Articles | Volume 22, issue 9
https://doi.org/10.5194/bg-22-2163-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-2163-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 May 2025
Research article |
| 05 May 2025
| 05 May 2025
Inadequacies in the representation of sub-seasonal phytoplankton dynamics in Earth system models
Madhavan Girijakumari Keerthi
CORRESPONDING AUTHOR
LOCEAN-IPSL, Sorbonne Université, CNRS, IRD, MNHN, Paris, France
LMD-IPSL, École Normale Supérieure, Université PSL, CNRS, École Polytechnique, Paris, France
Olivier Aumont
LOCEAN-IPSL, Sorbonne Université, CNRS, IRD, MNHN, Paris, France
Lester Kwiatkowski
LOCEAN-IPSL, Sorbonne Université, CNRS, IRD, MNHN, Paris, France
Marina Levy
LOCEAN-IPSL, Sorbonne Université, CNRS, IRD, MNHN, Paris, France
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Alban Planchat, Laurent Bopp, and Lester Kwiatkowski
Biogeosciences, 22, 6017–6055, https://doi.org/10.5194/bg-22-6017-2025, https://doi.org/10.5194/bg-22-6017-2025, 2025
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Disparities between observational and model-based estimates of the ocean carbon sink persist, highlighting the need for improved understanding and methodologies to reconcile differences in both magnitude and trends over recent decades. A potential key source of uncertainty lies in the pre-industrial air–sea carbon flux, which is essential for isolating the anthropogenic component from observations. Thus, we take a fresh look at this flux using the alkalinity budget, alongside the carbon budget.
Léna L. Champiot-Bayard, Lester L. Kwiatkowski, and Martin M. Vancoppenolle
EGUsphere, https://doi.org/10.5194/egusphere-2025-4296, https://doi.org/10.5194/egusphere-2025-4296, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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To investigate the future of primary production, we analyzed outputs from several climate models. Changes vary greatly from one region to another: some areas show large increases, while others experience little change or even declines. These differences reflect the balance between water temperature, light availability, and nutrient supply. We also found that the newer generation of climate models projects a much stronger increase than previous models, but with greater uncertainty.
Linus Vogt, Casimir de Lavergne, Jean-Baptiste Sallée, Lester Kwiatkowski, Thomas L. Frölicher, and Jens Terhaar
Earth Syst. Dynam., 16, 1453–1482, https://doi.org/10.5194/esd-16-1453-2025, https://doi.org/10.5194/esd-16-1453-2025, 2025
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Future projections of global ocean heat uptake (OHU) strongly differ between climate models. Here, we reveal an observational constraint on future OHU based on 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 % and suggests that previous constraints have underestimated future warming.
Quentin Hyvernat, Alexandre Mignot, Elodie Gutknecht, Giovanni Ruggiero, Coralie Perruche, Guillaume Samson, Raphaëlle Sauzède, Olivier Aumont, Hervé Claustre, and Fabrizio D'Ortenzio
EGUsphere, https://doi.org/10.5194/egusphere-2025-4369, https://doi.org/10.5194/egusphere-2025-4369, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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We introduce an iterative Importance Sampling (iIS) framework to optimize the PISCES model using BGC-Argo data. Using these data, 20 metrics are applied to better constrain parameter values. Three parameter selection strategies are compared: 29 main effects parameters, 66 parameters including interaction effects, and all 95 parameters. All yield statistically indistinguishable but significant skill gains, reducing NRMSE by 54–56% in median across assimilated metrics in the productive layer.
Nathaelle Bouttes, Lester Kwiatkowski, Elodie Bougeot, Manon Berger, Victor Brovkin, and Guy Munhoven
Biogeosciences, 22, 4531–4544, https://doi.org/10.5194/bg-22-4531-2025, https://doi.org/10.5194/bg-22-4531-2025, 2025
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Coral reefs are under threat due to warming and ocean acidification. It is difficult to project future coral reef production due to uncertainties in climate models, socioeconomic scenarios and coral adaptation to warming. Here we have included a coral reef module within a climate model for the first time to evaluate the range of possible futures. We show that coral reef production decreases in most future scenarios, but in some cases coral reef carbonate production can persist.
Mathieu Delteil, Marina Lévy, and Laurent Bopp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2805, https://doi.org/10.5194/egusphere-2025-2805, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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The ocean is losing oxygen due to climate change, threatening ecosystems, especially in naturally low-oxygen areas called Oxygen Minimum Zones (OMZs). Using the IPSL-CM6A-LR Large Ensemble, this study identifies when climate-driven changes in OMZ volumes and regional deoxygenation emerge from natural variability. We highlight hemispheric asymmetries due to ocean ventilation and provide model-based estimates for the timing of detectable OMZ evolution.
