Articles | Volume 22, issue 5
https://doi.org/10.5194/bg-22-1215-2025
© 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/bg-22-1215-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Mixing, spatial resolution and argon saturation in a suite of coupled general ocean circulation biogeochemical models off Mauritania
Heiner Dietze
CORRESPONDING AUTHOR
Department of Computer Science, Archaeoinformatics – Data Science, University of Kiel, Kiel, Germany
Department of Chemistry, King's College London, London, UK
Ulrike Löptien
Department of Computer Science, Archaeoinformatics – Data Science, University of Kiel, Kiel, Germany
Related authors
Heiner Dietze and Ulrike Löptien
Biogeosciences, 18, 4243–4264, https://doi.org/10.5194/bg-18-4243-2021, https://doi.org/10.5194/bg-18-4243-2021, 2021
Short summary
Short summary
In recent years fish-kill events caused by oxygen deficit have been reported in Eckernförde Bight (Baltic Sea). This study sets out to understand the processes causing respective oxygen deficits by combining high-resolution coupled ocean circulation biogeochemical modeling, monitoring data, and artificial intelligence.
Ulrike Löptien and Heiner Dietze
Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, https://doi.org/10.5194/bg-16-1865-2019, 2019
Short summary
Short summary
Anthropogenic greenhouse gas emissions trigger complex climate feedbacks. Output form Earth system models provides a basis for related political decision-making. One challenge is to arrive at reliable model parameter estimates for the ocean biogeochemistry module. We illustrate pitfalls through which flaws in the ocean module are masked by wrongly tuning the biogeochemistry and discuss ensuing uncertainties in climate projections.
Karin F. Kvale, Samar Khatiwala, Heiner Dietze, Iris Kriest, and Andreas Oschlies
Geosci. Model Dev., 10, 2425–2445, https://doi.org/10.5194/gmd-10-2425-2017, https://doi.org/10.5194/gmd-10-2425-2017, 2017
Short summary
Short summary
Computer models of ocean biology and chemistry are becoming increasingly complex, and thus more expensive, to run. One solution is to approximate the behaviour of the ocean physics and store that information outside of the model. That
offlineinformation can then be used to calculate a steady-state solution from the model's biology and chemistry, without waiting for a traditional
onlineintegration to complete. We show this offline method reproduces online results and is 100 times faster.
Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, https://doi.org/10.5194/bg-14-1561-2017, 2017
Short summary
Short summary
The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
Yonss Saranga José, Heiner Dietze, and Andreas Oschlies
Biogeosciences, 14, 1349–1364, https://doi.org/10.5194/bg-14-1349-2017, https://doi.org/10.5194/bg-14-1349-2017, 2017
Short summary
Short summary
This study aims to investigate the diverse subsurface nutrient patterns observed within anticyclonic eddies in the upwelling system off Peru. Two simulated anticyclonic eddies with opposing subsurface nitrate concentrations were analysed. The results show that diverse nutrient patterns within anticyclonic eddies are related to the presence of water mass from different origins at different depths, responding to variations in depth of the circulation strength at the edge of the eddy.
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
Short summary
Short summary
Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
Short summary
Short summary
Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 2014
A. Landolfi, H. Dietze, W. Koeve, and A. Oschlies
Biogeosciences, 10, 1351–1363, https://doi.org/10.5194/bg-10-1351-2013, https://doi.org/10.5194/bg-10-1351-2013, 2013
Henrike Schmidt, Julia Getzlaff, Ulrike Löptien, and Andreas Oschlies
Ocean Sci., 17, 1303–1320, https://doi.org/10.5194/os-17-1303-2021, https://doi.org/10.5194/os-17-1303-2021, 2021
Short summary
Short summary
Oxygen-poor regions in the open ocean restrict marine habitats. Global climate simulations show large uncertainties regarding the prediction of these areas. We analyse the representation of the simulated oxygen minimum zones in the Arabian Sea using 10 climate models. We give an overview of the main deficiencies that cause the model–data misfit in oxygen concentrations. This detailed process analysis shall foster future model improvements regarding the oxygen minimum zone in the Arabian Sea.
Heiner Dietze and Ulrike Löptien
Biogeosciences, 18, 4243–4264, https://doi.org/10.5194/bg-18-4243-2021, https://doi.org/10.5194/bg-18-4243-2021, 2021
Short summary
Short summary
In recent years fish-kill events caused by oxygen deficit have been reported in Eckernförde Bight (Baltic Sea). This study sets out to understand the processes causing respective oxygen deficits by combining high-resolution coupled ocean circulation biogeochemical modeling, monitoring data, and artificial intelligence.
Britta Munkes, Ulrike Löptien, and Heiner Dietze
Biogeosciences, 18, 2347–2378, https://doi.org/10.5194/bg-18-2347-2021, https://doi.org/10.5194/bg-18-2347-2021, 2021
Short summary
Short summary
Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood, which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtaposition of respective field and laboratory studies with state-of-the-art mathematical models reveals substantial uncertainty associated with nutrient demands, grazing, and death of cyanobacteria.
Ulrike Löptien and Heiner Dietze
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-96, https://doi.org/10.5194/bg-2020-96, 2020
Manuscript not accepted for further review
Short summary
Short summary
Nitrogen fixation, conducted by specific microorganisms, makes molecular nitrogen available for marine biota. By this means this process exerts major control on the growth of algae in the ocean. This study compares two contemporary paradigms, anticipating the ecological niche of N-fixing organisms in an Earth System Model. We illustrate respective uncertainties in climate projections and suggest specific observations to advance the reliable representation of nitrogen fixation in numerical models.
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, https://doi.org/10.5194/gmd-13-71-2020, 2020
Short summary
Short summary
We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
Ulrike Löptien and Heiner Dietze
Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, https://doi.org/10.5194/bg-16-1865-2019, 2019
Short summary
Short summary
Anthropogenic greenhouse gas emissions trigger complex climate feedbacks. Output form Earth system models provides a basis for related political decision-making. One challenge is to arrive at reliable model parameter estimates for the ocean biogeochemistry module. We illustrate pitfalls through which flaws in the ocean module are masked by wrongly tuning the biogeochemistry and discuss ensuing uncertainties in climate projections.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Volkmar Sauerland, Ulrike Löptien, Claudine Leonhard, Andreas Oschlies, and Anand Srivastav
Geosci. Model Dev., 11, 1181–1198, https://doi.org/10.5194/gmd-11-1181-2018, https://doi.org/10.5194/gmd-11-1181-2018, 2018
Short summary
Short summary
We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
Per Pemberton, Ulrike Löptien, Robinson Hordoir, Anders Höglund, Semjon Schimanke, Lars Axell, and Jari Haapala
Geosci. Model Dev., 10, 3105–3123, https://doi.org/10.5194/gmd-10-3105-2017, https://doi.org/10.5194/gmd-10-3105-2017, 2017
Short summary
Short summary
The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive ecosystem. Understanding the sea-ice pack is important for climate effect studies and forecasting. A NEMO-LIM3.6-based model setup for the North Sea/Baltic Sea is introduced, including a method for ice in the coastal zone. We evaluate different sea-ice parameters and overall find that the model agrees well with the observation though deformed ice is more challenging to capture.
Karin F. Kvale, Samar Khatiwala, Heiner Dietze, Iris Kriest, and Andreas Oschlies
Geosci. Model Dev., 10, 2425–2445, https://doi.org/10.5194/gmd-10-2425-2017, https://doi.org/10.5194/gmd-10-2425-2017, 2017
Short summary
Short summary
Computer models of ocean biology and chemistry are becoming increasingly complex, and thus more expensive, to run. One solution is to approximate the behaviour of the ocean physics and store that information outside of the model. That
offlineinformation can then be used to calculate a steady-state solution from the model's biology and chemistry, without waiting for a traditional
onlineintegration to complete. We show this offline method reproduces online results and is 100 times faster.
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
Short summary
Short summary
Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, https://doi.org/10.5194/bg-14-1561-2017, 2017
Short summary
Short summary
The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
Yonss Saranga José, Heiner Dietze, and Andreas Oschlies
Biogeosciences, 14, 1349–1364, https://doi.org/10.5194/bg-14-1349-2017, https://doi.org/10.5194/bg-14-1349-2017, 2017
Short summary
Short summary
This study aims to investigate the diverse subsurface nutrient patterns observed within anticyclonic eddies in the upwelling system off Peru. Two simulated anticyclonic eddies with opposing subsurface nitrate concentrations were analysed. The results show that diverse nutrient patterns within anticyclonic eddies are related to the presence of water mass from different origins at different depths, responding to variations in depth of the circulation strength at the edge of the eddy.
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
Short summary
Short summary
Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
Short summary
Short summary
Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
U. Löptien and L. Axell
The Cryosphere, 8, 2409–2418, https://doi.org/10.5194/tc-8-2409-2014, https://doi.org/10.5194/tc-8-2409-2014, 2014
Short summary
Short summary
The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In wintertime, on-time shipping depends crucially on sea ice forecasts. Among the forecasting tools heavily applied are numerical models, which suffer from a lack of calibration data because relevant ice properties are difficult (and costly) to monitor. We developed an innovative and inexpensive approach, by using ship speed observations obtained by the automatic identification system (AIS) to asses such models.
