Articles | Volume 21, issue 10
https://doi.org/10.5194/bg-21-2473-2024
© Author(s) 2024. 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-21-2473-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 May 2024
Research article |
| 24 May 2024
| 24 May 2024
Southern Ocean phytoplankton under climate change: a shifting balance of bottom-up and top-down control
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Jens Terhaar
Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
A. E. Friederike Prowe
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Thomas L. Frölicher
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Andreas Oschlies
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Ivy Frenger
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Related authors
Tianfei Xue, Ivy Frenger, A. E. Friederike Prowe, Yonss Saranga José, and Andreas Oschlies
Biogeosciences, 19, 455–475, https://doi.org/10.5194/bg-19-455-2022, https://doi.org/10.5194/bg-19-455-2022, 2022
Short summary
Short summary
The Peruvian system supports 10 % of the world's fishing yield. In the Peruvian system, wind and earth’s rotation bring cold, nutrient-rich water to the surface and allow phytoplankton to grow. But observations show that it grows worse at high upwelling. Using a model, we find that high upwelling happens when air mixes the water the most. Then phytoplankton is diluted and grows slowly due to low light and cool upwelled water. This study helps to estimate how it might change in a warming climate.
Haichao Guo, Wolfgang Koeve, Andreas Oschlies, Yan-Chun He, Tronje Peer Kemena, Lennart Gerke, and Iris Kriest
Ocean Sci., 21, 1167–1182, https://doi.org/10.5194/os-21-1167-2025, https://doi.org/10.5194/os-21-1167-2025, 2025
Short summary
Short summary
We evaluated the effectiveness of the inverse Gaussian transit time distribution (IG-TTD) with respect to estimating the mean state and temporal changes of seawater age, defined as the duration since water last had contact with the atmosphere, within the tropical thermocline. Results suggest that the IG-TTD underestimates seawater age. Moreover, the IG-TTD constrained by a single tracer gives spurious trends in water age. Incorporating an additional tracer improves IG-TTD's accuracy for estimating temporal change of seawater age.
Florian Schütte, Johannes Hahn, Ivy Frenger, Arne Bendinger, Fehmi Dilmahamod, Marco Schulz, and Peter Brandt
EGUsphere, https://doi.org/10.5194/egusphere-2025-2175, https://doi.org/10.5194/egusphere-2025-2175, 2025
Short summary
Short summary
We found extreme drops in oxygen levels in the tropical Atlantic linked to surprisingly long-lived, small subsurface eddies. These eddies are hidden beneath the surface (undetectable by satellites) and are unusually stable, even in the highly dynamic ocean near the equator. Using long-term measurements and computer models, we show that these features can strongly influence oxygen supply and potentially impact marine ecosystems.
Li-Qing Jiang, Amanda Fay, Jens Daniel Müller, Lydia Keppler, Dustin Carroll, Siv K. Lauvset, Tim DeVries, Judith Hauck, Christian Rödenbeck, Luke Gregor, Nicolas Metzl, Andrea J. Fassbender, Jean-Pierre Gattuso, Peter Landschützer, Rik Wanninkhof, Christopher Sabine, Simone R. Alin, Mario Hoppema, Are Olsen, Matthew P. Humphreys, Kumiko Azetsu-Scott, Dorothee C. E. Bakker, Leticia Barbero, Nicholas R. Bates, Nicole Besemer, Henry C. Bittig, Albert E. Boyd, Daniel Broullón, Wei-Jun Cai, Brendan R. Carter, Thi-Tuyet-Trang Chau, Chen-Tung Arthur Chen, Frédéric Cyr, John E. Dore, Ian Enochs, Richard A. Feely, Hernan E. Garcia, Marion Gehlen, Lucas Gloege, Melchor González-Dávila, Nicolas Gruber, Yosuke Iida, Masao Ishii, Esther Kennedy, Alex Kozyr, Nico Lange, Claire Lo Monaco, Derek P. Manzello, Galen A. McKinley, Natalie M. Monacci, Xose A. Padin, Ana M. Palacio-Castro, Fiz F. Pérez, Alizée Roobaert, J. Magdalena Santana-Casiano, Jonathan Sharp, Adrienne Sutton, Jim Swift, Toste Tanhua, Maciej Telszewski, Jens Terhaar, Ruben van Hooidonk, Anton Velo, Andrew J. Watson, Angelicque E. White, Zelun Wu, Hyelim Yoo, and Jiye Zeng
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-255, https://doi.org/10.5194/essd-2025-255, 2025
Preprint under review for ESSD
Short summary
Short summary
This review article provides an overview of 60 existing ocean carbonate chemistry data products, encompassing a broad range of types, including compilations of cruise datasets, gap-filled observational products, model simulations, and more. It is designed to help researchers identify and access the data products that best support their scientific objectives, thereby facilitating progress in understanding the ocean's changing carbonate chemistry.
Linus Vogt, Casimir de Lavergne, Jean-Baptiste Sallée, Lester Kwiatkowski, Thomas L. Frölicher, and Jens Terhaar
EGUsphere, https://doi.org/10.21203/rs.3.rs-3982037/v2, https://doi.org/10.21203/rs.3.rs-3982037/v2, 2025
Short summary
Short summary
Ocean heat uptake (OHU) accounts for over 90% of the Earth's excess energy storage due to climate change, but future (OHU) projections strongly differ between climate models. Here, we reveal an observational constraint on future OHU using historical Antarctic sea ice extent observations. This emergent constraint is based on a coupling between sea ice, deep and surface ocean temperatures, and cloud feedback. It implies an upward correction of 2024–2100 global OHU projections by up to 14%.
