Assimilation of Ocean Colour Data Into a Biochemical Model of the North Atlantic Part 1. Data Assimilation Experiments

An advanced multivariate sequential data assimilation method, the ensemble Kalman filter (EnKF), has been investigated with a three-dimensional biochemical model of the North Atlantic, utilizing real chlorophyll data from the from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The approach cho...

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Bibliographic Details
Main Authors: L. -j. Natvik, G. Evensen
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2003
Subjects:
Ensemble kalman filter
Assimilation
North Atlantic
Biogeochemistry
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.9577
http://www.nersc.no/~geir/EnKF/Publications/nat03a.pdf
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Summary:An advanced multivariate sequential data assimilation method, the ensemble Kalman filter (EnKF), has been investigated with a three-dimensional biochemical model of the North Atlantic, utilizing real chlorophyll data from the from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The approach chosen here differs significantly from conventional parameter estimation techniques. We keep the parameters fixed, and instead update the actual model state, allowing for unknown errors in the dynamical formulation. In the ensemble Kalman filter, estimates of the true dynamical error covariances are provided from an ensemble of model states.

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