State estimation in an ocean-biogeochemical model by assimilation of satellite ocean chlorophyll data


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Lars.Nerger [ at ] awi.de

Abstract

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. The assimilationis performed by a multivariate configuration of the SEIK filter whichis an ensemble-based Kalman filter scheme. The filter is simplified bythe use of a static error covariance matrix. It operates with alocalized analysis and is amended by an online bias correction scheme.The multivariate assimilation is applied to update the fourphytoplankton groups of the model as well as the simulated nutrientfields. The chlorophyll estimates of the model can be improved by theassimilation such that they outperform the assimilated SeaWiFS data.However, the results are less clear for the nutrients where the biasestimation is required for stability but reduces the assimilationimprovements.



Item Type
Conference (Poster)
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Not peer-reviewed
Publication Status
Published
Event Details
Workshop ``Data Assimilation in Support of Coastal Ocean Observing Systems'', Oregon State University, Corvallis, OR, April 3--5.
Eprint ID
16648
Cite as
Nerger, L. and Gregg, W. W. (2007): State estimation in an ocean-biogeochemical model by assimilation of satellite ocean chlorophyll data , Workshop ``Data Assimilation in Support of Coastal Ocean Observing Systems'', Oregon State University, Corvallis, OR, April 3--5 .


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