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 2014
A. Landolfi, H. Dietze, W. Koeve, and A. Oschlies
Biogeosciences, 10, 1351–1363, https://doi.org/10.5194/bg-10-1351-2013, https://doi.org/10.5194/bg-10-1351-2013, 2013
Related subject area
Biogeochemistry: Modelling, Aquatic
Efficiency metrics for ocean alkalinity enhancements under responsive and prescribed atmospheric pCO2 conditions
Changes in Arctic Ocean plankton community structure and trophic dynamics on seasonal to interannual timescales
Global impact of benthic denitrification on marine N2 fixation and primary production simulated by a variable-stoichiometry Earth system model
Modeling the contribution of micronekton diel vertical migrations to carbon export in the mesopelagic zone
Killing the predator: impacts of highest-predator mortality on the global-ocean ecosystem structure
Hydrodynamic and biochemical impacts on the development of hypoxia in the Louisiana–Texas shelf – Part 1: roles of nutrient limitation and plankton community
Validation of the coupled physical–biogeochemical ocean model NEMO–SCOBI for the North Sea–Baltic Sea system
Investigating ecosystem connections in the shelf sea environment using complex networks
Seasonal and interannual variability of the pelagic ecosystem and of the organic carbon budget in the Rhodes Gyre (eastern Mediterranean): influence of winter mixing
How much do bacterial growth properties and biodegradable dissolved organic matter control water quality at low flow?
Methane emissions from Arctic landscapes during 2000–2015: an analysis with land and lake biogeochemistry models
Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model–data comparison and impact on the ocean carbon cycle
Riverine impact on future projections of marine primary production and carbon uptake
Subsurface oxygen maximum in oligotrophic marine ecosystems: mapping the interaction between physical and biogeochemical processes
Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach
Assessing the spatial and temporal variability of methylmercury biogeochemistry and bioaccumulation in the Mediterranean Sea with a coupled 3D model
Hydrodynamic and biochemical impacts on the development of hypoxia in the Louisiana–Texas shelf – Part 2: statistical modeling and hypoxia prediction
Modelling the effects of benthic fauna on carbon, nitrogen and phosphorus dynamics in the Baltic Sea
Improved prediction of dimethyl sulfide (DMS) distributions in the northeast subarctic Pacific using machine-learning algorithms
Nutrient transport and transformation in macrotidal estuaries of the French Atlantic coast: a modeling approach using the Carbon-Generic Estuarine Model
A modelling study of temporal and spatial pCO2 variability on the biologically active and temperature-dominated Scotian Shelf
Modeling the marine chromium cycle: new constraints on global-scale processes
New insights into large-scale trends of apparent organic matter reactivity in marine sediments and patterns of benthic carbon transformation
Evaluation of ocean dimethylsulfide concentration and emission in CMIP6 models
Zooplankton mortality effects on the plankton community of the northern Humboldt Current System: sensitivity of a regional biogeochemical model
Multi-compartment kinetic–allometric (MCKA) model of radionuclide bioaccumulation in marine fish
Impact of bottom trawling on sediment biogeochemistry: a modelling approach
Cyanobacteria blooms in the Baltic Sea: a review of models and facts
Arctic Ocean acidification over the 21st century co-driven by anthropogenic carbon increases and freshening in the CMIP6 model ensemble
Modeling silicate–nitrate–ammonium co-limitation of algal growth and the importance of bacterial remineralization based on an experimental Arctic coastal spring bloom culture study
Role of jellyfish in the plankton ecosystem revealed using a global ocean biogeochemical model
Extreme event waves in marine ecosystems: an application to Mediterranean Sea surface chlorophyll
Use of optical absorption indices to assess seasonal variability of dissolved organic matter in Amazon floodplain lakes
The role of sediment-induced light attenuation on primary production during Hurricane Gustav (2008)
Quantifying spatiotemporal variability in zooplankton dynamics in the Gulf of Mexico with a physical–biogeochemical model
One size fits all? Calibrating an ocean biogeochemistry model for different circulations
Assessing the temporal scale of deep-sea mining impacts on sediment biogeochemistry
Seasonal patterns of surface inorganic carbon system variables in the Gulf of Mexico inferred from a regional high-resolution ocean biogeochemical model
Oxygen dynamics and evaluation of the single-station diel oxygen model across contrasting geologies
Oceanic CO2 outgassing and biological production hotspots induced by pre-industrial river loads of nutrients and carbon in a global modeling approach
Global trends in marine nitrate N isotopes from observations and a neural network-based climatology
Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry
Model constraints on the anthropogenic carbon budget of the Arctic Ocean
Modeling oceanic nitrate and nitrite concentrations and isotopes using a 3-D inverse N cycle model
Biogeochemical response of the Mediterranean Sea to the transient SRES-A2 climate change scenario
Modelling the biogeochemical effects of heterotrophic and autotrophic N2 fixation in the Gulf of Aqaba (Israel), Red Sea
A perturbed biogeochemistry model ensemble evaluated against in situ and satellite observations
Diazotrophy as the main driver of the oligotrophy gradient in the western tropical South Pacific Ocean: results from a one-dimensional biogeochemical–physical coupled model
Causes of simulated long-term changes in phytoplankton biomass in the Baltic proper: a wavelet analysis
Modelling N2 fixation related to Trichodesmium sp.: driving processes and impacts on primary production in the tropical Pacific Ocean
Michael D. Tyka
Biogeosciences, 22, 341–353, https://doi.org/10.5194/bg-22-341-2025, https://doi.org/10.5194/bg-22-341-2025, 2025
Short summary
Short summary
Marine CO2 removal (mCDR) is a promising technology for removing legacy emissions from the atmosphere. Its indirect nature makes it difficult to assess experimentally; instead one relies heavily on simulation. Many past papers have treated the atmosphere as non-responsive to the intervention studied. We show that even under these simplified assumptions, the increase in ocean CO2 inventory is equal to the equivalent quantity of direct CO2 removals occurring over time, in a realistic atmosphere.
Gabriela Negrete-García, Jessica Y. Luo, Colleen M. Petrik, Manfredi Manizza, and Andrew D. Barton
Biogeosciences, 21, 4951–4973, https://doi.org/10.5194/bg-21-4951-2024, https://doi.org/10.5194/bg-21-4951-2024, 2024
Short summary
Short summary
The Arctic Ocean experiences significant seasonal and year-to-year changes, impacting marine plankton populations. Using a plankton community model, we studied these effects on plankton communities and their influence on fish production. Our findings revealed earlier plankton blooms, shifts towards more carnivorous zooplankton, and increased fishery potential during summertime, especially in warmer years with less ice, highlighting the delicate balance of Arctic ecosystems.
Na Li, Christopher J. Somes, Angela Landolfi, Chia-Te Chien, Markus Pahlow, and Andreas Oschlies
Biogeosciences, 21, 4361–4380, https://doi.org/10.5194/bg-21-4361-2024, https://doi.org/10.5194/bg-21-4361-2024, 2024
Short summary
Short summary
N is a crucial nutrient that limits phytoplankton growth in large ocean areas. The amount of oceanic N is governed by the balance of N2 fixation and denitrification. Here we incorporate benthic denitrification into an Earth system model with variable particulate stoichiometry. Our model compares better to the observed surface nutrient distributions, marine N2 fixation, and primary production. Benthic denitrification plays an important role in marine N and C cycling and hence the global climate.
Hélène Thibault, Frédéric Ménard, Jeanne Abitbol-Spangaro, Jean-Christophe Poggiale, and Séverine Martini
EGUsphere, https://doi.org/10.5194/egusphere-2024-2074, https://doi.org/10.5194/egusphere-2024-2074, 2024
Short summary
Short summary
Micronekton significantly impacts oceanic carbon transport, yet often overlooked. Using a trait-based model, we simulated their diel vertical migrations and carbon production, revealing size, taxonomy, light and primary production as key factors. In temperate regions, micronekton influenced greatly the transport efficiency in summer. Future research must focus on micronekton metabolism and dynamics, considering global warming and their potential exploitation.
David Talmy, Eric Carr, Harshana Rajakaruna, Selina Våge, and Anne Willem Omta
Biogeosciences, 21, 2493–2507, https://doi.org/10.5194/bg-21-2493-2024, https://doi.org/10.5194/bg-21-2493-2024, 2024
Short summary
Short summary
The structure of plankton communities is central to global cycles of carbon, nitrogen, and other elements. This study explored the sensitivity of different assumptions about highest-predator mortality in ecosystem models with contrasting food web structures. In the context of environmental data, we find support for models assuming a density-dependent mortality of the highest predator, irrespective of assumed food web structure.
Yanda Ou and Z. George Xue
Biogeosciences, 21, 2385–2424, https://doi.org/10.5194/bg-21-2385-2024, https://doi.org/10.5194/bg-21-2385-2024, 2024
Short summary
Short summary
Developed for the Gulf of Mexico (2006–2020), a 3D hydrodynamic–biogeochemical model validated against in situ data reveals the impact of nutrients and plankton diversity on dissolved oxygen dynamics. It highlights the role of physical processes, sediment oxygen consumption, and nutrient distribution in shaping bottom oxygen levels and hypoxia. The model underscores the importance of complex plankton interactions for understanding primary production and hypoxia evolution.
Itzel Ruvalcaba Baroni, Elin Almroth-Rosell, Lars Axell, Sam T. Fredriksson, Jenny Hieronymus, Magnus Hieronymus, Sandra-Esther Brunnabend, Matthias Gröger, Ivan Kuznetsov, Filippa Fransner, Robinson Hordoir, Saeed Falahat, and Lars Arneborg
Biogeosciences, 21, 2087–2132, https://doi.org/10.5194/bg-21-2087-2024, https://doi.org/10.5194/bg-21-2087-2024, 2024
Short summary
Short summary
The health of the Baltic and North seas is threatened due to high anthropogenic pressure; thus, different methods to assess the status of these regions are urgently needed. Here, we validated a novel model simulating the ocean dynamics and biogeochemistry of the Baltic and North seas that can be used to create future climate and nutrient scenarios, contribute to European initiatives on de-eutrophication, and provide water quality advice and support on nutrient load reductions for both seas.
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
Short summary
Short summary
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.
