Articles | Volume 19, issue 15
https://doi.org/10.5194/gmd-19-7479-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-7479-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
13 Aug 2026
Development and technical paper |
| 13 Aug 2026
| 13 Aug 2026
Enhancing air–sea CO2 exchange and modulating seawater carbonate–pH dynamics: the role of wave effect mechanisms in the POP2–waves coupled model
Yung-Yao Lan
Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
National Land Resources Conservation Center, National Chung Hsing University, Taichung 40227, Taiwan
Huang-Hsiung Hsu
Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
Wei-Liang Lee
CORRESPONDING AUTHOR
Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
Simon Chou
Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
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Cited articles
Akhand, A., Chanda, A., Watanabe, K., Das, S., Tokoro, T., Hazra, S., and Kuwae, T.: Reduction in riverine freshwater supply changes inorganic and organic carbon dynamics and air-water CO2 fluxes in a tropical mangrove dominated estuary, J. Geophys. Res. G-Biogeo., 126, e2020JG006144, https://doi.org/10.1029/2020JG006144, 2021.
Andreas, E., Vlahos, P., and Monahan, E.: The potential role of sea spray droplets in facilitating air–sea gas transfer, in: IOP conference series: earth and environmental science, IOP Publishing, 35, 012003, https://doi.org/10.1088/1755-1315/35/1/012003, 2016.
Bakker, D. C. E., Pfeil, B., Landa, C. S., Metzl, N., O'Brien, K. M., Olsen, A., Smith, K., Cosca, C., Harasawa, S., Jones, S. D., Nakaoka, S., Nojiri, Y., Schuster, U., Steinhoff, T., Sweeney, C., Takahashi, T., Tilbrook, B., Wada, C., Wanninkhof, R., Alin, S. R., Balestrini, C. F., Barbero, L., Bates, N. R., Bianchi, A. A., Bonou, F., Boutin, J., Bozec, Y., Burger, E. F., Cai, W.-J., Castle, R. D., Chen, L., Chierici, M., Currie, K., Evans, W., Featherstone, C., Feely, R. A., Fransson, A., Goyet, C., Greenwood, N., Gregor, L., Hankin, S., Hardman-Mountford, N. J., Harlay, J., Hauck, J., Hoppema, M., Humphreys, M. P., Hunt, C. W., Huss, B., Ibánhez, J. S. P., Johannessen, T., Keeling, R., Kitidis, V., Körtzinger, A., Kozyr, A., Krasakopoulou, E., Kuwata, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lo Monaco, C., Manke, A., Mathis, J. T., Merlivat, L., Millero, F. J., Monteiro, P. M. S., Munro, D. R., Murata, A., Newberger, T., Omar, A. M., Ono, T., Paterson, K., Pearce, D., Pierrot, D., Robbins, L. L., Saito, S., Salisbury, J., Schlitzer, R., Schneider, B., Schweitzer, R., Sieger, R., Skjelvan, I., Sullivan, K. F., Sutherland, S. C., Sutton, A. J., Tadokoro, K., Telszewski, M., Tuma, M., van Heuven, S. M. A. C., Vandemark, D., Ward, B., Watson, A. J., and Xu, S.: A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016, 2016.
Bange, H. W., Mongwe, P., Shutler, J. D., Arévalo-Martínez, D. L., Bianchi, D., Lauvset, S. K., Liu, C., Löscher, C. R., Martins, H., Rosentreter, J. A., Schmale, O., Steinhoff, T., Upstill-Goddard, R. C., Wanninkhof, R., Wilson, S. T., and Xie, H.: Advances in understanding of air–sea exchange and cycling of greenhouse gases in the upper ocean, Elementa, 12, https://doi.org/10.1525/elementa.2023.00044, 2024.
Behncke, J., Landschützer, P., and Tanhua, T.: A detectable change in the air–sea CO2 flux estimate from sailboat measurements, Sci. Rep., 14, 3345, https://doi.org/10.1038/s41598-024-53159-0, 2024.
Bell, T. G., Landwehr, S., Miller, S. D., de Bruyn, W. J., Callaghan, A. H., Scanlon, B., Ward, B., Yang, M., and Saltzman, E. S.: Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO2 transfer velocities at intermediate–high wind speeds, Atmos. Chem. Phys., 17, 9019–9033, https://doi.org/10.5194/acp-17-9019-2017, 2017.
