Articles | Volume 11, issue 17
https://doi.org/10.5194/bg-11-4713-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-11-4713-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Impact of sea ice on the marine iron cycle and phytoplankton productivity
S. Wang
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
D. Bailey
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
K. Lindsay
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
J. K. Moore
Earth System Science, University of California, Irvine, CA, USA
M. Holland
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
Related authors
No articles found.
Cecilia Äijälä, Yafei Nie, Lucía Gutiérrez-Loza, Chiara De Falco, Siv Kari Lauvset, Bin Cheng, David A. Bailey, and Petteri Uotila
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-213, https://doi.org/10.5194/gmd-2024-213, 2024
Preprint under review for GMD
Short summary
Short summary
The sea ice around Antarctica has experienced record lows in recent years. To understand these changes, models are needed. MetROMS-UHel is a new version of an ocean–sea ice model with updated sea ice code and the atmospheric data. We investigate the effect of our updates on different variables with a focus on sea ice and show an improved sea ice representation as compared with observations.
Joshua Coupe, Nicole S. Lovenduski, Luise S. Gleason, Michael N. Levy, Kristen Krumhardt, Keith Lindsay, Charles Bardeen, Clay Tabor, Cheryl Harrison, Kenneth G. MacLeod, Siddhartha Mitra, and Julio Sepúlveda
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-94, https://doi.org/10.5194/gmd-2024-94, 2024
Preprint under review for GMD
Short summary
Short summary
We develop a new feature in the atmosphere and ocean components of the Community Earth System Model version 2. We have implemented ultraviolet (UV) radiation inhibition of photosynthesis of four marine phytoplankton functional groups represented in the Marine Biogeochemistry Library. The new feature is tested with varying levels of UV radiation. The new feature will enable an analysis of an asteroid impact’s effect on the ozone layer and how that affects the base of the marine food web.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
Short summary
Short summary
We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
Short summary
Short summary
Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243, https://doi.org/10.5194/gmd-15-8221-2022, https://doi.org/10.5194/gmd-15-8221-2022, 2022
Short summary
Short summary
Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI).
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
Short summary
Short summary
The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
Short summary
Short summary
The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
Short summary
Short summary
We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Ann Keen, Ed Blockley, David A. Bailey, Jens Boldingh Debernard, Mitchell Bushuk, Steve Delhaye, David Docquier, Daniel Feltham, François Massonnet, Siobhan O'Farrell, Leandro Ponsoni, José M. Rodriguez, David Schroeder, Neil Swart, Takahiro Toyoda, Hiroyuki Tsujino, Martin Vancoppenolle, and Klaus Wyser
The Cryosphere, 15, 951–982, https://doi.org/10.5194/tc-15-951-2021, https://doi.org/10.5194/tc-15-951-2021, 2021
Short summary
Short summary
We compare the mass budget of the Arctic sea ice in a number of the latest climate models. New output has been defined that allows us to compare the processes of sea ice growth and loss in a more detailed way than has previously been possible. We find that that the models are strikingly similar in terms of the major processes causing the annual growth and loss of Arctic sea ice and that the budget terms respond in a broadly consistent way as the climate warms during the 21st century.
Wei-Lei Wang, Guisheng Song, François Primeau, Eric S. Saltzman, Thomas G. Bell, and J. Keith Moore
Biogeosciences, 17, 5335–5354, https://doi.org/10.5194/bg-17-5335-2020, https://doi.org/10.5194/bg-17-5335-2020, 2020
Short summary
Short summary
Dimethyl sulfide, a volatile compound produced as a byproduct of marine phytoplankton activity, can be emitted to the atmosphere via gas exchange. In the atmosphere, DMS is oxidized to cloud condensation nuclei, thus contributing to cloud formation. Therefore, oceanic DMS plays an important role in regulating the planet's climate by influencing the radiation budget. In this study, we use an artificial neural network model to update the global DMS climatology and estimate the sea-to-air flux.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
Short summary
Short summary
The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
Short summary
Short summary
Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Nicole S. Lovenduski, Stephen G. Yeager, Keith Lindsay, and Matthew C. Long
Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, https://doi.org/10.5194/esd-10-45-2019, 2019
Short summary
Short summary
This paper shows that the absorption of carbon dioxide by the ocean is predictable several years in advance. This is important because fossil-fuel-derived carbon dioxide is largely responsible for anthropogenic global warming and because carbon dioxide emission management and global carbon cycle budgeting exercises can benefit from foreknowledge of ocean carbon absorption. The promising results from this new forecast system justify the need for additional oceanic observations.