Joelle Habib, Caroline Ulses, Claude Estournel, Milad Fakhri, Patrick Marsaleix, Mireille Pujo-Pay, Marine Fourrier, Laurent Coppola, Alexandre Mignot, Laurent Mortier, and Pascal Conan
Biogeosciences, 20, 3203–3228, https://doi.org/10.5194/bg-20-3203-2023, https://doi.org/10.5194/bg-20-3203-2023, 2023
Short summary
Short summary
The Rhodes Gyre, eastern Mediterranean Sea, is the main Levantine Intermediate Water formation site. In this study, we use a 3D physical–biogeochemical model to investigate the seasonal and interannual variability of organic carbon dynamics in the gyre. Our results show its autotrophic nature and its high interannual variability, with enhanced primary production, downward exports, and onward exports to the surrounding regions during years marked by intense heat losses and deep mixed layers.
Masihullah Hasanyar, Thomas Romary, Shuaitao Wang, and Nicolas Flipo
Biogeosciences, 20, 1621–1633, https://doi.org/10.5194/bg-20-1621-2023, https://doi.org/10.5194/bg-20-1621-2023, 2023
Short summary
Short summary
The results of this study indicate that biodegradable dissolved organic matter is responsible for oxygen depletion at low flow during summer seasons when heterotrophic bacterial activity is so intense. Therefore, the dissolved organic matter must be well measured in the water monitoring networks in order to have more accurate water quality models. It also advocates for high-frequency data collection for better quantification of the uncertainties related to organic matter.
Xiangyu Liu and Qianlai Zhuang
Biogeosciences, 20, 1181–1193, https://doi.org/10.5194/bg-20-1181-2023, https://doi.org/10.5194/bg-20-1181-2023, 2023
Short summary
Short summary
We are among the first to quantify methane emissions from inland water system in the pan-Arctic. The total CH4 emissions are 36.46 Tg CH4 yr−1 during 2000–2015, of which wetlands and lakes were 21.69 Tg yr−1 and 14.76 Tg yr−1, respectively. By using two non-overlap area change datasets with land and lake models, our simulation avoids small lakes being counted twice as both lake and wetland, and it narrows the gap between two different methods used to quantify regional CH4 emissions.
Corentin Clerc, Laurent Bopp, Fabio Benedetti, Meike Vogt, and Olivier Aumont
Biogeosciences, 20, 869–895, https://doi.org/10.5194/bg-20-869-2023, https://doi.org/10.5194/bg-20-869-2023, 2023
Short summary
Short summary
Gelatinous zooplankton play a key role in the ocean carbon cycle. In particular, pelagic tunicates, which feed on a wide size range of prey, produce rapidly sinking detritus. Thus, they efficiently transfer carbon from the surface to the depths. Consequently, we added these organisms to a marine biogeochemical model (PISCES-v2) and evaluated their impact on the global carbon cycle. We found that they contribute significantly to carbon export and that this contribution increases with depth.
Shuang Gao, Jörg Schwinger, Jerry Tjiputra, Ingo Bethke, Jens Hartmann, Emilio Mayorga, and Christoph Heinze
Biogeosciences, 20, 93–119, https://doi.org/10.5194/bg-20-93-2023, https://doi.org/10.5194/bg-20-93-2023, 2023
Short summary
Short summary
We assess the impact of riverine nutrients and carbon (C) on projected marine primary production (PP) and C uptake using a fully coupled Earth system model. Riverine inputs alleviate nutrient limitation and thus lessen the projected PP decline by up to 0.7 Pg C yr−1 globally. The effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projected ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver.
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
Short summary
Short summary
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.
Michael R. Stukel, Moira Décima, and Michael R. Landry
Biogeosciences, 19, 3595–3624, https://doi.org/10.5194/bg-19-3595-2022, https://doi.org/10.5194/bg-19-3595-2022, 2022
Short summary
Short summary
The biological carbon pump (BCP) transports carbon into the deep ocean, leading to long-term marine carbon sequestration. It is driven by many physical, chemical, and ecological processes. We developed a model of the BCP constrained using data from 11 cruises in 4 different ocean regions. Our results show that sinking particles and vertical mixing are more important than transport mediated by vertically migrating zooplankton. They also highlight the uncertainty in current estimates of the BCP.
Ginevra Rosati, Donata Canu, Paolo Lazzari, and Cosimo Solidoro
Biogeosciences, 19, 3663–3682, https://doi.org/10.5194/bg-19-3663-2022, https://doi.org/10.5194/bg-19-3663-2022, 2022
Short summary
Short summary
Methylmercury (MeHg) is produced and bioaccumulated in marine food webs, posing concerns for human exposure through seafood consumption. We modeled and analyzed the fate of MeHg in the lower food web of the Mediterranean Sea. The modeled spatial–temporal distribution of plankton bioaccumulation differs from the distribution of MeHg in surface water. We also show that MeHg exposure concentrations in temperate waters can be lowered by winter convection, which is declining due to climate change.
Yanda Ou, Bin Li, and Z. George Xue
Biogeosciences, 19, 3575–3593, https://doi.org/10.5194/bg-19-3575-2022, https://doi.org/10.5194/bg-19-3575-2022, 2022
Short summary
Short summary
Over the past decades, the Louisiana–Texas shelf has been suffering recurring hypoxia (dissolved oxygen < 2 mg L−1). We developed a novel prediction model using state-of-the-art statistical techniques based on physical and biogeochemical data provided by a numerical model. The model can capture both the magnitude and onset of the annual hypoxia events. This study also demonstrates that it is possible to use a global model forecast to predict regional ocean water quality.
Eva Ehrnsten, Oleg Pavlovitch Savchuk, and Bo Gustav Gustafsson
Biogeosciences, 19, 3337–3367, https://doi.org/10.5194/bg-19-3337-2022, https://doi.org/10.5194/bg-19-3337-2022, 2022
Short summary
Short summary
We studied the effects of benthic fauna, animals living on or in the seafloor, on the biogeochemical cycles of carbon, nitrogen and phosphorus using a model of the Baltic Sea ecosystem. By eating and excreting, the animals transform a large part of organic matter sinking to the seafloor into inorganic forms, which fuel plankton blooms. Simultaneously, when they move around (bioturbate), phosphorus is bound in the sediments. This reduces nitrogen-fixing plankton blooms and oxygen depletion.
Brandon J. McNabb and Philippe D. Tortell
Biogeosciences, 19, 1705–1721, https://doi.org/10.5194/bg-19-1705-2022, https://doi.org/10.5194/bg-19-1705-2022, 2022
Short summary
Short summary
The trace gas dimethyl sulfide (DMS) plays an important role in the ocean sulfur cycle and can also influence Earth’s climate. Our study used two statistical methods to predict surface ocean concentrations and rates of sea–air exchange of DMS in the northeast subarctic Pacific. Our results show improved predictive power over previous approaches and suggest that nutrient availability, light-dependent processes, and physical mixing may be important controls on DMS in this region.
Xi Wei, Josette Garnier, Vincent Thieu, Paul Passy, Romain Le Gendre, Gilles Billen, Maia Akopian, and Goulven Gildas Laruelle
Biogeosciences, 19, 931–955, https://doi.org/10.5194/bg-19-931-2022, https://doi.org/10.5194/bg-19-931-2022, 2022
Short summary
Short summary
Estuaries are key reactive ecosystems along the land–ocean aquatic continuum and are often strongly impacted by anthropogenic activities. We calculated nutrient in and out fluxes by using a 1-D transient model for seven estuaries along the French Atlantic coast. Among these, large estuaries with high residence times showed higher retention rates than medium and small ones. All reveal coastal eutrophication due to the excess of diffused nitrogen from intensive agricultural river basins.
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
Short summary
Short summary
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.
Frerk Pöppelmeier, David J. Janssen, Samuel L. Jaccard, and Thomas F. Stocker
Biogeosciences, 18, 5447–5463, https://doi.org/10.5194/bg-18-5447-2021, https://doi.org/10.5194/bg-18-5447-2021, 2021
Short summary
Short summary
Chromium (Cr) is a redox-sensitive element that holds promise as a tracer of ocean oxygenation and biological activity. We here implemented the oxidation states Cr(III) and Cr(VI) in the Bern3D model to investigate the processes that shape the global Cr distribution. We find a Cr ocean residence time of 5–8 kyr and that the benthic source dominates the tracer budget. Further, regional model–data mismatches suggest strong Cr removal in oxygen minimum zones and a spatially variable benthic source.
Felipe S. Freitas, Philip A. Pika, Sabine Kasten, Bo B. Jørgensen, Jens Rassmann, Christophe Rabouille, Shaun Thomas, Henrik Sass, Richard D. Pancost, and Sandra Arndt
Biogeosciences, 18, 4651–4679, https://doi.org/10.5194/bg-18-4651-2021, https://doi.org/10.5194/bg-18-4651-2021, 2021
Short summary
Short summary
It remains challenging to fully understand what controls carbon burial in marine sediments globally. Thus, we use a model–data approach to identify patterns of organic matter reactivity at the seafloor across distinct environmental conditions. Our findings support the notion that organic matter reactivity is a dynamic ecosystem property and strongly influences biogeochemical cycling and exchange. Our results are essential to improve predictions of future changes in carbon cycling and climate.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
Short summary
Short summary
In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations.
Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Mariana Hill Cruz, Iris Kriest, Yonss Saranga José, Rainer Kiko, Helena Hauss, and Andreas Oschlies
Biogeosciences, 18, 2891–2916, https://doi.org/10.5194/bg-18-2891-2021, https://doi.org/10.5194/bg-18-2891-2021, 2021
Short summary
Short summary
In this study we use a regional biogeochemical model of the eastern tropical South Pacific Ocean to implicitly simulate the effect that fluctuations in populations of small pelagic fish, such as anchovy and sardine, may have on the biogeochemistry of the northern Humboldt Current System. To do so, we vary the zooplankton mortality in the model, under the assumption that these fishes eat zooplankton. We also evaluate the model for the first time against mesozooplankton observations.
