Articles | Volume 15, issue 4
https://doi.org/10.5194/esd-15-875-2024
© 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/esd-15-875-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jul 2024
Research article |
| 15 Jul 2024
| 15 Jul 2024
A missing link in the carbon cycle: phytoplankton light absorption under RCP emission scenarios
Institute for Marine Ecosystem and Fishery Science, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, Germany
now at: University of Brest, Ifremer, CNRS, IRD, Laboratoire d'Océanographie Physique et Spatiale (LOPS), 29280, Plouzané, France
Philip B. Holden
Environment, Earth and Ecosystems, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK
Frank Lunkeit
Meteorological Institute, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, Germany
Inga Hense
Institute for Marine Ecosystem and Fishery Science, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, Germany
Related authors
Rémy Asselot, Frank Lunkeit, Philip B. Holden, and Inga Hense
Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
Short summary
Short summary
Previous studies show that phytoplankton light absorption can warm the atmosphere, but how this warming occurs is still unknown. We compare the importance of air–sea heat versus CO2 flux in the phytoplankton-induced atmospheric warming and determine the main driver. To shed light on this research question, we conduct simulations with a climate model of intermediate complexity. We show that phytoplankton mainly warms the atmosphere by increasing the air–sea CO2 flux.
Rémy Asselot, Frank Lunkeit, Philip Holden, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-91, https://doi.org/10.5194/esd-2021-91, 2021
Revised manuscript not accepted
Short summary
Short summary
Phytoplankton absorbing light can influence the climate system but its future effect on the climate is still unclear. We use a climate model to investigate the role of phytoplankton light absorption under global warming. We find out that the effect of phytoplankton light absorption is smaller under a high greenhouse gas emissions compared to reduced and intermediate greenhouse gas emissions. Additionally, we show that phytoplankton light absorption is an important mechanism for the carbon cycle.
Peng Sun, Philip B. Holden, and H. John B. Birks
Clim. Past, 20, 2373–2398, https://doi.org/10.5194/cp-20-2373-2024, https://doi.org/10.5194/cp-20-2373-2024, 2024
Short summary
Short summary
We develop the Multi Ensemble Machine Learning Model (MEMLM) for reconstructing palaeoenvironments from microfossil assemblages. The machine-learning approaches, which include random tree and natural language processing techniques, substantially outperform classical approaches under cross-validation, but they can fail when applied to reconstruct past environments. Statistical significance testing is found sufficient to identify these unreliable reconstructions.
Yuan-Bing Zhao, Nedjeljka Žagar, Frank Lunkeit, and Richard Blender
Weather Clim. Dynam., 4, 833–852, https://doi.org/10.5194/wcd-4-833-2023, https://doi.org/10.5194/wcd-4-833-2023, 2023
Short summary
Short summary
Coupled climate models have significant biases in the tropical Indian Ocean (TIO) sea surface temperature (SST). Our study shows that the TIO SST biases can affect the simulated global atmospheric circulation and its spatio-temporal variability on large scales. The response of the spatial variability is related to the amplitude or phase of the circulation bias, depending on the flow regime and spatial scale, while the response of the interannual variability depends on the sign of the SST bias.
Iana Strigunova, Richard Blender, Frank Lunkeit, and Nedjeljka Žagar
Weather Clim. Dynam., 3, 1399–1414, https://doi.org/10.5194/wcd-3-1399-2022, https://doi.org/10.5194/wcd-3-1399-2022, 2022
Short summary
Short summary
We show that the Eurasian heat waves (HWs) have signatures in the global circulation. We present changes in the probability density functions (PDFs) of energy anomalies in the zonal-mean state and in the Rossby waves at different zonal scales in relation to the changes in intramonthly variability. The skewness of the PDF of planetary-scale Rossby waves is shown to increase during HWs, while their intramonthly variability is reduced, a process referred to as blocking.
Negar Vakilifard, Richard G. Williams, Philip B. Holden, Katherine Turner, Neil R. Edwards, and David J. Beerling
Biogeosciences, 19, 4249–4265, https://doi.org/10.5194/bg-19-4249-2022, https://doi.org/10.5194/bg-19-4249-2022, 2022
Short summary
Short summary
To remain within the Paris climate agreement, there is an increasing need to develop and implement carbon capture and sequestration techniques. The global climate benefits of implementing negative emission technologies over the next century are assessed using an Earth system model covering a wide range of plausible climate states. In some model realisations, there is continued warming after emissions cease. This continued warming is avoided if negative emissions are incorporated.
