Assimilation of satellite ocean chlorophyll data for biogeochemical state estimation - univariate and multivariate aspects
Chlorophyll data from the Sea-viewing Wide Field-of-view Sensor(SeaWiFS) is assimilated into the three-dimensional global NASA OceanBiogeochemical Model (NOBM) for the period 1998-2004. Theensemble-based SEIK filter is applied in a multivariateconfiguration. It is used here with a localized analysis andsimplified by the use of a constant covariance matrix. In addition, anonline bias estimation algorithm is applied. The multivariateassimilation updates the four phytoplankton groups of the model aswell as nutrient fields. With assimilation, the chlorophyll estimatesbecome superior to both the free-run model and SeaWiFS data. However,the results are less clear for the nutrients. We discuss the behaviorand issues involved by the multivariate assimilation process.