CoChat
Sign Up
Cited by 64Marine and coastal ecosystemsClimate Change and GeoengineeringOceanographic and Atmospheric Processes

Modelling considerations for research on ocean alkalinity enhancement (OAE)

Open access
Fennel, Katja, Long, Matthew C., Algar, Christopher, Carter, Brendan, Keller, David, Laurent, Arnaud, Mattern, Jann Paul, Musgrave, Ruth +4 more·2023·State of the Planet
DOI 10.5194/sp-2-oae2023-9-2023

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Abstract. The deliberate increase in ocean alkalinity (referred to as ocean alkalinity enhancement, or OAE) has been proposed as a method for removing CO2 from the atmosphere. Before OAE can be implemented safely, efficiently, and at scale several research questions have to be addressed, including (1) which alkaline feedstocks are best suited and the doses in which they can be added safely, (2) how net carbon uptake can be measured and verified, and (3) what the potential ecosystem impacts are. These research questions cannot be addressed by direct observation alone but will require skilful and fit-for-purpose models. This article provides an overview of the most relevant modelling tools, including turbulence-, regional-, and global-scale biogeochemical models and techniques including approaches for model validation, data assimilation, and uncertainty estimation. Typical biogeochemical model assumptions and their limitations are discussed in the context of OAE research, which leads to an identification of further development needs to make models more applicable to OAE research questions. A description of typical steps in model validation is followed by proposed minimum criteria for what constitutes a model that is fit for its intended purpose. After providing an overview of approaches for sound integration of models and observations via data assimilation, the application of observing system simulation experiments (OSSEs) for observing system design is described within the context of OAE research. Criteria for model validation and intercomparison studies are presented. The article concludes with a summary of recommendations and potential pitfalls to be avoided.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5194/sp-2-oae2023-9-2023

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Incomplete air-sea flux is currently the focus of most modeling efforts, which remain under active development.

    “Incomplete air-sea flux is currently the focus of most modeling efforts, which remain under active development. 89”

    From A framework for understanding efficiency losses of Ocean Alkalinity Enhancement (2026) · cites this paper as [89]

    Section 2.2.5 says air–sea gas exchange is necessary to quantify OAE carbon uptake and that commonly used model parameterizations neglect potentially important processes. Section 2.3 identifies continuing model-development needs. Neither section says incomplete air–sea flux is the focus of most modeling efforts. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 156

  1. Aller, R. C.: Transport and reactions in the bioirrigated zone, in: The Benthic Boundary Layer, edited by: Boudreau, B. P., and Jorgensen, B. B., Oxford University Press, 269-301, ISBN 9780195118810, 2001.
  2. Bach, L. T., Gill, S. J., Rickaby, R. E., Gore, S., and Ren- forth, P.: CO 2 Removal With Enhanced Weathering and Ocean Alkalinity Enhancement: Potential Risks and Co- benefits for Marine Pelagic Ecosystems, Front. Clim., 1, 7, https://doi.org/10.3389/fclim.2019.00007, 2019. · DOI · Paper page
  3. Barrett, P. M., Resing, J. A., Buck, N. J., Freely, R. A., Bullister, J. L., Buck, C. S., and Landing, W. M.: Cal- cium carbonate dissolution in the upper 1000 m of the east- ern North Atlantic, Global Biogeochem. Cy., 28, 386-397, https://doi.org/10.1002/2013GB004619, 2014. · DOI
  4. Barton, A. D., Pershing, A. J., Litchman, E., Record, N. R., Ed- wards, K. F., Kinkel, Z. V., Kiørboe, T., and Ward, B. A.: The biogeography of marine plankton traits, Ecol. Lett., 16, 522-534, https://doi.org/10.1111/ele.12063, 2013. · DOI
  5. Bates, N. R. and Merlivat, L.: The influence of short-term wind vari- ability on air-sea CO 2 exchange, Geophys. Res. Lett., 28, 3281- 3284, https://doi.org/10.1029/2001GL012897, 2001. · DOI
  6. Bell, T. G., Landwehr, S., Miller, S. D., de Bruyn, W. J., Callaghan, A. H., Scanlon, B., Ward, B., Yang, M., and Saltz- man, E. S.: Estimation of bubble-mediated air-sea gas ex- change from concurrent DMS and CO 2 transfer velocities at intermediate-high wind speeds, Atmos. Chem. Phys., 17, 9019- 9033, https://doi.org/10.5194/acp-17-9019-2017, 2017. · DOI
  7. Bittig, H. C., Steinhoff, T., Claustre, H., Fiedler, B., Williams, N. L., Sauzède, R., Körtzinger, A., and Gattuso, J.-P.: An Alterna- tive to Static Climatologies: Robust Estimation of Open Ocean CO 2 Variables and Nutrient Concentrations From T, A, and O 2 Data using Bayesian Neural Networks, Front. Mar. Sci., 5, 328, https://doi.org/10.3389/fmars.2018.00328, 2018. · DOI
  8. Bleninger, T. and Jirka, G. H.: Near-and Far-Field Model Coupling Methodology for Wastewater Discharges, in: Environmental Hy- draulics and Sustainable Water Management, edited by: Lee, J. H. W. and Lam, K. M., Taylor & Francis, London, 447-453, https://doi.org/10.1201/b16814, 2004. · DOI
  9. Boudreau, B. P. (Eds.): Diagenetic Models and their Implementa- tion: Modelling Transport and Reactions in Aquatic Sciences, Springer, https://doi.org/10.1007/978-3-642-60421-8, 1997. · DOI
  10. Boudreau, B. P., Middelburg, J. J., and Meysman, F. J. R.: Carbon- ate compensation dynamics, Geophys. Res. Lett., 37, L03603, https://doi.org/10.1029/2009GL041847, 2010. · DOI
  11. Boudreau, B. P., Middelburg, J. J., and Luo, Y.: The role of calci- fication in carbonate compensation, Nat. Geosci., 11, 894-900, https://doi.org/10.1038/s41561-018-0259-5, 2018. · DOI