Miriam D'Errico, Flavio Pons, Pascal Yiou, Soulivanh Tao, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam., 13, 961–992, https://doi.org/10.5194/esd-13-961-2022, https://doi.org/10.5194/esd-13-961-2022, 2022
Short summary
Short summary
Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.
Maike Iris Esther Scheffold and Inga Hense
Ocean Sci., 18, 437–454, https://doi.org/10.5194/os-18-437-2022, https://doi.org/10.5194/os-18-437-2022, 2022
Short summary
Short summary
Organic carbon in the oceans can take various paths: it may e.g. sink to the sediment, be eaten, or be recycled to start all over again. Where carbon ends up for how long has implications for atmospheric CO2 concentrations and our climate. To assess which pathways exist and how they are structured, we introduce a qualitative concept of organic carbon pathways. This concept helps to identify pathways, compare ecosystems, and assess how human actions and environmental changes alter pathways.
Rémy Asselot, Frank Lunkeit, Philip B. Holden, and Inga Hense
Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
Short summary
Short summary
Previous studies show that phytoplankton light absorption can warm the atmosphere, but how this warming occurs is still unknown. We compare the importance of air–sea heat versus CO2 flux in the phytoplankton-induced atmospheric warming and determine the main driver. To shed light on this research question, we conduct simulations with a climate model of intermediate complexity. We show that phytoplankton mainly warms the atmosphere by increasing the air–sea CO2 flux.
Jenny Hieronymus, Kari Eilola, Malin Olofsson, Inga Hense, H. E. Markus Meier, and Elin Almroth-Rosell
Biogeosciences, 18, 6213–6227, https://doi.org/10.5194/bg-18-6213-2021, https://doi.org/10.5194/bg-18-6213-2021, 2021
Short summary
Short summary
Dense blooms of cyanobacteria occur every summer in the Baltic Proper and can add to eutrophication by their ability to turn nitrogen gas into dissolved inorganic nitrogen. Being able to correctly estimate the size of this nitrogen fixation is important for management purposes. In this work, we find that the life cycle of cyanobacteria plays an important role in capturing the seasonality of the blooms as well as the size of nitrogen fixation in our ocean model.
Rémy Asselot, Frank Lunkeit, Philip Holden, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-91, https://doi.org/10.5194/esd-2021-91, 2021
Revised manuscript not accepted
Short summary
Short summary
Phytoplankton absorbing light can influence the climate system but its future effect on the climate is still unclear. We use a climate model to investigate the role of phytoplankton light absorption under global warming. We find out that the effect of phytoplankton light absorption is smaller under a high greenhouse gas emissions compared to reduced and intermediate greenhouse gas emissions. Additionally, we show that phytoplankton light absorption is an important mechanism for the carbon cycle.
Félix Pellerin, Philipp Porada, and Inga Hense
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-55, https://doi.org/10.5194/esd-2020-55, 2020
Revised manuscript not accepted
Short summary
Short summary
While several biological processes are similar among terrestrial and marine ecosystems, their representation in Earth System Models may differ. By comparing the terrestrial and marine modules of 17 Earth System Models, we found multiple evidences of unjustified differences in processes representation. These inconsistencies may lead to wrong predictions about the role of biosphere in the climate system and skew our perception of the relative influence of each ecosystem on climate.
