Ensemble-based data assimilation at a coastline

Altug Aksoy, Fuqing Zhang, John W. Nielsen-Gammon, Craig Epifanio, Chris Snyder

Research output: Contribution to journalConference article

Abstract

The potential of the Ensemble Kalman filter in the area of model error estimation and reduction in a sea-breeze environment was analyzed. The test was performed after a 12-hour model run using 20 ensemble members and simulated buoyancy observations placed at 20km spacing in the horizontal and 250m in the vertical. The results show that some noise is introduced at the surface, especially around the sea-breeze front where phase difference between the mean forecast field and the truth field is most pronounced. It was suggested that, although this noise does not influence the domain-wide performance of the filter, it does introduce some unbalanced structure.

Original languageEnglish (US)
Pages (from-to)3031-3038
Number of pages8
JournalBulletin of the American Meteorological Society
StatePublished - Jun 1 2004
EventCombined Preprints: 84th American Meteorological Society (AMS) Annual Meeting - Seattle, WA., United States
Duration: Jan 11 2004Jan 15 2004

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All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Aksoy, A., Zhang, F., Nielsen-Gammon, J. W., Epifanio, C., & Snyder, C. (2004). Ensemble-based data assimilation at a coastline. Bulletin of the American Meteorological Society, 3031-3038.