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
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Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
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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
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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.
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Revised manuscript under review for CP
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Biogeosciences, 19, 223–239, https://doi.org/10.5194/bg-19-223-2022, https://doi.org/10.5194/bg-19-223-2022, 2022
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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.
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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
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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.
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Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-55, https://doi.org/10.5194/esd-2020-55, 2020
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A. M. Foley, P. B. Holden, N. R. Edwards, J.-F. Mercure, P. Salas, H. Pollitt, and U. Chewpreecha
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M.-A. Knietzsch, A. Schröder, V. Lucarini, and F. Lunkeit
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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
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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...
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