Jens Terhaar
Biogeosciences, 22, 1631–1649, https://doi.org/10.5194/bg-22-1631-2025, https://doi.org/10.5194/bg-22-1631-2025, 2025
Short summary
Short summary
The ocean is a major natural carbon sink. Despite its importance, estimates of the ocean carbon sink remain uncertain. Here, I present a hybrid model estimate of the ocean carbon sink from 1959 to 2022. By combining ocean models in hindcast mode and Earth system models, I keep the strength of each approach and remove the respective weaknesses. This composite model estimate is similar in magnitude to the best estimate of the Global Carbon Budget but 70 % less uncertain.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
Short summary
Short summary
HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Anne L. Morée, Fabrice Lacroix, William W. L. Cheung, and Thomas L. Frölicher
Biogeosciences, 22, 1115–1133, https://doi.org/10.5194/bg-22-1115-2025, https://doi.org/10.5194/bg-22-1115-2025, 2025
Short summary
Short summary
Using novel Earth system model simulations and applying the Aerobic Growth Index, we show that only about half of the habitat loss for marine species is realized when temperature stabilization is initially reached. The maximum habitat loss happens over a century after peak warming in a temperature overshoot scenario peaking at 2 °C before stabilizing at 1.5 °C. We also emphasize that species adaptation may be key in mitigating the long-term impacts of temperature stabilization and overshoot.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernardello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
Earth Syst. Dynam., 15, 1591–1628, https://doi.org/10.5194/esd-15-1591-2024, https://doi.org/10.5194/esd-15-1591-2024, 2024
Short summary
Short summary
The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
Short summary
Short summary
We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Miriam Tivig, David P. Keller, and Andreas Oschlies
Biogeosciences, 21, 4469–4493, https://doi.org/10.5194/bg-21-4469-2024, https://doi.org/10.5194/bg-21-4469-2024, 2024
Short summary
Short summary
Marine biological production is highly dependent on the availability of nitrogen and phosphorus. Rivers are the main source of phosphorus to the oceans but poorly represented in global model oceans. We include dissolved nitrogen and phosphorus from river export in a global model ocean and find that the addition of riverine phosphorus affects marine biology on millennial timescales more than riverine nitrogen alone. Globally, riverine phosphorus input increases primary production rates.
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.
Timothée Bourgeois, Olivier Torres, Friederike Fröb, Aurich Jeltsch-Thömmes, Giang T. Tran, Jörg Schwinger, Thomas L. Frölicher, Jean Negrel, David Keller, Andreas Oschlies, Laurent Bopp, and Fortunat Joos
EGUsphere, https://doi.org/10.5194/egusphere-2024-2768, https://doi.org/10.5194/egusphere-2024-2768, 2024
Short summary
Short summary
Anthropogenic greenhouse gas emissions significantly impact ocean ecosystems through climate change and acidification, leading to either progressive or abrupt changes. This study maps the crossing of physical and ecological limits for various ocean impact metrics under three emission scenarios. Using Earth system models, we identify when these limits are exceeded, highlighting the urgent need for ambitious climate action to safeguard the world's oceans and ecosystems.
Jens Terhaar
Biogeosciences, 21, 3903–3926, https://doi.org/10.5194/bg-21-3903-2024, https://doi.org/10.5194/bg-21-3903-2024, 2024
Short summary
Short summary
Despite the ocean’s importance in the carbon cycle and hence the climate, observing the ocean carbon sink remains challenging. Here, I use an ensemble of 12 models to understand drivers of decadal trends of the past, present, and future ocean carbon sink. I show that 80 % of the decadal trends in the multi-model mean ocean carbon sink can be explained by changes in decadal trends in atmospheric CO2. The remaining 20 % are due to internal climate variability and ocean heat uptake.
Katja Fennel, Matthew C. Long, Christopher Algar, Brendan Carter, David Keller, Arnaud Laurent, Jann Paul Mattern, Ruth Musgrave, Andreas Oschlies, Josiane Ostiguy, Jaime B. Palter, and Daniel B. Whitt
State Planet, 2-oae2023, 9, https://doi.org/10.5194/sp-2-oae2023-9-2023, https://doi.org/10.5194/sp-2-oae2023-9-2023, 2023
Short summary
Short summary
This paper describes biogeochemical models and modelling techniques for applications related to ocean alkalinity enhancement (OAE) research. Many of the most pressing OAE-related research questions cannot be addressed by observation alone but will require a combination of skilful models and observations. We present illustrative examples with references to further information; describe limitations, caveats, and future research needs; and provide practical recommendations.
Andreas Oschlies, Lennart T. Bach, Rosalind E. M. Rickaby, Terre Satterfield, Romany Webb, and Jean-Pierre Gattuso
State Planet, 2-oae2023, 1, https://doi.org/10.5194/sp-2-oae2023-1-2023, https://doi.org/10.5194/sp-2-oae2023-1-2023, 2023
Short summary
Short summary
Reaching promised climate targets will require the deployment of carbon dioxide removal (CDR). Marine CDR options receive more and more interest. Based on idealized theoretical studies, ocean alkalinity enhancement (OAE) appears as a promising marine CDR method. We provide an overview on the current situation of developing OAE as a marine CDR method and describe the history that has led to the creation of the OAE research best practice guide.
Iris Kriest, Julia Getzlaff, Angela Landolfi, Volkmar Sauerland, Markus Schartau, and Andreas Oschlies
Biogeosciences, 20, 2645–2669, https://doi.org/10.5194/bg-20-2645-2023, https://doi.org/10.5194/bg-20-2645-2023, 2023
Short summary
Short summary
Global biogeochemical ocean models are often subjectively assessed and tuned against observations. We applied different strategies to calibrate a global model against observations. Although the calibrated models show similar tracer distributions at the surface, they differ in global biogeochemical fluxes, especially in global particle flux. Simulated global volume of oxygen minimum zones varies strongly with calibration strategy and over time, rendering its temporal extrapolation difficult.
