Ensemble data assimilation simulation experiments for the coastal ocean: impact of different observed variables

Author: Ross N. Hoffman, Rui M. Ponte, Sergey Vinogradov, E.J. Kostelich, A.F. Blumberg and I. Szunyogh
Date: 
July 7, 2008 - July 11, 2008
Type: 
Presentation
Venue: 
Geoscience and Remote Sensing Symposium, 2008
Citation: 

Hoffman, R., R. Ponte, E. Kostelich, A. Blumberg, I. Szunyogh, and S. Vinogradov, 2008. Ensemble data assimilation simulation experiments for the coastal ocean: impact of different observed variables. 28th IEEE Geoscience and Remote Sensing Society Annual Symposium, Boston, July 2008.

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.