Ensemble Transform Kalman Filter-based ensemble perturbations in an operational global prediction system at NCEP

By Mozheng Wei, Z. Toth, R. Wobus, Yuejian Zhu, C. Bishop, Xuguang Wang. 2006

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The initial perturbations used for the operational global ensemble prediction system of the National Centers for Environmental Prediction are generated through the breeding method with a regional rescaling mechanism. Limitations of the system include the use of a climatologically fixed estimate of the analysis error variance and the lack of an orthogonalization in the breeding procedure. The Ensemble Transform Kalman Filter (ETKF) method is a natural extension of the concept of breeding and, as shown byWang and Bishop, can be used to generate ensemble perturbations that can potentially ameliorate these shortcomings. In the present paper, a spherical simplex 10-member ETKF ensemble, using the actual distribution and error characteristics of real-time observations and an innovation-based inflation, is tested and compared with a 5-pair breeding ensemble in an operational environment. The experimental results indicate only minor differences between the performances of the operational breeding and the experimental ETKF ensemble and only minor differences to Wang and Bishop’s earlier comparison studies. As for the ETKF method, the initial perturbation variance is found to respond to temporal changes in the observational network in the North Pacific. In other regions, however, 10 ETKF perturbations do not appear to be enough to distinguish spatial variations in observational network density. As expected, the whitening effect of the ETKF together with the use of the simplex algorithm that centres a set of quasi-orthogonal perturbations around the best analysis field leads to a significantly higher number of degrees of freedom as compared to the use of paired initial perturbations in operations. As a new result, the perturbations generated through the simplex method are also shown to exhibit a very high degree of consistency between initial analysis and short-range forecast perturbations, a feature that can be important in practical applications. Potential additional benefits of the ETKF and Ensemble Transform methods when using more ensemble members and a more appropriate inflation scheme will be explored in follow-up studies.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/d0e43623951bcdbb59e9cbaffa2002e098664aec

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Citations in the corpus

Initial perturbations based on the ensemble transform (ET) technique in the NCEP global operational forecast system (2008, methodology): “The research and experiments on using ET and ET with rescaling (ETR) for ensemble forecasts first started at NCEP before 2004, and the initial results were presented in the THORPEX Symposium in 2004 ( Wei et al., 2005a ).”
Ensemble forecasting (2008, methodology): “The ensemble transform Kalman filter technique has been compared with the bred vector method at NCEP for a 10-member ensemble [48].”
The MOGREPS short‐range ensemble prediction system (2008, methodology): “In previous studies (Wang et al., 2004; Wei et al., 2006), the similarity between the ETKF perturbations and bred perturbations has been noted.”
Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment (2017, methodology): “The forecast skill of the GEFS has been improved sig-niﬁcantly since then, beneﬁting from upgrades in ensemble initial perturbation generation (Wei et al. 2006, 2008), the inclusion of stochastic model perturbations (Hou et al. 2006), higher model resolution, and larger ensemble size, as well as…”