Jessica Liptak, Gretchen Keppel-Aleks, and Keith Lindsay
Biogeosciences, 14, 1383–1401, https://doi.org/10.5194/bg-14-1383-2017, https://doi.org/10.5194/bg-14-1383-2017, 2017
Short summary
Short summary
We analyzed the evolution of the atmospheric CO2 mean annual cycle simulated during 1950–2300 under three scenarios designed to separate the effects of climate change, CO2 fertilization, and land use change. CO2 fertilization in boreal and temperate ecosystems drove mean annual cycle amplification over the NH midlatitudes during 1950–2300. Boreal and Arctic climate change drove high-latitude amplification before 2200, after which CO2 fertilization contributed nearly equally to amplification.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
Short summary
Short summary
The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
Weiwei Fu, James T. Randerson, and J. Keith Moore
Biogeosciences, 13, 5151–5170, https://doi.org/10.5194/bg-13-5151-2016, https://doi.org/10.5194/bg-13-5151-2016, 2016
Short summary
Short summary
Global NPP and EP are reduced considerably for RCP8.5. Negative response of NPP and EP to stratification increases reflects a bottom-up control. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP driven by phytoplankton community composition shifts. Projections of the NPP response to climate change depend on the phytoplankton community structure, the efficiency of the biological pump and the levels of regenerated production.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary
Short summary
This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
N. S. Lovenduski, M. C. Long, and K. Lindsay
Biogeosciences, 12, 6321–6335, https://doi.org/10.5194/bg-12-6321-2015, https://doi.org/10.5194/bg-12-6321-2015, 2015
Short summary
Short summary
We investigate variability in surface ocean carbonate chemistry using output from a 1000-year control simulation of an Earth System Model. We find that the detection timescale for trends is strongly influenced by the variability. As the scientific community seeks to detect the anthropogenic influence on ocean carbonate chemistry, these results will aid the interpretation of trends calculated from spatially and temporally sparse observations.
A. Jahn, K. Lindsay, X. Giraud, N. Gruber, B. L. Otto-Bliesner, Z. Liu, and E. C. Brady
Geosci. Model Dev., 8, 2419–2434, https://doi.org/10.5194/gmd-8-2419-2015, https://doi.org/10.5194/gmd-8-2419-2015, 2015
Short summary
Short summary
Carbon isotopes have been added to the ocean model of the Community Earth System Model version 1 (CESM1). This paper describes the details of how the abiotic 14C tracer and the biotic 13C and 14C tracers were added to the existing ocean model of the CESM. In addition, it shows the first results of the new model features compared to observational data for the 1990s.
R. T. Letscher, J. K. Moore, Y.-C. Teng, and F. Primeau
Biogeosciences, 12, 209–221, https://doi.org/10.5194/bg-12-209-2015, https://doi.org/10.5194/bg-12-209-2015, 2015
Short summary
Short summary
Marine DOM is known to exhibit stoichiometry depleted in N and P compared with POM, suggesting variable production and remineralization stoichiometry for C, N, and P within marine DOM cycling. We utilize marine DOM observations and an inverse tracer modeling framework to optimize DOM cycling parameters for the BEC biogeochemistry ocean model of the CESM, finding a variable stoichiometry with faster turnover of P > N > C superior to the commonly assumed Redfield stoichiometry for marine DOM.
K. Misumi, K. Lindsay, J. K. Moore, S. C. Doney, F. O. Bryan, D. Tsumune, and Y. Yoshida
Biogeosciences, 11, 33–55, https://doi.org/10.5194/bg-11-33-2014, https://doi.org/10.5194/bg-11-33-2014, 2014
B. A. Blazey, M. M. Holland, and E. C. Hunke
The Cryosphere, 7, 1887–1900, https://doi.org/10.5194/tc-7-1887-2013, https://doi.org/10.5194/tc-7-1887-2013, 2013
Related subject area
Biogeochemistry: Modelling, Aquatic
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
Efficiency metrics for ocean alkalinity enhancement under responsive and prescribed atmosphere conditions
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
Argon Saturation in a Suite of Coupled General Ocean Circulation Biogeochemical Models off Mauretania
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
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.
