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Implications of the form of the ensemble transformation in the ensemble square root filters

Citation

Sakov, P and Oke, P and Corney, SP, Implications of the form of the ensemble transformation in the ensemble square root filters, Monthly Weather Review, 136, (3) pp. 1042-1053. ISSN 0027-0644 (2008) [Refereed Article]

DOI: doi:10.1175/2007MWR2021.1

Abstract

This paper considers implications of different forms of the ensemble transformation in the ensemble square root filters (ESRFs) for the performance of ESRF-based data assimilation systems. It highlights the importance of using mean-preserving solutions for the ensemble transform matrix (ETM). The paper shows that an arbitrary mean-preserving ETM can be represented as a product of the symmetric solution and an orthonormal mean-preserving matrix. The paper also introduces a new flavor of ESRF, referred to as ESRF with mean-preserving random rotations. To investigate the performance of different solutions for the ETM in ESRFs, experiments with two small models are conducted. In these experiments, the performances of two mean-preserving solutions, two non-mean-preserving solutions, and a traditional ensemble Kalman filter with perturbed observations are compared. The experiments show a significantly better performance of the mean-preserving solutions for the ETM in ESRFs compared to non-mean-preserving solutions. They also show that applying the mean-preserving random rotations prevents the buildup of ensemble outliers in ESRF-based data assimilation systems

Item Details

Item Type:Refereed Article
Research Division:Earth Sciences
Research Group:Atmospheric Sciences
Research Field:Atmospheric Sciences not elsewhere classified
Objective Division:Environment
Objective Group:Atmosphere and Weather
Objective Field:Weather
Author:Oke, P (Dr Peter Oke)
Author:Corney, SP (Dr Stuart Corney)
ID Code:71440
Year Published:2008
Web of Science® Times Cited:81
Deposited By:Research Division
Deposited On:2011-07-19
Last Modified:2011-07-19
Downloads:0

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