  12. Boyd, P. W., Claustre, H., Legendre, L., Gattuso, J.-P., and Le Traon, P.-Y.: Operational monitoring of open-ocean carbon diox- ide removal deployments: Detection, attribution, and determina- tion of side effects, in: Frontiers in Ocean Observing: Emerg- ing Technologies for Understanding and Managing a Changing Ocean, edited by: Kappel, E. S., Cullen, V., Costello, M. J., Galgani, L., Gordó-Vilaseca, C., Govindarajan, A., Kouhi, S., Lavin, C., McCartin, L., Müller, J. D., Pirenne, B., Tanhua, T., Zhao, Q., and Zhao, S., Oceanography, 36 (Supplement 1), 2- 10, https://doi.org/10.5670/oceanog.2023.s1.2, 2023. · DOI
  13. Briggs, E. M., Sandoval, S., Erten, A., Takeshita, Y., Kummel, A. C., and Martz, T. R.: Solid state sensor for simultaneous mea- surement of total alkalinity and pH of seawater, ACS Sens., 2, 1302-1309, https://doi.org/10.1021/acssensors.7b00305, 2017. · DOI
  14. Burdige, D. J.: Preservation of Organic Matter in Marine Sed- iments: Controls, Mechanisms, and an Imbalance in Sedi- ment Organic Carbon Budgets?, Chem. Rev., 107, 467-485, https://doi.org/10.1021/cr050347q, 2007. · DOI · Paper page
  15. Burt, D. J., Fröb, F., and Ilyina, T.: The sensitivity of the marine car- bonate system to regional ocean Alkalinity Enhancement, Front. Clim., 3, 624075, https://doi.org/10.3389/fclim.2021.624075, 2021. · DOI
  16. Bushinsky, S. M., Takeshita, Y., and Williams, N. L.: Ob- serving changes in ocean carbonate chemistry: Our au- tonomous future, Current Climate Change Reports, 5, 207-220, https://doi.org/10.1007/s40641-019-00129-8, 2019. · DOI
  17. Carrassi, A., Bocquet, M., Bertino, L., and Evensen, G.: Data assimilation in the geosciences: An overview of methods, issues, and perspectives, WIREs Clim Change, 9, e535, https://doi.org/10.1002/wcc.535, 2018. · DOI
  18. Carroll, D., Menemenlis, D., Adkins, J. F., Bowman, K. W., Brix, H., Dutkiewicz, S., Fenty, I., Gierach, M. M., Hill, C., Jahn, O., Landschützer, P., Lauderdale, J. M., Liu, J., Man- izza, M., Naviaux, J. D., Rödenbeck, C., Schimel, D. S. Van der Stockem T., and Zhang, H.:The ECCO-Darwin data- assimilative global ocean biogeochemistry model: Estimates of seasonal to multidecadal surface ocean pCO 2 and air-sea CO 2 flux, J. Adv. Model. Earth Sy., 12, e2019MS001888, https://doi.org/10.1029/2019MS001888, 2020. · DOI
  19. Caserini, S., Pagano, D., Campo, F., Abbà, A., De Marco, S., Righi, D., Renforth, P., and Grosso, M.: Potential of maritime transport for ocean liming and atmospheric CO 2 removal, Front. Clim., 3, 575900, https://doi.org/10.3389/fclim.2021.575900, 2021. · DOI
  20. Ciavatta, S., Brewin, R. J. W., Skákala, J., Polimene, L., de Mora, L., Artioli, Y., and Allen, J. I.: Assimilation of ocean- color plankton functional types to improve marine ecosys- tem simulations, J. Geophys. Res.-Oceans, 123, 834-854, https://doi.org/10.1002/2017JC013490, 2018. · DOI
  21. Chai, F., Johnson, K. S., Claustre, H., Xing, X., Wang, Y., Boss, E., Riser, S., Fennel, K., Schofield, O., and Sutton, A.: Moni- toring ocean biogeochemistry with autonomous platforms, Nat. Rev. Earth Environ., 1, 315-326, https://doi.org/10.1038/s43017- 020-0053-y, 2020. · DOI
  22. Chang, Y. S. and Scotti, A.: Modeling unsteady turbulent flows over ripples: Reynolds-averaged Navier-Stokes equations (RANS) versus large-eddy simulation (LES), J. Geophys. Res.-Oceans, 109, C09012, https://doi.org/10.1029/2003JC002208, 2004. · DOI
  23. Chua, E. J., Huettel, M., Fennel, K., and Fulweiler, R. W.: A case for addressing the unresolved role of permeable shelf sed- iments in ocean denitrification, Limnol. Oceanogr. Lett., 7, 11- 25, https://doi.org/10.1002/lol2.10218, 2022. · DOI
  24. CMEMS: Global Ocean Physics Analysis and Forecast. E.U. Copernicus Marine Service Information (CMEMS), Marine Data Store (MDS), https://doi.org/10.48670/moi-00016, 2023. · DOI
  25. Cossarini, G., Mariotti, L., Feudale, L., Mignot, A., Sa- lon, S., Taillandier, V., Teruzzi, A., and D'Ortenzio, F.: Towards operational 3D-Var assimilation of chlorophyll Biogeochemical-Argo float data into a biogeochemical model of the Mediterranean Sea, Ocean Model., 133, 112-128, https://doi.org/10.1016/j.ocemod.2018.11.005, 2019. · DOI
  26. Cullison Gray, S. E., DeGrandpre, M. D., Moore, T. S., Martz, T. R., Friederich, G. E., and Johnson, K. S.: Applications of in situ pH measurements for inorganic carbon calculations, Mar. Chem., 125, 82-90, https://doi.org/10.1016/j.marchem.2011.02.005, 2011. · DOI
  27. Denvil-Sommer, A., Gehlen, M., and Vrac, M.: Observation system simulation experiments in the Atlantic Ocean for enhanced sur- face ocean pCO 2 reconstructions, Ocean Sci., 17, 1011-1030, https://doi.org/10.5194/os-17-1011-2021, 2021. · DOI
  28. Dickson, A. G. and Riley, J. P.: The estimation of acid dissociation constants in seawater media from potentiometric titrations with strong base. I. The ionic product of water -Kw, Mar. Chem., 7, 89-99, https://doi.org/10.1016/0304-4203(79)90001-X, 1979. · DOI
  29. Doney, S. C., Lima, I., Moore, J. K., Lindsay, K., Behren- feld, M. J., Westberry, T. K., Mahowald, N., Glover, D. M., and Takahashi, T.: Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data, J. Mar. Syst., 76, 95-112, https://doi.org/10.1016/j.jmarsys.2008.05.015, 2009. · DOI
  30. Emerson, S. R. and Archer, D.: Calcium carbonate preserva- tion in the ocean, Philos. T. Roy. Soc. S-A., 331, 29-40, https://doi.org/10.1098/rsta.1990.0054, 1990. · DOI
  31. European Centre for Medium-Range Weather Forecasts (ECMWF): ECMWF IFS CY41r2 High-Resolution Operational Forecasts, European Centre for Medium-Range Weather Forecasts, 2016, updated monthly, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Sys- tems Laboratory, https://doi.org/10.5065/D68050ZV, 2023. · DOI
  32. Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimen- tal design and organization, Geosci. Model Dev., 9, 1937-1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. · DOI · Paper page
  33. Fairall, C. W., Hare, J. E., Edson, J. B., and McGillis, W.: Parameterization and micrometeorological measurement of air-sea gas transfer, Bound.-Lay. Meteorol., 96, 63-106, https://doi.org/10.1023/A:1002662826020, 2000. · DOI
