Articles | Volume 20, issue 18
https://doi.org/10.5194/bg-20-3717-2023
https://doi.org/10.5194/bg-20-3717-2023
Research article
 | 
15 Sep 2023
Research article |  | 15 Sep 2023

Alkalinity biases in CMIP6 Earth system models and implications for simulated CO2 drawdown via artificial alkalinity enhancement

Claudia Hinrichs, Peter Köhler, Christoph Völker, and Judith Hauck

Data sets

CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 CMIP historical T. Ziehn, M. Chamberlain, A. Lenton, R. Law, R. Bodman, M. Dix, Y. Wang, P. Dobrohotoff, J. Srbinovsky, L. Stevens, P. Vohralik, C. Mackallah, A. Sullivan, S. O’Farrell, and K. Druken https://doi.org/10.22033/ESGF/CMIP6.4272

CCCma CanESM5 model output prepared for CMIP6 CMIP historical N. C. Swart, J. N. S. Cole, V. V. Kharin, M. Lazare, J. F. Scinocca, N. P. Gillett, J. Anstey, V. Arora, J. R. Christian, Y. Jiao, W. G. Lee, F. Majaess, O. A. Saenko, C. Seiler, C. Seinen, A. Shao, L. Solheim, K. von Salzen, D. Yang, B. Winter, and M. Sigmond https://doi.org/10.22033/ESGF/CMIP6.3610

NCAR CESM2 model output prepared for CMIP6 CMIP historical G. Danabasoglu https://doi.org/10.22033/ESGF/CMIP6.7627

NCAR CESM2-WACCM model output prepared for CMIP6 CMIP historical G. Danabasoglu https://doi.org/10.22033/ESGF/CMIP6.10071

CNRM-CERFACS CNRM-ESM2-1 model output pre- pared for CMIP6 CMIP historical R. Seferian https://doi.org/10.22033/ESGF/CMIP6.4068

NOAA-GFDL GFDL-CM4 model output historical H. Guo, J. G. John, C. Blanton, C. McHugh, S. Nikonov, A. Radhakrishnan, K. Rand, N. T. Zadeh, V. Balaji, J. Durachta, C. Dupuis, R. Menzel, T. Robinson, S. Underwood, H. Vahlenkamp, M. Bushuk, K. A. Dunne, R. Dussin, P. P. G. Gauthier, P. Ginoux, S. M. Griffies, R. Hallberg, M. Harrison, W. Hurlin, P. Lin, S. Malyshev, V. Naik, F. Paulot, D. J. Paynter, J. Ploshay, B. G. Reichl, D. M. Schwarzkopf, C. J. Seman, A. Shao, L. Silvers, B. Wyman, X. Yan, Y. Zeng, A. Adcroft, J. P. Dunne, I. M. Held, J. P. Krasting, L. W. Horowitz, P. C. D. Milly, E. Shevliakova, M. Winton, M. Zhao, and R. Zhang https://doi.org/10.22033/ESGF/CMIP6.8594

NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP historical J. P. Krasting, J. G. John, C. Blanton, C. McHugh, S. Nikonov, A. Radhakrishnan, K. Rand, N. T. Zadeh, V. Balaji, J. Durachta, C. Dupuis, R. Menzel, T. Robinson, S. Underwood, H. Vahlenkamp, K. A. Dunne, P. P. G. Gauthier, P. Ginoux, S. M. Griffies, R. Hallberg, M. Harrison, W. Hurlin, S. Malyshev, V. Naik, F. Paulot, D. J. Paynter, J. Ploshay, B. G. Reichl, D. M. Schwarzkopf, C. J. Seman, L. Silvers, B. Wyman, Y. Zeng, A. Adcroft, J. P. Dunne, R. Dussin, H. Guo, J. He, I. M. Held, L. W. Horowitz, P. Lin, P. C. D. Milly, E. Shevliakova, C. Stock, M. Winton, A. T. Wittenberg, Y. Xie, and M. Zhao https://doi.org/10.22033/ESGF/CMIP6.8597

IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP historical O. Boucher, S. Denvil, G. Levavasseur, A. Cozic, A. Caubel, M.-A. Foujols, Y. Meurdesoif, P. Cadule, M. Devilliers, J. Ghattas, N. Lebas, T. Lurton, L. Mellul, I. Musat, J. Mignot, and F. Cheruy https://doi.org/10.22033/ESGF/CMIP6.5195

