Article Type:
Research Article

Ensemble Square Root Filters

Michael K. Tippett International Research Institute for Climate Prediction, Palisades, New York

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Jeffrey L. Anderson GFDL, Princeton, New Jersey

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Craig H. Bishop Naval Research Laboratory, Monterey, California

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Thomas M. Hamill NOAA–CIRES Climate Diagnostics Center, Boulder, Colorado

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Jeffrey S. Whitaker NOAA–CIRES Climate Diagnostics Center, Boulder, Colorado

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Print Publication:
01 Jul 2003
DOI:
https://doi.org/10.1175/1520-0493(2003)131<1485:ESRF>2.0.CO;2
Page(s):
1485–1490
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Abstract

Ensemble data assimilation methods assimilate observations using state-space estimation methods and low-rank representations 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.

Corresponding author address: Michael K. Tippett, IRI/LDEO, 223 Monell, P.O. Box 1000/61 Rt. 9W, Palisades, NY 10964-8000. Email: tippett@iri.columbia.edu

Abstract

Ensemble data assimilation methods assimilate observations using state-space estimation methods and low-rank representations 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.

Corresponding author address: Michael K. Tippett, IRI/LDEO, 223 Monell, P.O. Box 1000/61 Rt. 9W, Palisades, NY 10964-8000. Email: tippett@iri.columbia.edu

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