  34. Fakhraee, M., Li, Z., Planavsky, N. J., and Reinhard, C. T.: A bio- geochemical model of mineral-based ocean alkalinity enhance- ment: impacts on the biological pump and ocean carbon uptake, Environ. Res. Lett, 18, 044047, https://doi.org/10.1088/1748- 9326/acc9d4, 2023. · DOI
  35. Farsoiya, P. K., Magdelaine, Q., Antkowiak, A., Popinet, S., and Deike, L.: Direct numerical simulations of bubble-mediated gas transfer and dissolution in quiescent and turbulent flows, J. Fluid Mech., 954, A29, https://doi.org/10.1017/jfm.2022.994, 2023. · DOI
  36. Fassbender, A. J. Sabine, C. L., Lawrence-Slavas, N., De Carlo, E. H., Meinig, C., and Maenner Jones, S.: Robust sensor for extended autonomous measurements of surface ocean dis- solved inorganic carbon, Environ. Sci. Technol., 49, 3628-3635, https://doi.org/10.1021/es5047183, 2015. · DOI
  37. Feng, E. Y., Koeve, W., Keller, D. P., and Oschlies, A.: Model- Based Assessment of the CO 2 Sequestration Potential of Coastal Ocean Alkalization, Earths Future, 5, 1252-1266, https://doi.org/10.1002/2017EF000659, 2017. · DOI
  38. Fennel, K., Losch, M., Schröter, J., and Wenzel, M.: Test- ing a marine ecosystem model: sensitivity analysis and parameter optimization, J. Marine Syst., 28, 45-63, https://doi.org/10.1016/S0924-7963(00)00083-X, 2001. · DOI
  39. Fennel, K., Wilkin, J., Previdi, M., and Najjar, R.: Denitrification effects on air-sea CO 2 flux in the coastal ocean: Simulations for the Northwest North Atlantic, Geophys. Res. Lett., 35, L24608, https://doi.org/10.1029/2008GL036147, 2008. · DOI
  40. Fennel, K., Gehlen, M., Brasseur, P., Brown, C. W., Cia- vatta, S., Cossarini, G., Crise, A., Edwards, C. A., Ford, D., Friedrichs, M. A. M., Gregoire, M., Jones, E., Kim, H- C., Lamouroux, J., Murtugudde, R., Perruche, C., and the GODAE OceanView Marine Ecosystem Analysis and Pre- diction Task Team: Advancing Marine Biogeochemical and Ecosystem Reanalyses and Forecasts as Tools for Monitor- ing and Managing Ecosystem Health, Front. Mar. Sci., 6, 89, https://doi.org/10.3389/fmars.2019.00089, 2019. · DOI
  41. Fennel, K., Mattern, J. P., Doney, S., Bopp, L., Moore, A., Wang, B., and Yu, L.: Ocean biogeochemical modelling, Nat. Rev. Meth- ods Primers, 2, 76, https://doi.org/10.1038/s43586-022-00154-2, 2022. · DOI
  42. Ferderer, A., Chase, Z., Kennedy, F., Schulz, K. G., and Bach, L. T.: Assessing the influence of ocean alkalinity enhancement on a coastal phytoplankton community, Biogeosciences, 19, 5375- 5399, https://doi.org/10.5194/bg-19-5375-2022, 2022. · DOI
  43. Ford, D.: Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to in- form observing system design, Biogeosciences, 18, 509-534, https://doi.org/10.5194/bg-18-509-2021, 2021. · DOI
  44. Fornari, W., Picano, F., Sardinia, G., and Brandt, L.: Reduced par- ticle settling speed in turbulence, J. Fluid Mech., 808, 153-167, https://doi.org/10.1017/jfm.2016.648, 2016. · DOI
  45. Foteinis, S., Campbell, J. S., and Renforth, P.: Life cycle as- sessment of coastal enhanced weathering for carbon diox- ide removal from air, Environ. Sci. Technol., 57, 6169-6178, https://doi.org/10.1021/acs.est.2c08633, 2023. · DOI
  46. Fry, C. H., Tyrrell, T., Hain, M. P., Bates, N. R., and Achter- berg, E. P.: Analysis of global surface ocean alkalinity to determine controlling processes, Mar. Chem., 174, 46-57, https://doi.org/10.1016/j.marchem.2015.05.003, 2015. · DOI
  47. Fuhr, M., Geilert, S., Schmidt, M., Liebetrau, V., Vogt, C., Led- wig, B., and Wallmann, K.: Kinetics of olivine weathering in seawater: an experimental study, Front. Clim., 4, 831587, https://doi.org/10.3389/fclim.2022.831587, 2022. · DOI
  48. Gehlen, M., Bopp, L., and Aumont, O.: Short-term dissolution re- sponse of pelagic carbonate sediments to the invasion of an- thropogenic CO 2 : A model study, Geochem. Geophy. Geosy., 9, Q02012, https://doi.org/10.1029/2007GC001756, 2008. · DOI
  49. Gent, P. R. and McWilliams, J. C.: Isopycnal Mixing in Ocean Circulation Models, J. Phys. Oceanogr., 20, 150-155, https://doi.org/10.1175/1520- 0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990. · DOI
  50. Gentile, E., Tarantola, F., Lockley, A., Vivian, C., and Caserini, S.: Use of aircraft in ocean alkalin- ity enhancement, Sci. Total Environ., 822, 153484, https://doi.org/10.1016/j.scitotenv.2022.153484, 2022. · DOI
  51. Golshan, R., Tejada-Martínez, A. E., Juha, M. J., and Bazilevs, Y.: LES and RANS simulation of wind-and wave-forced oceanic turbulent boundary layers in shallow water with wall modeling, Comput. Fluids, 145, 96-108, https://doi.org/10.1016/j.compfluid.2016.05.016, 2017. · DOI
  52. Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Bal- aji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Hol- land, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231-3296, https://doi.org/10.5194/gmd-9-3231- 2016, 2016. · DOI
  53. Grigoratou, M., Monteiro, F. M., Wilson, J. D., Ridgwell, A., and Schmidt, D. N.: Exploring the impact of climate change on the global distribution of non-spinose planktonic foraminifera using a trait-based ecosystem model, Glob. Change Biol., 28, 1063- 1076, https://doi.org/10.1111/gcb.15964, 2022. · DOI
  54. Guo, J. A., Strzepek, R., Willis, A., Ferderer, A., and Bach, L. T.: Investigating the effect of nickel concentration on phytoplankton growth to assess potential side-effects of ocean alkalinity enhancement, Biogeosciences, 19, 3683-3697, https://doi.org/10.5194/bg-19-3683-2022, 2022. · DOI
  55. Haidvogel, D. B., Arango, H., Budgell, W. P., Cornuelle, B. D., Cur- chitser, E., Lorenzo, E. D., Fennel, K., Geyer, W. R., Hermann, A. J., Lanerolle, L., Levin, J., McWilliams, J. C., Miller, A. J., Moore, A. M., Powell, T. M., Shchepetkin, A. F., Sherwood, C. R., Signell, R. P., Warner, J. C., and Wilkin, J.: Ocean forecasting in terrain-following coordinates: Formulation and skill assess- ment of the Regional Ocean Modeling System, J. Comput. Phys., 227, 3595-3624, https://doi.org/10.1016/j.jcp.2007.06.016, 2008 (code available at: https://perma.cc/3BJY-U4LE, last access: 15 November 2023). · DOI