Roman Bezhenar, Kyeong Ok Kim, Vladimir Maderich, Govert de With, and Kyung Tae Jung
Biogeosciences, 18, 2591–2607, https://doi.org/10.5194/bg-18-2591-2021, https://doi.org/10.5194/bg-18-2591-2021, 2021
Short summary
Short summary
A new approach to predicting the accumulation of radionuclides in fish was developed by taking into account heterogeneity of distribution of contamination in the organism and dependence of metabolic process rates on the fish mass. Predicted concentrations of radionuclides in fish agreed well with the laboratory and field measurements. The model with the defined generic parameters could be used in marine environments without local calibration, which is important for emergency decision support.
Emil De Borger, Justin Tiano, Ulrike Braeckman, Adriaan D. Rijnsdorp, and Karline Soetaert
Biogeosciences, 18, 2539–2557, https://doi.org/10.5194/bg-18-2539-2021, https://doi.org/10.5194/bg-18-2539-2021, 2021
Short summary
Short summary
Bottom trawling alters benthic mineralization: the recycling of organic material (OM) to free nutrients. To better understand how this occurs, trawling events were added to a model of seafloor OM recycling. Results show that bottom trawling reduces OM and free nutrients in sediments through direct removal thereof and of fauna which transport OM to deeper sediment layers protected from fishing. Our results support temporospatial trawl restrictions to allow key sediment functions to recover.
Britta Munkes, Ulrike Löptien, and Heiner Dietze
Biogeosciences, 18, 2347–2378, https://doi.org/10.5194/bg-18-2347-2021, https://doi.org/10.5194/bg-18-2347-2021, 2021
Short summary
Short summary
Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood, which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtaposition of respective field and laboratory studies with state-of-the-art mathematical models reveals substantial uncertainty associated with nutrient demands, grazing, and death of cyanobacteria.
Jens Terhaar, Olivier Torres, Timothée Bourgeois, and Lester Kwiatkowski
Biogeosciences, 18, 2221–2240, https://doi.org/10.5194/bg-18-2221-2021, https://doi.org/10.5194/bg-18-2221-2021, 2021
Short summary
Short summary
The uptake of carbon, emitted as a result of human activities, results in ocean acidification. We analyse 21st-century projections of acidification in the Arctic Ocean, a region of particular vulnerability, using the latest generation of Earth system models. In this new generation of models there is a large decrease in the uncertainty associated with projections of Arctic Ocean acidification, with freshening playing a greater role in driving acidification than previously simulated.
Tobias R. Vonnahme, Martial Leroy, Silke Thoms, Dick van Oevelen, H. Rodger Harvey, Svein Kristiansen, Rolf Gradinger, Ulrike Dietrich, and Christoph Völker
Biogeosciences, 18, 1719–1747, https://doi.org/10.5194/bg-18-1719-2021, https://doi.org/10.5194/bg-18-1719-2021, 2021
Short summary
Short summary
Diatoms are crucial for Arctic coastal spring blooms, and their growth is controlled by nutrients and light. At the end of the bloom, inorganic nitrogen or silicon can be limiting, but nitrogen can be regenerated by bacteria, extending the algal growth phase. Modeling these multi-nutrient dynamics and the role of bacteria is challenging yet crucial for accurate modeling. We recreated spring bloom dynamics in a cultivation experiment and developed a representative dynamic model.
Rebecca M. Wright, Corinne Le Quéré, Erik Buitenhuis, Sophie Pitois, and Mark J. Gibbons
Biogeosciences, 18, 1291–1320, https://doi.org/10.5194/bg-18-1291-2021, https://doi.org/10.5194/bg-18-1291-2021, 2021
Short summary
Short summary
Jellyfish have been included in a global ocean biogeochemical model for the first time. The global mean jellyfish biomass in the model is within the observational range. Jellyfish are found to play an important role in the plankton ecosystem, influencing community structure, spatiotemporal dynamics and biomass. The model raises questions about the sensitivity of the zooplankton community to jellyfish mortality and the interactions between macrozooplankton and jellyfish.
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
Short summary
Short summary
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.
Maria Paula da Silva, Lino A. Sander de Carvalho, Evlyn Novo, Daniel S. F. Jorge, and Claudio C. F. Barbosa
Biogeosciences, 17, 5355–5364, https://doi.org/10.5194/bg-17-5355-2020, https://doi.org/10.5194/bg-17-5355-2020, 2020
Short summary
Short summary
In this study, we analyze the seasonal changes in the dissolved organic matter (DOM) quality (based on its optical properties) in four Amazon floodplain lakes. DOM plays a fundamental role in surface water chemistry, controlling metal bioavailability and mobility, and nutrient cycling. The model proposed in our paper highlights the potential to study DOM quality at a wider spatial scale, which may help to better understand the persistence and fate of DOM in the ecosystem.
Zhengchen Zang, Z. George Xue, Kehui Xu, Samuel J. Bentley, Qin Chen, Eurico J. D'Sa, Le Zhang, and Yanda Ou
Biogeosciences, 17, 5043–5055, https://doi.org/10.5194/bg-17-5043-2020, https://doi.org/10.5194/bg-17-5043-2020, 2020
Taylor A. Shropshire, Steven L. Morey, Eric P. Chassignet, Alexandra Bozec, Victoria J. Coles, Michael R. Landry, Rasmus Swalethorp, Glenn Zapfe, and Michael R. Stukel
Biogeosciences, 17, 3385–3407, https://doi.org/10.5194/bg-17-3385-2020, https://doi.org/10.5194/bg-17-3385-2020, 2020
Short summary
Short summary
Zooplankton are the smallest animals in the ocean and important food for fish. Despite their importance, zooplankton have been relatively undersampled. To better understand the zooplankton community in the Gulf of Mexico (GoM), we developed a model to simulate their dynamics. We found that heterotrophic protists are important for supporting mesozooplankton, which are the primary prey of larval fish. The model developed in this study has the potential to improve fisheries management in the GoM.
Iris Kriest, Paul Kähler, Wolfgang Koeve, Karin Kvale, Volkmar Sauerland, and Andreas Oschlies
Biogeosciences, 17, 3057–3082, https://doi.org/10.5194/bg-17-3057-2020, https://doi.org/10.5194/bg-17-3057-2020, 2020
Short summary
Short summary
Constants of global biogeochemical ocean models are often tuned
by handto match observations of nutrients or oxygen. We investigate the effect of this tuning by optimising six constants of a global biogeochemical model, simulated in five different offline circulations. Optimal values for three constants adjust to distinct features of the circulation applied and can afterwards be swapped among the circulations, without losing too much of the model's fit to observed quantities.
Laura Haffert, Matthias Haeckel, Henko de Stigter, and Felix Janssen
Biogeosciences, 17, 2767–2789, https://doi.org/10.5194/bg-17-2767-2020, https://doi.org/10.5194/bg-17-2767-2020, 2020
Short summary
Short summary
Deep-sea mining for polymetallic nodules is expected to have severe environmental impacts. Through prognostic modelling, this study aims to provide a holistic assessment of the biogeochemical recovery after a disturbance event. It was found that the recovery strongly depends on the impact type; e.g. complete removal of the surface sediment reduces seafloor nutrient fluxes over centuries.
Fabian A. Gomez, Rik Wanninkhof, Leticia Barbero, Sang-Ki Lee, and Frank J. Hernandez Jr.
Biogeosciences, 17, 1685–1700, https://doi.org/10.5194/bg-17-1685-2020, https://doi.org/10.5194/bg-17-1685-2020, 2020
Short summary
Short summary
We use a numerical model to infer annual changes of surface carbon chemistry in the Gulf of Mexico (GoM). The main seasonality drivers of partial pressure of carbon dioxide and aragonite saturation state from the model are temperature and river runoff. The GoM basin is a carbon sink in winter–spring and carbon source in summer–fall, but uptake prevails near the Mississippi Delta year-round due to high biological production. Our model results show good correspondence with observational studies.
Simon J. Parker
Biogeosciences, 17, 305–315, https://doi.org/10.5194/bg-17-305-2020, https://doi.org/10.5194/bg-17-305-2020, 2020
Short summary
Short summary
Dissolved oxygen (DO) models typically assume constant ecosystem respiration over the course of a single day. Using a data-driven approach, this research examines this assumption in four streams across two (hydro-)geological types (Chalk and Greensand). Despite hydrogeological equivalence in terms of baseflow index for each hydrogeological pairing, model suitability differed within, rather than across, geology types. This corresponded with associated differences in timings of DO minima.
Fabrice Lacroix, Tatiana Ilyina, and Jens Hartmann
Biogeosciences, 17, 55–88, https://doi.org/10.5194/bg-17-55-2020, https://doi.org/10.5194/bg-17-55-2020, 2020
Short summary
Short summary
Contributions of rivers to the oceanic cycling of carbon have been poorly represented in global models until now. Here, we assess the long–term implications of preindustrial riverine loads in the ocean in a novel framework which estimates the loads through a hierarchy of weathering and land–ocean export models. We investigate their impacts for the oceanic biological production and air–sea carbon flux. Finally, we assess the potential incorporation of the framework in an Earth system model.
Patrick A. Rafter, Aaron Bagnell, Dario Marconi, and Timothy DeVries
Biogeosciences, 16, 2617–2633, https://doi.org/10.5194/bg-16-2617-2019, https://doi.org/10.5194/bg-16-2617-2019, 2019
Short summary
Short summary
The N isotopic composition of nitrate (
nitrate δ15N) is a useful tracer of ocean N cycling and many other ocean processes. Here, we use a global compilation of marine nitrate δ15N as an input, training, and validating dataset for an artificial neural network (a.k.a.,
machine learning) and examine basin-scale trends in marine nitrate δ15N from the surface to the seafloor.