Blomquist, B. W,, Brumer, S. E., Fairall, C. W., Huebert, B. J., Zappa, C. J., Brooks, I. M., Yang, M., Bariteau, L., Prytherch, J., Hare, J. E., Czerski, H., Matei, A., and Pascal, R. W.: Wind speed and sea state dependencies of air–sea gas transfer: Results from the High Wind speed Gas exchange Study (HiWinGS), J. Geophys. Res.-Oceans, 122, 8034–8062, https://doi.org/10.1002/2017JC013181, 2017.
Blumberg, A. F. and Mellor, G. L.: A Description of a Three-Dimensional Coastal Ocean Circulation Model, in: Coastal and Estuarine Sciences, edited by: Heaps, N. S., Book 4, American Geophysical Union, 1–6, ISBN 978-1-118-66504-6, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/CO004p0001 (last access: 10 August 2026), 1987.
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Caubel, A., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., D'Andrea, F., Davini, P., de Lavergne, C., Denvil, S., Deshayes, J., Devilliers, M., Ducharne, A., Dufresne, J.-L., Dupont, E., Éthé, C., Fairhead, L., Falletti, L., Flavoni, S., Foujols, M.-A., Gardoll, S., Gastineau, G., Ghattas, J., Grandpeix, J.-Y., Guenet, B., Guez, L. E., Guilyardi, E., Guimberteau, M., Hauglustaine, D., Hourdin, F., Idelkadi, A., Joussaume, S., Kageyama, M., Khodri, M., Krinner, G., Lebas, N., Levavasseur, G., Lévy, C., Li, L., Lott, F., Lurton, T., Luyssaert, S., Madec, G., Madeleine, J.-B., Maignan, F., Marchand, M., Marti, O., Mellul, L., Meurdesoif, Y., Mignot, J., Musat, I., Ottlé, C., Peylin, P., Planton, Y., Polcher, J., Rio, C., Rochetin, N., Rousset, C., Sepulchre, P., Sima, A., Swingedouw, D., Thiéblemont, R., Traore, A. K., Vancoppenolle, M., Vial, J., Vialard, J., Viovy, N., and Vuichard, N.: Presentation and Evaluation of the IPSL-CM6A-LR Climate Model, J. Adv. Model. Earth Sy., 12, e2019MS002010, https://doi.org/10.1029/2019MS002010, 2020.
Brumer, S. E., Zappa, C. J., Blomquist, B. W., Fairall, C. W., Cifuentes-Lorenzen, A., Edson, J. B., Brooks, I. M., and Huebert, B. J.: Wave-related Reynolds number parameterizations of CO2 and DMS transfer velocities, Geophys. Res. Lett., 44, 9865–9875, https://doi.org/10.1002/2017GL074979, 2017.
Chikamoto, M. O. and DiNezio, P.: Multi-century changes in the ocean carbon cycle controlled by the tropical oceans and the Southern Ocean, Global Biogeochem. Cy., 35, e2021GB007090, https://doi.org/10.1029/2021GB007090, 2021.
Chikamoto, M. O., DiNezio, P., and Lovenduski, N.: Long-term slowdown of ocean carbon uptake by alkalinity dynamics, Geophys. Res. Lett., 50, e2022GL101954, https://doi.org/10.1029/2022GL101954, 2023.
Coggins, A., Watson, A. J., Schuster, U., Mackay, N., King, B., McDonagh, E., and Poulton, A. J.: Surface ocean carbon budget in the 2017 South Georgia diatom bloom: Observations and validation of profiling biogeochemical argo floats, Deep-Sea Res. Pt. II, 209, 105275, https://doi.org/10.1016/j.dsr2.2023.105275, 2023.
Couldrey, M. P., Oliver, K. I. C., Yool, A., Halloran, P. R., and Achterberg, E. P.: On which timescales do gastransfer velocities control NorthAtlantic CO2 flux variability?, Global Biogeochem. Cy., 30 787–802, https://doi.org/10.1002/2015GB005267, 2016.
Czerski, H., Brooks, I. M., Gunn, S., Pascal, R., Matei, A., and Blomquist, B.: Ocean bubbles under high wind conditions – Part 2: Bubble size distributions and implications for models of bubble dynamics, Ocean Sci., 18, 587–608, https://doi.org/10.5194/os-18-587-2022, 2022.