  56. Hain, M. P., Sigman, D. M., Higgins, J. A., and Haug, G. H.: The effects of secular calcium and magnesium concentration changes on the thermodynamics of seawater acid/base chem- istry: Implications for Eocene and Cretaceous ocean carbon chemistry and buffering, Global Biogeochem. Cy., 29, 517-533, https://doi.org/10.1002/2014GB004986, 2015. · DOI
  57. Halliwell, G. R., Kourafalou, V., Le Hénaff, M., Shay, L. K., and Atlas, R.: OSSE impact analysis of airborne ocean sur- veys for improving upper-ocean dynamical and thermodynami- cal forecasts in the Gulf of Mexico, Prog. Oceanogr., 130, 32-46, https://doi.org/10.1016/j.pocean.2014.09.004, 2015. · DOI
  58. Hartmann, J., Suitner, N., Lim, C., Schneider, J., Marín-Samper, L., Arístegui, J., Renforth, P., Taucher, J., and Riebesell, U.: Stability of alkalinity in ocean alkalinity enhancement (OAE) approaches -consequences for durability of CO 2 storage, Biogeosciences, 20, 781-802, https://doi.org/10.5194/bg-20-781-2023, 2023. · DOI · Paper page
  59. Harvey, L. D. D.: Mitigating the atmospheric CO 2 in- crease and ocean acidification by adding limestone pow- der to upwelling regions, J. Geophys. Res., 113, C04028, https://doi.org/10.1029/2007JC004373, 2008. · DOI
  60. He, J. and Tyka, M. D.: Limits and CO 2 equilibration of near-coast alkalinity enhancement, Biogeosciences, 20, 27-43, https://doi.org/10.5194/bg-20-27-2023, 2023. · DOI
  61. Heuzé, C.: Antarctic Bottom Water and North Atlantic Deep Water in CMIP6 models, Ocean Sci., 17, 59-90, https://doi.org/10.5194/os-17-59-2021, 2021. · DOI
  62. Hinrichs, C., Köhler, P., Völker, C., and Hauck, J.: Alkalinity biases in CMIP6 Earth system models and implications for simulated CO 2 drawdown via artificial alkalinity enhancement, Biogeosciences, 20, 3717-3735, https://doi.org/10.5194/bg-20- 3717-2023, 2023. · DOI
  63. Ho, D. T., Bopp, L., Palter, J. B., Long, M. C., Boyd, P. W., Neuker- mans, G., and Bach, L. T.: Monitoring, reporting, and verification for ocean alkalinity enhancement, in: Guide to Best Practices in Ocean Alkalinity Enhancement Research, edited by: Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gattuso, J.-P., Copernicus Publica- tions, State Planet, 2-oae2023, 12, https://doi.org/10.5194/sp-2- oae2023-12-2023, 2023. · DOI
  64. Hoffman, R. N. and Atlas, R.: Future observing system simu- lation experiments, B. Am. Meteorol. Soc., 97, 1601-1616, https://doi.org/10.1175/BAMS-D-15-00200.1, 2016. · DOI
  65. House, K. Z., House, C. H., Schrag, D. P., and Aziz, M. J.: Electrochemical acceleration of chemical weathering for car- bon capture and sequestration, Enrgy. Proced., 1, 4953-4960, https://doi.org/10.1016/j.egypro.2009.02.327, 2009. · DOI
  66. Huettel, M., Berg, P., and Kostka, J. E.: Benthic exchange and bio- geochemical cycling in permeable sediments, Ann. Rev. Mar. Sci., 6, 23-51, https://doi.org/10.1146/annurev-marine-051413- 012706, 2014. · DOI
  67. Ilyina, T., Wolf-Gladrow, D., Munhoven, G., and Heinze, C.: Assessing the potential of calcium-based artificial ocean alkalinization to mitigate rising atmospheric CO 2 and ocean acidification, Geophys. Res. Lett., 40, 5909-5914, https://doi.org/10.1002/2013GL057981, 2013. · DOI · Paper page
  68. IPCC: Climate Change 2013: The Physical Science Basis, Contri- bution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P. M., Cambridge Uni- versity Press, 1585 pp., ISBN 978-92-9169-138-8, 2013.
  69. Jahnke, R. A.: Global synthesis, in: Carbon and nutrient fluxes in continental margins: A global synthesis, edited by: Liu, K.-K., Atkinson, L., Quiñones, R., and Talaue- McManus, L., Springer, Berlin, Heidelberg, Germany, 597-615, https://doi.org/10.1007/978-3-540-92735-8, 2010. · DOI
  70. Juckes, M., Taylor, K. E., Durack, P. J., Lawrence, B., Mizielinski, M. S., Pamment, A., Peterschmitt, J.-Y., Rixen, M., and Sénési, S.: The CMIP6 Data Request (DREQ, version 01.00.31), Geosci. Model Dev., 13, 201-224, https://doi.org/10.5194/gmd-13-201- 2020, 2020. · DOI
  71. Keller, D. P., Oschlies, A., and Eby, M.: A new marine ecosystem model for the University of Victoria Earth Sys- tem Climate Model, Geosci. Model Dev., 5, 1195-1220, https://doi.org/10.5194/gmd-5-1195-2012, 2012. · DOI
  72. Keller, D. P., Feng, E. Y., and Oschlies, A.: Potential cli- mate engineering effectiveness and side effects during a high carbon dioxide-emission scenario, Nat. Commun., 5, 3304, https://doi.org/10.1038/ncomms4304, 2014. · DOI
  73. Keller, D. P., Lenton, A., Scott, V., Vaughan, N. E., Bauer, N., Ji, D., Jones, C. D., Kravitz, B., Muri, H., and Zickfeld, K.: The Carbon Dioxide Removal Model Intercomparison Project (CDR- MIP): rationale and experimental protocol for CMIP6, Geosci. Model Dev., 11, 1133-1160, https://doi.org/10.5194/gmd-11- 1133-2018, 2018. · DOI
  74. Kitagawa, G.: A self-organizing state-space model. J. Am. Stat. As- soc., 93, 1203-1215, https://doi.org/10.2307/2669862, 1998. · DOI
  75. Ko, Y. H., Lee, K., Eom, K. H., and Han, I.-S.: Organic alkalin- ity produced by phytoplankton and its effect on the computation of ocean carbon parameters, Limnol. Oceanogr., 61, 1462-1471, https://doi.org/10.1002/lno.10309, 2016. · DOI
  76. Koeve, W. and Oschlies, A.: Potential impact of DOM ac- cumulation on f CO 2 and carbonate ion computations in ocean acidification experiments, Biogeosciences, 9, 3787-3798, https://doi.org/10.5194/bg-9-3787-2012, 2012. · DOI
  77. Köhler, P., Hartmann, J., and Wolf-Gladrow, D. A.: Geoengi- neering potential of artificially enhanced silicate weather- ing of olivine, P. Natl. Acad. Sci. USA, 107, 20228-20233, https://doi.org/10.1073/pnas.1000545107, 2010. · DOI · Paper page
  78. Köhler, P., Abrams, J. F., Völker, C., Hauck, J., and Wolf- Gladrow, D. A.: Geoengineering impact of open ocean dis- solution of olivine on atmospheric CO 2 , surface ocean pH and marine biology, Environ. Res. Lett., 8, 014009, https://doi.org/10.1088/1748-9326/8/1/014009, 2013. · DOI
