A Hybrid Ensemble Kalman Filter to Mitigate Non-Gaussianity in Nonlinear Data Assimilation
Author:
Affiliation:
1. Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan
Publisher
Meteorological Society of Japan
Link
https://www.jstage.jst.go.jp/article/jmsj/102/5/102_2024-027/_pdf
Reference46 articles.
1. Amezcua, J., K. Ide, C. H. Bishop, and E. Kalnay, 2012: Ensemble clustering in deterministic ensemble Kalman filters. Tellus A, 64, 18039, doi: 10.3402/tellusa.v64i0.18039.
2. Anderson, J. L., 2001: An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev., 129, 2884–2903.
3. Anderson, J. L., 2010: A non-Gaussian ensemble filter update for data assimilation. Mon. Wea. Rev., 138, 4186–4198.
4. Bishop, C. H., B. J. Etherton, and S. J. Majumdar, 2001: Adaptive sampling with the ensemble transform Kalman filter. Part I: Theoretical aspects. Mon. Wea. Rev., 129, 420–436.
5. Bocquet, M., C. A. Pires, and L. Wu, 2010: Beyond Gaussian statistical modeling in geophysical data assimilation. Mon. Wea. Rev., 138, 2997–3023.
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