A multi-scale localization approach to an ensemble Kalman filter

Scientific Online Letters on the Atmosphere

Volumn 9, Issue 1, 2013, Pages 170-173

  Miyoshi, Takemasa ^a,b,c   Kondo, Keiichi ^a,d  

^a RIKEN   (Japan)

^b UNIVERSITY OF MARYLAND   (United States)

^c JAPAN AGENCY FOR MARINE EARTH SCIENCE AND TECHNOLOGY   (Japan)

^d UNIVERSITY OF TSUKUBA   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84906331341     PISSN: None     EISSN: 13496476     Source Type: Journal    
DOI: 10.2151/sola.2013-038     Document Type: Article

References (11)

1. Buehner, M., 2012: Evaluation of a spatial/spectral covariance localization approach for atmospheric data assimilation. Mon. Wea. Rev., 140, 617-636.
2. Hamill, T. M., J. S. Whitaker, and C. Snyder, 2001: Distancedependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776-2790.
3. Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126, 796-811.
4. Hunt, B. R., E. J. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D, 230, 112-126.
5. Kang, J.-S., E. Kalnay, J. Liu, I. Fung, T. Miyoshi, and K. Ide, 2011: "Variable localization" in an Ensemble Kalman Filter: application to the carbon cycle data assimilation. J. Geophys. Res., 116, D09110, doi:10.1029/2010JD014673.
6. Kang, J.-S., E. Kalnay, T. Miyoshi, J. Liu, and I. Fung, 2012: Estimation of surface carbon fluxes with an advanced data assimilation methodology. J. Geophys. Res., 117, D24101. doi:10.1029/2012JD018259.
7. Miyoshi, T., 2005: Ensemble Kalman filter experiments with a primitive-equation global model, Ph.D. dissertation, University of Maryland, College Park, 197 pp.
8. Miyoshi, T., 2011: The gaussian approach to adaptive covariance inflation and its implementation with the local ensemble transform Kalman filter. Mon. Wea. Rev., 139, 1519-1535, doi:10.1175/2010MWR3570.1.
9. Miyoshi, T., and K. Aranami, 2006: Applying a four-dimensional local ensemble transform Kalman filter (4D-LETKF) to the JMA nonhydrostatic model (NHM). SOLA, 2, 128-131, doi:10.2151/sola.2006-033.
10. Molteni, F., 2003: Atmospheric simulations using a GCM with simplified physical parametrizations. I: model climatology and variability in multi-decadal experiments. Clim. Dyn., 20, 175-191.
11. Zhang, F., Y. Weng, J. A. Sippel, Z. Meng, and C. H. Bishop, 2009: Cloud-resolving hurricane initialization and prediction through assimilation of Doppler radar observations with an ensemble Kalman filter. Mon. Wea. Rev., 137, 2105-2125.