DocumentCode
2698135
Title
Ensemble Data Assimilation Simulation Experiments for the Coastal Ocean: Impact of Different Observed Variables
Author
Hoffman, R. ; Ponte, R.M. ; Kostelich, E. ; Blumberg, A. ; Szunyogh, I. ; Vinogradov, S.V.
Author_Institution
Atmos. & Environ. Res., Inc., Lexington, MA
Volume
5
fYear
2008
fDate
7-11 July 2008
Abstract
A coastal ocean data assimilation system tested in simulation earlier is examined for sensitivity to the different types of observational data. The system couples an advanced ensemble Kalman filter algorithm to a detailed and sophisticated primitive equations coastal ocean model. It is found that assimilating only one type of data, say temperature, greatly slows down the approach to asymptotic behavior of the analysis of the other variables. Assimilating temperature alone does not help to infer salinity and vice versa.
Keywords
Kalman filters; data assimilation; geophysical signal processing; ocean temperature; oceanographic techniques; seawater; sensitivity analysis; ensemble Kalman filter algorithm; ensemble data assimilation simulation; ocean temperature; primitive equations coastal ocean model; salinity; sensitivity analysis; Atmospheric modeling; Data assimilation; Error analysis; Filtering; Kalman filters; Mathematics; Ocean temperature; Sea measurements; Sea surface; Statistics; Kalman filtering; coastal ocean model; data assimilation; data impact;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location
Boston, MA
Print_ISBN
978-1-4244-2807-6
Electronic_ISBN
978-1-4244-2808-3
Type
conf
DOI
10.1109/IGARSS.2008.4780123
Filename
4780123
Link To Document