Marina Lévy, Karina von Schuckmann, Patrick Vincent, Bruno Blanke, Joachim Claudet, Patrice Guillotreau, Audrey Hasson, Claire Jolly, Yunne Shin, Olivier Thébaud, Adrien Vincent, and Pierre Bahurel
State Planet, 6-osr9, 1, https://doi.org/10.5194/sp-6-osr9-1-2025, https://doi.org/10.5194/sp-6-osr9-1-2025, 2025
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The Ocean is vital to humanity, but humans are putting it at risk. The Starfish Barometer is a new yearly civic rendezvous that shows how people and the Ocean affect each other. Using science-based facts, it highlights major trends in ocean health, the pressures it faces, the harm to people, and current protection efforts and opportunities. The goal is to raise awareness to secure a better future for the Ocean and humanity.
Lisa Di Matteo, Fabio Benedetti, Sakina-Dorothée Ayata, and Olivier Aumont
EGUsphere, https://doi.org/10.5194/egusphere-2025-1465, https://doi.org/10.5194/egusphere-2025-1465, 2025
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Mesozooplankton gather small current-drifting animals. They are very diverse and play key roles in the functioning of marine ecosystem and ocean carbon cycle, especially through the production of rapidly sinking particles. Usually under-represented in marine biogeochemical models, we add 3 feeding strategies in the PISCES model and investigate their impact on carbon cycle at global scale. We find distinct distributions between mesozooplankton types with different contributions to carbon export.
Stéphane Doléac, Marina Lévy, Roy El Hourany, and Laurent Bopp
Biogeosciences, 22, 841–862, https://doi.org/10.5194/bg-22-841-2025, https://doi.org/10.5194/bg-22-841-2025, 2025
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The marine biogeochemistry components of Coupled Model Intercomparison Project phase 6 (CMIP6) models vary widely in their process representations. Using an innovative bioregionalization of the North Atlantic, we reveal that this model diversity largely drives the divergence in net primary production projections under a high-emission scenario. The identification of the most mechanistically realistic models allows for a substantial reduction in projection uncertainty.
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, https://doi.org/10.5194/gmd-17-6513-2024, 2024
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Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
Alban Planchat, Laurent Bopp, Lester Kwiatkowski, and Olivier Torres
Earth Syst. Dynam., 15, 565–588, https://doi.org/10.5194/esd-15-565-2024, https://doi.org/10.5194/esd-15-565-2024, 2024
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Ocean acidification is likely to impact all stages of the ocean carbonate pump. We show divergent responses of CaCO3 export throughout this century in earth system models, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. While we confirm the limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification, we highlight a potentially abrupt shift in CaCO3 dissolution from deep to subsurface waters beyond 2100.
Roy El Hourany, Juan Pierella Karlusich, Lucie Zinger, Hubert Loisel, Marina Levy, and Chris Bowler
Ocean Sci., 20, 217–239, https://doi.org/10.5194/os-20-217-2024, https://doi.org/10.5194/os-20-217-2024, 2024
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Satellite observations offer valuable information on phytoplankton abundance and community structure. Here, we employ satellite observations to infer seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. The link has been established using machine learning approaches. The output of this work provides excellent tools to collect essential biodiversity variables and a foundation to monitor the evolution of marine biodiversity.
Narimane Dorey, Sophie Martin, and Lester Kwiatkowski
Biogeosciences, 20, 4289–4306, https://doi.org/10.5194/bg-20-4289-2023, https://doi.org/10.5194/bg-20-4289-2023, 2023
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Human CO2 emissions are modifying ocean carbonate chemistry, causing ocean acidification and likely already impacting marine ecosystems. Here, we added CO2 to intertidal pools at the start of emersion to investigate the influence of future ocean acidification on net community production (NCP) and calcification (NCC). By day, adding CO2 fertilized the pools (+20 % NCP). By night, pools experienced net community dissolution, a dissolution that was further increased (+40 %) by the CO2 addition.
Inès Mangolte, Marina Lévy, Clément Haëck, and Mark D. Ohman
Biogeosciences, 20, 3273–3299, https://doi.org/10.5194/bg-20-3273-2023, https://doi.org/10.5194/bg-20-3273-2023, 2023
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Ocean fronts are ecological hotspots, associated with higher diversity and biomass for many marine organisms, from bacteria to whales. Using in situ data from the California Current Ecosystem, we show that far from being limited to the production of diatom blooms, fronts are the scene of complex biophysical couplings between biotic interactions (growth, competition, and predation) and transport by currents that generate planktonic communities with an original taxonomic and spatial structure.