  79. Krumhardt, K. M., Lovenduski, N. S., Iglesias-Rodriguez, M. D., and Lkeypas, J. A.: Coccolithophore growth and calcifi- cation in a changing ocean, Prog. Oceanogr., 159, 276-295, https://doi.org/10.1016/j.pocean.2017.10.007, 2017. · DOI
  80. Laurent, A., Fennel, K., Wilson, R., Lehrter, J., and Devereux, R.: Parameterization of biogeochemical sediment-water fluxes using in situ measurements and a diagenetic model, Biogeosciences, 13, 77-94, https://doi.org/10.5194/bg-13-77-2016, 2016. · DOI
  81. Laurent, A., Fennel, K., and Kuhn, A.: An observation-based evalu- ation and ranking of historical Earth system model simulations in the northwest North Atlantic Ocean, Biogeosciences, 18, 1803- 1822, https://doi.org/10.5194/bg-18-1803-2021, 2021. · DOI
  82. Lellouche, J.-M., Greiner, E., Bourdallé-Badie, R., Garric, G., Melet, A., Drévillon, M., Bricaud, C., Hamon, M., Le Gal- loudec, O., Regnier, C., Candela, T., Testut. C.-E., Gas- parin, F., Ruggiero, G., Benkiran, M., Drillet, Y., and Le Traon, P.-Y.: The Copernicus Global 1/12 • Oceanic and Sea Ice GLORYS12 Reanalysis, Front. Earth Sci., 9, 698876, https://doi.org/10.3389/feart.2021.698876, 2021. · DOI
  83. Lewis, E. R. and Wallace, D. W. R.: Program developed for CO 2 system calculations, Environmental System Sci- ence Data Infrastructure for a Virtual Ecosystem (ESS- DIVE), United States, US Lawrence Berkely National Lab, https://doi.org/10.15485/1464255, 1998. · DOI
  84. Li, G., Iskandarani, M., Le Hénaff, M., Winokur, J., Le Maître, O. P., and Knio, O. M.: Quantifying initial and wind forcing un- certainties in the Gulf of Mexico, Computat. Geosci., 20, 1133- 1153, https://doi.org/10.1007/s10596-016-9581-4, 2016. · DOI
  85. Liang, J.-H., McWilliams, J. C., Sullivan, P. P., and Basckek, B.: Modeling bubbles and dissolved gases in the ocean, J. Geophys. Res.-Oceans, 116, C03015, https://doi.org/10.1029/2010JC006579, 2011. · DOI
  86. Liang, J.-H., Deutsch, C., McWilliams, J. C., Baschek, B., Sulli- van, P. P., and Chiba, D.: Parameterizing bubble-mediated air- sea gas exchange and its effect on ocean ventilation, Global Bio- geochem. Cy., 27, 894-905, https://doi.org/10.1002/gbc.20080, 2013. · DOI
  87. Lohrenz, S. E., Cai, W.-J., Chakraborty, S., Huang, W.-J., Guo, X., He, R., Xue, Z., Fennel, K., Howden, S., and Tian, H.: Satellite estimation of coastal pCO 2 and air-sea flux of carbon dioxide in the northern Gulf of Mexico, Remote Sens. Environ., 207, 71-83, https://doi.org/10.1016/j.rse.2017.12.039, 2018. · DOI
  88. Long, J. S., Hu, C., Robbins, L. L., Byrne, R. H., Paul, J. H., and Wolny, J. L.: Optical and biochemical properties of a southwest Florida whiting event, Estuar. Coast. Shelf S., 196, 258-268, https://doi.org/10.1016/j.ecss.2017.07.017, 2017. · DOI
  89. Long, M. C., Moore, J. K., Lindsay, K., Levy, M., Doney, S. C., Luo, J. Y., Krumhardt, K. M., Letscher, R. T., Grover, M., and Sylvester, Z. T.: Simulations with the marine biogeo- chemistry library (MARBL), J. Adv. Model. Earth Syst., 13, e2021MS002647, https://doi.org/10.1029/2021ms002647, 2021. · DOI
  90. Mattern, J. P., Fennel, K., and Dowd, M.: Estimating time- dependent parameters for a biological ocean model us- ing an emulator approach, J. Mar. Syst., 96-97, 32-47, https://doi.org/10.1016/j.jmarsys.2012.01.015, 2012. · DOI
  91. Mattern, J. P., Fennel, K., and Dowd, M.: Periodic time- dependent parameters improving forecasting abilities of bio- logical ocean models, Geophys. Res. Lett., 41, 6848-6854, https://doi.org/10.1002/2014GL061178, 2014. · DOI
  92. Mattern, J. P., Song, H., Edwards, C. A., Moore, A. M., and Fiechter, J.: Data assimilation of physical and chloro- phyll observations in the California Current System us- ing two biogeochemical models, Ocean Model., 109, 55-71, https://doi.org/10.1016/j.ocemod.2016.12.002, 2017. · DOI
  93. Maurer, T. L., Plant, J. N., and Johnson, K. S.: Delayed-Mode Quality Control of Oxygen, Nitrate, and pH Data on SOCCOM Biogeochemical Profiling Floats, Front. Mar. Sci., 8, 683207, https://doi.org/10.3389/fmars.2021.683207, 2021. · DOI
  94. McLaughlin, K., Weisberg, S. B., Dickson, A. G., Hofmann, G., Newton, J. A., Aseltine-Neilson, D., Barton, A., Cudd, S., Feely, R. A., Jefferds, I. W., Jewett, E. B., King, T., Langdon, C. J., McAfee, S., Pleschner-Steele, D., and Steele, B.: Core prin- ciples of the California current acidification network: Link- ing chemistry, physics, and ecological effects, Oceanography, 28, 160-169, http://www.jstor.org/stable/24861878 (last access: 15 November 2023), 2015.
  95. Mengis, N., Keller, D. P., MacDougall, A. H., Eby, M., Wright, N., Meissner, K. J., Oschlies, A., Schmittner, A., MacIsaac, A. J., Matthews, H. D., and Zickfeld, K.: Evaluation of the University of Victoria Earth System Climate Model version 2.10 (UVic ESCM 2.10), Geosci. Model Dev., 13, 4183-4204, https://doi.org/10.5194/gmd-13-4183-2020, 2020. · DOI
  96. Mensa, J. A., Özgökmen, T. M., Poje, A. C., and Imberger, J.: Material transport in a convective surface mixed layer under weak wind forcing, Ocean Model., 96, 226-242, https://doi.org/10.1016/j.ocemod.2015.10.006, 2015. · DOI
  97. Meysman, F. J. R. and Montserrat, F.: Negative CO 2 emissions via enhanced silicate weathering in coastal environments, Biol. Lett., 13, 20160905, https://doi.org/10.1098/rsbl.2016.0905, 2017. · DOI
  98. Meysman, F. J. R., Middelburg, J. J., and Heip, C. H. R.: Bioturba- tion: a fresh look at Darwin's last idea, Trends Ecol. Evol., 21, 688-695, https://doi.org/10.1016/j.tree.2006.08.002, 2006. · DOI
  99. Middelburg, J. J., Soetaert, K., and Hagens, M.: Ocean Alkalin- ity, Buffering and Biogeochemical Processes, Rev. Geophys., 58, e2019RG000681, https://doi.org/10.1029/2019RG000681, 2020. · DOI
  100. Millero, F. J.: The Marine Inorganic Carbon Cycle, Chem. Rev., 107, 308-341, https://doi.org/10.1021/cr0503557, 2007. · DOI