Michael Dominik Tyka
EGUsphere, https://doi.org/10.5194/egusphere-2024-2150, https://doi.org/10.5194/egusphere-2024-2150, 2024
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 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.
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.
Heiner Dietze and Ulrike Löptien
EGUsphere, https://doi.org/10.5194/egusphere-2024-918, https://doi.org/10.5194/egusphere-2024-918, 2024
Short summary
Short summary
We introduce argon saturation as a prognostic variable in a suite of coupled general ocean circulation biogeochemical models off Mauretania. 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.
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
Aguilar-Islas, A. M., Rember, R. D., Mordy, C. W., and Wu, J.: Sea ice-derived dissolved iron and its potential influence on the spring algal bloom in the Bering Sea, Geophys. Res. Lett., 35, L24601, https://doi.org/10.1029/2008gl035736, 2008.
Arrigo, K. R., Worthen, D. L., and Robinson, D. H.: A coupled ocean-ecosystem model of the Ross Sea: 2. Iron regulation of phytoplankton taxonomic variability and primary production, J. Geophys. Res.-Oceans, 108, 3231, https://doi.org/10.1029/2001jc000856, 2003.
Arrigo, K. R., van Dijken, G., and Pabi, S.: Impact of a shrinking Arctic ice cover on marine primary production, Geophys. Res. Lett., 35, L19603, https://doi.org/10.1029/2008gl035028, 2008.
Bhatia, M. P., Kujawinski, E. B., Das, S. B., Breier, C. F., Henderson, P. B., and Charette, M. A.: Greenland meltwater as a significant and potentially bioavailable source of iron to the ocean, Nat. Geosci., 6, 274–278, 2013.
Boe, J. L., Hall, A., and Qu, X.: September sea-ice cover in the Arctic Ocean projected to vanish by 2100, Nature Geosci., 2, 341–343, 2009.
Boyd, P. W.: Environmental factors controlling phytoplankton processes in the Southern Ocean, J. Phycol., 38, 844–861, 2002.
Boyd, P. W., Crossley, A. C., DiTullio, G. R., Griffiths, F. B., Hutchins, D. A., Queguiner, B., Sedwick, P. N., and Trull, T. W.: Control of phytoplankton growth by iron supply and irradiance in the subantarctic Southern Ocean: Experimental results from the SAZ Project, J. Geophys. Res.-Oceans, 106, 31573–31583, 2001.
Boyd, P. W., Arrigo, K. R., Strzepek, R., and van Dijken, G. L.: Mapping phytoplankton iron utilization: Insights into Southern Ocean supply mechanisms, J. Geophys. Res, 117, C06009, https://doi.org/10.1029/2011jc007726, 2012.
Danabasoglu, G., Bates, S. C., Briegleb, B. P., Jayne, S. R., Jochum, M., Large, W. G., Peacock, S., and Yeager, S. G.: The CCSM4 Ocean Component, J. Climate, 25, 1361–1389, 2012.
Danabasoglu, G., Yeager, S. G., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V. M., Cassou, C., Chassignet, E., Coward, A. C., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P. G., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., George Nurser, A. J., Pirani, A., y Mélia, D. S., Samuels, B. L., Scheinert, M., Sidorenko, D., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., and Wang, Q.: North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II), Part I: Mean states, Ocean Modell., 73, 76–107, 2014.
Deal, C., Jin, M. B., Elliott, S., Hunke, E., Maltrud, M., and Jeffery, N.: Large-scale modeling of primary production and ice algal biomass within arctic sea ice in 1992, J. Geophys. Res.-Oceans, 116, C07004, https://doi.org/10.1029/2010jc006409, 2011.
de Boyer Montégut, C., Madec, G., Fischer, A. S., Lazar, A., and Iudicone, D.: Mixed layer depth over the global ocean: An examination of profile data and a profile-based climatology, J. Geophys. Res., 109, C12003, https://doi.org/10.1029/2004jc002378, 2004.
de Jong, J., Schoemann, V., Maricq, N., Mattielli, N., Langhorne, P., Haskell, T., and Tison, J.-L.: Iron in land-fast sea ice of McMurdo Sound derived from sediment resuspension and wind-blown dust attributes to primary productivity in the Ross Sea, Antarctica, 157, 24–40, 2013.
