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A data assimilation technique applied to estimate parameters for the NEMURO marine ecosystem model
Kuroda, H.; Kishi, M.J. (2004). A data assimilation technique applied to estimate parameters for the NEMURO marine ecosystem model. Ecol. Model. 172(1): 69-85
In: Ecological Modelling. Elsevier: Amsterdam; Lausanne; New York; Oxford; Shannon; Tokyo. ISSN 0304-3800, more
Peer reviewed article  

Available in Authors 

Keyword
    Marine

Authors  Top 
  • Kuroda, H.
  • Kishi, M.J.

Abstract
    We have applied a data assimilation technique to determine biological parameters in the PICES (North Pacific Marine ScienceOrganization) proto type lower trophic level model (NEMURO). North Pacific Ecosystem Model for Understanding RegionalOceanography (NEMURO) has about 80 biological parameters and 11 initial values. We used a sensitivity analysis to chooseeight parameters which mostly impacted the simulated values of interest. These parameters were selected as control variablesfor the data assimilation. Using an adjoint method, we assimilated biological and chemical data from Stn.A7 (off Hokkaido,Japan) into the model. Twin experiments were conducted to determine whether the data constrain those eight control variables.Model output, using optimum parameter values determined by the assimilation, agreed with the data better than those obtainedwith the first guess parameter values. But some problems still remain even in the simulations using the optimum parameters:namely a large discrepancy is seen between the simulation and data for small zooplankton and the simulated bloom of largephytoplankton that is too large.

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