Elena Terzić, Paolo Lazzari, Emanuele Organelli, Cosimo Solidoro, Stefano Salon, Fabrizio D'Ortenzio, and Pascal Conan
Biogeosciences, 16, 2527–2542, https://doi.org/10.5194/bg-16-2527-2019, https://doi.org/10.5194/bg-16-2527-2019, 2019
Short summary
Short summary
Measuring ecosystem properties in the ocean is a hard business. Recent availability of data from Biogeochemical-Argo floats can help make this task easier. Numerical models can integrate these new data in a coherent picture and can be used to investigate the functioning of ecosystem processes. Our new approach merges experimental information and model capabilities to quantitatively demonstrate the importance of light and water vertical mixing for algae dynamics in the Mediterranean Sea.
Jens Terhaar, James C. Orr, Marion Gehlen, Christian Ethé, and Laurent Bopp
Biogeosciences, 16, 2343–2367, https://doi.org/10.5194/bg-16-2343-2019, https://doi.org/10.5194/bg-16-2343-2019, 2019
Short summary
Short summary
A budget of anthropogenic carbon in the Arctic Ocean, the main driver of open-ocean acidification, was constructed for the first time using a high-resolution ocean model. The budget reveals that anthropogenic carbon enters the Arctic Ocean mainly by lateral transport; the air–sea flux plays a minor role. Coarser-resolution versions of the same model, typical of earth system models, store less anthropogenic carbon in the Arctic Ocean and thus underestimate ocean acidification in the Arctic Ocean.
Taylor S. Martin, François Primeau, and Karen L. Casciotti
Biogeosciences, 16, 347–367, https://doi.org/10.5194/bg-16-347-2019, https://doi.org/10.5194/bg-16-347-2019, 2019
Short summary
Short summary
Nitrite is a key intermediate in many nitrogen (N) cycling processes in the ocean, particularly in areas with low oxygen that are hotspots for N loss. We have created a 3-D global N cycle model with nitrite as a tracer. Stable isotopes of N are also included in the model and we are able to model the isotope fractionation associated with each N cycling process. Our model accurately represents N concentrations and isotope distributions in the ocean.
Camille Richon, Jean-Claude Dutay, Laurent Bopp, Briac Le Vu, James C. Orr, Samuel Somot, and François Dulac
Biogeosciences, 16, 135–165, https://doi.org/10.5194/bg-16-135-2019, https://doi.org/10.5194/bg-16-135-2019, 2019
Short summary
Short summary
We evaluate the effects of climate change and biogeochemical forcing evolution on the nutrient and plankton cycles of the Mediterranean Sea for the first time. We use a high-resolution coupled physical and biogeochemical model and perform 120-year transient simulations. The results indicate that changes in external nutrient fluxes and climate change may have synergistic or antagonistic effects on nutrient concentrations, depending on the region and the scenario.
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
Short summary
Short summary
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.
Prima Anugerahanti, Shovonlal Roy, and Keith Haines
Biogeosciences, 15, 6685–6711, https://doi.org/10.5194/bg-15-6685-2018, https://doi.org/10.5194/bg-15-6685-2018, 2018
Short summary
Short summary
Minor changes in the biogeochemical model equations lead to major dynamical changes. We assessed this structural sensitivity for the MEDUSA biogeochemical model on chlorophyll and nitrogen concentrations at five oceanographic stations over 10 years, using 1-D ensembles generated by combining different process equations. The ensemble performed better than the default model in most of the stations, suggesting that our approach is useful for generating a probabilistic biogeochemical ensemble model.
Audrey Gimenez, Melika Baklouti, Thibaut Wagener, and Thierry Moutin
Biogeosciences, 15, 6573–6589, https://doi.org/10.5194/bg-15-6573-2018, https://doi.org/10.5194/bg-15-6573-2018, 2018
Short summary
Short summary
During the OUTPACE cruise conducted in the oligotrophic to ultra-oligotrophic region of the western tropical South Pacific, two contrasted regions were sampled in terms of N2 fixation rates, primary production rates and nutrient availability. The aim of this work was to investigate the role of N2 fixation in the differences observed between the two contrasted areas by comparing two simulations only differing by the presence or not of N2 fixers using a 1-D biogeochemical–physical coupled model.
Jenny Hieronymus, Kari Eilola, Magnus Hieronymus, H. E. Markus Meier, Sofia Saraiva, and Bengt Karlson
Biogeosciences, 15, 5113–5129, https://doi.org/10.5194/bg-15-5113-2018, https://doi.org/10.5194/bg-15-5113-2018, 2018
Short summary
Short summary
This paper investigates how phytoplankton concentrations in the Baltic Sea co-vary with nutrient concentrations and other key variables on inter-annual timescales in a model integration over the years 1850–2008. The study area is not only affected by climate change; it has also been subjected to greatly increased nutrient loads due to extensive use of agricultural fertilizers. The results indicate the largest inter-annual coherence of phytoplankton with the limiting nutrient.
Cyril Dutheil, Olivier Aumont, Thomas Gorguès, Anne Lorrain, Sophie Bonnet, Martine Rodier, Cécile Dupouy, Takuhei Shiozaki, and Christophe Menkes
Biogeosciences, 15, 4333–4352, https://doi.org/10.5194/bg-15-4333-2018, https://doi.org/10.5194/bg-15-4333-2018, 2018
Short summary
Short summary
N2 fixation is recognized as one of the major sources of nitrogen in the ocean. Thus, N2 fixation sustains a significant part of the primary production (PP) by supplying the most common limiting nutrient for phytoplankton growth. From numerical simulations, the local maximums of Trichodesmium biomass in the Pacific are found around islands, explained by the iron fluxes from island sediments. We assessed that 15 % of the PP may be due to Trichodesmium in the low-nutrient, low-chlorophyll areas.
Cited articles
Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World ocean atlas 2009, Volume 2: Salinity, in: NOAA Atlas NESDIS 69, edited by: Levitus, S., vol. 2, US Government Printing Office, Washington DC, 184, 2009. a
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical processes of the UCLA general circulation model, Methods in Computational Physics, 17, 173–265, 1977. a
Banerjee, T., Danilov, S., and Klingbeil, K.: Discrete variance decay analsis of spurious mixing, Ocean Model., 192, 102460, https://doi.org/10.1016/j.ocemod.2024.102460, 2024. a
Barton, E. D.: Meanders, eddies and intrusions in the thermohaline fron off Northwest Africa, Oceanol. Acta, 10, 267–283, 1987. a
Bieri, R. H., Koide, M., and Goldberg, E. D.: The noble gas contents of pacific seawaters, J. Geophys. Res., 71, 5243–5265, https://doi.org/10.1029/JZ071i022p05243, 1966. a
Braghiere, R. K., Wang, Y., Gagné-Landmann, A., Brodrick, P. G., Bloom, A. A., Norton, A. J., Ma, A., Levine, P., Longo, M., Deck, K., Gentine, P., Worden, J. R., Frankenberg, C., and Schneider, T.: The importance of hyperspectral soil albedo information for improving Earth system model projections, AGU Advances, 4, e2023AV000910, https://doi.org/10.1029/2023AV000910, 2023. a
Brett, G. J., Whitt, D. B., Long, M. C., Bryan, F. O., Feloy, K., and Richards, K. J.: Submesoscale effects on changes to export production under global warming, Global Biogeochem. Cy., 37, e2022GB007619, https://doi.org/10.1029/2022GB007619, 2023. a, b
Burchard, H. and Rennau, H.: Comparative quantification of physically and numerically induced mixing in ocean models, Ocean Model., 20, 293–311, https://doi.org/10.1016/j.ocemod.2007.10.003, 2008. a, b, c
Camp, L. V. V., Nykjær, L., Mittelstaedt, E., and Schlittenhardt, P.: Upwelling and boundary circulation off Northwest Africa as depicted by infrared and visible satellite observations, Prog. Oceanogr., 26, 357–402, https://doi.org/10.1016/0079-6611(91)90012-B, 1991. a
Capet, X., Williams, J. C. M., Molemaker, M. J., and Shchepetkin, A. F.: Mesoscale to sub-mesoscale transition in the California current system. Part I: Flow structure, eddy flux, and observational tests, J. Phys. Oceanogr., 38, 29–43, https://doi.org/10.1175/2007JPO3671.1, 2008. a
Counillon, F., Keenlyside, N., Wang, S., Devilliers, M., Gupta, A., Koseki, S., and Shen, M.-L.: Framework for an ocean-connected supermodel of the Earth system, J. Adv. Model. Earth Sy., 15, e2022MS003310, https://doi.org/10.1029/2022MS003310, 2023. a
Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio, P. N., Fiore, A., Frankignoul, C., Fyfe, J. C., Horton, D. E., Kay, J. E., Knutti, R., Lovenduski, N. S., Marotzke, J., McKinnon, K. A., Minobe, S., Randerson, J., Screen, J. A., Simpson, I. R., and Ting, M.: Insights from Earth system model initial-condition large ensembles and future prospects, Nat. Clim. Change, 10, 277–286, https://doi.org/10.1038/s41558-020-0731-2, 2020. a