Anne L. Morée, Tayler M. Clarke, William W. L. Cheung, and Thomas L. Frölicher
Biogeosciences, 20, 2425–2454, https://doi.org/10.5194/bg-20-2425-2023, https://doi.org/10.5194/bg-20-2425-2023, 2023
Short summary
Short summary
Ocean temperature and oxygen shape marine habitats together with species’ characteristics. We calculated the impacts of projected 21st-century warming and oxygen loss on the contemporary habitat volume of 47 marine species and described the drivers of these impacts. Most species lose less than 5 % of their habitat at 2 °C of global warming, but some species incur losses 2–3 times greater than that. We also calculate which species may be most vulnerable to climate change and why this is the case.
Jiajun Wu, David P. Keller, and Andreas Oschlies
Earth Syst. Dynam., 14, 185–221, https://doi.org/10.5194/esd-14-185-2023, https://doi.org/10.5194/esd-14-185-2023, 2023
Short summary
Short summary
In this study we investigate an ocean-based carbon dioxide removal method: macroalgae open-ocean mariculture and sinking (MOS), which aims to cultivate seaweed in the open-ocean surface and to sink matured biomass quickly to the deep seafloor. Our results suggest that MOS has considerable potential as an ocean-based CDR method. However, MOS has inherent side effects on marine ecosystems and biogeochemistry, which will require careful evaluation beyond this first idealized modeling study.
Natacha Le Grix, Jakob Zscheischler, Keith B. Rodgers, Ryohei Yamaguchi, and Thomas L. Frölicher
Biogeosciences, 19, 5807–5835, https://doi.org/10.5194/bg-19-5807-2022, https://doi.org/10.5194/bg-19-5807-2022, 2022
Short summary
Short summary
Compound events threaten marine ecosystems. Here, we investigate the potentially harmful combination of marine heatwaves with low phytoplankton productivity. Using satellite-based observations, we show that these compound events are frequent in the low latitudes. We then investigate the drivers of these compound events using Earth system models. The models share similar drivers in the low latitudes but disagree in the high latitudes due to divergent factors limiting phytoplankton production.
Jens Terhaar, Thomas L. Frölicher, and Fortunat Joos
Biogeosciences, 19, 4431–4457, https://doi.org/10.5194/bg-19-4431-2022, https://doi.org/10.5194/bg-19-4431-2022, 2022
Short summary
Short summary
Estimates of the ocean sink of anthropogenic carbon vary across various approaches. We show that the global ocean carbon sink can be estimated by three parameters, two of which approximate the ocean ventilation in the Southern Ocean and the North Atlantic, and one of which approximates the chemical capacity of the ocean to take up carbon. With observations of these parameters, we estimate that the global ocean carbon sink is 10 % larger than previously assumed, and we cut uncertainties in half.
Chia-Te Chien, Jonathan V. Durgadoo, Dana Ehlert, Ivy Frenger, David P. Keller, Wolfgang Koeve, Iris Kriest, Angela Landolfi, Lavinia Patara, Sebastian Wahl, and Andreas Oschlies
Geosci. Model Dev., 15, 5987–6024, https://doi.org/10.5194/gmd-15-5987-2022, https://doi.org/10.5194/gmd-15-5987-2022, 2022
Short summary
Short summary
We present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, and air–sea gas exchange of CO2 and O2. As shown by our evaluation, FOCI-MOPS shows an overall adequate performance that makes it an appropriate tool for Earth climate system simulations.
Tianfei Xue, Ivy Frenger, A. E. Friederike Prowe, Yonss Saranga José, and Andreas Oschlies
Biogeosciences, 19, 455–475, https://doi.org/10.5194/bg-19-455-2022, https://doi.org/10.5194/bg-19-455-2022, 2022
Short summary
Short summary
The Peruvian system supports 10 % of the world's fishing yield. In the Peruvian system, wind and earth’s rotation bring cold, nutrient-rich water to the surface and allow phytoplankton to grow. But observations show that it grows worse at high upwelling. Using a model, we find that high upwelling happens when air mixes the water the most. Then phytoplankton is diluted and grows slowly due to low light and cool upwelled water. This study helps to estimate how it might change in a warming climate.
Karin Kvale, David P. Keller, Wolfgang Koeve, Katrin J. Meissner, Christopher J. Somes, Wanxuan Yao, and Andreas Oschlies
Geosci. Model Dev., 14, 7255–7285, https://doi.org/10.5194/gmd-14-7255-2021, https://doi.org/10.5194/gmd-14-7255-2021, 2021
Short summary
Short summary
We present a new model of biological marine silicate cycling for the University of Victoria Earth System Climate Model (UVic ESCM). This new model adds diatoms, which are a key aspect of the biological carbon pump, to an existing ecosystem model. Our modifications change how the model responds to warming, with net primary production declining more strongly than in previous versions. Diatoms in particular are simulated to decline with climate warming due to their high nutrient requirements.
Olaf Duteil, Ivy Frenger, and Julia Getzlaff
Ocean Sci., 17, 1489–1507, https://doi.org/10.5194/os-17-1489-2021, https://doi.org/10.5194/os-17-1489-2021, 2021
Short summary
Short summary
The large oxygen minimum zones in the tropical Pacific Ocean are still not well represented by typical climate models. We analyze a set of ocean models and highlight the fact that an oxygen concentration that is too low at intermediate depth in the subtropical regions associated with a sluggish representation of the intermediate equatorial current system may be responsible for the overly large extension of the modeled oxygen minimum zones, potentially hampering future projections.
Maria-Theresia Verwega, Christopher J. Somes, Markus Schartau, Robyn Elizabeth Tuerena, Anne Lorrain, Andreas Oschlies, and Thomas Slawig
Earth Syst. Sci. Data, 13, 4861–4880, https://doi.org/10.5194/essd-13-4861-2021, https://doi.org/10.5194/essd-13-4861-2021, 2021
Short summary
Short summary
This work describes a ready-to-use collection of particulate organic carbon stable isotope ratio data sets. It covers the 1960s–2010s and all main oceans, providing meta-information and gridded data. The best coverage exists in Atlantic, Indian and Southern Ocean surface waters during the 1990s. It indicates no major difference between methods and shows decreasing values towards high latitudes, with the lowest in the Southern Ocean, and a long-term decline in all regions but the Southern Ocean.