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Deike, L.: Mass transfer at the ocean-atmosphere interface: The role of wave breaking, droplets, and bubbles, Annu. Rev. Fluid Mech, 54, 191–224, https://doi.org/10.1146/annurev-fluid-030121-014132, 2022.
Deike, L. and Melville, W. K.: Gas transfer by breaking waves, Geophys. Res. Lett., 45, 10482–10492, https://doi.org/10.1029/2018GL078758, 2018.
Deike, L., Zhou, X., Rustogi, P., Stanley, R. H. R., Reichl, B. G., Bushinsky, S. M., and Resplandy, L.: A universal wind–wave–bubble formulation for air–sea gas exchange and its impact on oxygen fluxes, P. Natl. Acad. Sci. USA, 122, e2419319122, https://doi.org/10.1073/pnas.2419319122, 2025.
Dickson, A. G.: An exact definition of total alkalinity and a procedure for the estimation of alkalinity and total inorganic carbon from titration data, Deep-Sea Res., 28A, 609–623, https://doi.org/10.1016/0198-0149(81)90121-7, 1981.
Dong, Y., Yang, M., Bakker, D. C. E., Kitidis, V., and Bell, T. G.: Uncertainties in eddy covariance air–sea CO2 flux measurements and implications for gas transfer velocity parameterisations, Atmos. Chem. Phys., 21, 8089–8110, https://doi.org/10.5194/acp-21-8089-2021, 2021.
Dong, Y., Bakker, D. C. E., Bell, T. G., Huang, B., Landschützer, P., Liss, P. S., and Yang, M.: Update on the temperature corrections of global air–sea CO2 flux estimates, Global Biogeochem. Cy., 36, e2022GB007360, https://doi.org/10.1029/2022GB007360, 2022.
Edson, J. B., Fairall, C. W., Bariteau, L., Zappa, C. J., Cifuentes-Lorenzen, A., McGillis, W. R., Pezoa, S., Hare, J. E., and Helmig, D.: Direct covariance measurement of CO2 gas transfer velocity during the 2008 Southern Ocean Gas Exchange Experiment: Wind speed dependency, J. Geophys. Res.-Oceans, 116, https://doi.org/10.1029/2011jc007022, 2011.
Fay, A. R., Gregor, L., Landschützer, P., McKinley, G. A., Gruber, N., Gehlen, M., Iida, Y., Laruelle, G. G., Rödenbeck, C., Roobaert, A., and Zeng, J.: SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach, Earth Syst. Sci. Data, 13, 4693–4710, https://doi.org/10.5194/essd-13-4693-2021, 2021.
Fay, A. R., Munro, D. R., McKinley, G. A., Pierrot, D., Sutherland, S. C., Sweeney, C., and Wanninkhof, R.: Updated climatological mean ΔfCO2 and net sea–air CO2 flux over the global open ocean regions, Earth Syst. Sci. Data, 16, 2123–2139, https://doi.org/10.5194/essd-16-2123-2024, 2024.
Gray, A. R., Johnson, K. S., Bushinsky, S. M., Riser, S. C., Russell, J. L., Talley, L. D., Wanninkhof, R., Williams, N. L., and Sarmiento, J. L.: Autonomous biogeochemical floats detect significant carbon dioxide outgassing in the high-latitude Southern Ocean, Geophys. Res. Lett., 45, 9049–9057, https://doi.org/10.1029/2018GL078013, 2018.
Gutiérrez-Loza, L., Nilsson, E., Wallin, M. B., Sahlée, E., and Rutgersson, A.: On physical mechanisms enhancing air–sea CO2 exchange, Biogeosciences, 19, 5645–5665, https://doi.org/10.5194/bg-19-5645-2022, 2022.
Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M., Ohgaito, R., Ito, A., Yamazaki, D., Okajima, H., Ito, A., Takata, K., Ogochi, K., Watanabe, S., and Kawamiya, M.: Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks, Geosci. Model Dev., 13, 2197–2244, https://doi.org/10.5194/gmd-13-2197-2020, 2020.
Heimdal, T. H., McKinley, G. A., Sutton, A. J., Fay, A. R., and Gloege, L.: Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling, Biogeosciences, 21, 2159–2176, https://doi.org/10.5194/bg-21-2159-2024, 2024.