Andrew H. MacDougall, Thomas L. Frölicher, Chris D. Jones, Joeri Rogelj, H. Damon Matthews, Kirsten Zickfeld, Vivek K. Arora, Noah J. Barrett, Victor Brovkin, Friedrich A. Burger, Micheal Eby, Alexey V. Eliseev, Tomohiro Hajima, Philip B. Holden, Aurich Jeltsch-Thömmes, Charles Koven, Nadine Mengis, Laurie Menviel, Martine Michou, Igor I. Mokhov, Akira Oka, Jörg Schwinger, Roland Séférian, Gary Shaffer, Andrei Sokolov, Kaoru Tachiiri, Jerry Tjiputra, Andrew Wiltshire, and Tilo Ziehn
Biogeosciences, 17, 2987–3016, https://doi.org/10.5194/bg-17-2987-2020, https://doi.org/10.5194/bg-17-2987-2020, 2020
Short summary
Short summary
The Zero Emissions Commitment (ZEC) is the change in global temperature expected to occur following the complete cessation of CO2 emissions. Here we use 18 climate models to assess the value of ZEC. For our experiment we find that ZEC 50 years after emissions cease is between −0.36 to +0.29 °C. The most likely value of ZEC is assessed to be close to zero. However, substantial continued warming for decades or centuries following cessation of CO2 emission cannot be ruled out.
Andreas Wernecke, Tamsin L. Edwards, Isabel J. Nias, Philip B. Holden, and Neil R. Edwards
The Cryosphere, 14, 1459–1474, https://doi.org/10.5194/tc-14-1459-2020, https://doi.org/10.5194/tc-14-1459-2020, 2020
Short summary
Short summary
We investigate how the two-dimensional characteristics of ice thickness change from satellite measurements can be used to judge and refine a high-resolution ice sheet model of Antarctica. The uncertainty in 50-year model simulations for the currently most drastically changing part of Antarctica can be reduced by nearly 40 % compared to a simpler, non-spatial approach and nearly 90 % compared to the original spread in simulations.
Philip B. Holden, Neil R. Edwards, Thiago F. Rangel, Elisa B. Pereira, Giang T. Tran, and Richard D. Wilkinson
Geosci. Model Dev., 12, 5137–5155, https://doi.org/10.5194/gmd-12-5137-2019, https://doi.org/10.5194/gmd-12-5137-2019, 2019
Short summary
Short summary
We describe the development of the Paleoclimate PLASIM-GENIE emulator and its application to derive a high-resolution spatio-temporal description of the climate of the last 5 x 106 years. Spatial fields of bioclimatic variables are emulated at 1000-year intervals, driven by time series of scalar boundary-condition forcing (CO2, orbit, and ice volume). Emulated anomalies are interpolated into modern climatology to produce a high-resolution climate reconstruction of the Pliocene–Pleistocene.
Valerio Lembo, Frank Lunkeit, and Valerio Lucarini
Geosci. Model Dev., 12, 3805–3834, https://doi.org/10.5194/gmd-12-3805-2019, https://doi.org/10.5194/gmd-12-3805-2019, 2019
Short summary
Short summary
The Thermodynamic Diagnostic Tool (TheDiaTo v1.0) is a collection of diagnostics for the study of the thermodynamics of the climate system in climate models. This is fundamental in order to understand where the imbalances affecting climate projections come from and also to allow for easy comparison of different scenarios and atmospheric regimes. The tool is currently being developed for the assessment of models that are part of the next phase of the Coupled Model Intercomparison Project (CMIP).
Jamie D. Wilson, Stephen Barker, Neil R. Edwards, Philip B. Holden, and Andy Ridgwell
Biogeosciences, 16, 2923–2936, https://doi.org/10.5194/bg-16-2923-2019, https://doi.org/10.5194/bg-16-2923-2019, 2019
Short summary
Short summary
The remains of plankton rain down from the surface ocean to the deep ocean, acting to store CO2 in the deep ocean. We used a model of biology and ocean circulation to explore the importance of this process in different regions of the ocean. The amount of CO2 stored in the deep ocean is most sensitive to changes in the Southern Ocean. As plankton in the Southern Ocean are likely those most impacted by future climate change, the amount of CO2 they store in the deep ocean could also be affected.
Krista M. S. Kemppinen, Philip B. Holden, Neil R. Edwards, Andy Ridgwell, and Andrew D. Friend
Clim. Past, 15, 1039–1062, https://doi.org/10.5194/cp-15-1039-2019, https://doi.org/10.5194/cp-15-1039-2019, 2019
Short summary
Short summary
We simulate the Last Glacial Maximum atmospheric CO2 decrease with a large ensemble of parameter sets to investigate the range of possible physical and biogeochemical Earth system changes accompanying the CO2 decrease. Amongst the dominant ensemble changes is an increase in terrestrial carbon, which we attribute to a slower soil respiration rate, and the preservation of carbon by the LGM ice sheets. Further investigation into the role of terrestrial carbon is warranted.