  101. Mongin, M., Baird, M. E., Tilbrook, B., Matear, R. J., Lenton, A., Herzfeld, M., Wild-Allen, K., Skerratt, J., Margvelashvili, N., Robson, B. J., Duarte, C. M., Gustafsson, M. S. M., Ralph, P. J., and Steven, A. D. L.: The exposure of the Great Bar- rier Reef to ocean acidification, Nat. Commun., 7, 10732, https://doi.org/10.1038/ncomms10732, 2016. · DOI
  102. Mongin, M., Baird, M. E., Lenton, A., Neill, C., and Akl, J.: Reversing ocean acidification along the Great Barrier Reef using alkalinity injection, Environ. Res. Lett., 16, 064068, https://doi.org/10.1088/1748-9326/ac002d, 2021. · DOI
  103. Montserrat, F., Renforth, P., Hartmann, J., Leermakers, M., Knops, P., and Meysman, F. J. R.: Olivine dissolution in seawater: Im- plications for CO 2 sequestration through enhanced weathering in coastal environments, Environ. Sci. Technol., 51, 3960-3972, https://doi.org/10.1021/acs.est.6b05942, 2017. · DOI
  104. Moras, C. A., Bach, L. T., Cyronak, T., Joannes-Boyau, R., and Schulz, K. G.: Ocean alkalinity enhancement -avoiding runaway CaCO 3 precipitation during quick and hydrated lime dissolution, Biogeosciences, 19, 3537-3557, https://doi.org/10.5194/bg-19- 3537-2022, 2022. · DOI
  105. Moriarty, J. M., Harris, C. K., Fennel, K., Friedrichs, M. A. M., Xu, K., and Rabouille, C.: The roles of resuspension, diffu- sion and biogeochemical processes on oxygen dynamics off- shore of the Rhône River, France: a numerical modeling study, Biogeosciences, 14, 1919-1946, https://doi.org/10.5194/bg-14- 1919-2017, 2017. · DOI
  106. Moriarty, J. M., Harris, C. K., Friedrichs, M. A. M., Fennel, K., and Xu, K.: Impact of seabed resuspension on oxygen and ni- trogen dynamics in the northern Gulf of Mexico: A numeri- cal modeling study, J. Geophys. Res-Oceans, 123, 7237-7263, https://doi.org/10.1029/2018JC013950, 2018. · DOI
  107. Morse, J. W., Mucci, A., and Millero, F. J.: The solubility of cal- cite and aragonite in seawater of 35 %. Salinity at 25 • C and atmospheric pressure, Geochim. Cosmochim. Ac., 44, 85-94, https://doi.org/10.1016/0016-7037(80)90178-7, 1980. · DOI
  108. Mu, L., Palter, J. B., and Wang, H.: Considerations for hy- pothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed, Biogeosciences, 20, 1963-1977, https://doi.org/10.5194/bg-20-1963-2023, 2023. · DOI
  109. Naveira Garabato, A. C., MacGilchrist, G. A., Brown, P. J., Evans, D. G., Meijers, A. J. S., and Zika, J. D.: High-latitude ocean ven- tilation and its role in Earth's climate transitions, Philos. T. Roy. Soc. A, 375, 20160324, https://doi.org/10.1098/rsta.2016.0324, 2017. · DOI
  110. Negrete-García, G., Luo, J. Y., Long, M. C., Lindsay, K., Levy, M., and Barton, A. D.: Plankton energy flows using a global size- structured and trait-based model, Prog. Oceanogr., 209, 102898, https://doi.org/10.1016/j.pocean.2022.102898, 2022. · DOI
  111. Oschlies, A.: Impact of atmospheric and terrestrial CO 2 feedbacks on fertilization-induced marine carbon uptake, Biogeosciences, 6, 1603-1613, https://doi.org/10.5194/bg-6-1603-2009, 2009. · DOI
  112. Paquay, F. S. and Zeebe, R. E.: Assessing possible consequences of ocean liming on ocean pH, atmospheric CO 2 concentration and associated costs, Int. J. Green. Gas Con., 17, 183-188, https://doi.org/10.1016/j.ijggc.2013.05.005, 2013. · DOI
  113. Pascoe, C., Lawrence, B. N., Guilyardi, E., Juckes, M., and Taylor, K. E.: Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6), Geosci. Model Dev., 13, 2149-2167, https://doi.org/10.5194/gmd-13-2149-2020, 2020. · DOI
  114. Paul, A. J. and Bach, L. T.: Universal response pattern of phyto- plankton growth rates to increase CO 2 , New Phytol., 228, 1710- 1716, https://doi.org/10.1111/nph.16806, 2020. · DOI
  115. Paulmier, A., Kriest, I., and Oschlies, A.: Stoichiometries of rem- ineralisation and denitrification in global biogeochemical ocean models, Biogeosciences, 6, 923-935, https://doi.org/10.5194/bg- 6-923-2009, 2009. · DOI
  116. Petrie, R., Denvil, S., Ames, S., Levavasseur, G., Fiore, S., Allen, C., Antonio, F., Berger, K., Bretonnière, P.-A., Cinquini, L., Dart, E., Dwarakanath, P., Druken, K., Evans, B., Franchistéguy, L., Gardoll, S., Gerbier, E., Greenslade, M., Hassell, D., Iwi, A., Juckes, M., Kindermann, S., Lacinski, L., Mirto, M., Nasser, A. B., Nassisi, P., Nienhouse, E., Nikonov, S., Nuzzo, A., Richards, C., Ridzwan, S., Rixen, M., Serradell, K., Snow, K., Stephens, A., Stockhause, M., Vahlenkamp, H., and Wagner, R.: Coordi- nating an operational data distribution network for CMIP6 data, Geosci. Model Dev., 14, 629-644, https://doi.org/10.5194/gmd- 14-629-2021, 2021. · DOI
  117. Raimondi, L., Matthews, J. B. R., Atamanchuk, D., Azetsu- Scott, K., and Wallace, D. W. R.: The internal consistency of the marine carbon dioxide system for high latitude ship- board and in situ monitoring, Mar. Chem., 213, 49-70, https://doi.org/10.1016/j.marchem.2019.03.001, 2019. · DOI
  118. Ramadhan, A., Wagner, G., Hill, C., Campin, J.-M., Chu- ravy, V., Besard, T., Souza, A., Edelman, A., Ferrari, R., and Marshall, J.: Oceananigans.jl: Fast and friendly geophys- ical fluid dynamics in GPUs, J. Open Source Softw., 5, 2018, https://doi.org/10.21105/joss.02018, 2020 (code avail- able at: https://github.com/CliMA/Oceananigans.jl, last access: 15 November 2023). · DOI
  119. Rau, G. H., McLeod, E. L., and Hoegh-Guldberg, O.: The need for new ocean conservation strategies in a high- carbon dioxide world, Nat. Clim. Change, 2, 720-724, https://doi.org/10.1038/nclimate1555, 2012. · DOI
  120. Riebesell, U., Wold-Gladrow, D. A., and Smetacek, V.: Carbon dioxide limitation of marine phytoplankton growth rates, Nature, 361, 249-251, https://doi.org/10.1038/361249a0, 1993. · DOI
  121. Ringham, M.: High resolution, in-situ studies of seawater carbonate chemistry and carbon cycling in costal systems using CHAN- nelized Opticals System II, PhD thesis, Massachusetts Institute of Technology, 127 pp., https://hdl.handle.net/1721.1/144860, 2022.