Dietze, H. and Löptien, U.: Effects of surface current–wind interactionconfiguration in an eddy-rich general ocean circulation simulation of the Baltic Sea, Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, 2016. a
Dietze, H. and Löptien, U.: Retracing hypoxia in Eckernförde Bight (Baltic Sea), Biogeosciences, 18, 4243–4264, https://doi.org/10.5194/bg-18-4243-2021, 2021. a
Dietze, H. and Löptien, U.: Argon Saturation in a Suite of Coupled General Ocean Circulation Biogeochemical Models off Mauretania, Zenodo [code and data set], https://doi.org/10.5281/zenodo.5549894, 2023. a, b
Dietze, H. and Oschlies, A.: Modeling abiotic production of apparent oxygen utilisation in the oligotrophic subtropical North Atlantic, Ocean Dynam., 55, 28–33, https://doi.org/10.1007/s10236-005-0109-z, 2005a. a, b, c
Dietze, H., Löptien, U., and Getzlaff, K.: MOMBA 1.1 – a high-resolution Baltic Sea configuration of GFDL's Modular Ocean Model, Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, 2014. a, b, c
Dietze, H., Getzlaff, J., and Löptien, U.: Simulating natural carbon sequestration in the Southern Ocean: on uncertainties associated with eddy parameterizations and iron deposition, Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, 2017. a
Dietze, H., Löptien, U., and Getzlaff, J.: MOMSO 1.0 – an eddying Southern Ocean model configuration with fairly equilibrated natural carbon, Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, 2020. a, b, c
Doumbouya, A., Camara, O. T., Mamie, J., Intchama, J. F., Jarra, A., Ceesay, S., Guéye, A., Ndiaye, D., Beibou, E., Padilla, A., and Belhabib, D.: Assessing the effectiveness of monitoring control and surveillance of illegal fishing: the case of West Africa, Frontiers in Marine Science, 4, 50, https://doi.org/10.3389/fmars.2017.00050, 2017. a
Eden, C. and Dietze, H.: Effects of mesoscale eddy/wind interactions on biological new production and eddy kinetic energy, J. Geophys. Res., 114, https://doi.org/10.1029/2008JC005129, 2009. a
Ellison, E., Mashayek, A., and Mazloff, M.: The sensitivity of southern ocean air-sea carbon fluxes to background turbulent diapycnal mixing variability, J. Geophys. Res.-Oceans, 128, e2023JC019756, https://doi.org/10.1029/2023JC019756, 2023. a, b
Emerson, S., Ito, T., and Hamme, R. C.: Argon supersaturation indicates low decadal-scale vertical mixing in the ocean thermocline, Geophys. Res. Lett., 3, 19, https://doi.org/10.1029/2012GL053054, 2012. a, b, c
Faye, S., Lazar, A., Sow, B. A., and Gaye, A. T.: A model study of the seasonality of sea surface temperature and circulation in the Atlantic north-eastern tropical upwelling system, AIP Conf. Proc., 3, 76, https://doi.org/10.3389/fphy.2015.00076, 2015. a
Feng, E. Y., Koeve, W., Keller, D. P., and Oschlies, A.: Model-based assessment of the CO2 sequestration potential of coastal ocean alkalinization, Earth's Future, 5, 1252–1266, https://doi.org/10.1002/2017EF000659, 2017. a
Feng, E. Y., Su, B., and Oschlies, A.: Geoengineered ocean vertical water exchange can accelerate global deoxygenation, Geophys. Res. Lett., 47, e2020GL088263, https://doi.org/10.1029/2020GL088263, 2020. a
Flato, G. M.: Earth system models: an overview, WIREs Clim. Change, 2, 783–800, https://doi.org/10.1002/wcc.148, 2011. a
Foltz, G. R., Schmid, C., and Lumpkin, R.: Seasonal cycle of the mixed layer heat budget in the northeastern tropical Atlantic Ocean, J. Climate, 26, 8169–8188, https://doi.org/10.1175/JCLI-D-13-00037.1, 2013. a
Fratantoni, D. M.: North Atlantic surface circulation during the 1990's observed with satellite-tracked drifters, J. Geophys. Res.-Oceans, 106, C10, 22067–22093, https://doi.org/10.1029/2000JC000730, 2001. a
Galbraith, E. D., Gnanadesikan, A., Dunne, J. P., and Hiscock, M. R.: Regional impacts of iron-light colimitation in a global biogeochemical model, Biogeosciences, 7, 1043–1064, https://doi.org/10.5194/bg-7-1043-2010, 2010. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., and Antonov, J. I.: World ocean atlas 2009, Volume 4: Nutrients (phosphate, nitrate, silicate), in: NOAA Atlas NESDIS 71, edited by: Levitus, S., vol. 4, US Government Printing Office, Washington DC, 398 pp., 2010a. a
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 3: Dissolved oxygen, apparent oxygen utilization, and oxygen saturation, in: NOAA Atlas NESDIS 70, edited by: Levitus, S., vol. 4, US Government Printing Office, Washington DC, 344 pp., 2010b. a
Gaspard, P. Y. G. and Lefevre, J.-M.: A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: Tests at station Papa and long-term upper ocean study site, J. Geophys. Res.-Oceans, 95, 16179–16193, https://doi.org/10.1029/JC095iC09p16179, 1990. a
Gerdes, R., Köberle, C., and Willebrand, J.: The influence of numerical advection schemes on the results of ocean general circulation models, Clim. Dynam., 5, 211–226, 1991. a
Getzlaff, J., Nurser, G., and Oschlies, A.: Diagnostics of diapycnal diffusion in z-level ocean models. Part II: 3-dimensional OGCM, Ocean Model., 45–46, 27–37, https://doi.org/10.1016/j.ocemod.2011.11.006 2012. a, b
Getzlaff, J., Dietze, H., and Löptien, U.: Tracing net diapycnal mixing in ocean circulation models with argon saturation, 7–12 April 2019, Vienna, Geophysical Research Abstracts, 21, EGU2019–11174, 2019. a
Gibson, A. H., Hogg, A. M., Kiss, A. E., Shakespeare, C. J., and Adcroft, A.: Attribution of horizontal and vertical contributions to spurious mixing in an arbitrary Lagrangian–Eulerian ocean model, Ocean Model., 119, 45–56, https://doi.org/10.1016/j.ocemod.2017.09.008, 2017. a
Gnanadesikan, A., Pradal, A.-A., and Abernathey, R.: Isopycnal mixing by mesoscale eddies significantly impacts oceanic anthropogenic carbon uptake, Geophys. Res. Lett., 42, 4249–4255, https://doi.org/10.1002/2015GL064100, 2015. a
Griffies, S. M. and Hallberg, R. W.: Biharmonic friction with a Smagorinsky-like viscosity for use in largescale eddy-permitting ocean models, Mon. Weather Rev., 128, 2935–2946, https://doi.org/10.1175/1520-0493(2000)128<2935:BFWASL>2.0.CO;2, 2000. a
Griffies, S. M., Pacanowski, R. C., and Hallberg, R. W.: Spurious diapycnal mixing associated with advection in a z-coordinate ocean model, Mon. Weather Rev., 128, 538–564, https://doi.org/10.1175/1520-0493(2000)128<0538:SDMAWA>2.0.CO;2, 2000. a, b
Gulev, S., Jung, T., and Ruprecht, E.: Estimation of the impact of sampling errors in the VOS observations on air-sea fluxes. Part II: impacts on trends and interannual variability, J. Climate, 20, 302–315, https://doi.org/10.1175/JCLI4008.1, 2007. a
Gutjahr, O., Putrasahan, D., Lohmann, K., Jungclaus, J. H., von Storch, J.-S., Brüggemann, N., Haak, H., and Stössel, A.: Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP), Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, 2019. a
Hamme, R. C., Emerson, S. R., Severinghaus, J. P., Long, M. C., and Yashayaev, I.: Using noble gas measurements to derive air-sea process information and predict physical gas saturations, Geophys. Res. Lett., 44, 9901–9909, https://doi.org/10.1002/2017GL075123, 2017. a, b, c
Hauss, H., Christiansen, S., Schütte, F., Kiko, R., Edvam Lima, M., Rodrigues, E., Karstensen, J., Löscher, C. R., Körtzinger, A., and Fiedler, B.: Dead zone or oasis in the open ocean? Zooplankton distribution and migration in low-oxygen modewater eddies, Biogeosciences, 13, 1977–1989, https://doi.org/10.5194/bg-13-1977-2016, 2016. a
Hecht, M. W.: Cautionary tales of persistent accumulation of numerical error: dispersive centered advection, Ocean Model., 35, 270–276, https://doi.org/10.1016/j.ocemod.2010.07.005, 2010. a
Henning, C. C., Archer, D., and Fung, I.: Argon as a tracer of cross-isopycnal mixing in the thermocline, J. Phys. Oceanogr., 36, 2090–2105, https://doi.org/10.1175/JPO2961.1, 2011. a, b
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hewitt, H. T., Roberts, M., Mathiot, P., Biastoch, A., Blockley, E., Chassignet, E. P., Fox-Kemper, B., Hyder, P., Marshall, D. P., Treguier, E. P. A.-M., Zanna, L., Yool, A., Yu, Y., Beadling, R., Bell, M., Kuhlbrodt, T., Arsouze, T., Belluci, A., Castuccio, F., Gan, B., Putrasahan, D., Roberts, C. D., Roekel, L. V., and Zhang, Q.: Resolving and parameterising the ocean mesoscale in Earth system models, Current Climate Change Reports, 6, 137–152, https://doi.org/10.1007/s40641-020-00164-w, 2020. a
Hill, C., Ferreira, D., Campin, J.-M., Marshall, J., Abernathey, R., and Barrie, N.: Controlling spurious diapycnal mixing in eddy-resolving height-coordinate ocean models – insights from virtual deliberate tracer release experiments, Ocean Model., 45/46, 14–26, https://doi.org/10.1016/j.ocemod.2011.12.001, 2012. a