Tamás Bódai, Valerio Lucarini, and Frank Lunkeit
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2018-30, https://doi.org/10.5194/esd-2018-30, 2018
Revised manuscript not accepted
Short summary
Short summary
We establish a framework to conduct a scenario analysis of the best possible outcomes under geoengineering. The scenarios may consist of scenarios of greenhouse gas emission the choice of the quantity that we want to keep under control. The motivation is the desire of an efficient way of assessing the side-effects of geoengineering, concerning the unwanted and uncontrolled changes. Countering CO2 emission by modulating insolation, we find considerable changes in local temperatures or rainfall.
John S. Keery, Philip B. Holden, and Neil R. Edwards
Clim. Past, 14, 215–238, https://doi.org/10.5194/cp-14-215-2018, https://doi.org/10.5194/cp-14-215-2018, 2018
Short summary
Short summary
In the Eocene (~ 55 million years ago), the Earth had high levels of atmospheric CO2, so studies of the Eocene can provide insights into the likely effects of present-day fossil fuel burning. We ran a low-resolution but very fast climate model with 50 combinations of CO2 and orbital parameters, and an Eocene layout of the oceans and continents. Climatic effects of CO2 are dominant but precession and obliquity strongly influence monsoon rainfall and ocean–land temperature contrasts, respectively.
Philip B. Holden, H. John B. Birks, Stephen J. Brooks, Mark B. Bush, Grace M. Hwang, Frazer Matthews-Bird, Bryan G. Valencia, and Robert van Woesik
Geosci. Model Dev., 10, 483–498, https://doi.org/10.5194/gmd-10-483-2017, https://doi.org/10.5194/gmd-10-483-2017, 2017
Short summary
Short summary
We describe BUMPER, a Bayesian transfer function for inferring past climate from micro-fossil assemblages. BUMPER is fully self-calibrating, straightforward to apply, and computationally fast. We apply BUMPER to a range of proxies, including both real and artificial data, demonstrating ease of use and applicability to multi-proxy reconstructions.
Inga Hense, Irene Stemmler, and Sebastian Sonntag
Biogeosciences, 14, 403–413, https://doi.org/10.5194/bg-14-403-2017, https://doi.org/10.5194/bg-14-403-2017, 2017
Short summary
Short summary
Marine biota drives a number of climate-relevant mechanisms, not all of which are included in current Earth system models (ESMs) used for climate projections. We identify three classes of mechanisms and argue that, to adequately resolve these mechanisms and to ensure links to and feedbacks with other Earth system components, ESMs need to account for five marine organism groups.
Philip B. Holden, Neil R. Edwards, Klaus Fraedrich, Edilbert Kirk, Frank Lunkeit, and Xiuhua Zhu
Geosci. Model Dev., 9, 3347–3361, https://doi.org/10.5194/gmd-9-3347-2016, https://doi.org/10.5194/gmd-9-3347-2016, 2016
Short summary
Short summary
We describe the development, tuning and climate of PLASIM–GENIE, a new intermediate complexity Atmosphere–Ocean General Circulation Model (AOGCM), built by coupling the Planet Simulator to the GENIE Earth system model.
Frazer Matthews-Bird, Stephen J. Brooks, Philip B. Holden, Encarni Montoya, and William D. Gosling
Clim. Past, 12, 1263–1280, https://doi.org/10.5194/cp-12-1263-2016, https://doi.org/10.5194/cp-12-1263-2016, 2016
Short summary
Short summary
Chironomidae are a family of two-winged aquatic fly of the order Diptera. The family is species rich (> 5000 described species) and extremely sensitive to environmental change, particualy temperature. Across the Northern Hemisphere, chironomids have been widely used as paleotemperature proxies as the chitinous remains of the insect are readily preserved in lake sediments. This is the first study using chironomids as paleotemperature proxies in tropical South America.