Honkanen, M., Tuovinen, J.-P., Laurila, T., Mäkelä, T., Hatakka, J., Kielosto, S., and Laakso, L.: Measuring turbulent CO2 fluxes with a closed-path gas analyzer in a marine environment, Atmos. Meas. Tech., 11, 5335–5350, https://doi.org/10.5194/amt-11-5335-2018, 2018.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P., Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: The Community Earth System Model: A framework for collaborative research, B. Am. Meteorol. Soc., 94, 1339–1360, https://doi.org/10.1175/BAMS-D-12-00121.1, 2013.
Jacobson, A. R., Gruber, N., Sarmiento, J. L., Gloor, M., and Fletcher, S. E. M.: A joint atmosphere-ocean inversion for surface fluxes of carbon dioxide: I. methods and global-scale fluxes, Global. Biogeochem. Cy., 21, GB1020, https://doi.org/10.1029/2005GB002556, 2007.
Jin, C. X., Zhou, T. J., Chen, X. L., and Wu, B: Seasonally evolving dominant interannual variability mode of air–sea CO2 flux over the western North Pacific simulated by CESM1-BGC, Sci. China Earth Sci., 60, 1854–1865, https://doi.org/10.1007/s11430-015-9085-4, 2017.
Johansson, M. M., Björkqvist, J.-V., Särkkä, J., Leijala, U., and Kahma, K. K.: Correlation of wind waves and sea level variations on the coast of the seasonally ice-covered Gulf of Finland, Nat. Hazards Earth Syst. Sci., 22, 813–829, https://doi.org/10.5194/nhess-22-813-2022, 2022.
Koseki, S., Tjiputra, J., Fransner, F., Crespo, L. R., and Keenlyside, N. S.: isentangling the impact of Atlantic Niño on sea–air CO2 flux, Nat. Commun., 14, 3649, https://doi.org/10.1038/s41467-023-38718-9, 2023.
Krall, K. E., Smith, A. W., Takagaki, N., and Jähne, B.: Air–sea gas exchange at wind speeds up to 85 m s−1, Ocean Sci., 15, 1783–1799, https://doi.org/10.5194/os-15-1783-2019, 2019.
Lan, Y.-Y.: POP2–waves coupled model in CESM1.2.2 framework, Zenodo [code], https://doi.org/10.5281/zenodo.15795234, 2025.
Lan, Y.-Y., Hsu, H.-H., Tsuang, B.-J., and Tu, C.-Y.: rceclccr/CAM5_SIT_v1.0 (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.5510795, 2021.
Li, S, Babanin, A. V., and Guan, C.: Dimensionless Parameterizations of Air–Sea CO2 Gas Transfer Velocity on Surface Waves, Tellus B, 75, 1–12, https://doi.org/10.16993/tellusb.1867, 2023.
Liu, B., Six, K. D., and Ilyina, T.: Incorporating the stable carbon isotope 13C in the ocean biogeochemical component of the Max Planck Institute Earth System Model, Biogeosciences, 18, 4389–4429, https://doi.org/10.5194/bg-18-4389-2021, 2021.
Long, M. C., Lindsay, K., Peacock, S., Moore, J. K., and Doney, S. C.: Twentieth-Century oceanic carbon uptake and storage in CESM1 (BGC), J. Climate, 26, 6775–6800, https://doi.org/10.1175/JCLI-D-12-00184.1, 2013.
Lovato, T., Peano, D., Butenschön, M., Materia, S., Iovino, D., Scoccimarro, E., Fogli, P. G., Cherchi, A., Bellucci, A., Gualdi, S., Masina, S., and Navarra, A.: CMIP6 Simulations With the CMCC Earth System Model (CMCC-ESM2), J. Adv. Model. Earth Sy., 14, e2021MS002814, https://doi.org/10.1029/2021MS002814, 2022.
Lovenduski, N. S., Yeager, S. G., Lindsay, K., and Long, M. C.: Predicting near-term variability in ocean carbon uptake, Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, 2019.
Macovei, V. A., Petersen, W., Brix, H., and Voynova, Y. G.: Reduced ocean carbon sink in the south and central North Sea (2014–2018) revealed from FerryBox observations, Geophys. Res. Lett., 48, e2021GL092645, https://doi.org/10.1029/2021GL092645, 2021.
