allen, K., Skerratt, J., Margvelashvili, N., Robson, B. J., and Duarte, C. M.: The exposure of the Great Barrier Reef to ocean acidification, Nat. Commun., 7, 10732, https://doi.org/10.1038/ncomms10732, 2016.
Nerger, L. and Gregg, W. W.: Improving assimilation of SeaWiFS data by the application of bias correction with a local SEIK filter, J. Marine Syst., 73, 87–102, https://doi.org/10.1016/j.jmarsys.2007.09.007, 2008.
Neumann, T.: Towards a 3D-ecosystem model of the Baltic Sea, J. Marine Syst., 25, 405–419, https://doi.org/10.1016/S0924-7963(00)00030-0, 2000.
Neumann, T., Siegel, H., and Gerth, M.: A new radiation model for Baltic Sea ecosystem modelling, J. Marine Syst., 152, 83–91, https://doi.org/10.1016/j.jmarsys.2015.08.001, 2015.
Palmer, J. R. and Totterdell, I. J.: Production and export in a global ocean ecosystem model, Deep-Sea Res. Pt. I, 48, 1169–1198, https://doi.org/10.1016/S0967-0637(00)00080-7, 2001.
Pradhan, H. K., Völker, C., Losa, S. N., Bracher, A., and Nerger, L.: Global assimilation of ocean-color data of phytoplankton functional types: Impact of different data sets, J. Geophys. Res.-Oceans, 125, e2019JC015586, https://doi.org/10.1029/2019JC015586, 2020.
Redfield, A. C.: On the proportions of organic derivatives in sea water and their relation to the composition of plankton, vol. 1, University Press of Liverpool, 1934.
Rosati, G., Canu, D., Lazzari, P., and Solidoro, C.: Assessing the spatial and temporal variability of methylmercury biogeochemistry and bioaccumulation in the Mediterranean Sea with a coupled 3D model, Biogeosciences, 19, 3663–3682, https://doi.org/10.5194/bg-19-3663-2022, 2022.
Salon, S., Cossarini, G., Bolzon, G., Feudale, L., Lazzari, P., Teruzzi, A., Solidoro, C., and Crise, A.: Novel metrics based on Biogeochemical Argo data to improve the model uncertainty evaluation of the CMEMS Mediterranean marine ecosystem forecasts, Ocean Sci., 15, 997–1022, https://doi.org/10.5194/os-15-997-2019, 2019.
Schmidtko, S., Stramma, L., and Visbeck, M.: Decline in global oceanic oxygen content during the past five decades, Nature, 542, 335–339, https://doi.org/10.1038/nature21399, 2017.
Séférian, R., Berthet, S., Yool, A., Palmiéri, J., Bopp, L., Tagliabue, A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., and Gehlen, M.: Tracking improvement in simulated marine biogeochemistry between CMIP5 and CMIP6, Current Climate Change Reports, 6, 95–119, https://doi.org/10.1007/s40641-020-00160-0, 2020.
Skákala, J., Ford, D., Brewin, R. J., McEwan, R., Kay, S., Taylor, B., De Mora, L., and Ciavatta, S.: The assimilation of phytoplankton functional types for operational forecasting in the northwest European shelf, J. Geophys. Res.-Oceans, 123, 5230–5247, 2018.
Skákala, J., Bruggeman, J., Brewin, R. J., Ford, D. A., and Ciavatta, S.: Improved representation of underwater light field and its impact on ecosystem dynamics: A study in the North Sea, J. Geophys. Res.-Oceans, 125, e2020JC016122, https://doi.org/10.1029/2020JC016122, 2020.
Skákala, J., Ford, D., Bruggeman, J., Hull, T., Kaiser, J., King, R. R., Loveday, B., Palmer, M. R., Smyth, T., Williams, C. A., and Ciavatta, S.: Towards a multi-platform assimilative system for North Sea biogeochemistry, J. Geophys. Res.-Oceans, 126, e2020JC016649, https://doi.org/10.1029/2020JC016649, 2021.
Soetaert, K., Middelburg, J. J., Herman, P. M., and Buis, K.: On the coupling of benthic and pelagic biogeochemical models, Earth-Sci. Rev., 51, 173–201, https://doi.org/10.1016/S0012-8252(00)00004-0, 2000.