Giang T. Tran, Kevin I. C. Oliver, András Sóbester, David J. J. Toal, Philip B. Holden, Robert Marsh, Peter Challenor, and Neil R. Edwards
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 17–37, https://doi.org/10.5194/ascmo-2-17-2016, https://doi.org/10.5194/ascmo-2-17-2016, 2016
Short summary
Short summary
In this work, we combine the information from a complex and a simple atmospheric model to efficiently build a statistical representation (an emulator) of the complex model and to study the relationship between them. Thanks to the improved efficiency, this process is now feasible for complex models, which are slow and costly to run. The constructed emulator provide approximations of the model output, allowing various analyses to be made without the need to run the complex model again.
A. M. Foley, P. B. Holden, N. R. Edwards, J.-F. Mercure, P. Salas, H. Pollitt, and U. Chewpreecha
Earth Syst. Dynam., 7, 119–132, https://doi.org/10.5194/esd-7-119-2016, https://doi.org/10.5194/esd-7-119-2016, 2016
Short summary
Short summary
We introduce GENIEem-PLASIM-ENTSem (GPem), a climate-carbon cycle emulator, showing how model emulation can be used in integrated assessment modelling to resolve regional climate impacts and systematically capture uncertainty. In a case study, we couple GPem to FTT:Power-E3MG, a non-equilibrium economic model with technology diffusion. We find that when the electricity sector is decarbonised by 90 %, further emissions reductions must be achieved in other sectors to avoid dangerous climate change.
M.-A. Knietzsch, A. Schröder, V. Lucarini, and F. Lunkeit
Earth Syst. Dynam., 6, 591–615, https://doi.org/10.5194/esd-6-591-2015, https://doi.org/10.5194/esd-6-591-2015, 2015
Short summary
Short summary
A general circulation model with an aquaplanet setup is used to study the impact of changes in the oceanic heat transport (OHT) on the atmospheric circulation. The atmosphere counterbalances the imposed changes in OHT. A stronger OHT leads to a decline in the intensity and a poleward shift of the maxima of both the Hadley and Ferrel cells. The efficiency of the climate machine, the intensity of the Lorenz energy cycle and the material entropy production of the system decline with increased OHT.
P. B. Holden, N. R. Edwards, P. H. Garthwaite, K. Fraedrich, F. Lunkeit, E. Kirk, M. Labriet, A. Kanudia, and F. Babonneau
Geosci. Model Dev., 7, 433–451, https://doi.org/10.5194/gmd-7-433-2014, https://doi.org/10.5194/gmd-7-433-2014, 2014
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
P. B. Holden, N. R. Edwards, S. A. Müller, K. I. C. Oliver, R. M. Death, and A. Ridgwell
Biogeosciences, 10, 1815–1833, https://doi.org/10.5194/bg-10-1815-2013, https://doi.org/10.5194/bg-10-1815-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
P. B. Holden, N. R. Edwards, D. Gerten, and S. Schaphoff
Biogeosciences, 10, 339–355, https://doi.org/10.5194/bg-10-339-2013, https://doi.org/10.5194/bg-10-339-2013, 2013
Related subject area
Topics: Biogeochemical processes | Interactions: Biosphere/atmosphere interactions | Methods: Earth system and climate modeling
Combining local model calibration with the emergent constraint approach to reduce uncertainty in the tropical land carbon cycle feedback
Nina Raoult, Tim Jupp, Ben Booth, and Peter Cox
Earth Syst. Dynam., 14, 723–731, https://doi.org/10.5194/esd-14-723-2023, https://doi.org/10.5194/esd-14-723-2023, 2023
Short summary
Short summary
Climate models are used to predict the impact of climate change. However, poorly constrained parameters used in the physics of the models mean that we simulate a large spread of possible future outcomes. We can use real-world observations to reduce the uncertainty of parameter values, but we do not have observations to reduce the spread of possible future outcomes directly. We present a method for translating the reduction in parameter uncertainty into a reduction in possible model projections.