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., Brovkin, V., Claussen, M., Crueger, T., Esch, M., Fast, I., Fiedler, S., Flaeschner, D., Gayler, V., Giorgetta, M., Goll, D. S., Haak, H., Hagemann, S., Hedemann, C., Hohenegger, C., Ilyina, T., Jahns, T., Jimenéz-de-la Cuesta, D., Jungclaus, J., Kleinen, T., Kloster, S., Kracher, D., Kinne, S., Kleberg, D., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Moebis, B., Mueller, W. A., Nabel, J. E. M. S., Nam, C. C. W., Notz, D., Nyawira, S.-S., Paulsen, H., Peters, K., Pincus, R., Pohlmann, H., Pongratz, J., Popp, M., Raddatz, T. J., Rast, S., Redler, R., Reick, C. H., Rohrschneider, T., Schemann, V., Schmidt, H., Schnur, R., Schulzweida, U., Six, K. D., Stein, L., Stemmler, I., Stevens, B., von Storch, J.-S., Tian, F., Voigt, A., Vrese, P., Wieners, K.-H., Wilkenskjeld, S., Winkler, A., and Roeckner, E.: Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Sy., 11, 998–1038, https://doi.org/10.1029/2018MS001400, 2019.
McKinley, G. A., Fay, A. R., Eddebbar, Y. A., Gloege, L., and Lovenduski, N. S.: External forcing explains recentdecadal variability of the ocean carbonsink, AGU Advances, 1, e2019AV00014, https://doi.org/10.1029/2019AV000149, 2020.
Mellor, G. L., Donelan, M. A., and Oey, L.-Y.: A surface wave model for coupling with numerical ocean circulation models. J. Atmos. Ocean. Technol., 25, 1785–1807, https://doi.org/10.1175/2008JTECHO573.1, 2008.
Monahan, E. C. and Spillane, M. C.: The role of oceanic whitecaps in air–sea gas exchange, in: Gas transfer at water surfaces, edited by: Brutsaert, W. and Jirka, G. H., Reidel, Hingham, MA, 495–503, https://doi.org/10.1007/978-94-017-1660-4_45, 1984.
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine ecosystem dynamics and biogeochemical cycling in the Community Earth System Model [CESM1 (BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 scenarios, J. Climate, 26, 9291–9312, https://doi.org/10.1175/JCLI-D-12-00566.1, 2013.
Müller, J. D., Gruber, N., Carter, B., Feely, R., Ishii, M., Lange, N., Lauvset, S. K., Murata, A., Olsen, A., Pérez, F. F., Sabine, C., Tanhua, T., Wanninkhof, R., and Zhu, D.: Decadal trends in the oceanic storage of anthropogenic carbon from 1994 to 2014, AGU Advances, 4, e2023AV000875, https://doi.org/10.1029/2023AV000875, 2023.
Reichl, B. G. and Deike, L.: Contribution of Sea-State Dependent Bubbles to Air–sea Carbon Dioxide Fluxes, Geophys. Res. Lett., 47, e2020GL087267, https://doi.org/10.1029/2020GL087267, 2020.
Roobaert, A., Resplandy, L., Laruelle, G. G., Liao, E., and Regnier, P.: Unraveling the physical and biological controls of the global coastal CO2 sink, Global Biogeochem. Cy., 38, e2023GB007799, https://doi.org/10.1029/2023GB007799, 2024.
Rustogi, P., Resplandy, L., Liao, E., Reichl, B. G., and Deike, L.: Influence of wave‐induced variability on ocean carbon uptake, Global Biogeochem. Cy., 39, e2024GB008382, https://doi.org/10.1029/2024GB008382, 2025.
Sabine, C., Sutton, A., McCabe, K., Lawrence-Slavas, N., Alin, S, Feely, R., Jenkins, R., Maenner, S., Meinig, C., Thomas, J., van Ooijen, E., Passmore, A., and Tilbrook, B.: Evaluation of a new carbon dioxide system for autonomous surface vehicles, J. Atmos. Ocean. Tech., 37, 1305–1317, https://doi.org/10.1175/JTECH-D-20-0010.1, 2020.
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M., Sénési, S., Franchisteguy, L., Vial, J., Mallet, M., Joetzjer, E., Geoffroy, O., Guérémy, J.-F., Moine, M.-P., Msadek, R., Ribes, A., Rocher, M., Roehrig, R., Salas-y-Mélia, D., Sanchez, E., Terray, L., Valcke, S., Waldman, R., Aumont, O., Bopp, L., Deshayes, J., Éthé, C., and Madec, G.: Evaluation of CNRM Earth-System model, CNRM-ESM2-1: role of Earth system processes in present-day and future climate, J. Adv. Model. Earth Sy., 11, 4182–4227, https://doi.org/10.1029/2019MS001791, 2019.
