Multivariate Assimilation of Satellite Ocean Chlorophyll Data Into a Global Model - Prospects and Challenges


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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 using amultivariate configuration of the SEIK filter which is anensemble Kalman filter scheme. The SEIK filter is applied here with alocalized analysis and simplified by the use of a constant covariancematrix. The multivariate assimilation is applied to update thefour phytoplankton groups of the model as well as the simulatednutrient fields. While the chlorophyll estimates of the model can besignificantly improved by the assimilation, the results are less clearfor the nutrients. We discuss the behavior of the multivariateassimilation process and the challenges involved by it.



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Conference (Poster)
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Not peer-reviewed
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Published
Event Details
AGU Fall Meeting, San Francisco, CA, USA, December 11-15.
Eprint ID
16086
Cite as
Nerger, L. and Gregg, W. W. (2006): Multivariate Assimilation of Satellite Ocean Chlorophyll Data Into a Global Model - Prospects and Challenges , AGU Fall Meeting, San Francisco, CA, USA, December 11-15 .


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