Ducklow, H. W., Schofield, O., Vernet, M., Stammerjohn, S., and Erickson, M.: Multiscale control of bacterial production by phytoplankton dynamics and sea ice along the western Antarctic Peninsula: A regional and decadal investigation, J. Mar. Syst., 98/99, 26–39, 2012.
Fitch, D. T. and Moore, J. K.: Wind speed influence on phytoplankton bloom dynamics in the southern ocean marginal ice zone, J. Geophys. Res.-Oceans, 112, C08006, https://doi.org/10.1029/2006jc004061, 2007.
Garcia , H. E., Locarnini, R. A., Boyer, T. P., and Antonov, J. I.: World Ocean Atlas 2005, Volume 4: Nutrients (phosphate, nitrate, silicate), edited by: Levitus, S., NOAA Atlas NESDIS 64, US Government Printing Office, Washington, DC, 396 pp., 2006.
Geider, R. J., MacIntyre, H. L., and Kana, T. M.: A Dynamic Regulatory Model of Phytoplanktonic Acclimation to Light, Nutrients, and Temperature, Limnol. Oceanogr., 43, 679–694, 1998.
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z. L., and Zhang, M. H.: The Community Climate System Model Version 4, J. Climate, 24, 4973–4991, 2011.
Grotti, M., Soggia, F., Ianni, C., and Frache, R.: Trace metals distributions in coastal sea ice of Terra Nova Bay, Ross Sea, Antarctica, Antarc. Sci., 17, 289–300, 2005.
Holland, M. M., Bitz, C. M., and Tremblay, B.: Future abrupt reductions in the summer Arctic sea ice, Geophys. Res. Lett., 33, L23503, https://doi.org/10.1029/2006gl028024, 2006.
Holland, M. M., Bailey, D. A., Briegleb, B. P., Light, B., and Hunke, E.: Improved Sea Ice Shortwave Radiation Physics in CCSM4: The Impact of Melt Ponds and Aerosols on Arctic Sea Ice, J. Climate, 25, 1413–1430, 2012.
Holland, P. R. and Kwok, R.: Wind-driven trends in Antarctic sea-ice drift, Nat. Geosci., 5, 872–875, 2012.
Hunke, E. C. and Lipscomb, W. H.: CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual Version 4.1 LA-CC-06-012, T-3 Fluid Dynamics Group, Los Alamos National Laboratory, 2010.
Jeffery, N., Hunke, E. C., and Elliott, S. M.: Modeling the transport of passive tracers in sea ice, J. Geophys. Res.-Oceans, 116, C07020, https://doi.org/10.1029/2010jc006527, 2011.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., laRoche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., and Torres, R.: Global iron connections between desert dust, ocean biogeochemistry, and climate, Science, 308, 67–71, 2005.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, Bull. Am. Meteorol. Soc., 77, 437–471, 1996.
Key, R. M., Kozyr, A., Sabine, C. L., Lee, K., Wanninkhof, R., Bullister, J. L., Feely, R. A., Millero, F. J., Mordy, C., and Peng, T. H.: A global ocean carbon climatology: Results from Global Data Analysis Project (GLODAP), Global Biogeochem. Cy., 18, GB4031, https://doi.org/10.1029/2004gb002247, 2004.
Klunder, M. B., Bauch, D., Laan, P., de Baar, H. J. W., van Heuven, S., and Ober, S.: Dissolved iron in the Arctic shelf seas and surface waters of the central Arctic Ocean: Impact of Arctic river water and ice-melt, J. Geophys. Res.-Oceans, 117, C01027, https://doi.org/10.1029/2011jc007133, 2012.
Kurtz, N. T. and Markus, T.: Satellite observations of Antarctic sea ice thickness and volume, J. Geophys. Res.-Oceans, 117, C08025, https://doi.org/10.1029/2012jc008141, 2012.
Kwok, R., Cunningham, G. F., Wensnahan, M., Rigor, I., Zwally, H. J., and Yi, D.: Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008, J. Geophys. Res.-Oceans, 114, C07005, 10.1029/2009jc005312, 2009.
