Articles | Volume 13, issue 10
https://doi.org/10.5194/gmd-13-4663-2020
https://doi.org/10.5194/gmd-13-4663-2020
Model description paper
 | 
02 Oct 2020
Model description paper |  | 02 Oct 2020

Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 1: Implementation and model behaviour

Markus Pahlow, Chia-Te Chien, Lionel A. Arteaga, and Andreas Oschlies

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Cited articles

Ågren, G. I.: The C : N : P stoichiometry of autotrophs – theory and observations, Ecol. Lett., 7, 185–191, https://doi.org/10.1111/j.1461-0248.2004.00567.x, 2004. a
Anderson, L. A. and Sarmiento, J. L.: Redfield ratios of remineralization determined by nutrient data analysis, Global Biogeochem. Cycles, 8, 65–80, https://doi.org/10.1029/93GB03318, 1994. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a
Arteaga, L., Pahlow, M., and Oschlies, A.: Global patterns of phytoplankton nutrient and light colimitation inferred from an optimality-based model, Global Biogeochem. Cycles, 28, 648–661, https://doi.org/10.1002/2013GB004668, 2014. a
Arteaga, L., Pahlow, M., and Oschlies, A.: Modelled Chl:C ratio and derived estimates of phytoplankton carbon biomass and its contribution to total particulate organic carbon in the global surface ocean, Global Biogeochem. Cycles, 30, 1791–1810, https://doi.org/10.1002/2016GB005458, 2016. a, b
Short summary
The stoichiometry of marine biotic processes is important for the regulation of atmospheric CO2 and hence the global climate. We replace a simplistic, fixed-stoichiometry plankton module in an Earth system model with an optimal-regulation model with variable stoichiometry. Our model compares better to the observed carbon transfer from the surface to depth and surface nutrient distributions. This work could aid our ability to describe and project the role of marine ecosystems in the Earth system.