4D ensemble Kalman filtering for assimilation of asynchronous observations

T. Sauer, B. R. Hunt, J. A. Yorke, A. V. Zimin, E. Ott, Eric Kostelich, I. Szunyogh, G. Gyarmati, E. Kalnay, D. J. Patil

Research output: Contribution to journalConference articlepeer-review

Abstract

A 4-dimensional ensemble Kalman filter method (4DEnKF), which adapts ensemble Kalman filtering to the assimilation of observations that are asynchronous with the analysis cycle, is discussed. In the ideal case of linear dynamics between consecutive analyses, the algorithm is equivalent to Kalman filtering assimilation at each observation time. Tests of 4DEnKF on the Lorenz 40 variable model are conducted.

Original languageEnglish (US)
Pages (from-to)3075-3079
Number of pages5
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 '4D ensemble Kalman filtering for assimilation of asynchronous observations'. Together they form a unique fingerprint.

Cite this