Articles | Volume 14, issue 6
https://doi.org/10.5194/bg-14-1647-2017
https://doi.org/10.5194/bg-14-1647-2017
Reviews and syntheses
 | 
29 Mar 2017
Reviews and syntheses |  | 29 Mar 2017

Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling

Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies

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Cited articles

Acevedo-Trejos, E., Brandt, G., Bruggeman, J., and Merico, A.: Mechanisms shaping size structure and functional diversity of phytoplankton communities in the ocean, Scient. Rep., 5, 8918, https://doi.org/10.1038/srep08918, 2015.
Akaike, H.: Information theory and an extension of the maximum likelihood principle, in: Proceeding of the Second International Symposium on Information Theory, edited byL Petrov, B. N. and Caski, F., Akademiai Kiado, 267–281, 1973.
Aksnes, D. L. and Egge, J. K.: A theoretical model for nutrient uptake in phytoplankton, Mar. Ecol. Prog. Ser., 70, 65–72, 1991.
Allen, J. I., Eknes, M., and Evensen, G.: An Ensemble Kalman Filter with a complex marine ecosystem model: hindcasting phytoplankton in the Cretan Sea, Ann. Geophys., 21, 399–411, https://doi.org/10.5194/angeo-21-399-2003, 2003.
Anderson, T. R.: Plankton functional type modelling: running before we can walk?, J. Plankton Res., 27, 1073–1081, https://doi.org/10.1093/plankt/fbi076, 2005.
Short summary
Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
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