Lancelot, C., de Montety, A., Goosse, H., Becquevort, S., Schoemann, V., Pasquer, B., and Vancoppenolle, M.: Spatial distribution of the iron supply to phytoplankton in the Southern Ocean: a model study, Biogeosciences, 6, 2861–2878, https://doi.org/10.5194/bg-6-2861-2009, 2009.
Lannuzel, D., Schoemann, V., de Jong, J., Tison, J. L., and Chou, L.: Distribution and biogeochemical behaviour of iron in the East Antarctic sea ice, Mar. Chem., 106, 18–32, 2007.
Lannuzel, D., Schoemann, V., de Jong, J., Chou, L., Delille, B., Becquevort, S., and Tison, J. L.: Iron study during a time series in the western Weddell pack ice, Mar. Chem., 108, 85–95, 2008.
Lannuzel, D., Schoemann, V., de Jong, J., Pasquer, B., van der Merwe, P., Masson, F., Tison, J. L., and Bowie, A.: Distribution of dissolved iron in Antarctic sea ice: Spatial, seasonal, and inter-annual variability, J. Geophys. Res.-Biogeosciences , 115, G03022, https://doi.org/10.1029/2009jg001031, 2010.
Lannuzel, D., Bowie, A. R., van der Merwe, P. C., Townsend, A. T., and Schoemann, V.: Distribution of dissolved and particulate metals in Antarctic sea ice, Mar. Chem., 124, 134–146, 2011.
Lannuzel, D., Schoemann, V., Dumont, I., Content, M., de Jong, J., Tison, J.-L., Delille, B., and Becquevort, S.: Effect of melting Antarctic sea ice on the fate of microbial communities studied in microcosms, Polar Biol., 36, 1483–1497, 2013.
Lannuzel, D., van der Merwe, P. C., Townsend, A. T., and Bowie, A. R.: Size fractionation of iron, manganese and aluminium in Antarctic fast ice reveals a lithogenic origin and low iron solubility, Mar. Chem., 161, 47–56, 2014.
Large, W. G. and Yeager, S. G.: The global climatology of an interannually varying air–sea flux data set, Clim. Dynam., 33, 341–364, 2009.
Lee, S. H., Kim, B. K., Yun, M. S., Joo, H., Yang, E. J., Kim, Y. N., Shin, H. C., and Lee, S.: Spatial distribution of phytoplankton productivity in the Amundsen Sea, Antarctica, Polar Biol., 35, 1721–1733, 2012.
Lin, H., Rauschenberg, S., Hexel, C. R., Shaw, T. J., and Twining, B. S.: Free-drifting icebergs as sources of iron to the Weddell Sea, Deep-Sea Res. Pt. I, 58, 1392–1406, 2011.
Maenhaut, W., Ducastel, G., Leck, C., Nilsson, E. D., and Heintzenberg, J.: Multi-elemental composition and sources of the high Arctic atmospheric aerosol during summer and autumn, Tellus B, 48, 300–321, 1996.
Mahowald, N. M., Baker, A. R., Bergametti, G., Brooks, N., Duce, R. A., Jickells, T. D., Kubilay, N., Prospero, J. M., and Tegen, I.: Atmospheric global dust cycle and iron inputs to the ocean, Global Biogeochem. Cy., 19, Gb4025, https://doi.org/10.1029/2004gb002402, 2005.
Maslanik, J. A., Fowler, C., Stroeve, J., Drobot, S., Zwally, J., Yi, D., and Emery, W.: A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss, Geophys. Res. Lett., 34, L24501, https://doi.org/10.1029/2007gl032043, 2007.
Measures, C. I.: The role of entrained sediments in sea ice in the distribution of aluminium and iron in the surface waters of the Arctic Ocean, Mar. Chem., 68, 59–70, 1999.
Moore, J. K. and Braucher, O.: Sedimentary and mineral dust sources of dissolved iron to the world ocean, Biogeosciences, 5, 631–656, https://doi.org/10.5194/bg-5-631-2008, 2008.
Moore, J. K., Doney, S. C., Kleypas, J. A., Glover, D. M., and Fung, I. Y.: An intermediate complexity marine ecosystem model for the global domain, Deep-Sea Res. Part II, 49, 403–462, 2002.
