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Description

The Ensemble Kalman filter uses the evolving spread of an ensemble of ocean states to estimate the evolving multivariate error statistics. A major improvement in the MvOI and EnKF has been the introduction of an algorithm to filter spurious large lag information from the background error covariances due to small ensemble sizes. In the filtering algorithm, documented in Keppenne and Rienecker (2001), the resulting error covariances have compact support.

Latest Experiments
Comparisons with the EnKF and UOI

Recent Publications

Error Covariance Modeling in the GMAO Ocean Ensemble Kalman Filter (htm)
Ensemble Data Assimilation and its Impact on Seasonal Hindcast Skill (ppt)
Assimilation of Temperature, Salinity, and Sea Surface Height Data into the GMAO Ensemble Kalman Filter and its Impact on Seasonal Hindcast Skill (pdf)