Session 6 Data Assimilation Techniques. c: Ensemble Kalman Filters

Tuesday, 8 January 2013: 1:30 PM-3:00 PM
Room 9C (Austin Convention Center)
Host: 17th Conference on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)
Chair:
Jeffrey Anderson, NCAR, IMAGE, Boulder, CO

Papers:
1:30 PM
6.1
An Empirical Localization of Surface Observations
Lili Lei, University of Colorado/CIRES, Boulder, CO; and J. Anderson
Recorded Presentation

1:45 PM
6.2
Spatial Structure of the Ensemble Weights in the LETKF and Its Insights
Takemasa Miyoshi, University of Maryland, College Park, MD; and K. Kondo, S. C. Yang, and E. Kalnay
Recorded Presentation

2:00 PM
6.3
Self-optimization of Model Parameters with the LETKF: from Idealized Experiments to a Real-world Application
Juan J. Ruiz, University of Buenos Aires, Buenos Aires, Argentina; and T. Miyoshi, M. Kunii, and M. Pulido
Recorded Presentation

2:15 PM
6.4
Validation and Evaluation of the NCAR 4D-REKF ensemble data assimilation and forecasting system
Yubao Liu, NCAR, Boulder, CO; and L. Pan, Y. Wu, A. Bourgeois, J. Knievel, S. Swerdlin, J. Pace, F. W. Gallagher III, and S. F. Halvorson

2:30 PM
6.6
Evaluation of high-resolution surface analyses and forecasts with ensemble data assimilation in regions of complex terrain
Zhaoxia Pu, University of Utah, Salt Lake City, UT; and H. Zhang and X. Zhang
Recorded Presentation

2:45 PM
An Approach for Addressing Non-Gaussian Error in Microphysical Parameterization by Marcus Van Lier-Walqui
Recorded Presentation

6.5
Employ multi-model ensemble background error covariance in four-dimensional ensemble data assimilation

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
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