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

R. Hoffman, R. M. Ponte, Eric Kostelich, A. Blumberg, I. Szunyogh, S. V. Vinogradov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PagesV441-V444
Edition1
DOIs
StatePublished - Dec 1 2008
Event2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings - Boston, MA, United States
Duration: Jul 6 2008Jul 11 2008

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Number1
Volume5

Other

Other2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Country/TerritoryUnited States
CityBoston, MA
Period7/6/087/11/08

Keywords

  • Coastal ocean model
  • Kalman filtering
  • data assimilation
  • data impact

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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