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Advances in Meteorology
Volume 2010 (2010), Article ID 432160, 10 pages
Beating the Uncertainties: Ensemble Forecasting and Ensemble-Based Data Assimilation in Modern Numerical Weather Prediction
Department of Atmospheric Sciences, University of Utah, 135 S 1460 E, Rm. 819, Salt Lake City, UT 84112, USA
Received 1 January 2010; Revised 31 March 2010; Accepted 3 June 2010
Academic Editor: Hann-Ming Henry Juang
Copyright © 2010 Hailing Zhang and Zhaoxia Pu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citations to this Article [6 citations]
The following is the list of published articles that have cited the current article.
- Emilia Paula Diaconescu, and René Laprise, “Singular vectors in atmospheric sciences: A review,” Earth-Science Reviews, vol. 113, no. 3-4, pp. 161–175, 2012.
- C. Peralta, Z. Ben Bouallegue, S. E. Theis, C. Gebhardt, and M. Buchhold, “Accounting for initial condition uncertainties in COSMO-DE-EPS,” Journal of Geophysical Research-Atmospheres, vol. 117, 2012.
- Amelia Caffarra, Fabio Zottele, Emily Gleeson, and Alison Donnelly, “Spatial heterogeneity in the timing of birch budburst in response to future climate warming in Ireland,” International Journal of Biometeorology, 2013.
- Christopher J. Hutton, Zoran Kapelan, Lydia Vamvakeridou-Lyroudia, and Dragan A. Savic, “Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation,” Journal of Water Resources Planning and Management, vol. 140, no. 2, pp. 169–183, 2014.
- Peter Bauer, Alan Thorpe, and Gilbert Brunet, “The quiet revolution of numerical weather prediction,” Nature, vol. 525, no. 7567, pp. 47–55, 2015.
- Chun Yang, Jinzhong Min, and Youmin Tang, “Evaluation of two modified Kalman gain algorithms for radar data assimilation in the WRF model,” Tellus Series A-Dynamic Meteorology And Oceanography, vol. 67, 2015.