Hundsdorfer, W. and Trompert, R.: Methods of lines and direct discretization: a comparison for linear advection, Appl. Numer. Math., 13, 469–490, https://doi.org/10.1016/0168-9274(94)90009-4, 1994. a
Ilicak, M.: Quantifying spatial distribution of spurious mixing in ocean models, Ocean Model., 108, 30–38, https://doi.org/10.1016/j.ocemod.2016.11.002, 2016. a, b
Ilicak, M., Adcroft, A., Griffies, S. M., and Hallberg, R. W.: Spurious dianeutral mixing and the role of momentum closure, Ocean Model., 45–46, 37–58, https://doi.org/10.1016/j.ocemod.2011.10.003, 2012. a
Ito, T. and Deutsch, C.: Understanding the saturation state of argon in the thermocline: the role of air-sea gas exchange and diapycnal mixing, Global Biogeochem. Cy., 20, GB3019, https://doi.org/10.1029/2005GB002655, 2006. a, b
Ito, T., Deutsch, C., Emerson, S., and Hamme, R. C.: Impact of diapycnal mixing on the saturation state of argon in the subtropical North Pacific, Geophys. Res. Lett., 34, L09602, https://doi.org/10.1029/2006GL029209, 2007. a, b
Jenkins, W. J., Seltzer, A. M., Gebbie, G., and German, C. R.: Noble gas evidence of a millennial-scale deep North Pacific palaeo-barometric anomaly, Nat. Geosci., 17, 114–117, https://doi.org/10.1038/s41561-023-01368-z, 2023. a
Karleskind, P., Lévy, M., and Mémery, L.: Modifications of mode water properties by sub-mesoscales in a biophysical model of the Northeast Atlantic, Ocean Model., 39, 47–60, https://doi.org/10.1016/j.ocemod.2010.12.003, 2011. a, b
Karstensen, J., Fiedler, B., Schütte, F., Brandt, P., Körtzinger, A., Fischer, G., Zantopp, R., Hahn, J., Visbeck, M., and Wallace, D.: Open ocean dead zones in the tropical North Atlantic Ocean, Biogeosciences, 12, 2597–2605, https://doi.org/10.5194/bg-12-2597-2015, 2015. a, b
Keller, D. P., Feng, E. Y., and Oschlies, A.: Potential climate engineering effectiveness and side effects during a high carbon dioxide-emission scenario, Nat. Commun., 5, 3304, https://doi.org/10.1038/ncomms4304, 2014. a
Khatiwala, S.: Efficient spin-up of Earth System Models using sequence acceleration, Science Advances, 10, eadn2839, https://doi.org/10.1126/sciadv.adn2839, 2024. a
Klenz, T., Dengler, M., and Brandt, P.: Seasonal Variability of the Mauretania Current and Hydrography at 18° N, J. Geophys. Res.-Oceans, 123, 8122–8137, https://doi.org/10.1029/2018JC014264, 2018. a
Klingbeil, K., Mohammadi-Aragh, M., Gräwe, U., and Burchard, H.: Quantification of spurious dissipation and mixing – Discrete variance decay in a Finite-Volume framework, Ocean Model., 81, 49–64, https://doi.org/10.1016/j.ocemod.2014.06.001, 2014. a
Klingbeil, K., Burchard, H., Danilov, S., Goetz, C., and Iske, A.: Reducing spurious diapycnal mixing in ocean models, in: Energy Transfers in Atmosphere and Ocean. Mathematics of Planet Earth, edited by: Carsten, C. and Iske, A., vol. 1, Springer, https://doi.org/10.1007/978-3-030-05704-6_8, 2019. a
Kuhlbrodt, T., Griesel, A., Montoya, M., Levermann, A., Hofmann, M., and Rahmstorf, S.: On the driving process of the Atlantic meridional overturning circulation, Rev. Geophys., 45, RG2001, https://doi.org/10.1029/2004RG000166, 2007. a
Kunze, E.: Internal-Wave-Driven Mixing: Global geography and budgets, J. Phys. Oceanogr., 47, 1325–1345, https://doi.org/10.1175/JPO-D-16-0141.1, 2017. a, b
Lachkar, Z. and Gruber, N.: A comparative study of biological production in eastern boundary upwelling systems using an artificial neural network, Biogeosciences, 9, 293–308, https://doi.org/10.5194/bg-9-293-2012, 2012. a
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies, 2004. a
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air-sea flux data set, Clim. Dynam., 33, 341–364, https://doi.org/10.1007/s00382-008-0441-3, 2008. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Ocean vertical mixing: a review and a model with a nonlocal boundary layer paramterization, Rev. Geophys, 32, 363–403, https://doi.org/10.1029/94RG01872, 1994. a, b
Ledwell, J. R., Watson, A., and Law, C. S.: Evidence for slow mixing across the pycnocline from an open-ocean tracer-release experiment, Nature, 364, 701–703, https://doi.org/10.1038/364701a0, 1993. a
Lee, M.-M., Coward, A. C., and Nurser, A. J. G.: Spurious diapycnal mixing of the deep waters in an eddy-permitting global ocean model, J. Phys. Oceanogr., 32, 1522–1535, https://doi.org/10.1175/1520-0485(2002)032<1522:SDMOTD>2.0.CO;2, 2002. a
Leonard, B. P.: A stable and accurate convective modelling procedure based on quadratic upstream interpolation, Comput. Method. Appl. M., 19, 59–98, https://doi.org/10.1016/0045-7825(79)90034-3, 1979. a
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, S. G.: World ocean atlas 2009, Volume 1: Temperature, in: NOAA Atlas NESDIS 69, edited by: Levitus, S., vol. 1, 184 pp., US Government Printing Office, Washington DC, 2010. a
Löptien, U. and Dietze, H.: Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks?, Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, 2015. a
Löptien, U. and Dietze, H.: Effects of parameter indeterminacy in pelagic biogeochemical modules of Earth system models on projections into a warming future: the scale of the problem, Global Biogeochem. Cy., 31, 1155–1172, https://doi.org/10.1002/2017GB005690, 2017. a
Löptien, U. and Dietze, H.: Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing, Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, 2019. a, b
Löptien, U., Dietze, H., Preuss, R., and Toussaint, U. V.: Mapping manifestations of parametric uncertainty in projected pelagic oxygen concentrations back to contemporary local model fidelity, Sci. Rep.-UK, 11, 20949, https://doi.org/10.1038/s41598-021-00334-2, 2021. a, b, c
Luecke, C. A., Arbic, B. K., Richman, J. G., Shriver, J. F., Alford, M. H., Ansong, J. K., Bassette, S. L., Buijsman, M. C., and Menemenlis, D.: Statistical comparisons of temperature variance and kinetic energy in global ocean models and observations: results from mesoscale to internal wave frequencies, J. Geophys. Res.-Oceans, 125, e2019JC015306, https://doi.org/10.1029/2019JC015306, 2020. a
MacKinnon, J. A., Zhao, Z., Whalen, C. B., Waterhouse, A. F., Trossman, D. S., Sun, O. M., Laurent, L. C. S., Simmons, H. L., Polzin, K., Pinkel, R., Pickering, A., Norton, N. J., Nash, J. D., Musgrave, R., Merchant, L. M., Melet, A. V., Mater, B., Legg, S., Large, W. G., Kunze, E., Klymak, J. M., Jochum, M., Jayne, S. R., Hallberg, R. W., Griffies, S. M., Diggs, S., Danabasoglu, G., Chassignet, E. P., Buijsman, M. C., Bryan, F. O., Briegleb, B. P., Barna, A., Arbic, B. K., Ansong, J. K., and Alford, M. H.: Climate Process Team on Internal Wave–Driven Ocean Mixing, B. Am. Meteorol. Soc., 98, 2429–2454, https://doi.org/10.1175/BAMS-D-16-0030.1, 2017. a
Mahadevan, A. and Archer, D.: Modeling the impact of fronts and mesoscale circulation on the nutrient supply and biogeochemistry of the upper ocean, J. Geophys. Res., 105, 1209–1225, https://doi.org/10.1029/1999JC900216, 2000. a, b, c, d
Mahadevan, A. and Tandon, A.: An analysis of mechanisms for submesoscale vertical motion at ocean fronts, Ocean Model., 14, 241–256, https://doi.org/10.1016/j.ocemod.2006.05.006, 2006. a, b, c
Martin, A. and Pondaven, P.: On estimates for the vertical nitrate flux due to eddy pumping, J. Geophys. Res, 108, 3359, https://doi.org/10.1029/2003JC001841, 2003. a, b, c
Martin, A. P. and Richards, K. J.: Mechanisms for the vertical nutrient transport within a North Atlantic mesoscale eddy, Deep-Sea Res. Pt. II, 48, 757–773, https://doi.org/10.1016/S0967-0645(00)00096-5, 2001. a
Marzocchi, A., Hirschi, J. J.-M., Holliday, N. P., Blaker, S. A. C. A. T., and Coward, A. C.: The North Atlantic subpolar circulation in an eddy-resolving global ocean model, J. Marine Syst., 142, 126–143, https://doi.org/10.1016/j.jmarsys.2014.10.007, 2015. a
McGraw, R., Yang, F., and Fierce, L. M.: Preserving tracer correlations in moment based atmospheric transport models, J. Adv. Model. Earth Sy., 16, e2023MS003621, https://doi.org/10.1029/2023MS003621, 2024. a
Megann, A.: Estimating the numerical diapycnal mixing in an eddy-permitting ocean model, Ocean Model., 121, 19–33, https://doi.org/10.1016/j.ocemod.2017.11.001, 2018. a, b
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, 1982. a
Messié, M., Ledesma, J., Kolber, D. D., Michisaki, R. P., Foley, D. G., and Chavez, F. P.: Potential new production estimates in four eastern boundary upwelling ecosystems, Prog. Oceanogr., 83, 151–158, https://doi.org/10.1016/j.pocean.2009.07.018, 2009. a
National Geophysical Data Center: 5-minute Gridded Global Relief Data (ETOPO5), National Geophysical Data Center, NOAA [data set], https://doi.org/10.7289/V5D798BF (last access: June 2010), 1993. a