Cited articles
Anderson, S., Barton, A., Clayton, S., Dutkiewicz, S., and Rynearson, T.: Marine phytoplankton functional types exhibit diverse responses to thermal change, Nat. Commun., 12, 1–9, 2021. a
Anderson, W., Gnanadesikan, A., Hallberg, R., Dunne, J., and Samuels, B.: Impact of ocean color on the maintenance of the Pacific Cold Tongue, Geophys. Res. Lett., 34, L11609, https://doi.org/10.1029/2007GL030100, 2007. a
Asselot, R., Lunkeit, F., Holden, P. B., and Hense, I.: The relative importance of phytoplankton light absorption and ecosystem complexity in an Earth system model, J. Adv. Model. Earth Sy., 13, e2020MS002110, https://doi.org/10.1029/2020MS002110, 2021. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from satellite–based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20, 1997. a
Boyce, D. G., Dowd, M., Lewis, M. R., and Worm, B.: Estimating global chlorophyll changes over the past century, Prog. Oceanogr., 122, 163–173, 2014. a
Cael, B., Bisson, K., Boss, E., Dutkiewicz, S., and Henson, S.: Global climate-change trends detected in indicators of ocean ecology, Nature, 1–4, 2023. a
Cameron, D. R., Lenton, T. M., Ridgwell, A. J., Shepherd, J. G., Marsh, R., and Yool, A.: A factorial analysis of the marine carbon cycle and ocean circulation controls on atmospheric CO2, Global Biogeochem. Cy., 19, GB4027, https://doi.org/10.1029/2005GB002489, 2005. a
Capone, D. G., Subramaniam, A., Montoya, J. P., Voss, M., Humborg, C., Johansen, A. M., Siefert, R. L., and Carpenter, E. J.: An extensive bloom of the N2-fixing cyanobacterium Trichodesmium erythraeum in the central Arabian Sea, Mar. Ecol.-Prog. Ser., 172, 281–292, 1998. a
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre, M.-F., Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R., Ganopolski, A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov, V., Stone, P., and Wang, W.: Earth system models of intermediate complexity: closing the gap in the spectrum of climate system models, Clim. Dynam., 18, 579–586, 2002. a
Conkright, M. E.: World Ocean Atlas 2001. Volume 4, Nutrients, edited by: Levitus, S., NOAA Atlas NESDIS, 1102, 2002. a
Gibbs, S. J., Bown, P. R., Ridgwell, A., Young, J. R., Poulton, A. J., and O'Dea, S. A.: Ocean warming, not acidification, controlled coccolithophore response during past greenhouse climate change, Geology, 44, 59–62, 2016. a
Goldman, J. C.: Temperature effects on phytoplankton growth in continuous culture, Limnol. Oceanogr., 22, 932–936, 1977. a
Greene, S., Ridgwell, A., Kirtland Turner, S., Schmidt, D. N., Pälike, H., Thomas, E., Greene, L., and Hoogakker, B.: Early Cenozoic decoupling of climate and carbonate compensation depth trends, Paleoceanogr. Paleocl., 34, 930–945, 2019. a
Hense, I.: Regulative feedback mechanisms in cyanobacteria-driven systems: a model study, Mar. Ecol.-Prog. Ser., 339, 41–47, 2007. a
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. a
Hibler, W. D.: A dynamic thermodynamic sea ice model, J. Phys. Oceanogr., 9, 815–846, 1979. a
Holden, P. B., Edwards, N. R., Müller, S. A., Oliver, K. I. C., Death, R. M., and Ridgwell, A.: Controls on the spatial distribution of oceanic δ13CDIC, Biogeosciences, 10, 1815–1833, https://doi.org/10.5194/bg-10-1815-2013, 2013. a
Holden, P. B., Edwards, N. R., Fraedrich, K., Kirk, E., Lunkeit, F., and Zhu, X.: PLASIM–GENIE v1.0: a new intermediate complexity AOGCM, Geosci. Model Dev., 9, 3347–3361, https://doi.org/10.5194/gmd-9-3347-2016, 2016. a
Kahru, M., Leppanen, J.-M., and Rud, O.: Cyanobacterial blooms cause heating of the sea surface, Mar. Ecol.-Prog. Ser., 101, 1–7, 1993. a
Kvale, K. F. and Meissner, K. J.: Primary production sensitivity to phytoplankton light attenuation parameter increases with transient forcing, Biogeosciences, 14, 4767–4780, https://doi.org/10.5194/bg-14-4767-2017, 2017. a, b
