Use of SeaWiFS data for light availability and parameter estimation of a phytoplankton production model of the Bay of Biscay

Type Article
Date 2007-03
Language English
Author(s) Huret MartinORCID1, Gohin Francis1, Delmas Daniel2, Lunven Michel1, Garcon Véronique3
Affiliation(s) 1 : IFREMER, Ctr Brest, F-29280 Plouzane, France.
2 : IFREMER, CREMA LHoumeau, CNRS, F-17137 LHoumeau, France.
3 : CNRS, LEGOS, F-31401 Toulouse, France.
Source Journal of Marine Systems (0924-7963) (Elsevier), 2007-03 , Vol. 65 , N. 1-4 , P. 509-531
DOI 10.1016/j.jmarsys.2005.07.007
WOS© Times Cited 35
Keyword(s) Bay of Biscay, SeaWiFS, Parameter estimation, Chlorophyll, Suspended Particulate Matter, Physical biogeochemical modelling
Abstract Processing SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data provides useful information for the observation and modelling of the phytoplankton production of the Bay of Biscay. Empirical algorithms allow the retrieval of chlorophyll a and non-living Suspended Particulate Matter (SPM) concentrations. These data are used to constrain a coupled 3D physical-biogeochemical model of the Bay of Biscay continental shelf Two issues are investigated, depending on the variable used, to constrain the winter to spring phytoplankton production for the year 2001. First, SPM data is used as forcing data to correct the corresponding state variable of our model. This allows the realistic simulation of the light limited bloom at the end of February 2001, as observed with SeaWiFS chlorophyll a images and from the NUTRIGAS field cruise. Second, chlorophyll a data is used for parameter estimation of the biogeochemical model. The ability of assimilating these data is tested to improve the simulation of strong blooms observed in late May 2001 in the Loire and Gironde plumes. A global optimization method (Evolutive Strategies) is adapted to the complete 3-D coupled model, in order to find the best set of parameters. The hydrological conditions during the bloom can be validated with data from the PELO I field cruise. After selection of the most sensitive parameters, the method is tested with twin experiments. Then, the use of real SeaWiFS data reduces the model/data misfit by a factor of two, improving the simulation of bloom intensities and extensions. The sets of parameters retrieved in each plume are discussed.
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