Saeed Hariri, Sabrina Speich, Bruno Blanke, and Marina Lévy
Ocean Sci., 19, 1183–1201, https://doi.org/10.5194/os-19-1183-2023, https://doi.org/10.5194/os-19-1183-2023, 2023
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This work presents a series of studies conducted by the authors on the application of the Lagrangian approach for the connectivity analysis between different ocean locations in an idealized open-ocean model. We assess how the connectivity properties of typical oceanic flows are affected by the fine-scale circulation and discuss the challenges facing ocean connectivity estimates related to the spatial resolution. Our results are important to improve the understanding of marine ecosystems.
Clément Haëck, Marina Lévy, Inès Mangolte, and Laurent Bopp
Biogeosciences, 20, 1741–1758, https://doi.org/10.5194/bg-20-1741-2023, https://doi.org/10.5194/bg-20-1741-2023, 2023
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Phytoplankton vary in abundance in the ocean over large regions and with the seasons but also because of small-scale heterogeneities in surface temperature, called fronts. Here, using satellite imagery, we found that fronts enhance phytoplankton much more where it is already growing well, but despite large local increases the enhancement for the region is modest (5 %). We also found that blooms start 1 to 2 weeks earlier over fronts. These effects may have implications for ecosystems.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
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
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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.
Laurent Bopp, Olivier Aumont, Lester Kwiatkowski, Corentin Clerc, Léonard Dupont, Christian Ethé, Thomas Gorgues, Roland Séférian, and Alessandro Tagliabue
Biogeosciences, 19, 4267–4285, https://doi.org/10.5194/bg-19-4267-2022, https://doi.org/10.5194/bg-19-4267-2022, 2022
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The impact of anthropogenic climate change on the biological production of phytoplankton in the ocean is a cause for concern because its evolution could affect the response of marine ecosystems to climate change. Here, we identify biological N fixation and its response to future climate change as a key process in shaping the future evolution of marine phytoplankton production. Our results show that further study of how this nitrogen fixation responds to environmental change is essential.
Martí Galí, Marcus Falls, Hervé Claustre, Olivier Aumont, and Raffaele Bernardello
Biogeosciences, 19, 1245–1275, https://doi.org/10.5194/bg-19-1245-2022, https://doi.org/10.5194/bg-19-1245-2022, 2022
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Part of the organic matter produced by plankton in the upper ocean is exported to the deep ocean. This process, known as the biological carbon pump, is key for the regulation of atmospheric carbon dioxide and global climate. However, the dynamics of organic particles below the upper ocean layer are not well understood. Here we compared the measurements acquired by autonomous robots in the top 1000 m of the ocean to a numerical model, which can help improve future climate projections.
Alain de Verneil, Zouhair Lachkar, Shafer Smith, and Marina Lévy
Biogeosciences, 19, 907–929, https://doi.org/10.5194/bg-19-907-2022, https://doi.org/10.5194/bg-19-907-2022, 2022
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The Arabian Sea is a natural CO2 source to the atmosphere, but previous work highlights discrepancies between data and models in estimating air–sea CO2 flux. In this study, we use a regional ocean model, achieve a flux closer to available data, and break down the seasonal cycles that impact it, with one result being the great importance of monsoon winds. As demonstrated in a meta-analysis, differences from data still remain, highlighting the great need for further regional data collection.
Zouhair Lachkar, Michael Mehari, Muchamad Al Azhar, Marina Lévy, and Shafer Smith
Biogeosciences, 18, 5831–5849, https://doi.org/10.5194/bg-18-5831-2021, https://doi.org/10.5194/bg-18-5831-2021, 2021
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This study documents and quantifies a significant recent oxygen decline in the upper layers of the Arabian Sea and explores its drivers. Using a modeling approach we show that the fast local warming of sea surface is the main factor causing this oxygen drop. Concomitant summer monsoon intensification contributes to this trend, although to a lesser extent. These changes exacerbate oxygen depletion in the subsurface, threatening marine habitats and altering the local biogeochemistry.
Damien Couespel, Marina Lévy, and Laurent Bopp
Biogeosciences, 18, 4321–4349, https://doi.org/10.5194/bg-18-4321-2021, https://doi.org/10.5194/bg-18-4321-2021, 2021
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An alarming consequence of climate change is the oceanic primary production decline projected by Earth system models. These coarse-resolution models parameterize oceanic eddies. Here, idealized simulations of global warming with increasing resolution show that the decline in primary production in the eddy-resolved simulations is half as large as in the eddy-parameterized simulations. This stems from the high sensitivity of the subsurface nutrient transport to model resolution.
Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet
Geosci. Model Dev., 14, 4069–4086, https://doi.org/10.5194/gmd-14-4069-2021, https://doi.org/10.5194/gmd-14-4069-2021, 2021
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The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
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
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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.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483, https://doi.org/10.5194/gmd-13-5465-2020, https://doi.org/10.5194/gmd-13-5465-2020, 2020
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In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
Cited articles
Alexander, M. A., Scott, J. D., Friedland, K. D., Mills, K. E., Nye, J. A., Pershing, A. J., and Thomas, A. C.: Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans, Elem. Sci. Anth., 6, 9, https://doi.org/10.1525/elementa.191, 2018.
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, 2006.
Benedetti, F., Gruber, N., and Vogt, M.: Global gradients in species richness of marine plankton functional groups, J. Plankton Res., 45, 832–852, 2023.
Bentsen, M., Oliviè, D. J. L., Seland, O., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, Kjetil, S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-MM model output prepared for CMIP6 CMIP historical, Version 20191108, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8040, 2019a.
Bentsen, M., Oliviè, D. J. L., Seland, O., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, Kjetil, S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-MM model output prepared for CMIP6 ScenarioMIP ssp585, Version 20230616, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8321, 2019b.
Bindoff, N. L., Cheung, W. W. L., Kairo, J. G., Arístegui, J., Guinder, V. A., Hallberg, R., Hilmi, N., Jiao, N., Karim, M. S., Levin, L., O’Donoghue, S., Purca, S. R., Rinkevich, B., Suga, T., Tagliabue, A., and Williamson, P.: Changing Ocean, Marine Ecosystems, and Dependent Communities, in: 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, United Kingdom, 447–587, 2022.
Bopp, L., Monfray, P., Aumont, O., Dufresne, J.-L., Treut, H. L., 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.
Bopp, L., Aumont, O., Cadule, P., Alvain, S., and Gehlen, M.: Response of diatoms distribution to global warming and potential implications: A global model study, Geophys. Res. Lett., 32, L19606, https://doi.org/10.1029/2005GL023653, 2005.
Bopp, L., 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.
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols, M., Meurdesoif, Y., Cadule, P., Devilliers, M., Ghattas, J., Lebas, N., Lurton, T., Mellul, L., Musat, I., Mignot, J., and Cheruy, F.: IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP historical, Version 2021, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.5195, 2018.
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols, M., Meurdesoif, Y., Balkanski, Y., Checa-Garcia, R., Hauglustaine, D., Bekki, S., and Marchand, M.: IPSL IPSL-CM6A-LR-INCA model output prepared for CMIP6 CMIP historical. Version 2021, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.13601, 2021.
Cabré, A., Marinov, I., and Leung, S.: Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 earth system models, Clim. Dynam., 45, 1253–1280, https://doi.org/10.1007/s00382-014-2374-3, 2014.
Cai, W., Santoso, A., Wang, G., Yeh, S. W., An, S. I., Cobb, K. M., Collins, M., Guilyardi, E., Jin, F. F., Kug, J. S., and Lengaigne, M.: ENSO and greenhouse warming, Nat. Clim. Change, 5, 849–859, 2015.
Cai, W., Santoso, A., Collins, M., Dewitte, B., Karamperidou, C., Kug, J. S., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Taschetto, A. S., and Timmermann, A.: Changing El Niño–Southern oscillation in a warming climate, Nature Reviews Earth & Environment, 2, 628–644, 2021.
Carranza, M. M. and Gille, S. T: Southern Ocean wind-driven entrainment enhances satellite chlorophyll-a through the summer, J. Geophys. Res.-Oceans, 120, 304–323, 2015.
Danabasoglu, G.: NCAR CESM2 model output prepared for CMIP6 CMIP historical, Version 20190308, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.7627, 2019a.
Danabasoglu, G.: NCAR CESM2-FV2 model output prepared for CMIP6 CMIP historical, Version 20191120, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.11297, 2019b.
Danabasoglu, G.: NCAR CESM2-WACCM-FV2 model output prepared for CMIP6 CMIP historical, Version 20191120, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.11298, 2019c.
Demarcq, H., Reygondeau, G., Alvain, S., and Vantrepotte, V: Monitoring marine phytoplankton seasonality from space, Remote Sens. Environ., 117, 211–222, 2012.