Miriam Tivig, David P. Keller, and Andreas Oschlies
Biogeosciences, 18, 5327–5350, https://doi.org/10.5194/bg-18-5327-2021, https://doi.org/10.5194/bg-18-5327-2021, 2021
Short summary
Short summary
Nitrogen is one of the most important elements for life in the ocean. A major source is the riverine discharge of dissolved nitrogen. While global models often omit rivers as a nutrient source, we included nitrogen from rivers in our Earth system model and found that additional nitrogen affected marine biology not only locally but also in regions far off the coast. Depending on regional conditions, primary production was enhanced or even decreased due to internal feedbacks in the nitrogen cycle.
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.
Jaard Hauschildt, Soeren Thomsen, Vincent Echevin, Andreas Oschlies, Yonss Saranga José, Gerd Krahmann, Laura A. Bristow, and Gaute Lavik
Biogeosciences, 18, 3605–3629, https://doi.org/10.5194/bg-18-3605-2021, https://doi.org/10.5194/bg-18-3605-2021, 2021
Short summary
Short summary
In this paper we quantify the subduction of upwelled nitrate due to physical processes on the order of several kilometers in the coastal upwelling off Peru and its effect on primary production. We also compare the prepresentation of these processes in a high-resolution simulation (~2.5 km) with a more coarsely resolved simulation (~12 km). To do this, we combine high-resolution shipboard observations of physical and biogeochemical parameters with a complex biogeochemical model configuration.
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.
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.
Markus Pahlow, Chia-Te Chien, Lionel A. Arteaga, and Andreas Oschlies
Geosci. Model Dev., 13, 4663–4690, https://doi.org/10.5194/gmd-13-4663-2020, https://doi.org/10.5194/gmd-13-4663-2020, 2020
Short summary
Short summary
The stoichiometry of marine biotic processes is important for the regulation of atmospheric CO2 and hence the global climate. We replace a simplistic, fixed-stoichiometry plankton module in an Earth system model with an optimal-regulation model with variable stoichiometry. Our model compares better to the observed carbon transfer from the surface to depth and surface nutrient distributions. This work could aid our ability to describe and project the role of marine ecosystems in the Earth system.
Chia-Te Chien, Markus Pahlow, Markus Schartau, and Andreas Oschlies
Geosci. Model Dev., 13, 4691–4712, https://doi.org/10.5194/gmd-13-4691-2020, https://doi.org/10.5194/gmd-13-4691-2020, 2020
Short summary
Short summary
We demonstrate sensitivities of tracers to parameters of a new optimality-based plankton–ecosystem model (OPEM) in the UVic-ESCM. We find that changes in phytoplankton subsistence nitrogen quota strongly impact the nitrogen inventory, nitrogen fixation, and elemental stoichiometry of ordinary phytoplankton and diazotrophs. We introduce a new likelihood-based metric for model calibration, and it shows the capability of constraining globally averaged oxygen, nitrate, and DIC concentrations.
Nadine Mengis, David P. Keller, Andrew H. MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, Alexander J. MacIsaac, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, https://doi.org/10.5194/gmd-13-4183-2020, 2020
Short summary
Short summary
In this paper, we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used in the next phase of model intercomparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. Additionally, the model is able to reproduce the three-dimensional distribution of many ocean tracers.
Cited articles
Anderson, T. R., Gentleman, W. C., and Sinha, B.: Influence of grazing formulations on the emergent properties of a complex ecosystem model in a global ocean general circulation model, Prog. Oceanogr., 87, 201–213, https://doi.org/10.1016/j.pocean.2010.06.003, 2010. a
Arteaga, L. A., Pahlow, M., and Oschlies, A.: Modeled Chl: C ratio and derived estimates of phytoplankton carbon biomass and its contribution to total particulate organic carbon in the global surface ocean, Global Biogeochem. Cy., 30, 1791–1810, https://doi.org/10.1002/2016GB005458, 2016. a
Barnes, C., Maxwell, D., Reuman, D. C., and Jennings, S.: Global patterns in predator–prey size relationships reveal size dependency of trophic transfer efficiency, Ecology, 91, 222–232, https://doi.org/10.1890/08-2061.1, 2010. a
Behrenfeld, M. J., O’Malley, R. T., Siegel, D. A., McClain, C. R., Sarmiento, J. L., Feldman, G. C., Milligan, A. J., Falkowski, P. G., Letelier, R. M., and Boss, E. S.: Climate-driven trends in contemporary ocean productivity, Nature, 444, 752–755, https://doi.org/10.1038/nature05317, 2006. a, b, c
Bopp, L., Monfray, P., Aumont, O., Dufresne, J.-L., Le Treut, H., Madec, G., Terray, L., and Orr, J. C.: Potential impact of climate change on marine export production, Global Biogeochem. Cy., 15, 81–99, https://doi.org/10.1029/1999GB001256, 2001. a
Bopp, L., Aumont, O., Cadule, P., Alvain, S., and Gehlen, M.: Response of diatoms distribution to global warming and potential implications: A global model study, Geophys. Res. Lett., 32, L19606, https://doi.org/10.1029/2005GL023653, 2005. a
