Articles | Volume 15, issue 22
Geosci. Model Dev., 15, 8473–8540, 2022
https://doi.org/10.5194/gmd-15-8473-2022
Geosci. Model Dev., 15, 8473–8540, 2022
https://doi.org/10.5194/gmd-15-8473-2022
Model description paper
22 Nov 2022
Model description paper | 22 Nov 2022

Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates

Thomas Neumann et al.

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Cited articles

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. a
Bakker, D. C. E., Alin, S. R., Becker, M., Bittig, H. C., Castaño-Primo, R., Feely, R. A., Gkritzalis, T., Kadono, K., Kozyr, A., Lauvset, S. K., Metzl, N., Munro, D. R., Nakaoka, S., Nojiri, Y., O'Brien, K. M., Olsen, A., Pfeil, B., Pierrot, D., Steinhoff, T., Sullivan, K. F., Sutton, A. J., Sweeney, C., Tilbrook, B., Wada, C., Wanninkhof, R., Willstrand W., Anna, A., John, A., L. B., Bates, N., Beatty, C. M., Burger, E. F., Cai, W.-J., Cosca, C. E., Corredor, J. E., Cronin, M., Cross, J. N., De Carlo, E. H., DeGrandpre, M. D., Emerson, S., Enright, M. P., Enyo, K., Evans, W., Frangoulis, C., Fransson, A., García-Ibáñez, M. I., Gehrung, M., Giannoudi, L., Glockzin, M., Hales, B., Howden, S. D., Hunt, C. W., Ibánhez, J. S. P., Jones, S. D., Kamb, L., Körtzinger, A., Landa, C. S., Landschützer, P., Lefèvre, N., Lo Monaco, C., Macovei, V. A., Maenner Jones, S., Meinig, C., Millero, F. J., Monacci, N. M., Mordy, C., Morell, J. M., Murata, A., Musielewicz, S., Neill, C., Newberger, T., Nomura, D., Ohman, M., Ono, T., Passmore, A., Petersen, W., Petihakis, G., Perivoliotis, L., Plueddemann, A. J., Rehder, G., Reynaud, T., Rodriguez, C., Ross, A. C., Rutgersson, A., Sabine, C. L., Salisbury, J. E., Schlitzer, R., Send, U., Skjelvan, I., Stamataki, N., Sutherland, S. C., Sweeney, C., Tadokoro, K., Tanhua, T., Telszewski, M., Trull, T., Vandemark, D., van Ooijen, E., Voynova, Y. G., Wang, H., Weller, R. A., Whitehead, C., and Wilson, D.: Surface Ocean CO2 Atlas Database Version 2022 (SOCATv2022) (NCEI Accession 0253659), NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/1h9f-nb73, 2022. a
Carlson, C. A. and Hansell, D. A.: Chapter 3 – DOM Sources, Sinks, Reactivity, and Budgets, in: Biogeochemistry of Marine Dissolved Organic Matter, 2nd edn., edited by: Carlson, D. A. and Hansell, C. A., Academic Press, Boston, 65–126, https://doi.org/10.1016/B978-0-12-405940-5.00003-0, 2015. a, b
Carlson, C. A., Ducklow, H. W., Hansell, D. A., and Smith Jr., W. O.: Organic carbon partitioning during spring phytoplankton blooms in the Ross Sea polynya and the Sargasso Sea, Limnol. Oceanogr., 43, 375–386, https://doi.org/10.4319/lo.1998.43.3.0375, 1998. a
Chien, C.-T., Pahlow, M., Schartau, M., and Oschlies, A.: Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration, Geosci. Model Dev., 13, 4691–4712, https://doi.org/10.5194/gmd-13-4691-2020, 2020. a
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Short summary
Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.