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
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
Lewis, M. R., Cullen, J. J., and Platt, T.: Phytoplankton and thermal structure in the upper ocean: consequences of nonuniformity in chlorophyll profile, J. Geophys. Res.-Oceans, 88, 2565–2570, 1983. a
Mahowald, N. M., Yoshioka, M., Collins, W. D., Conley, A. J., Fillmore, D. W., and Coleman, D. B.: Climate response and radiative forcing from mineral aerosols during the last glacial maximum, pre-industrial, current and doubled-carbon dioxide climates, Geophys. Res. Lett., 33, L20705, https://doi.org/10.1029/2006GL026126, 2006. a
Manizza, M., Le Quéré, C., Watson, A. J., and Buitenhuis, E. T.: Bio-optical feedbacks among phytoplankton, upper ocean physics and sea-ice in a global model, Geophys. Res. Lett., 32, L05603, https://doi.org/10.1029/2004GL020778, 2005. a, b
McClain, C. R., Signorini, S. R., and Christian, J. R.: Subtropical gyre variability observed by ocean-color satellites, Deep-Sea Res. Pt. II, 51, 281–301, 2004. a
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J.-F., Matsumoto, K., Montzka, S.A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M., and van Vuuren, D. P. P.: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300, Climatic Change, 109, 213, https://doi.org/10.1007/s10584-011-0156-z, 2011 (data available at: https://www.pik-potsdam.de/~mmalte/rcps/, last access: 10 July 2024). a, b, c, d
Meyer, K., Ridgwell, A., and Payne, J.: The influence of the biological pump on ocean chemistry: implications for long-term trends in marine redox chemistry, the global carbon cycle, and marine animal ecosystems, Geobiology, 14, 207–219, 2016. a
Moore, J. K., Doney, S. C., Kleypas, J. A., Glover, D. M., and Fung, I. Y.: An intermediate complexity marine ecosystem model for the global domain, Deep-Sea Res. Pt. II, 49, 403–462, 2001. a
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., Van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of scenarios for climate change research and assessment, Nature, 463, 747–756, 2010. a, b
Paulsen, H.: The effects of marine nitrogen-fixing cyanobacteria on ocean biogeochemistry and climate – an Earth system model perspective, PhD thesis, Universität Hamburg Hamburg, https://doi.org/10.17617/2.2598976, 2018. a, b, c
Pellerin, F., Porada, P., and Hense, I.: ESD Reviews: Evidence of multiple inconsistencies between representations of terrestrial and marine ecosystems in Earth System Models, Earth Syst. Dynam. Discuss. [preprint], https://doi.org/10.5194/esd-2020-55, 2020. a, b
Polovina, J. J., Howell, E. A., and Abecassis, M.: Ocean's least productive waters are expanding, Geophys. Res. Lett., 35, L03618, https://doi.org/10.1029/2007GL031745, 2008. a
Reale, M., Cossarini, G., Lazzari, P., Lovato, T., Bolzon, G., Masina, S., Solidoro, C., and Salon, S.: Acidification, deoxygenation, and nutrient and biomass declines in a warming Mediterranean Sea, Biogeosciences, 19, 4035–4065, https://doi.org/10.5194/bg-19-4035-2022, 2022. a
Reinhard, C. T., Planavsky, N. J., Ward, B. A., Love, G. D., Le Hir, G., and Ridgwell, A.: The impact of marine nutrient abundance on early eukaryotic ecosystems, Geobiology, 18, 139–151, 2020. a
Rhee, G.-Y. and Gotham, I. J.: The effect of environmental factors on phytoplankton growth: temperature and the interactions of temperature with nutrient limitation, Limnol. Oceanogr., 26, 635–648, 1981. a
Richon, C., Dutay, J.-C., Bopp, L., Le Vu, B., Orr, J. C., Somot, S., and Dulac, F.: Biogeochemical response of the Mediterranean Sea to the transient SRES-A2 climate change scenario, Biogeosciences, 16, 135–165, https://doi.org/10.5194/bg-16-135-2019, 2019. a
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007. a, b, c, d, e