Doney, S. C., Bopp, L., and Long, M. C.: Historical and future trends in ocean climate and biogeochemistry, Oceanography, 27, 108–119, https://doi.org/10.5670/oceanog.2014.14, 2014.
Edwards, A. M. and Brindley, J.: Oscillatory behaviour in a three-component plankton population model, Dyn. Syst., 11, 347–370, https://doi.org/10.1080/02681119608806231, 1996.
Edwards, A. M. and Brindley, J.: Zooplankton mortality and the dynamical behaviour of plankton population models, B. Math. Biol., 61, 303–339, 1999.
Edwards, A. M. and Yool, A.: The role of higher predation in plankton population models, J. Plankton Res., 6, 1085–1112, 2000.
Frölicher, T. L., Fischer, E. M., and Gruber, N.: Marine heatwaves under global warming, Nature, 560, 360–364, 2018.
Fu, W., Randerson, J. T., and Moore, J. K.: Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models, Biogeosciences, 13, 5151–5170, https://doi.org/10.5194/bg-13-5151-2016, 2016.
Gaube, P., McGillicuddy Jr., D. J., Chelton, D. B., Behrenfeld, M. J., and Strutton, P. G.: Regional variations in the influence of mesoscale eddies on near-surface chlorophyll. J. Geophys. Res.-Oceans, 119, 8195–8220, 2014.
Gilpin, M. E.: Spiral chaos in a predator-prey model, Amer. Nat., 113, 306–308, 1979.
Gregg, W. W., Casey, N. W., and McClain, C. R.: Recent trends in global ocean chlorophyll, Geophys. Res. Lett., 32, L03606, https://doi.org/10.1029/2004GL021808, 2005.
Henson, S. A., Sarmiento, J. L., Dunne, J. P., Bopp, L., Lima, I., Doney, S. C., John, J., and Beaulieu, C.: Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity, Biogeosciences, 7, 621–640, https://doi.org/10.5194/bg-7-621-2010, 2010.
Henson, S., Cole, H., Beaulieu, C., and Yool, A.: The impact of global warming on seasonality of ocean primary production, Biogeosciences, 10, 4357–4369, https://doi.org/10.5194/bg-10-4357-2013, 2013.
Henson, S. A., Beaulieu, C., and Lampitt, R. Observing climate change trends in ocean biogeochemistry: when and where, Global Biogeochem. Cy., 22, 1561–1571, 2016.
Huisman, J. and Weissing, F. J.: Biodiversity of plankton by species oscillations and chaos, Nature, 402, 407–410, 1999.
Huisman, J. and Weissing, F. J.: Biological conditions for oscillations and chaos generated by multispecies competition, Ecology, 82, 2682–2695, 2001.
Jo, A. R., Lee, J.-Y., Timmermann, A., Jin, F.-F., Yamaguchi, R., and Gallego, A.: Future amplification of sea surface temperature seasonality due to enhanced ocean stratification, Geophys. Res. Lett., 49, e2022GL098607, https://doi.org/10.1029/2022GL098607, 2022.
Jungclaus, J., Bittner, M., Wieners, k., Wachsmann, F., Schupfner, M., Legutke, S., Giorgetta, M., Reick, C., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Esch, M., Mauritsen, T., von Storch, J., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP piControl, Version 20190710, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6674, 2019a.
Jungclaus, J., Bittner, M., Wieners, k., Wachsmann, F., Schupfner, M., Legutke, S., Giorgetta, M., Reick, C., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Esch, M., Mauritsen, T., von Storch, J., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-HR model output prepared for CMIP6 CMIP historical, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6594, 2019b.
Keerthi, M. G., Lengaigne, M., Vialard, J., de Boyer Montégut, C., and Muraleedharan, P. M.: Interannual variability of the Tropical Indian Ocean mixed layer depth, Clim. Dynam., 40, 743–759, 2013.
Keerthi, M. G., Lengaigne, M., Drushka, K., Vialard, J., de Boyer Montégut, C., Pous, S., Levy, M., and Muraleedharan, P. M.: Intraseasonal variability of mixed layer depth in the tropical Indian Ocean, Clim. Dynam., 46, 2633–2655, 2016.
Keerthi, M. G., Lévy, M., Aumont, O., Lengaigne, M., and Antoine, D.: Contrasted contribution of intraseasonal time scales to surface chlorophyll variations in a bloom and an oligotrophic regime, J. Geophys. Res.-Oceans, 125, e2019JC015701, https://doi.org/10.1029/2019JC015701, 2020.