Seland, Ø., Bentsen, M., Olivié, D., Toniazzo, T., Gjermundsen, A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y.-C., 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., Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z., Heinze, C., Iversen, T., and Schulz, M.: Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations, Geosci. Model Dev., 13, 6165–6200, https://doi.org/10.5194/gmd-13-6165-2020, 2020.
Sellar, A. A., Jones, C. G., Mulcahy, J. P., Tang, Y., Yool, A., Wiltshire, A., O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., de Mora, L., Kuhlbrodt, T., Rumbold, S. T., Kelley, D. I., Ellis, R., Johnson, C. E., Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T., Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J., Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A., Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat, S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A., Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and Zerroukat, M.: UKESM1: Description and Evaluation of the U.K. Earth System Model, J. Adv. Model. Earth Syst., 11, 4513–4558, https://doi.org/10.1029/2019MS001739, 2019.
Shutler, J. D., Wanninkhof, R., Nightingale, P. D., Woolf, D. K., Bakker, D. C., Watson, A., Ashton, I., Holding, T., Chapron, B., Quilfen, Y., Fairall, C., Schuster, U., Nakajima, M., and Donlon, C. J.: Satellites will address critical science priorities for quantifying ocean carbon, Front. Ecol. Environ., 18, 27–35, https://doi.org/10.1002/fee.2129, 2019.
Sigmond, M., Anstey, J., Arora, V., Digby, R., Gillett, N., Kharin, V., Merryfield, W., Reader, C., Scinocca, J., Swart, N., Virgin, J., Abraham, C., Cole, J., Lambert, N., Lee, W.-S., Liang, Y., Malinina, E., Rieger, L., von Salzen, K., Seiler, C., Seinen, C., Shao, A., Sospedra-Alfonso, R., Wang, L., and Yang, D.: Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1, Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, 2023.
Signorini, S. R. and McClain, C. R.: Effect of uncertainties in climatologic wind, ocean pCO2, and gas transfer algorithms on the estimate of global sea–air CO2 flux, Global Biogeochem. Cy., 23, GB2025, https://doi.org/10.1029/2008GB003246, 2009.
Smith, R., Jones, P., Briegleb, B., Bryan, F., Danabasoglu, G., Dennis, J., Dukowicz, J., Eden, C., Fox-Kemper, B., Gent, P., Hecht, M., Jayne, S., Jochum, M., Large, W., Lindsay, K., Maltrud, M., Norton, N., Peacock, S., Vertenstein, M., and Yeager, S.: The Parallel Ocean Program (POP) reference manual ocean component of the Community Climate System Model (CCSM) and Community Earth System Model (CESM), Los Alamos National Laboratory Tech. Rep. LAUR-10-01853, 140 pp., https://files.cesm.ucar.edu/models/pop/2/POPRefManual.pdf (last access: 8 August 2026), 2010.
Soloviev, A. and Lukas, R.: Effects of Bubbles and Sea Spray on Air–Sea Exchange in Hurricane Conditions, Bound.-Layer Meteorol., 136, 365–376, https://doi.org/10.1007/s10546-010-9505-0, 2010.
Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P., Laufkötter, C., Paulot, F., and Zadeh, N.: Ocean biogeochemistry in GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2, J. Adv. Model. Earth Sy., 12, e2019MS002043, https://doi.org/10.1029/2019MS002043, 2020.
Sutton, A. J., Sabine, C. L., Maenner-Jones, S., Lawrence-Slavas, N., Meinig, C., Feely, R. A., Mathis, J. T., Musielewicz, S., Bott, R., McLain, P. D., Fought, H. J., and Kozyr, A.: A high-frequency atmospheric and seawater pCO2 data set from 14 open-ocean sites using a moored autonomous system, Earth Syst. Sci. Data, 6, 353–366, https://doi.org/10.5194/essd-6-353-2014, 2014.
Sutton, A. J., Williams, N. L., and Tilbrook, B.: Constraining Southern Ocean CO2 flux uncertainty using uncrewed surface vehicle observations, Geophys. Res. Lett., 48, e2020GL091748, https://doi.org/10.1029/2020GL091748, 2021.
