Ensemble-based data assimilation

Fuqing Zhang, Chris Snyder

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

On 10-12 April 2006, researchers assembled at Marble Falls, Texas, to discuss advances in ensemble-based data assimilation for state and parameter estimation in numerical weather prediction models ranging from convective to global in scale. Participants agreed that the Ensemble Kalman filter (EnKF) is a maturing assimilation technique for numerical weather prediction (NWP) across a range of scales. Beyond the evident scientific progress, the workshop was also remarkable for the breadth of applications and forecast models considered and because all of the EnKF systems discussed at the workshop were developed by small research groups.

Original languageEnglish (US)
Pages (from-to)565-568
Number of pages4
JournalBulletin of the American Meteorological Society
Volume88
Issue number4
DOIs
StatePublished - Apr 1 2007

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Kalman filter
data assimilation
weather
prediction
marble
parameter estimation
assimilation
forecast

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Zhang, Fuqing ; Snyder, Chris. / Ensemble-based data assimilation. In: Bulletin of the American Meteorological Society. 2007 ; Vol. 88, No. 4. pp. 565-568.
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Ensemble-based data assimilation. / Zhang, Fuqing; Snyder, Chris.

In: Bulletin of the American Meteorological Society, Vol. 88, No. 4, 01.04.2007, p. 565-568.

Research output: Contribution to journalArticle

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