Keerthi, M. G., Lévy, M., and Aumont, O.: Intermittency in phytoplankton bloom triggered by modulations in vertical stability, Sci. Rep., 11, 1–9, 2021.
Keerthi, M. G., Prend, C. J., Aumont, O., and Lévy, M.: Annual variations in phytoplankton biomass driven by small-scale physical processes, Nat. Geosci., 15, 1027–1033, https://doi.org/10.1038/s41561-022-01057-3, 2022.
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.
Kiorboe, T.: How zooplankton feed: mechanisms, traits and trade-offs, Biol. Rev., 86, 311–339, 2011.
Knutson, T ., Camargo, S. J., Chan, J. C., Emanuel, K., Ho, C. H., Kossin, J., Mohapatra, M., Satoh, M., Sugi, M., Walsh, K., and Wu, L.: Tropical cyclones and climate change assessment: Part II: Projected response to anthropogenic warming, B. Am. Meteorol. Soc., 101, E303–E322, 2020.
Krumhardt, K. M., Lovenduski, N. S., Long, M. C., and Lindsay, K.: Avoidable impacts of ocean warming on marine primary production: Insights from the CESM ensembles, Global Biogeochem. Cy., 31, 114–133, https://doi.org/10.1002/2016GB005528, 2017.
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.
Kwiatkowski, L., Aumont, O., and Bopp, L.: Consistent trophic amplification of marine biomass declines under climate change, Global Biogeochem. Cy., 25, 218–229, https://doi.org/10.1111/gcb.14468, 2018.
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.
Lévy, M., Ferrari, R., Franks, P. J. S., Martin, A. P., and Rivière, P.: Bringing physics to life at the submesoscale, Geophys. Res. Lett., 39, L14602, https://doi.org/10.1029/2012GL052756, 2012.
Lévy, M., Couespel, D., Haëck, C., Keerthi, M. G., Mangolte, I., and Prend, C. J.: The impact of fine-scale currents on biogeochemical cycles in a changing ocean, Annu. Rev. Mar. Sci., 16, 191–215, 2024.
Lovenduski, N. S. and Gruber, N.: Impact of the Southern Annular Mode on Southern Ocean circulation and biology, Geophys. Res. Lett., 32, L11603, https://doi.org/10.1029/2005GL022727, 2005.
Martinez, E., Raitsos, D. E., and Antoine, D.: Warmer, deeper, and greener mixed layers in the North Atlantic subpolar gyre over the last 50 years, Global Biogeochem. Cy., 22, 604–612, 2016.
Martínez-Moreno, J., Hogg, A. M., England, M. H., Constantinou, N. C., Kiss, A. E., and Morrison, A. K.: Global changes in oceanic mesoscale currents over the satellite altimetry record, Nat. Clim. Chang., 11, 397–403, https://doi.org/10.1038/s41558-021-01006-9, 2021.
Martínez-Moreno, J., Hogg, A. M., and England, M. H.: Climatology, seasonality, and trends of spatially coherent ocean eddies, J. Geophys. Res.-Oceans, 127, e2021JC017453, https://doi.org/10.1029/2021JC017453, 2022.
Mayersohn, B., Smith, K. S., Mangolte, I., and Lévy, M.: Intrinsic timescales of variability in a marine plankton model, Ecol. Model., 443, 109446, https://doi.org/10.1016/j.ecolmodel.2021.109446, 2021.
Mayersohn, B., L.vy, M., Mangolte, I., and Smith, K. S.: Emergence of broadband variability in a marine plankton model under external forcing, J. Geophys. Res.-Biogeo., 127, e2022JG007011. https://doi.org/10.1029/2022JG007011, 2022.
Moore, J. K., Fu, W., Primeau, F., Britten, G. L., Lindsay, K., Long, M., Doney, S. C., Mahowald, N., Hoffman, F., and Randerson, J. T.: Sustained climate warming drives declining marine biological productivity, Science, 359, 1139–1143, https://doi.org/10.1126/science.aao6379, 2018.
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M., Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., and Ilyina, T.: A higher-resolution version of the Max Planck Institute Earth System Model (MPI-ESM1.2-HR), J. Adv. Model. Earth Syst., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018.
Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Stoll, J., Folini, D. S., Tegen, I., Wieners, K., Mauritsen, T., Stemmler, I., Barthel, S., Bey, I., Daskalakis, N., Heinold, B., Kokkola, H., Partridge, D., Rast, S., Schmidt, H., Schutgens, N., Stanelle, T., Stier, P., Watson-Parris, D., and Lohmann, U.: HAMMOZ-Consortium MPI-ESM1.2-HAM model output prepared for CMIP6 CMIP historical. Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.5016, 2019.