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013. a
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., and Vuichard, N.: Presentation and evaluation of the IPSL-CM6A-LR climate model, J. Adv. Model. Earth Sy., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020. a
Bowman, D. M., Kolden, C. A., Abatzoglou, J. T., Johnston, F. H., van der Werf, G. R., and Flannigan, M.: Vegetation fires in the Anthropocene, Nat. Rev. Earth Environ., 1, 500–515, https://doi.org/10.1038/s43017-020-0085-3, 2020. a
Boyce, D. G., Lewis, M. R., and Worm, B.: Global phytoplankton decline over the past century, Nature, 466, 591–596, https://doi.org/10.1038/nature09268, 2010. a
Caron, D. A. and Hutchins, D. A.: The effects of changing climate on microzooplankton grazing and community structure: drivers, predictions and knowledge gaps, J. Plankton Res., 35, 235–252, https://doi.org/10.1093/plankt/fbs091, 2013. a
Chang, P., Xu, G., Kurian, J., Small, R. J., Danabasoglu, G., Yeager, S., Castruccio, F., Zhang, Q., Rosenbloom, N., and Chapman, P.: Uncertain future of sustainable fisheries environment in eastern boundary upwelling zones under climate change, Commun. Earth Environ., 4, 19, https://doi.org/10.1038/s43247-023-00681-0, 2023. a
Chien, C.-T., Durgadoo, J. V., Ehlert, D., Frenger, I., Keller, D. P., Koeve, W., Kriest, I., Landolfi, A., Patara, L., Wahl, S., and Oschlies, A.: FOCI-MOPS v1 – integration of marine biogeochemistry within the Flexible Ocean and Climate Infrastructure version 1 (FOCI 1) Earth system model, Geosci. Model Dev., 15, 5987–6024, https://doi.org/10.5194/gmd-15-5987-2022, 2022. a, b
Christian, J. R., Denman, K. L., Hayashida, H., Holdsworth, A. M., Lee, W. G., Riche, O. G. J., Shao, A. E., Steiner, N., and Swart, N. C.: Ocean biogeochemistry in the Canadian Earth System Model version 5.0.3: CanESM5 and CanESM5-CanOE, Geosci. Model Dev., 15, 4393–4424, https://doi.org/10.5194/gmd-15-4393-2022, 2022. a
Chust, G., Allen, J. I., Bopp, L., Schrum, C., Holt, J., Tsiaras, K., Zavatarelli, M., Chifflet, M., Cannaby, H., Dadou, I., and Irigoien, X.: Biomass changes and trophic amplification of plankton in a warmer ocean, Glob. Change Biol., 20, 2124–2139, https://doi.org/10.1111/gcb.12562, 2014. a, b, c, d
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D., DuVivier, A., Edwards, J., Emmons, L., Fasullo, J., Garcia, R., Gettelman, A., and Strand, W.: The community earth system model version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a
Deppeler, S. L. and Davidson, A. T.: Southern Ocean phytoplankton in a changing climate, Front. Mar. Sci., 4, 40, https://doi.org/10.3389/fmars.2017.00040, 2017. a, b, c
Dunne, J., Horowitz, L., Adcroft, A., Ginoux, P., Held, I., John, J., Krasting, J., Malyshev, S., Naik, V., Paulot, F., and Zhao, M.: The GFDL Earth System Model version 4.1 (GFDL-ESM 4.1): Overall coupled model description and simulation characteristics, J. Adv. Model. Earth Sy., 12, e2019MS002015, https://doi.org/10.1029/2019MS002015, 2020. a
ESA: GlobColour Project, https://www.globcolour.info/, last access: 22 May 2024. a
ESGF: DKRZ ESGF-CoG Node, https://esgf-data.dkrz.de, last access: 22 May 2024. a
Field, C. B., Behrenfeld, M. J., Randerson, J. T., and Falkowski, P.: Primary production of the biosphere: integrating terrestrial and oceanic components, Science, 281, 237–240, https://doi.org/10.1126/science.281.5374.237, 1998. a
Frenger, I., Münnich, M., and Gruber, N.: Imprint of Southern Ocean mesoscale eddies on chlorophyll, Biogeosciences, 15, 4781–4798, https://doi.org/10.5194/bg-15-4781-2018, 2018. a
Frölicher, T. L., Rodgers, K. B., Stock, C. A., and Cheung, W. W.: Sources of uncertainties in 21st century projections of potential ocean ecosystem stressors, Global Biogeochem. Cy., 30, 1224–1243, https://doi.org/10.1002/2015GB005338, 2016. a
Geider, R. J.: Light and temperature dependence of the carbon to chlorophyll a ratio in microalgae and cyanobacteria: implications for physiology and growth of phytoplankton, New Phytol., 106, 1–34, https://doi.org/10.1111/j.1469-8137.1987.tb04788.x, 1987. a
Hall, A., Cox, P., Huntingford, C., and Klein, S.: Progressing emergent constraints on future climate change, Nat. Clim. Change, 9, 269–278, https://doi.org/10.1038/s41558-019-0436-6, 2019. a
Hamilton, D. S., Moore, J. K., Arneth, A., Bond, T. C., Carslaw, K. S., Hantson, S., Ito, A., Kaplan, J. O., Lindsay, K., Nieradzik, L., and Mahowald, N. M.: Impact of changes to the atmospheric soluble iron deposition flux on ocean biogeochemical cycles in the Anthropocene, Global Biogeochem. Cy., 34, e2019GB006448, https://doi.org/10.1029/2019GB006448, 2020. a
Henley, S. F., Cavan, E. L., Fawcett, S. E., Kerr, R., Monteiro, T., Sherrell, R. M., Bowie, A. R., Boyd, P. W., Barnes, D. K., Schloss, I. R., and Shantelle, S.: Changing biogeochemistry of the Southern Ocean and its ecosystem implications, Front. Mar. Sci., 7, 581, https://doi.org/10.3389/fmars.2020.00581, 2020. a, b
Holte, J. and Talley, L.: A new algorithm for finding mixed layer depths with applications to Argo data and Subantarctic Mode Water formation, J. Atmos. Ocean. Tech., 26, 1920–1939, https://doi.org/10.1175/2009JTECHO543.1, 2009. a