O'Kane, T., Matear, R., Chamberlain, M., and Oke, P.: ENSO regimes and the late 1970's climate regime shift: the role of synoptic weather and South Pacific ocean spiciness, J. Comput. Phys., 271, 19–38, https://doi.org/10.1016/j.jcp.2013.10.058, 2014. a
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016. a
ould Dedah, S.: Wind, surface water temperature, surface salinity and pollution in the area of the Banc d'Arguin, Mauritania, Hydrobiologica, 258, 9–19, https://doi.org/10.1007/978-94-011-1986-3_2, 1993. a
Pacanowski, R. C. and Philander, S. G. H.: Parameterization of vertical mixing in numerical models of the tropical oceans, J. Phys. Oceanogr., 11, 1443–1451, https://doi.org/10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2, 2981. a
Pöppelmeier, F., Baggenstos, D., Grimmer, M., Liu, Z., Schmitt, J., Fischer, H., and Stocker, T. F.: The effect of past saturation changes on noble gas reconstructions of mean ocean temperature, Geophys. Res. Lett., 50, e2022GL102055, https://doi.org/10.1029/2022GL102055, 2023. a
Reissmann, J. H., Burchard, H., Feistel, R., Hagen, E., Lass, H. U., Mohrholz, V., Nausch, G., Umlauf, L., and Wieczorek, G.: Vertical mixing in the Baltic Sea and consequences for eutrophication – a review, Prog. Oceanogr., 82, 47–80, https://doi.org/10.1016/j.pocean.2007.10.004, 2009. a
Rogers, A., Medlyn, B. E., Dukes, J. S., Bonan, G., von Caemmerer, S., Dietze, M. C., Kattge, J., Leakey, A. D. B., Mercado, L. M., Niinemets, U., Prentice, I. C., Serbin, S. P., Sitch, S., Way, D. A., and Zaehle, S.: A roadmap for improving the representation of photosynthesis in Earth system models, New Phytol., 213, 22–42, https://doi.org/10.1111/nph.14283, 2017. a
Ruan, X., Couespel, D., Lévy, Mak, L. J., and Wang, Y.: Combined physical and biogeochemical assessment of mesoscale eddy parameterisations in ocean models: Eddy induced advection at non-eddying resolutions, Ocean Model., 183, 102204, https://doi.org/10.1016/j.ocemod.2023.102204, 2023. a, b
Sallée, J.-B., Matear, R. J., Rintoul, S. R., and Lenton, A.: Localized subduction of anthropogenic carbon dioxide in the Southern Hemisphere oceans, Nat. Geosci., 5, 579–584, https://doi.org/10.1038/ngeo1523, 2012. a
Schafstall, J., Dengler, M., Brandt, P., and Bange, H.: Tidal-induced mixing and diapycnal nutrient fluxes in the Mauritanian upwelling region, J. Geophys. Res.-Oceans, 115, C10, https://doi.org/10.1029/2009JC005940, 2010. a
Schlichting, D., Qu, L., Kobashi, D., and Hetland, R.: Quantification of physical and numerical mixing in a coastal ocean model using salinity variance budgets, J. Adv. Model. Earth Sy., 15, e2022MS003380, https://doi.org/10.1029/2022MS003380, 2023. a
Schmittner, A., Urban, N. M., Keller, K., and Matthews, D.: Using tracer observations to reduce the uncertainty of ocean diapycnal mixing and climate-carbon cycle projections, Global Biogeochem. Cy., 23, GB4009, https://doi.org/10.1029/2008GB003421, 2009. a, b
Seltzer, A. M., Nicholson, D. P., Smethie, W. M., Tyne, R. L., Roy, E. L., Stanley, R. H. R., Stute, M., Barry, P. H., McPaul, K., Davidson, P. W., Chang, B. X., Rafter, P. A., Lethaby, P., Johnson, R. J., Khatiwala, S., and Jenkins, W. J.: Dissolved gases in the deep North Atlantic track ocean ventilation processes, P. Natl. Acad. Sci. USA, 120, e2217946120, https://doi.org/10.1073/pnas.2217946120, 2023. a
Semmler, T., Jungclaus, J., Danek, C., Goessling, H. F., Koldunov, N. V., Rackow, T., and Sidorenko, D.: Ocean model formulation influences transient climate response, J. Geophys. Res.-Oceans, 126, e2021JC017633, https://doi.org/10.1029/2021JC017633, 2021. a
Shapiro, R.: Smoothing, filtering, and boundary effects, Rev. Geophys. Space GE, 8, 359–387, https://doi.org/10.1029/RG008i002p00359, 1970. a
Shcherbina, A. Y., D'Asaro, E. A., Lee, C. M., Klymak, J. M., Molemaker, M. J., and McWilliams, J. C.: Statistics of vertical vorticity, divergence, and strain in a developed sub-mesoscale turbulence field, Geophys. Res. Lett., 40, 4706–4711, https://doi.org/10.1002/grl.50919, 2013. a
Siedler, G., Zangenberg, N., and Onken, R.: Seasonal changes in the tropical atlantic circulation: observation and simulation of the Guinea Dome, J. Geophys. Res, 97, 703–715, https://doi.org/10.1029/91JC02501, 1992. a
Smagorinsky, J.: General circulation experiments with the primitive equations: I. the basic experiment, Mon. Weather Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1993a. a
Smagorinsky, J.: Some historical remarks on the use of nonlinear viscosities, in: Large Eddy Simulation of Complex Engineering and Geophysical Flows, edited by: Galperin, B. and Orszag, S. A., Cambridge University Press, 3–36, ISBN 9780521131339, 1993b. a
Spitzer, W. S. and Jenkins, W. J.: Rates of vertical mixing, gas exchange and new production: estimates from seasonal gas cycles in the upper ocean near Bermuda, J. Mar. Res., 47, 169–196, 1989. a
Stewart, K. D., Hogg, A. M., Griffies, S. M., Heerdegen, A. P., Ward, M. L., Spence, P., and England, M. H.: Vertical resolution of baroclinic modes in global ocean models, Ocean Model., 113, 50–65, https://doi.org/10.1016/j.ocemod.2017.03.012, 2017. a
Sweby, P.: High-resolution schemes using flux limiters for hyperbolic conservation-laws, SIAM J. Numer, Anal., 21, 995–1011, https://doi.org/10.1137/0721062, 1984. a
Tomczak, M. J.: De l'origine et la distribution de l'eau remontée à la surface au large de la côte Nor-Ouest Africaine, Annales Hydrographiques, Série 5, 6, 5–14, 1978. a
Tomczak, M. J. and Hughes, P.: Three dimensional variability of water masses and currents in the Canary upwelling region, Meteor. Forschungsergebnisse, 21, 1–24, 1980. a
Trossman, D. S., Whalen, C. B., Haine, T. W. N., Waterhouse, A. F., Nguyen, A. T., Bigdeli, A., Mazloff, M., and Heimbach, P.: Tracer and observationally derived constraints on diapycnal diffusivities in an ocean state estimate, Ocean Sci., 18, 729–759, https://doi.org/10.5194/os-18-729-2022, 2022. a
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G., Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W., Bozec, A., Chassignet, E. P., Curchitser, E., Dias, F. B., Durack, P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C., Kobayashi, S., Komuro, Y., Large, W. G., Sommer, J. L., Marsland, S. J., Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.: JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do), Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018. a
von Appen, W.-J., Strass, V. H., Bracher, A., Xi, H., Hörstmann, C., Iversen, M. H., and Waite, A. M.: High-resolution physical–biogeochemical structure of a filament and an eddy of upwelled water off northwest Africa, Ocean Sci., 16, 253–270, https://doi.org/10.5194/os-16-253-2020, 2020. a
Waterhouse, A. F., MacKinnon, J. A., Nash, J. D., Alford, M. H., Kunze, E., Simmons, H. L., Polzin, K. L., Laurent, L. C. S., Sun, O. M., Pinkel, R., Talley, L. D., Whalen, C. B., Huussen, T. N., Carter, G. S., Fer, I., Waterman, S., Garabato, A. C. N., Sanford, T. B., and Lee, C. M.: Global patterns of diapycnal mixing from measurements of the turbulent dissipation rate, J. Phys. Oceanogr., 44, 1854–1872, https://doi.org/10.1175/JPO-D-13-0104.1, 2014. a
Whalen, C. B., MacKinnon, J. A., Talley, L. D., and Waterhouse, A. F.: Estimating the Mean Diapycnal Mixing Using a Finescale Strain Parameterization, J. Phys. Oceanogr., 45, 1174–1188, https://doi.org/10.1175/JPO-D-14-0167.1, 2015. a
Wolff, W. J., van der Land, J., Nienhuis, P. H., and de Wilde, P. A. W. J.: The functioning of the ecosystem of the Banc d'Arguin, Mauretania, Hydrobiologica, 258, 211–222, https://doi.org/10.1007/BF00006198, 1993. a
Wunsch, C. and Ferrari, R.: Vertical mixing, energy, and the general circulation of the oceans, Annu. Rev. Fluid Mech., 36, 281–314, https://doi.org/10.1146/annurev.fluid.36.050802.122121, 2004. a
Zenk, W., Klein, B., and Schroder, M.: Cape Verde frontal zone, Oceanographic Research Papers, 38, S505–S530, https://doi.org/10.1016/S0198-0149(12)80022-7, 1991. a
Zhu, Y., Zhang, R.-H., and Sun, J.: North Pacific upper-ocean cold temperature biases in CMIP6 simulations and the role of regional vertical mixing, J. Climate, 33, 7523–7538, https://doi.org/10.1175/JCLI-D-19-0654.1, 2020. a
Short summary
We introduce argon saturation as a prognostic variable in a suite of coupled general ocean circulation biogeochemical models off Mauritania. Our results indicate that the effect of increasing the spatial horizontal model resolutions from 12 km to 1.5 km leads to changes comparable to other infamous spurious effects of state-of-the-art numerical advection numerics.
We introduce argon saturation as a prognostic variable in a suite of coupled general ocean...
Altmetrics
Final-revised paper
Preprint