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    Assessment of skill and portability in regional marine biogeochemical models : role of multiple planktonic groups

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    Article (568.1Kb)
    Figure S1: The equations, state variables, parameter formulations and parameter values for Model 3. (241.2Kb)
    Figure S2: The equations for Model 4. (126.2Kb)
    Figure S3: The state variables, parameter formulations and parameter values for Model 4. (2.293Mb)
    Figure S4: The equations for Model 5. (27.42Kb)
    Figure S5: The equations, state variables, parameter formulations and parameter values for Model 8. (165.6Kb)
    Figure S6: The equations for Model 9. (71.73Kb)
    Figure S7: The parameter values used for Model 10. (3.308Mb)
    Figure S8: The equations for Model 11. (214.6Kb)
    Figure S9: The state variables and parameter formulations used for Model 11. (394.1Kb)
    Figure S10: The parameter values used for Model 11. (465.3Kb)
    Additional file information (2.778Kb)
    Text S1: The text describing Models 3, 4, 5, 8, 9, 10 and 11. (3.855Kb)
    Date
    2007-08-02
    Author
    Friedrichs, Marjorie A. M.  Concept link
    Dusenberry, Jeffrey A.  Concept link
    Anderson, Laurence A.  Concept link
    Armstrong, Robert A.  Concept link
    Chai, Fei  Concept link
    Christian, James R.  Concept link
    Doney, Scott C.  Concept link
    Dunne, John P.  Concept link
    Fujii, Masahiko  Concept link
    Hood, Raleigh R.  Concept link
    McGillicuddy, Dennis J.  Concept link
    Moore, J. Keith  Concept link
    Schartau, Markus  Concept link
    Spitz, Yvette H.  Concept link
    Wiggert, Jerry D.  Concept link
    Metadata
    Show full item record
    Citable URI
    https://hdl.handle.net/1912/3561
    As published
    https://doi.org/10.1029/2006JC003852
    DOI
    10.1029/2006JC003852
    Keyword
     Ecosystem model comparison; Biogeochemical data assimilation; Phytoplankton functional groups 
    Abstract
    Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.
    Description
    Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C08001, doi:10.1029/2006JC003852.
    Collections
    • Applied Ocean Physics and Engineering (AOP&E)
    • Marine Chemistry and Geochemistry (MC&G)
    Suggested Citation
    Journal of Geophysical Research 112 (2007): C08001
     

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