  122. Rothstein, L. M., Cullen, J. J., Abbott, M., Chassignet, E. P., Den- man, K., Doney, S. C., Ducklow, H., Fennel, K., Follows, M., Haidvogel, D., Hofmann, E., Karl, D. M., Kindle, J., Lima, I., Maltrud, M., McClain, C., McGillicuddy, D., Olascoaga, M. J., Spitz, Y., Wiggert, J., and Woder, J.: Modeling Ocean Ecosys- tems: The PARADIGM Program, Oceanography, 19, 22-51, https://doi.org/10.5670/oceanog.2006.89, 2015. · DOI
  123. Rutherford, K., Fennel, K., Atamanchuk, D., Wallace, D., and Thomas, H.: A modelling study of temporal and spatial pCO 2 variability on the biologically active and temperature- dominated Scotian Shelf, Biogeosciences, 18, 6271-6286, https://doi.org/10.5194/bg-18-6271-2021, 2021. · DOI
  124. Sarmiento, J. L. and Gruber, N.: Ocean Biogeochemical Dynamics, Princeton University Press, https://doi.org/10.2307/j.ctt3fgxqx, 2006. · DOI
  125. Sauerland, V., Kriest, I., Oschlies, A., and Srivastav, A.: Multiobjective calibration of a global biogeochemical ocean model against nutrients, oxygen, and oxygen min- imum zones, J. Adv. Model. Earth Sy., 11, 1285-1308, https://doi.org/10.1029/2018MS001510, 2019. · DOI
  126. Schartau, M., Wallhead, P., Hemmings, J., Löptien, U., Kriest, I., Krishna, S., Ward, B. A., Slawig, T., and Oschlies, A.: Re- views and syntheses: parameter identification in marine plank- tonic ecosystem modelling, Biogeosciences, 14, 1647-1701, https://doi.org/10.5194/bg-14-1647-2017, 2017. · DOI
  127. Schmittner, A., Oschlies, A., Matthews, H. D., and Galbraith, E. D.: Future changes in climate, ocean circulation, ecosystems, and biogeochemical cycling simulated for a business-as-usual CO 2 emission scenario until 4000 AD, Global Biogeochem. Cy., 22, GB1013, https://doi.org/10.1029/2007GB002953, 2008. · DOI
  128. Schulz, K. G., Bach, L. T., and Dickson, A. G.: Seawater car- bonate chemistry considerations for ocean alkalinity enhance- ment research: theory, measurements, and calculations, in: Guide to Best Practices in Ocean Alkalinity Enhancement Research, edited by: Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gat- tuso, J.-P., Copernicus Publications, State Planet, 2-oae2023, 2, https://doi.org/10.5194/sp-2-oae2023-2-2023, 2023. · DOI · Paper page
  129. Seitzinger, S. P., Mayorga, E., Bouwman, A. F., Kroeze, C., Beusen, H. W., Billen, G., Van Dracht, G., Du- mont, E., Fekete, B. M., Garnier, J., and Harrison, J. A.: Global river nutrient export: A scenario analysis of past and future trends, Global Biogeochem. Cy., 24, GB0A08, https://doi.org/10.1029/2009GB003587, 2010. · DOI
  130. Shangguan, Q., Prody, A., Wirth, T. S., Briggs, E. M., Martz, T. R., and DeGrandpre, M. D.: An inter-comparison of au- tonomous in situ instruments for ocean CO 2 measurements un- der laboratory-controlled conditions, Mar. Chem., 240, 104085, https://doi.org/10.1016/j.marchem.2022.104085, 2022. · DOI
  131. Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Model., 9, 347-404, https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. · DOI
  132. Smagorinsky, J.: General circulation experiments with the primitive equations, Mon. Weather Rev., 91, 99-164, https://doi.org/10.1175/1520- 0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. · DOI
  133. Smith, K. M., Hamlington, P. E., Niemeyer, K. E., Fox-Kemper, B., and Lovenduski, N. S.: Effects of Langmuir turbulence on upper ocean carbonate chemistry, J. Adv. Model. Earth Sy., 10, 3030- 3048, https://doi.org/10.1029/2018MS001486, 2018. · DOI
  134. Soetaert, K., Hofmann, A. F., Middelburg, J. J., Meysman, F. J. R., and Greenwood, J.: The effect of biogeo- chemical processes on pH, Mar. Chem., 105, 30-51, https://doi.org/10.1016/j.marchem.2006.12.012, 2007. · DOI
  135. Sonnichsen, C., Atamanchuk, D., Hendricks, A., Morgan, S., Smith, J., Grundke, I., Luy, E., and Sieben, V. J.: An Automated Microfluidic Analyzer for in-situ Mon- itoring of Total Alkalinity, ACS Sens., 8, 344-352, https://doi.org/10.1021/acssensors.2c02343, 2023. · DOI
  136. Stammer, D.: Global Characteristics of Ocean Variability Estimated from Regional TOPEX/POSEIDON Altimeter Measurements, J. Phys. Oceanogr., 27, 1743-1769, https://doi.org/10.1175/1520- 0485(1997)027<1743:GCOOVE>2.0.CO;2, 1997. · DOI
  137. Stow, C. A., Jolliff, J., McGillicuddy Jr., D. J., Doney, S. C., Allen, J. I., Friedrichs, M. A. M., Rose, K. A., and Wallhead, P.: Skill assessment for coupled biological/phys- ical models of marine systems, J. Mar. Syst., 76, 4-15, https://doi.org/10.1016/j.jmarsys.2008.03.011, 2009. · DOI
  138. Subhas, A. V., Dong, S., Naviaux, J. D., Rollins, N. E., Ziveri, P., Gray, W., Rae, J. W. B., Liu, X., Bryne, R. H., Chen, S., Moore, C., Martell-Bonnet, L., Steiner, Z., Antler, G., Hu, H., Lunstrum, A., Hou, Y., Kemnits, N., Stutsman, J., Pal- lacks, S., Dugenne, M., Quay, P. D., Berelson, W. M., and Adkins, J. F.: Shallow calcium carbonate cycling in the North Pacific Ocean, Global Biogeochem. Cy., 36, e2022GB007388, https://doi.org/10.1029/2022GB007388, 2022. · DOI · Paper page
  139. Subhas, A. V., Lehmann, N., and Rickaby, R. E. M.: Natural analogs to ocean alkalinity enhancement, in: Guide to Best Practices in Ocean Alkalinity Enhancement Research, edited by: Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gattuso, J.-P., Copernicus Publi- cations, State Planet, 2-oae2023, 8, https://doi.org/10.5194/sp-2- oae2023-8-2023, 2023. · DOI
  140. Sulpis, O., Jeansseon, E., Dinauer, A., Lauvset, S. K., and Middel- burg, J. J.: Calcium carbonate dissolution patterns in the ocean, Nat. Geosci., 14, 423-428, https://doi.org/10.1038/s41561-021- 00743-y, 2021. · DOI · Paper page
  141. Takeshita, Y., Jones, B. D., Johnson, K. S., Chavez, F. P., Rudnick, D. L., Blum, M., Conner, K., Jensen, S., Long, J. S., Maughan, T., Mertz, K. L., Sherman, J. T., and Warren, J. K.: Accurate pH and O 2 Measurements from Spray Underwater Gliders, J. Atmos. Ocean. Tech., 38, 181-195, https://doi.org/10.1175/JTECH-D- 20-0095.1, 2021. · DOI
  142. Taylor, J. R., Smith, K. M., and Vreugdenhil, C. A.: The influence of submesoscales and vertical mixing on the export of sinking tracers in Large-Eddy Simulations, J. Phys. Oceanogr., 50, 1319- 1339, https://doi.org/10.1175/JPO-D-19-0267.1, 2020. · DOI
