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gfdl's home page > gfdl on-line bibliography > 2003: Monthly Weather Review, 131(7), 1485-1490
Ensemble square root filters
| Tippett, M. K., J. L. Anderson, C. H. Bishop, and T. M. Hamill and J. S. Whitaker, 2003: Ensemble square root filters, Monthly Weather Review, 131(7), 1485-1490. |
| Abstract: Ensemble data assimilation methods assimilate observations using state-space estimation methods and low-rank representation of forecast and analysis error covariances. A key element of such methods is the transformation of the forecast ensemble into an analysis ensemble with appropriate statistics. This transformation may be performed stochastically by treating observations as random variables, or deterministically by requiring that the updated analysis perturbations satisfy the Kalman filter analysis error covariance equation. Deterministic analysis ensemble updates are implementations of Kalman square root filters. The nonuniqueness of the deterministic transformation used in square root Kalman filters provides a framework to compare three recently proposed ensemble data assimilation methods. |