Holte, J., Talley, L. D., Gilson, J., and Roemmich, D.: An Argo mixed layer climatology and database, Geophys. Res. Lett., 44, 5618–5626, https://doi.org/10.1002/2017GL073426, 2017 (data available at: http://mixedlayer.ucsd.edu/, last access: 22 May 2024). a
IPCC: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 755 pp., https://doi.org/10.1017/9781009157964, 2019. a
Kessler, A. and Tjiputra, J.: The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks, Earth Syst. Dynam., 7, 295–312, https://doi.org/10.5194/esd-7-295-2016, 2016. a
Kiørboe, T.: A mechanistic approach to plankton ecology, ASLO Web Lectures, 1, 1–91, 2009. a
Krumhardt, K. M., Long, M. C., Sylvester, Z. T., and Petrik, C. M.: Climate drivers of Southern Ocean phytoplankton community composition and potential impacts on higher trophic levels, Front. Mar. Sci., 9, 916140, https://doi.org/10.3389/fmars.2022.916140, 2022. a
Kwiatkowski, L., Bopp, L., Aumont, O., Ciais, P., Cox, P. M., Laufkötter, C., Li, Y., and Séférian, R.: Emergent constraints on projections of declining primary production in the tropical oceans, Nat. Clim. Change, 7, 355–358, https://doi.org/10.1038/nclimate3265, 2017. a, b, c
Kwiatkowski, L., Aumont, O., and Bopp, L.: Consistent trophic amplification of marine biomass declines under climate change, Glob. Change Biol., 25, 218–229, https://doi.org/10.1111/gcb.14468, 2019. a, b, c
Kwiatkowski, L., Torres, O., Bopp, L., Aumont, O., Chamberlain, M., Christian, J. R., Dunne, J. P., Gehlen, M., Ilyina, T., John, J. G., Lenton, A., Li, H., Lovenduski, N. S., Orr, J. C., Palmieri, J., Santana-Falcón, Y., Schwinger, J., Séférian, R., Stock, C. A., Tagliabue, A., Takano, Y., Tjiputra, J., Toyama, K., Tsujino, H., Watanabe, M., Yamamoto, A., Yool, A., and Ziehn, T.: Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections, Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, 2020. a, b, c, d
Laufkötter, C., Vogt, M., Gruber, N., Aita-Noguchi, M., Aumont, O., Bopp, L., Buitenhuis, E., Doney, S. C., Dunne, J., Hashioka, T., Hauck, J., Hirata, T., John, J., Le Quéré, C., Lima, I. D., Nakano, H., Seferian, R., Totterdell, I., Vichi, M., and Völker, C.: Drivers and uncertainties of future global marine primary production in marine ecosystem models, Biogeosciences, 12, 6955–6984, https://doi.org/10.5194/bg-12-6955-2015, 2015. a, b, c, d, e, f, g
Le Grix, N., Zscheischler, J., Rodgers, K. B., Yamaguchi, R., and Frölicher, T. L.: Hotspots and drivers of compound marine heatwaves and low net primary production extremes, Biogeosciences, 19, 5807–5835, https://doi.org/10.5194/bg-19-5807-2022, 2022. a
Le Quéré, C., Buitenhuis, E. T., Moriarty, R., Alvain, S., Aumont, O., Bopp, L., Chollet, S., Enright, C., Franklin, D. J., Geider, R. J., Harrison, S. P., Hirst, A. G., Larsen, S., Legendre, L., Platt, T., Prentice, I. C., Rivkin, R. B., Sailley, S., Sathyendranath, S., Stephens, N., Vogt, M., and Vallina, S. M.: Role of zooplankton dynamics for Southern Ocean phytoplankton biomass and global biogeochemical cycles, Biogeosciences, 13, 4111–4133, https://doi.org/10.5194/bg-13-4111-2016, 2016. a, b, c
Lotze, H. K., Tittensor, D. P., Bryndum-Buchholz, A., Eddy, T. D., Cheung, W. W., Galbraith, E. D., Barange, M., Barrier, N., Bianchi, D., Blanchard, J. L., and Worm, B.: Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change, P. Natl. Acad. Sci. USA, 116, 12907–12912, https://doi.org/10.1073/pnas.1900194116, 2019. a, b, c
Lovato, T., Peano, D., Butenschön, M., Materia, S., Iovino, D., Scoccimarro, E., Fogli, P., Cherchi, A., Bellucci, A., Gualdi, S., and Masina, S.: CMIP6 Simulations With the CMCC Earth System Model (CMCC-ESM2), J. Adv. Model. Earth Sy., 14, e2021MS002814, https://doi.org/10.1029/2021MS002814, 2022. a
Marinov, I., Gnanadesikan, A., Toggweiler, J., and Sarmiento, J. L.: The Southern Ocean biogeochemical divide, Nature, 441, 964–967, https://doi.org/10.1038/nature04883, 2006. a
Marinov, I., Doney, S. C., and Lima, I. D.: Response of ocean phytoplankton community structure to climate change over the 21st century: partitioning the effects of nutrients, temperature and light, Biogeosciences, 7, 3941–3959, https://doi.org/10.5194/bg-7-3941-2010, 2010. a, b
Martin, J. H., Gordon, R. M., and Fitzwater, S. E.: Iron in Antarctic waters, Nature, 345, 156–158, https://doi.org/10.1038/345156a0, 1990. a, b
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1. 2) and its response to increasing CO2, J. Adv. Model. Earth Sy., 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019. a
Mitchell, B. G., Brody, E. A., Holm-Hansen, O., McClain, C., and Bishop, J.: Light limitation of phytoplankton biomass and macronutrient utilization in the Southern Ocean, Limnol. Oceanogr., 36, 1662–1677, https://doi.org/10.4319/lo.1991.36.8.1662, 1991. a
Moore, C., Mills, M., Arrigo, K., Berman-Frank, I., Bopp, L., Boyd, P., Galbraith, E., Geider, R., Guieu, C., Jaccard, S., and Ulloa, O.: Processes and patterns of oceanic nutrient limitation, Nat. Geosci., 6, 701–710, https://doi.org/10.1038/ngeo1765, 2013. a, b
