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| Titel |
Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks? |
| VerfasserIn |
U. Löptien, H. Dietze |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1812-0784
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| Digitales Dokument |
URL |
| Erschienen |
In: Ocean Science ; 11, no. 4 ; Nr. 11, no. 4 (2015-07-20), S.573-590 |
| Datensatznummer |
250117265
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| Publikation (Nr.) |
 copernicus.org/os-11-573-2015.pdf |
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| Zusammenfassung |
| In a changing climate, marine pelagic biogeochemistry may modulate the
atmospheric concentrations of climate-relevant species such as CO2 and
N2O. To date, projections rely on earth system models, featuring simple
pelagic biogeochemical model components, embedded into 3-D ocean circulation
models. Most of these biogeochemical model components rely on the hyperbolic
Michaelis–Menten (MM) formulation which specifies the limiting effect of
light and nutrients on carbon assimilation by autotrophic phytoplankton. The
respective MM constants, along with other model parameters, of 3-D coupled
biogeochemical ocean-circulation models are usually tuned; the parameters are
changed until a "reasonable" similarity to observed standing stocks is
achieved.
Here, we explore with twin experiments (or synthetic "observations") the
demands on observations that allow for a more objective estimation of model
parameters. We start with parameter retrieval experiments based on
"perfect" (synthetic) observations which we distort, step by step, by
low-frequency noise to approach realistic conditions. Finally, we confirm our
findings with real-world observations. In summary, we find that MM constants
are especially hard to constrain because even modest noise (10 %) inherent
to observations may hinder the parameter retrieval already. This is of
concern since the MM parameters are key to the model's sensitivity to
anticipated changes in the external conditions. Furthermore, we illustrate
problems caused by high-order parameter dependencies when parameter
estimation is based on sparse observations of standing stocks. Somewhat
counter to intuition, we find that more observational data can sometimes
degrade the ability to constrain certain parameters. |
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