HR: 0800h
AN: A31B-01    [Abstracts]
TI: Assimilation of satellite ocean chlorophyll data for biogeochemical state estimation - univariate and multivariate aspects
AU: * Nerger, L
EM: lnerger@gmao.gsfc.nasa.gov
AF: Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771, United States
AU: * Nerger, L
EM: lnerger@gmao.gsfc.nasa.gov
AF: Goddard Earth Sciences and Technology Center, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, United States
AU: Gregg, W W
EM: watson.gregg@nasa.gov
AF: Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Code 610.1, Greenbelt, MD 20771, United States
AB: Chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is assimilated into the three- dimensional global NASA Ocean Biogeochemical Model (NOBM) for the period 1998-2004. The ensemble-based SEIK filter is applied in a multivariate configuration. It is used here with a localized analysis and simplified by the use of a constant covariance matrix. In addition, an online bias estimation algorithm is applied. The multivariate assimilation updates the four phytoplankton groups of the model as well as nutrient fields. With assimilation, the chlorophyll estimates become superior to both the free-run model and SeaWiFS data. However, the results are less clear for the nutrients. We discuss the behavior and issues involved by the multivariate assimilation process.
DE: 4260 Ocean data assimilation and reanalysis (3225)
DE: 4805 Biogeochemical cycles, processes, and modeling (0412, 0414, 0793, 1615, 4912)
DE: 4845 Nutrients and nutrient cycling (0470, 1050)
SC: Atmospheric Sciences [A]
MN: 2007 Joint Assembly