Omta, A. W., Heiny, E. A., Rajakaruna, H., Talmy, D., and Follows, M. J.: Trophic model closure influences ecosystem response to enrichment, Ecol. Modell., 475, 110183, https://doi.org/10.1016/j.ecolmodel.2022.110183, 2023.
Pata, P. R., and Hunt, B. P. V.: Harmonizing marine zooplankton trait data toward a mechanistic understanding of ecosystem functioning, Limnol. Oceanogr., 68, 1–14, https://doi.org/10.1002/lno.12478, 2023.
Petrik, C. M., Jessica, Y. L., Heneghan, R. F., Everett, J. D., Harrison, C. S., and Richardson, A. J.: Assessment and constraint of mesozooplankton in CMIP6 Earth system models, Global Biogeochem. Cy., 36, e2022GB007367, https://doi.org/10.1029/2022GB007367, 2022.
Planchat, A., Kwiatkowski, L., Bopp, L., Torres, O., Christian, J. R., Butenschön, M., Lovato, T., Séférian, R., Chamberlain, M. A., Aumont, O., Watanabe, M., Yamamoto, A., Yool, A., Ilyina, T., Tsujino, H., Krumhardt, K. M., Schwinger, J., Tjiputra, J., Dunne, J. P., and Stock, C.: The representation of alkalinity and the carbonate pump from CMIP5 to CMIP6 Earth system models and implications for the carbon cycle, Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, 2023.
Prend, C. J., Keerthi, M. G., Levy, M., Aumont, O., Gille, S. T., and Talley, L. D.: Sub-seasonal forcing drives year-to-year variations of Southern Ocean primary productivity, Global Biogeochem. Cy., 36, e2022GB007329, https://doi.org/10.1029/2022GB007329, 2022.
Racault, M. F., Sathyendranath, S., Brewin, R. J., Raitsos, D. E., Jackson, T., and Platt, T.: Impact of El Niño variability on oceanic phytoplankton, Front. Mar. Sci., 4, 133, https://doi.org/10.3389/fmars.2017.00133, 2017.
Resplandy, L., Vialard, J., Lévy, M., Aumont, O., and Dandonneau, Y.: Seasonal and intraseasonal biogeochemical variability in the thermocline ridge of the southern tropical Indian Ocean, J. Geophys. Res.-Oceans, 114, C07024, https://doi.org/10.1029/2008JC005246, 2009.
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, Communications Earth & Environment, 4, 212, https://doi.org/10.1038/s43247-023-00871-w, 2023.
Sailley, S. F., Vogt, M., Doney, S. C., Aita, M. N., Bopp, L., Buitenhuis, E. T., Hashioka, T., Lima, I., Le Quéré, C., and Yamanaka, Y.: Comparing food web structures and dynamics across a suite of global marine ecosystem models, Ecol. Modell., 261–262, 43–57, https://doi.org/10.1016/j.ecolmodel.2013.04.006, 2013.
Sarmiento, J. L., Slater, R., Barber, R., Bopp, L., Doney, S. C., Hirst, A. C., Kleypas, J., Matear, R., Mikolajewicz, U., Monfray, P., Soldatov, V., Spall, S. A., and Stouffer, R.: Response of ocean ecosystems to climate warming, Global Biogeochem. Cy., 18, GB3003, https://doi.org/10.1029/2003GB002134, 2004.
Sathyendranath, S. and Krasemann, H.: Ocean Colour Climate Change Initiative (OC-CCI) — Phase One, Climate Assessment Report, 2014.
Sathyendranath, S. and Krasemann, H.: Ocean Colour Climate Change Initiative (OC-CCI) — Phase one, Climate Assessment Report, 2014.
Schulzweida, U.: CDO User Guide (2.3.0), Zenodo [software], https://doi.org/10.5281/zenodo.10020800, 2023.
Schupfner, M., Wieners, K., Wachsmann, F., Steger, C., Bittner, M., Jungclaus, J., Früh, B., Pankatz, K., Giorgetta, M., Reick, C., Legutke, S., Esch, M., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-ESM1.2-HR model output prepared for CMIP6 ScenarioMIP ssp585, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4403, 2019.
Séférian, R.: CNRM-CERFACS CNRM-ESM2-1 model output prepared for CMIP6 CMIP historical, Version 20180917, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4068, 2018.
Séférian, R., Berthet, S., Yool, A., Palmiéri, J., Bopp, L., Tagliabue, A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., and Gehlen, M.: Tracking improvement in simulated marine biogeochemistry between CMIP5 and CMIP6, Current Climate Change Reports, 6, 95–119, https://doi.org/10.1007/s40641-020-00160-0, 2020.