Tagliabue, A., Bopp, L., and Gehlen, M.: The response of marine carbon and nutrient cycles to ocean acidification: large uncertainties related to phytoplankton physiological assumptions, Global Biogeochem. Cy., 25, GB3017, https://doi.org/10.1029/2010GB003929, 2011.
Teruzzi, A., Dobricic, S., Solidoro, C., and Cossarini, G.: A 3-D variational assimilation scheme in coupled transport-biogeochemical models: Forecast of Mediterranean biogeochemical properties, J. Geophys. Res.-Oceans, 119, 200–217, https://doi.org/10.1002/2013JC009277, 2014.
Teruzzi, A., Bolzon, G., Feudale, L., and Cossarini, G.: Deep chlorophyll maximum and nutricline in the Mediterranean Sea: emerging properties from a multi-platform assimilated biogeochemical model experiment, Biogeosciences, 18, 6147–6166, https://doi.org/10.5194/bg-18-6147-2021, 2021.
Travers, M., Shin, Y. J., Jennings, S., Machu, E., Huggett, J. A., Field, J. G., and Cury, P. M.: Two-way coupling versus one-way forcing of plankton and fish models to predict ecosystem changes in the Benguela, Ecol. Model., 220, 3089–3099, https://doi.org/10.1016/j.ecolmodel.2009.08.016, 2009.
Verdy, A. and Mazloff, M. R.: A data assimilating model for estimating Southern Ocean biogeochemistry, J. Geophys. Res.-Oceans, 122, 6968–6988, 2017.
Vichi, M., Pinardi, N., and Masina, S.: A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: Theory, J. Marine Syst., 64, 89–109, https://doi.org/10.1016/j.jmarsys.2006.03.006, 2017.
Wagner, C. C., Amos, H. M., Thackray, C. P., Zhang, Y., Lundgren, E. W., Forget, G., and Sunderland, E. M.: A global 3-D ocean model for PCBs: Benchmark compounds for understanding the impacts of global change on neutral persistent organic pollutants, Global Biogeochem. Cy., 33, 469–481, https://doi.org/10.1029/2018GB006018, 2019.
Wang, B., Fennel, K., Yu, L., and Gordon, C.: Assessing the value of biogeochemical Argo profiles versus ocean color observations for biogeochemical model optimization in the Gulf of Mexico, Biogeosciences, 17, 4059–4074, https://doi.org/10.5194/bg-17-4059-2020, 2020.
Xiao, Y. and Friedrichs, M. A. M.: Using biogeochemical data assimilation to assess the relative skill of multiple ecosystem models in the Mid-Atlantic Bight: effects of increasing the complexity of the planktonic food web, Biogeosciences, 11, 3015–3030, https://doi.org/10.5194/bg-11-3015-2014, 2014.
Yumruktepe, V. Ç., Samuelsen, A., and Daewel, U.: ECOSMO II(CHL): a marine biogeochemical model for the North Atlantic and the Arctic, Geosci. Model Dev., 15, 3901–3921, https://doi.org/10.5194/gmd-15-3901-2022, 2022.
Yumruktepe, V. Ç., Mousing, E. A., Tjiputra, J., and Samuelsen, A.: An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas, Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, 2023.
Zeebe, R. E. and Wolf-Gladrow, D.: CO2 in seawater: equilibrium, kinetics, isotopes, Elsevier Science, ISBN 9780444509468, 2001.
Zhang, Y., Soerensen, A. L., Schartup, A. T., and Sunderland, E. M.: A global model for methylmercury formation and uptake at the base of marine food webs, Global Biogeochem. Cy., 34, 1–21, https://doi.org/10.1029/2019GB006348, 2020.
Short summary
Marine biogeochemistry refers to the cycling of chemical elements resulting from physical transport, chemical reaction, uptake, and processing by living organisms. Biogeochemical models can have a wide range of complexity, from a single nutrient to fully explicit representations of multiple nutrients, trophic levels, and functional groups. Uncertainty sources are the lack of knowledge about the parameterizations, the initial and boundary conditions, and the lack of observations.
Marine biogeochemistry refers to the cycling of chemical elements resulting from physical...
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