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Can biogeochemical fluxes be recovered from nitrate and chlorophyll data? A case study assimilating data in the Northwestern Mediterranean Sea at the JGOFS-DYFAMED station
Faugeras, B.; Lévy, M.; Mémery, L.; Verron, J.; Blum, J.; Charpentier, I. (2003). Can biogeochemical fluxes be recovered from nitrate and chlorophyll data? A case study assimilating data in the Northwestern Mediterranean Sea at the JGOFS-DYFAMED station, in: Grégoire, M. et al. (Ed.) The use of data assimilation in coupled hydrodynamic, ecological and bio-geo-chemical models of the ocean. Selected papers from the 33rd International Liege Colloquium on Ocean Dynamics, held in Liege, Belgium on May 7-11th, 2001. Journal of Marine Systems, 40-41: pp. 99-125. dx.doi.org/10.1016/S0924-7963(03)00015-0
In: Grégoire, M. et al. (Ed.) (2003). The use of data assimilation in coupled hydrodynamic, ecological and bio-geo-chemical models of the ocean. Selected papers from the 33rd International Liege Colloquium on Ocean Dynamics, held in Liege, Belgium on May 7-11th, 2001. Journal of Marine Systems, 40-41. Elsevier: Amsterdam. 1-406 pp., more
In: Journal of Marine Systems. Elsevier: Tokyo; Oxford; New York; Amsterdam. ISSN 0924-7963, more
Peer reviewed article  

Also published as
  • Faugeras, B.; Lévy, M.; Mémery, L.; Verron, J.; Blum, J.; Charpentier, I. (2003). Can biogeochemical fluxes be recovered from nitrate and chlorophyll data? A case study assimilating data in the Northwestern Mediterranean Sea at the JGOFS-DYFAMED station. J. Mar. Syst. 40-41: 99-125. dx.doi.org/10.1016/S0924-7963(03)00015-0, more

Available in Authors 
Document type: Conference paper

Keywords
    Biogeochemical cycle; Models; Parameterization; Marine

Authors  Top 
  • Faugeras, B.
  • Lévy, M.
  • Mémery, L.
  • Verron, J.
  • Blum, J.
  • Charpentier, I.

Abstract
    One of the principal objectives of studying biogeochemical cycles is to obtain precise estimates of the main fluxes, such as total, new and export oceanic productions. Since models can incorporate the a priori knowledge of the most important processes, they are increasingly used for this purpose. However, biogeochemical models are characterized by a large number of poorly known parameters. Moreover, the available data are rather sparse in both time and space, and represent concentrations, not fluxes. Therefore, the major challenge is to constrain the relevant fluxes using information from a limited number of observations and from models incorporating poorly known internal parameters.

    The present study attempts to meet this challenge. In a 1D framework at the DYFAMED station (NW Mediterranean Sea), near-monthly nitrate and chlorophyll profiles and daily surface chlorophyll concentrations are assimilated in a coupled dynamical–biological model using the tangent linear and adjoint models. Following sensitivity analyses that show that some parameters cannot be recovered from the data set used, assimilation of observed 1997 data is performed. The first inversion considered clearly shows that, in agreement with previous studies, (1) the data impose a C/Chl ratio that varies with depth (i.e. light) and (2) the "initial" conditions (e.g. winter nitrate profile) strongly constrain the annual biogeochemical fluxes. After assimilation of the 1997 data, the agreement between the data and the model is quantitatively improved in 1995 and 1996, which can be considered a good validation of the methodology. However, the order of magnitude of the biogeochemical fluxes, and especially of the particulate export and regenerated production, are not correctly recovered. An analysis of the simulations shows that this result is associated with a strong decrease in zooplankton concentrations. An additional constraint of maintaining acceptable levels of zooplankton is therefore added. The results are improved, but remain unsatisfactory. A final inversion, which takes into account the a priori estimates of the major annual fluxes, is then performed. This shows that there is no inconsistency between the NO3 and chlorophyll data, the order of magnitude of the fluxes and the model. The work therefore demonstrates that recovering biogeochemical fluxes from available data of concentrations and stocks is not a straightforward exercise: the coverage and type of observations, and the nonlinearities of the biogeochemical model all contribute to this difficulty.


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