  143. Teruzzi, A., Bolzon, G., Salon, S., Lazzari, P., Solidoro, C., and Cossarini, G.: Assimilation of coastal and open sea biogeochemical data to improve phytoplankton simula- tion in the Mediterranean Sea, Ocean Model., 132, 46-60, https://doi.org/10.1016/j.ocemod.2018.09.007, 2018. · DOI
  144. Thacker, W. C.: The role of the Hessian matrix in fitting mod- els to measurements, J. Geophys. Res.-Oceans, 95, 6177-6196, https://doi.org/10.1029/JC094iC05p06177, 1989. · DOI
  145. Thacker, W. C., Srinivasan, A., Iskandarani, M., Knio, O. M., and Le Hénaff, M.: Propagating boundary uncertainties us- ing polynomial expansions, Ocean Model., 43-44, 52-63, https://doi.org/10.1016/j.ocemod.2011.11.011, 2012. · DOI
  146. Turner, K. E., Smith, D. M., Katavouta, A., and Williams, R. G.: Reconstructing ocean carbon storage with CMIP6 Earth system models and synthetic Argo observations, Biogeosciences, 20, 1671-1690, https://doi.org/10.5194/bg-20-1671-2023, 2023. · DOI
  147. Verdy, A. and Mazloff, M. R.: A data assimilating model for esti- mating Southern Ocean biogeochemistry, J. Geophys. Res., 122, 6968-6988, https://doi.org/10.1002/2016JC012650, 2017. · DOI
  148. Waliser, D., Gleckler, P. J., Ferraro, R., Taylor, K. E., Ames, S., Biard, J., Bosilovich, M. G., Brown, O., Chepfer, H., Cinquini, L., Durack, P. J., Eyring, V., Mathieu, P.-P., Lee, T., Pinnock, S., Potter, G. L., Rixen, M., Saunders, R., Schulz, J., Thépaut, J.-N., and Tuma, M.: Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6, Geosci. Model Dev., 13, 2945- 2958, https://doi.org/10.5194/gmd-13-2945-2020, 2020. · DOI
  149. Wang, B., Fennel, K., Yu, L., and Gordon, C.: Assessing the value of biogeochemical Argo profiles versus ocean color observations for biogeochemical model optimization in the Gulf of Mexico, Biogeosciences, 17, 4059-4074, https://doi.org/10.5194/bg-17- 4059-2020, 2020. · DOI
  150. Wang, H., Pilcher, D. J., Kearney, K. A., Cross, J. N., Shugart, O. M., Eisaman, M. D., and Carter, B. R.: Simulated im- pact of ocean alkalinity enhancement on atmospheric CO 2 re- moval in the Bering Sea, Earths Future, 11, e2022EF002816, https://doi.org/10.1029/2022ef002816, 2023. · DOI
  151. Wang, Z. A., Sonnichsen, F. N., Bradley, A. M., Hoering, K. A., Lanagan, T. M., Chu, S. N., Hammar, T. R., and Camilli, R.: In situ sensor technology for simultaneous spec- trophotometric measurements of seawater total dissolved inor- ganic carbon and pH, Environ. Sci. Technol., 49, 4441-4449, https://doi.org/10.1021/es504893n, 2015. · DOI
  152. Wanninkhof, R.: Relationship between wind speed and gas ex- change over the ocean revisited, Limnol. Oceanogr.-Meth., 12, 351-362, https://doi.org/10.4319/lom.2014.12.351, 2014. · DOI
  153. 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 Cli- mate Model: Model Description, Climatology, and Applica- tions to Past, Present and Future Climates, Atmosphere-Ocean, 39, 361-428, https://doi.org/10.1080/07055900.2001.9649686, 2001 (code available at: https://perma.cc/8VUY-BHSP, last ac- cess: 15 November 2023). · DOI
  154. Whitt, D. B., Lévy, M., and Taylor, J. R.: Submesoscales enhance storm-driven vertical mixing of nutrients: insights from a biogeo- chemical large eddy simulation, J. Geophys. Res.-Oceans, 124, 8140-8165, https://doi.org/10.1029/2019JC015370, 2019. · DOI
  155. Wilcox, L. J., Allen, R. J., Samset, B. H., Bollasina, M. A., Grif- fiths, P. T., Keeble, J., Lund, M. T., Makkonen, R., Merikanto, J., O'Donnell, D., Paynter, D. J., Persad, G. G., Rumbold, S. T., Takemura, T., Tsigaridis, K., Undorf, S., and West- ervelt, D. M.: The Regional Aerosol Model Intercompari- son Project (RAMIP), Geosci. Model Dev., 16, 4451-4479, https://doi.org/10.5194/gmd-16-4451-2023, 2023. · DOI
  156. Yu, L., Fennel, K., Bertino, L., Gharamti, M. E., and Thompson, K. R.: Insights on multivariate updates of physical and biogeo- chemical ocean variables using an Ensemble Kalman Filter and an idealized model of upwelling, Ocean Model., 126, 13-28, https://doi.org/10.1016/j.ocemod.2018.04.005, 2018. · DOI

Cited by

Sorted by citations

Authors
Fennel, K., Long, M. C., Algar, C., Carter, B., Keller, D., Laurent, A., Mattern, J. P., Musgrave, R., Oschlies, A., Ostiguy, J., Palter, J. B., & Whitt, D. B.
Affiliations
  • Dalhousie University (CA)
  • NSF National Center for Atmospheric Research (US)
  • National Oceanic and Atmospheric Administration (US)
  • GEOMAR Helmholtz Centre for Ocean Research Kiel (DE)
  • University of California, Santa Cruz (US)
  • University of Rhode Island (US)
  • Ames Research Center (US)
Corresponding author
Fennel, Katja
ORCID
Venue
State of the Planet
Publisher
Copernicus GmbH
Published
2023-11-27
Volume
2-oae2023
Pages
1-29
ISSN
2752-0706 (ISSN-L)
DOI
10.5194/sp-2-oae2023-9-2023
OpenAlex
W4389056079
Cited by
64
References
5
Citations by year
2026: 17 · 2025: 23 · 2024: 16 · 2023: 8
FWCI
8.60
Type
journal article
Language
en
Open access
Licence
Locations
  • State of the Planet (publishedVersion, cc-by)
  • Helmholtz Centre for Ocean Research Kiel (GEOMAR) (acceptedVersion)
  • Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
Funders
  • ClimateWorks Foundation (22-0296)
  • Prince Albert II of Monaco Foundation (n/a)
  • Natural Sciences and Engineering Research Council of Canada (Discovery and Alliance Programs)
  • Canada Excellence Research Chairs, Government of Canada (n/a)
  • Ocean Acidification Program (NA19OAR0170357)
  • Earth Sciences Division (New Investigator Program)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Marine and coastal ecosystems
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Geoengineering
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
Keywords
ocean alkalinity enhancement, ocean alkalinity, carbon dioxide removal, ocean carbon uptake, biogeochemical modeling, model validation, data assimilation, observing system simulation experiments, observing system design, model intercomparison, uncertainty estimation, ecosystem impacts

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review