Tjiputra, J. F., Schwinger, J., Bentsen, M., Morée, A. L., Gao, S., Bethke, I., Heinze, C., Goris, N., Gupta, A., He, Y.-C., Olivié, D., Seland, Ø., and Schulz, M.: Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2), Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, 2020.
Tokoro, T., Hosokawa, S., Miyoshi, E., Tada, K., Watanabe, K., Montani, S., Kayanne, H., and Kuwae, T.: Net uptake of atmospheric CO2 by coastal submerged aquatic vegetation, Glob. Change Biol., 20, 1873–1884, https://doi.org/10.1111/gcb.12543, 2014.
Van Dam, B., Polsenaere, P., Barreras-Apodaca, A., Lopes, C., Sanchez-Mejia, Z., Tokoro, T., Kuwae, T., Loza, L. G., Rutgersson, A., Fourqurean, J., and Thomas, H.: Global trends in air-water CO2 exchange over seagrass meadows revealed by atmospheric Eddy Covariance, Global Biogeochem. Cy., 35, e2020GB006848, https://doi.org/10.1029/2020GB006848, 2021.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean, J. Geophys. Res.-Oceans, 97, 7373–7382, https://doi.org/10.1029/92JC00188, 1992.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean revisited, Limnol. Oceanogr-Meth., 12, 351–362, https://doi.org/10.4319/lom.2014.12.351, 2014.
Weiss, R. F.: Carbon dioxide in water and seawater: the solubility of a non-ideal gas, Mar. Chem., 2, 203–215, https://doi.org/10.1016/0304-4203(74)90015-2, 1974.
Williams, N. L., Juranek, L. W., Feely, R. A., Johnson, K. S., Sarmiento, J. L., Talley, L. D., Dickson, A. G., Gray, A. R., Wanninkhof, R., Russell, J. L., and Riser, S. C.: Calculating surface ocean pCO2 from biogeochemical Argo floats equipped with pH: An uncertainty analysis, Global Biogeochem. Cy., 31, 591–604, https://doi.org/10.1002/2016GB005541, 2017.
Wu, L., Cai, Y., and Rutgersson, A.: Ocean surface waves impact on global air–sea CO2 flux, Biogeochemistry, 168, 68, https://doi.org/10.1007/s10533-025-01267-y, 2025.
Wu, Y. and Qi, D.: The controversial Southern Ocean air–sea CO2 flux in the era of autonomous ocean observations, Sci. Bull., 68, 2519–2522, https://doi.org/10.1016/j.scib.2023.08.059, 2023.
Yang, X., Wynn-Edwards, C. A., Strutton, P. G., and Shadwick, E. H.: Drivers of air–sea CO2 flux in the subantarctic zone revealed by time series observations, Global Biogeochem. Cy., 38, e2023GB007766, https://doi.org/10.1029/2023GB007766, 2024.
Yool, A., Palmiéri, J., Jones, C. G., de Mora, L., Kuhlbrodt, T., Popova, E. E., Nurser, A. J. G., Hirschi, J., Blaker, A. T., Coward, A. C., Blockley, E. W., and Sellar, A. A.: Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations, Geosci. Model Dev., 14, 3437–3472, https://doi.org/10.5194/gmd-14-3437-2021, 2021.
Zhou, X., Reichl, B. G., Romero, L., and Deike, L.: A sea state dependent gas transfer velocity for CO2 unifying theory, model, and field data, Earth Space Sci., 10, e2023EA003237, https://doi.org/10.1029/2023EA003237, 2023.
Ziehn, T., Chamberlain, M., Law, R., Lenton, A., Bodman, R., Dix, M., Stevens, L., Wang, Y.-P., and Srbinovsky, J.: The Australian Earth System Model: ACCESS-ESM1.5, J. South. Hemisph. Earth Syst. Sci., 70, 193–214, https://doi.org/10.1071/ES19035, 2020.
Short summary
This study links wave and ocean models in real time to better simulate how our oceans breathe. Unlike older models that treat waves and oceans separately, this new approach captures their dynamic interactions. It reveals that wave-generated bubbles drive up to 40% of the gas exchange, boosting the estimated global ocean carbon sink by 1.8%. This helps scientists better predict climate change and understand the ocean's natural capacity to buffer global warming.
This study links wave and ocean models in real time to better simulate how our oceans breathe....