Moore, J. K., Doney, S. C., Glover, D. M., and Fung, I. Y.: Iron cycling and nutrient-limitation patterns in surface waters of the World Ocean, Deep-Sea Res. Pt. II, 49, 463–507, https://doi.org/10.1016/S0967-0645(01)00109-6, 2001. a
Moriarty, R. and O'Brien, T. D.: Distribution of mesozooplankton biomass in the global ocean, Earth Syst. Sci. Data, 5, 45–55, https://doi.org/10.5194/essd-5-45-2013, 2013. a
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M., Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., and Marotzke, J.: A Higher-resolution Version of the Max Planck Institute Earth System Model (MPI-ESM1.2-HR), J. Adv. Model. Earth Sy., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018. a
Nissen, C., Gruber, N., Münnich, M., and Vogt, M.: Southern Ocean phytoplankton community structure as a gatekeeper for global nutrient biogeochemistry, Global Biogeochem. Cy., 35, e2021GB006991, https://doi.org/10.1029/2021GB006991, 2021. a
Pauly, D. and Christensen, V.: Primary production required to sustain global fisheries, Nature, 374, 255–257, https://doi.org/10.1038/374255a0, 1995. a
Petrik, C., Luo, J., Heneghan, R., Everett, J., and Harrison, A.: Assessment and constraint of mesozooplankton in CMIP6 Earth system models, Global Biogeochem. Cy., 36, e2022GB007367, https://doi.org/10.1029/2022GB007367, 2022. a
Petrou, K., Kranz, S. A., Trimborn, S., Hassler, C. S., Ameijeiras, S. B., Sackett, O., Ralph, P. J., and Davidson, A. T.: Southern Ocean phytoplankton physiology in a changing climate, J. Plant Physiol., 203, 135–150, https://doi.org/10.1016/j.jplph.2016.05.004, 2016. a, b
Prowe, A. F., Visser, A. W., Andersen, K. H., Chiba, S., and Kiørboe, T.: Biogeography of zooplankton feeding strategy, Limnol. Oceanogr., 64, 661–678, https://doi.org/10.1002/lno.11067, 2019. a, b
Prowe, A. F., Su, B., Nejstgaard, J. C., and Schartau, M.: Food web structure and intraguild predation affect ecosystem functioning in an established plankton model, Limnol. Oceanogr., 67, 843–855, https://doi.org/10.1002/lno.12039, 2022. a
Ratnarajah, L., Abu-Alhaija, R., Atkinson, A., Batten, S., Bax, N. J., Bernard, K. S., Canonico, G., Cornils, A., Everett, J. D., Grigoratou, M., and Yebra, L.: Monitoring and modelling marine zooplankton in a changing climate, Nat. Commun., 14, 564, https://doi.org/10.1038/s41467-023-36241-5, 2023. a
Rohr, T., Richardson, A. J., Lenton, A., Chamberlain, M. A., and Shadwick, E. H.: Zooplankton grazing is the largest source of uncertainty for marine carbon cycling in CMIP6 models, Commun. Earth Environ., 4, 212, https://doi.org/10.1038/s43247-023-00871-w, 2023. a, b
Ryan-Keogh, T. J., Thomalla, S. J., Monteiro, P. M., and Tagliabue, A.: Multidecadal trend of increasing iron stress in Southern Ocean phytoplankton, Science, 379, 834–840, https://doi.org/10.1126/science.abl5237, 2023. a
Sarmiento, J. L., Gruber, N., Brzezinski, M., and Dunne, J.: High-latitude controls of thermocline nutrients and low latitude biological productivity, Nature, 427, 56–60, https://doi.org/10.1038/nature02127, 2004a. a
Sarmiento, J. L., Slater, R., Barber, R., Bopp, L., Doney, S., Hirst, A., Kleypas, J., Matear, R., Mikolajewicz, U., Monfray, P., and Stouffer, R.: Response of ocean ecosystems to climate warming, Global Biogeochem. Cy., 18, GB3003, https://doi.org/10.1029/2003GB002134, 2004b. a, b, c, d
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M., S., S., and Madec, G.: Evaluation of CNRM earth system model, CNRM-ESM2-1: Role of earth system processes in present-day and future climate, J. Adv. Model. Earth Sy., 11, 4182–4227, https://doi.org/10.1029/2019MS001791, 2019. a
Séférian, R., Berthet, S., Yool, A., Palmieri, J., Bopp, L., Tagliabue, A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., and Yamamoto, A.: Tracking improvement in simulated marine biogeochemistry between CMIP5 and CMIP6, Current Climate Change Reports, 6, 95–119, https://doi.org/10.1007/s40641-020-00160-0, 2020. a
Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A., O'connor, F. M., Stringer, M., Hill, R., Palmieri, J., and Zerroukat, M.: UKESM1: Description and evaluation of the UK Earth System Model, J. Adv. Model. Earth Sy., 11, 4513–4558, https://doi.org/10.1029/2019MS001739, 2019. a
Shurin, J. B., Clasen, J. L., Greig, H. S., Kratina, P., and Thompson, P. L.: Warming shifts top-down and bottom-up control of pond food web structure and function, Philos. T. Roy. Soc. B, 367, 3008–3017, https://doi.org/10.1098/rstb.2012.0243, 2012. a
Song, H., Long, M. C., Gaube, P., Frenger, I., Marshall, J., and McGillicuddy Jr, D. J.: Seasonal variation in the correlation between anomalies of sea level and chlorophyll in the Antarctic Circumpolar Current, Geophys. Res. Lett., 45, 5011–5019, https://doi.org/10.1029/2017GL076246, 2018. a
Steinacher, M., Joos, F., Frölicher, T. L., Bopp, L., Cadule, P., Cocco, V., Doney, S. C., Gehlen, M., Lindsay, K., Moore, J. K., Schneider, B., and Segschneider, J.: Projected 21st century decrease in marine productivity: a multi-model analysis, Biogeosciences, 7, 979–1005, https://doi.org/10.5194/bg-7-979-2010, 2010. a, b
