A local ensemble kalman filter for the NCEP GFS model

Istvan Szunyogh, Eric Kostelich, Gyorgyi Gyarmati, Brian R. Hunt, Edward Ott, Aleksey V. Zimin, Eugenia Kalnay, Dhanurjay Patil, James A. Yorke

Research output: Contribution to journalConference article

1 Scopus citations

Abstract

This paper outlines the basic concept and mathematical formulation of the Local Ensemble Kalman Filter (LEKF, Ott et al. 2002 and 2003) data assimilation scheme. Some important properties of the scheme are illustrated by numerical experiments with the Lorenz-96 model. Initial implementations of the LEKF on the National Centers for Environmental Prediction Global Forecast System (NCEP GFS) are discussed. Tests of these implementations under the perfect model hypothesis are conducted.

Original languageEnglish (US)
Pages (from-to)67-77
Number of pages11
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

ASJC Scopus subject areas

  • Atmospheric Science

Fingerprint Dive into the research topics of 'A local ensemble kalman filter for the NCEP GFS model'. Together they form a unique fingerprint.

  • Cite this

    Szunyogh, I., Kostelich, E., Gyarmati, G., Hunt, B. R., Ott, E., Zimin, A. V., Kalnay, E., Patil, D., & Yorke, J. A. (2004). A local ensemble kalman filter for the NCEP GFS model. Bulletin of the American Meteorological Society, 67-77.