Ridgwell, A., Reinhard, C., van de Velde, S., Asselot, R., Adloff, M., Wilson, J., Ward, B., Hülse, D., Monteiro, F., and Vervoort, P.: crem33/EcoGENIE_LA: Asselotetal2021_ESD (Asselotetal2021_ESD), Zenodo [code], https://doi.org/10.5281/zenodo.5676165, 2021. a
Schlunegger, S., Rodgers, K. B., Sarmiento, J. L., Ilyina, T., Dunne, J. P., Takano, Y., Christian, J. R., Long, M. C., Frölicher, T. L., Slater, R., and Lehner, F.: Time of emergence and large ensemble intercomparison for ocean biogeochemical trends, Global Biogeochem. Cy., 34, e2019GB006453, https://doi.org/10.1029/2019GB006453, 2020. a
Semtner, A. J.: A model for the thermodynamic growth of sea ice in numerical investigations of climate, J. Phys. Oceanogr., 6, 379–389, 1976. a
Shell, K., Frouin, R., Nakamoto, S., and Somerville, R.: Atmospheric response to solar radiation absorbed by phytoplankton, J. Geophys. Res.-Atmos., 108, 4445, https://doi.org/10.1029/2003JD003440, 2003. a, b, c
Stockey, R. G., Pohl, A., Ridgwell, A., Finnegan, S., and Sperling, E. A.: Decreasing Phanerozoic extinction intensity as a consequence of Earth surface oxygenation and metazoan ecophysiology, P. Natl. Acad. Sci. USA, 118, e2101900118, https://doi.org/10.1073/pnas.2101900118, 2021. a
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, 3, 738224, https://doi.org/10.3389/fclim.2021.738224, 2021. a
Thompson, S. L. and Warren, S. G.: Parameterization of outgoing infrared radiation derived from detailed radiative calculations, J. Atmos. Sci., 39, 2667–2680, 1982. a
Trenberth, K. E.: A global ocean wind stress climatology based on ECMWF analyses, NCAR Tech. note, 93, https://cir.nii.ac.jp/crid/1572543024240012928 (last access: 9 July 2024), 1989. a
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean, J. Geophys. Res.-Oceans, 97, 7373–7382, 1992. a
Weaver, A. J., Eby, M., Wiebe, E. C., Bitz, C. M., Duffy, P. B., Ewen, T. L., Fanning, A. F., Holland, M. M., MacFadyen, A., Matthews, H. D., Meissner, K. J., Saenko, O., Schmittner, A., Wang, H., and Yoshimori, M.: The UVic Earth System Climate Model: Model description, climatology, and applications to past, present and future climates, Atmos.-Ocean, 39, 361–428, 2001. a, b
Wilson, J., Monteiro, F., Schmidt, D., Ward, B., and Ridgwell, A.: Linking marine plankton ecosystems and climate: A new modeling approach to the warm early Eocene climate, Paleoceanogr. Paleocl., 33, 1439–1452, 2018. a
Wurl, O., Bird, K., Cunliffe, M., Landing, W. M., Miller, U., Mustaffa, N. I. H., Ribas-Ribas, M., Witte, C., and Zappa, C. J.: Warming and inhibition of salinization at the ocean's surface by cyanobacteria, Geophys. Res. Lett., 45, 4230–4237, 2018. a
Zickfeld, K., Eby, M., Weaver, A. J., Alexander, K., Crespin, E., Edwards, N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E., Friedlingstein, P., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E., Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider Von Deimling, T., Shaffer, G., Sokolov, A., Spahni, R., Steinacher, M., Tachiiri, K., Tokos, K. S., Yoshimori, M., Zeng, N., and Zhao, F.: Long-term climate change commitment and reversibility: an EMIC intercomparison, J. Climate, 26, 5782–5809, 2013. a, b, c, d, e, f
Short summary
Phytoplankton are tiny oceanic algae able to absorb the light penetrating the ocean. The light absorbed by these organisms is re-emitted as heat in the surrounding environment, a process commonly called phytoplankton light absorption (PLA). As a consequence, PLA increases the oceanic temperature. We studied this mechanism with a climate model under different climate scenarios. We show that phytoplankton light absorption is reduced under strong warming scenarios, limiting oceanic warming.
Phytoplankton are tiny oceanic algae able to absorb the light penetrating the ocean. The light...
Altmetrics
Final-revised paper
Preprint