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model, Global Biogeochem. Cy., 18, GB4028, https://doi.org/10.1029/2004gb002220, 2004.
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth System Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 Scenarios, J. Climate, 26, 9291–9312, 2013.
Nakayama, Y., Fujita, S., Kuma, K., and Shimada, K.: Iron and humic-type fluorescent dissolved organic matter in the Chukchi Sea and Canada Basin of the western Arctic Ocean, J. Geophys. Res.-Oceans, 116, C07031, https://doi.org/10.1029/2010jc006779, 2011.
Nghiem, S. V., Rigor, I. G., Perovich, D. K., Clemente-Colon, P., Weatherly, J. W., and Neumann, G.: Rapid reduction of Arctic perennial sea ice, Geophys. Res. Lett., 34, L19504, https://doi.org/10.1029/2007gl031138, 2007.
Nishimura, S., Kuma, K., Ishikawa, S., Omata, A., and Saitoh, S.: Iron, nutrients, and humic-type fluorescent dissolved organic matter in the northern Bering Sea shelf, Bering Strait, and Chukchi Sea, J. Geophys. Res.-Oceans, 117, C02025, https://doi.org/10.1029/2011jc007355, 2012.
Nurnberg, D., Wollenburg, I., Dethleff, D., Eicken, H., Kassens, H., Letzig, T., Reimnitz, E., and Thiede, J.: Sediments in Arctic sea ice: Implications for entrainment, transport and release, Mar. Geol., 119, 185–214, 1994.
Oza, S. R., Singh, R. K. K., Srivastava, A., Dash, M. K., Das, I. M. L., and Vyas, N. K.: Inter-annual variations observed in spring and summer Antarctic sea ice extent in recent decade, Mausam, 62, 633–640, 2011.
Pabi, S., van Dijken, G. L., and Arrigo, K. R.: Primary production in the Arctic Ocean, 1998–2006, J. Geophys. Res.-Oceans, 113, C08005, https://doi.org/10.1029/2007jc004578, 2008.
Parkinson, C. L. and Cavalieri, D. J.: Antarctic sea ice variability and trends, 1979–2010, Cryosphere, 6, 871–880, 2012.
Planquette, H., Sherrell, R. M., Stammerjohn, S., and Field, M. P.: Particulate iron delivery to the water column of the Amundsen Sea, Antarctica, Mar. Chem., 153, 15–30, 2013.
Rothrock, D. A., Yu, Y., and Maykut, G. A.: Thinning of the Arctic sea-ice cover, Geophys. Res. Lett., 26, 3469–3472, 1999.
Sedwick, P. N. and DiTullio, G. R.: Regulation of algal blooms in Antarctic shelf waters by the release of iron from melting sea ice, Geophys. Res. Lett., 24, 2515–2518, 1997.
Serreze, M. C., Holland, M. M., and Stroeve, J.: Perspectives on the Arctic's shrinking sea-ice cover, Science, 315, 1533–1536, 2007.
Shaw, T. J., Raiswell, R., Hexel, C. R., Vu, H. P., Moore, W. S., Dudgeon, R., and Smith, K. L.: Input, composition, and potential impact of terrigenous material from free-drifting icebergs in the Weddell Sea, Deep-Sea Res. Pt. I, 58, 1376–1383, 2011.
Smith, K. L., Robison, B. H., Helly, J. J., Kaufmann, R. S., Ruhl, H. A., Shaw, T. J., Twining, B. S., and Vernet, M.: Free-drifting icebergs: Hot spots of chemical and biological enrichment in the Weddell Sea, Science, 317, 478–482, 2007.
Smith, R. D., Jones, P., Briegleb, B. P., Bryan, F., Danabasoglu, G., Dennis, J., Dukowicz, J., Eden, C., Fox-Kemper, B., Gent, P., Hecht, M., Jayne, S., Jochum, M., Large, W., Lindsay, K., Maltrud, M., Norton, N., Peacock, S., Vertenstein, M., and Yeager, S.: The Parallel Ocean Program (POP) reference manual, ocean component of the Community Climate System Model (CCSM), Los Alamos National Laboratory Tech. Rep. LAUR-10-01853, 141 pp., 2010.