Stock, C. A., Dunne, J. P., and John, J. G.: Drivers of trophic amplification of ocean productivity trends in a changing climate, Biogeosciences, 11, 7125–7135, https://doi.org/10.5194/bg-11-7125-2014, 2014a. a, b, c
Stock, C., Dunne, J. P., and John, J. G.: Global-scale carbon and energy flows through the marine planktonic food web: An analysis with a coupled physical–biological model, Prog. Oceanogr., 120, 1–28, https://doi.org/10.1016/j.pocean.2013.07.001, 2014b. a, b
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019. a
Tagliabue, A., Aumont, O., DeAth, R., Dunne, J. P., Dutkiewicz, S., Galbraith, E., Misumi, K., Moore, J. K., Ridgwell, A., Sherman, E., and Yool, A.: How well do global ocean biogeochemistry models simulate dissolved iron distributions?, Global Biogeochem. Cy., 30, 149–174, https://doi.org/10.1002/2015GB005289, 2016. a
Tagliabue, A., Bowie, A. R., Boyd, P. W., Buck, K. N., Johnson, K. S., and Saito, M. A.: The integral role of iron in ocean biogeochemistry, Nature, 543, 51–59, https://doi.org/10.1038/nature21058, 2017. a, b
Tagliabue, A., Kwiatkowski, L., Bopp, L., Butenschön, M., Cheung, W., Lengaigne, M., and Vialard, J.: Persistent uncertainties in ocean net primary production climate change projections at regional scales raise challenges for assessing impacts on ecosystem services, Frontiers in Climate, p. 149, https://doi.org/10.3389/fclim.2021.738224, 2021. a
Terhaar, J., Kwiatkowski, L., and Bopp, L.: Emergent constraint on Arctic Ocean acidification in the twenty-first century, Nature, 582, 379–383, https://doi.org/10.1038/s41586-020-2360-3, 2020. a
Terhaar, J., Frölicher, T. L., and Joos, F.: Southern Ocean anthropogenic carbon sink constrained by sea surface salinity, Sci. Adv., 7, eabd5964, https://doi.org/10.1126/sciadv.abd5964, 2021a. a, b
Terhaar, J., Torres, O., Bourgeois, T., and Kwiatkowski, L.: Arctic Ocean acidification over the 21st century co-driven by anthropogenic carbon increases and freshening in the CMIP6 model ensemble, Biogeosciences, 18, 2221–2240, https://doi.org/10.5194/bg-18-2221-2021, 2021b. a
Terhaar, J., Frölicher, T. L., and Joos, F.: Observation-constrained estimates of the global ocean carbon sink from Earth system models, Biogeosciences, 19, 4431–4457, https://doi.org/10.5194/bg-19-4431-2022, 2022. a
Tjiputra, J. F., Schwinger, J., Bentsen, M., Morée, A. L., Gao, S., Bethke, I., Heinze, C., Goris, N., Gupta, A., He, Y.-C., Olivié, D., Seland, Ø., and Schulz, M.: Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2), Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, 2020. a
Tsujino, H., Nakano, H., Sakamoto, K., Urakawa, S., Hirabara, M., Ishizaki, H., and Yamanaka, G.: Reference manual for the Meteorological Research Institute Community Ocean Model version 4 (MRI. COMv4), Technical Reports of the Meteorological Research Institute, 80, 306, 2017. a
Uchida, T., Balwada, D., Abernathey, R., Prend, C. J., Boss, E., and Gille, S. T.: Southern Ocean phytoplankton blooms observed by biogeochemical floats, J. Geophys. Res.-Oceans, 124, 7328–7343, https://doi.org/10.1029/2019JC015355, 2019. a
Westberry, T., Behrenfeld, M., Siegel, D., and Boss, E.: Carbon-based primary productivity modeling with vertically resolved photoacclimation, Global Biogeochem. Cy., 22, GB2024, https://doi.org/10.1029/2007GB003078, 2008. a
Williamson, M. S., Thackeray, C. W., Cox, P. M., Hall, A., Huntingford, C., and Nijsse, F. J.: Emergent constraints on climate sensitivities, Rev. Mod. Phys., 93, 025004, https://doi.org/10.1103/RevModPhys.93.025004, 2021. a, b, c
Woodward, S., Roberts, D., and Betts, R.: A simulation of the effect of climate change–induced desertification on mineral dust aerosol, Geophys. Res. Lett., 32, L18810, https://doi.org/10.1029/2005GL023482, 2005. a
Xue, T., Frenger, I., Oschlies, A., Stock, C. A., Koeve, W., John, J. G., and Prowe, A. E.: Mixed layer depth promotes trophic amplification on a seasonal scale, Geophys. Res. Lett., 49, e2022GL098720, https://doi.org/10.1029/2022GL098720, 2022a. a, b
Xue, T., Frenger, I., Prowe, A. E. F., José, Y. S., and Oschlies, A.: Mixed layer depth dominates over upwelling in regulating the seasonality of ecosystem functioning in the Peruvian upwelling system, Biogeosciences, 19, 455–475, https://doi.org/10.5194/bg-19-455-2022, 2022b. a
Ziehn, T., Chamberlain, M. A., Law, R. M., Lenton, A., Bodman, R. W., Dix, M., Stevens, L., Wang, Y.-P., and Srbinovsky, J.: The Australian earth system model: ACCESS-ESM1.5, Journal of Southern Hemisphere Earth Systems Science, 70, 193–214, https://doi.org/10.1071/ES19035, 2020. a
Short summary
Phytoplankton play a crucial role in marine ecosystems. However, climate change's impact on phytoplankton biomass remains uncertain, particularly in the Southern Ocean. In this region, phytoplankton biomass within the water column is likely to remain stable in response to climate change, as supported by models. This stability arises from a shallower mixed layer, favoring phytoplankton growth but also increasing zooplankton grazing due to phytoplankton concentration near the surface.
Phytoplankton play a crucial role in marine ecosystems. However, climate change's impact on...
Altmetrics
Final-revised paper
Preprint