Seland, Ø., Bentsen, M., Oliviè, D.J.L., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-LM model output prepared for CMIP6 CMIP piControl, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8217, 2019a.
Seland, Ø., Bentsen, M., Oliviè, D. J. L., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-LM model output prepared for CMIP6 CMIP historical, Version 20191108, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8036, 2019b.
Seland, Ø., Bentsen, M., Oliviè, D. J. L., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A., He, Y., Kirkevåg, A., Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller, J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-LM model output prepared for CMIP6 ScenarioMIP ssp585, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8319, 2019c.
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.
Strutton, P. G., Ryan, J. P., and Chavez, F. P.: Enhanced chlorophyll associated with tropical instability waves in the equatorial Pacific, Geophys. Res. Lett., 28, 2005–2008, 2001.
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, Front. Clim., 3, 738224, https://doi.org/10.3389/fclim.2021.738224, 2021.
Talmy, D., Carr, E., Rajakaruna, H., Våge, S., and Willem Omta, A.: Killing the predator: impacts of highest-predator mortality on the global-ocean ecosystem structure, Biogeosciences, 21, 2493–2507, https://doi.org/10.5194/bg-21-2493-2024, 2024.
Thomalla, S. J., Fauchereau, N., Swart, S., and Monteiro, P. M. S.: Regional scale characteristics of the seasonal cycle of chlorophyll in the Southern Ocean, Biogeosciences, 8, 2849–2866, https://doi.org/10.5194/bg-8-2849-2011, 2011.
Thomalla, S. J., Nicholson, S. A., Ryan-Keogh, T. J., and Smith, M. E.: Widespread changes in Southern Ocean phytoplankton blooms linked to climate drivers, Nat. Clim. Change, 13, 975–984, 2023.
Tilman, D.: Resource competition between plankton algae: An experimental and theoretical approach, Ecology, 58, 338–348, 1977.
Vaittinada Ayar, P., Battisti, D. S., Li, C., King, M., Vrac, M., and Tjiputra, J.: A regime view of ENSO flavors through clustering in CMIP6 models, Earth's Future, 11, e2022EF003460, https://doi.org/10.1029/2022EF003460, 2023.
Vantrepotte, V. and Mélin, F.: Temporal variability of 10-year global SeaWiFS time-series of phytoplankton chlorophyll a concentration, ICES J. Mar. Sci. 66, 1547–1556, 2009.
Vantrepotte, V. and Mélin, F.: Inter-annual variations in the SeaWiFS global chlorophyll a concentration (1997–2007), Deep-Sea Res. Pt. I, 58, 429–441, 2011.
Walsh, K. J., McBride, J. L., Klotzbach, P. J., Balachandran, S., Camargo, S. J., Holland, G., Knutson, T. R., Kossin, J. P., Lee, T. C., Sobel, A., and Sugi, M.: Tropical cyclones and climate change, WIRES Clim. Change, 7, 65–89, 2016.
Weaver, A. and Courtier, P.: Correlation modelling on the sphere using a generalized diffusion equation, Q. J. Roy. Meteor. Soc., 127, 1815–1846, 2001.
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M., Legutke, S., Schupfner, M., Wachsmann, F., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP piControl, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6675, 2019a.
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M., Legutke, S., Schupfner, M., Wachsmann, F., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP historical, Version 2019, Earth System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.6595 [data set], 2019b.
Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E.: MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 ScenarioMIP ssp585, Version 2019, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6705, 2019c.
Wilson, C. and Adamec, D.: Correlations between surface chlorophyll and sea surface height in the tropical Pacific during the 1997–1999 El Niño-Southern Oscillation event, J. Geophys. Res.-Oceans, 106, 31175–31188, 2001.
Xu, T., Li, S., Hamzah, F., Setiawan, A., Susanto, R. D., Cao, G., and Wei, Z.: Intraseasonal flow and its impact on the chlorophyll-a concentration in the Sunda Strait and its vicinity, Deep-Sea Res. Pt. I, 136, 84–90, 2018.
Short summary
We assessed how well climate models replicate sub-seasonal changes in ocean chlorophyll observed by satellites. Models struggle to capture these variations accurately. Some overestimate fluctuations and their impact on annual chlorophyll variability, while others underestimate them. The underestimation is likely due to limited model resolution, while the overestimation may come from internal model oscillations.
We assessed how well climate models replicate sub-seasonal changes in ocean chlorophyll observed...
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