Smith, W. O. and Nelson, D. M.: phytoplankton bloom produced by a receding ice edge in the ross sea – spatial coherence with the density field, Science, 227, 163–166, 1985.
Stabeno, P., Napp, J., Mordy, C., and Whitledge, T.: Factors influencing physical structure and lower trophic levels of the eastern Bering Sea shelf in 2005: Sea ice, tides and winds, Prog. Oceanogr., 85, 180–196, 2010.
Stroeve, J. C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland, M., and Meier, W. N.: Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations, Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012gl052676, 2012.
Tagliabue, A. and Arrigo, K. R.: Processes governing the supply of iron to phytoplankton in stratified seas, J. Geophys. Res., 111, C06019, https://doi.org/10.1029/2005jc003363, 2006.
Tagliabue, A., Bopp, L., Dutay, J.-C., Bowie, A. R., Chever, F., Jean-Baptiste, P., Bucciarelli, E., Lannuzel, D., Remenyi, T., Sarthou, G., Aumont, O., Gehlen, M., and Jeandel, C.: Hydrothermal contribution to the oceanic dissolved iron inventory, Nature Geosci., 3, 252–256, 2010.
Tagliabue, A., Mtshali, T., Aumont, O., Bowie, A. R., Klunder, M. B., Roychoudhury, A. N., and Swart, S.: A global compilation of dissolved iron measurements: focus on distributions and processes in the Southern Ocean, Biogeosciences, 9, 2333–2349, https://doi.org/10.5194/bg-9-2333-2012, 2012.
Tagliabue, A., Sallée, J.-B., Bowie, A. R. , Lévy, M., Swart, S., and Boyd, P. W. : Surface-water iron supplies in the Southern Ocean sustained by deep winter mixing, Nature Geosci., 7, 314–320, 2014.
Taylor, M. H., Losch, M., and Bracher, A.: On the drivers of phytoplankton blooms in the Antarctic marginal ice zone: A modeling approach, J. Geophys. Res.-Oceans, 118, 63–75, 2013.
Thomas, D. N. and Dieckmann, G. S.: Ocean science – Antarctic Sea ice – a habitat for extremophites, Science, 295, 641–644, 2002.
Tovar-Sanchez, A., Duarte, C. M., Alonso, J. C., Lacorte, S., Tauler, R., and Galban-Malagon, C.: Impacts of metals and nutrients released from melting multiyear Arctic sea ice, J. Geophys. Res.-Oceans, 115, C07003, https://doi.org/10.1029/2009jc005685, 2010.
US Department of Commerce: 2-minute global gridded relief data. National Oceanographic and Atmospheric Administration, National Geophysical Data Center, 2006.
van der Merwe, P., Lannuzel, D., Nichols, C. A. M., Meiners, K., Heil, P., Norman, L., Thomas, D. N., and Bowie, A. R.: Biogeochemical observations during the winter-spring transition in East Antarctic sea ice: Evidence of iron and exopolysaccharide controls, Mar. Chem., 115, 163–175, 2009.
van der Merwe, P., Lannuzel, D., Bowie, A. R., and Meiners, K. M.: High temporal resolution observations of spring fast ice melt and seawater iron enrichment in East Antarctica, J. Geophys. Res.-Biogeosciences, 116, G03017, https://doi.org/10.1029/2010jg001628, 2011a.
van der Merwe, P., Lannuzel, D., Bowie, A. R., Nichols, C. A. M., and Meiners, K. M.: Iron fractionation in pack and fast ice in East Antarctica: Temporal decoupling between the release of dissolved and particulate iron during spring melt, Deep-Sea Res. Pt. I, 58, 1222–1236, 2011b.
Vancoppenolle, M., Goosse, H., de Montety, A., Fichefet, T., Tremblay, B., and Tison, J. L.: Modeling brine and nutrient dynamics in Antarctic sea ice: The case of dissolved silica, J. Geophys. Res.-Oceans, 115, C02005, https://doi.org/10.1029/2009jc005369, 2010.
Wang, S. and Moore, J. K.: Incorporating Phaeocystis into a Southern Ocean ecosystem model, J. Geophys. Res., 116, C01019, https://doi.org/10.1029/2009jc005817, 2011.
Altmetrics
Final-revised paper
Preprint