MPI-M MPI-ESM1.2-HR model output prepared 85 for CMIP6 CMIP historical J. Jungclaus, M. Bittner, K.-H. Wieners, F. Wachsmann, M. Schupfner, S. Legutke, M. Giorgetta, C. Reick, V. Gayler, H. Haak, P. de Vrese, T. Raddatz, M. Esch, T. Mauritsen, J.-S. von Storch, J. Behrens, V. Brovkin, M. Claussen, T. Crueger, I. Fast, S. Fiedler, S. Hagemann, C. Hohenegger, T. Jahns, S. Kloster, S. Kinne, G. Lasslop, L. Kornblueh, J. Marotzke, D. Matei, K. Meraner, U. Mikolajewicz, K. Modali, W. Müller, J. Nabel, D. Notz, K. Peters-von Gehlen, R. Pincus, H. Pohlmann, J. Pongratz, S. Rast, H. Schmidt, R. Schnur, U. Schulzweida, K. Six, B. Stevens, A. Voigt, and E. Roeckner https://doi.org/10.22033/ESGF/CMIP6.6594

MPI-M MPI-ESM1.2-LR model output prepared for CMIP6 CMIP historical Wieners, K.-H., Giorgetta, M., Jungclaus, J., Reick, C., Esch, M., Bittner, M., Legutke, S., Schupfner, M., Wachsmann, F., Gayler, V., Haak, H., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Behrens, J., Brovkin, V., Claussen, M., Crueger, T., Fast, I., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kloster, S., Kinne, S., Lasslop, G., Kornblueh, L., Marotzke, J., Matei, D., Meraner, K., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Peters-von Gehlen, K., Pincus, R., Pohlmann, H., Pongratz, J., Rast, S., Schmidt, H., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Voigt, A., and Roeckner, E. https://doi.org/10.22033/ESGF/CMIP6.6595

MRI MRI-ESM2.0 model output prepared for15 CMIP6 CMIP historical S. Yukimoto, T. Koshiro, H. Kawai, N. Oshima, K. Yoshida, S. Urakawa, H. Tsujino, M. Deushi, T. Tanaka, M. Hosaka, H. Yoshimura, E. Shindo, R. Mizuta, M. Ishii, A. Obata, and Y. Adachi https://doi.org/10.22033/ESGF/CMIP6.6842

NCC NorESM2-LM model output prepared for CMIP6 CMIP historical Ø. Seland, M. Bentsen, D. J. L. Oliviè, T. Toniazzo, A. Gjermundsen, L. S. Graff, J. B. Debernard, A. K. Gupta, Y. He, A. Kirkevåg, J. Schwinger, J. Tjiputra, K. S. Aas, I. Bethke, Y. Fan, J. Griesfeller, A. Grini, C. Guo, M. Ilicak, I. H. H. Karset, O. A. Landgren, J. Liakka, K. O. Moseid, A. Nummelin, C. Spensberger, H. Tang, Z. Zhang, C. Heinze, T. Iversen, and M. Schulz https://doi.org/10.22033/ESGF/CMIP6.8036

NCC NorESM2-MM model output prepared for CMIP6 CMIP historical M. Bentsen, D. J. L. Oliviè, Ø. Seland, T. Toniazzo, A. Gjermundsen, L. S. Graff, J. B. Debernard, A. K. Gupta, Y. He, A. Kirkevåg, J. Schwinger, J. Tjiputra, K. S. Aas, I. Bethke, Y. Fan, J. Griesfeller, A. Grini, C. Guo, M. Ilicak, I. H. H. Karset, O. A. Landgren, J. Liakka, K. O. Moseid, A. Nummelin, C. Spensberger, H. Tang, Z. Zhang, C. Heinze, T. Iversen, and M. Schulz https://doi.org/10.22033/ESGF/CMIP6.8040

MOHC UKESM1.0-LL model output prepared for CMIP6 CMIP historical Y. Tang, S. Rumbold, R. Ellis, D. Kelley, J. Mulcahy, A. Sellar, J. Walton, and C. Jones https://doi.org/10.22033/ESGF/CMIP6.6113

Model code and software

Program Developed for CO2 System Calculations E. R. Lewis and D. W. R. Wallace https://doi.org/10.15485/1464255

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Short summary
This study evaluated the alkalinity distribution in 14 climate models and found that most models underestimate alkalinity at the surface and overestimate it in the deeper ocean. It highlights the need for better understanding and quantification of processes driving alkalinity distribution and calcium carbonate dissolution and the importance of accounting for biases in model results when evaluating potential ocean alkalinity enhancement experiments.
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