87th AMS Annual Meeting

Session 4: Advanced Methods for Data Assimilation

Tuesday, 16 January 2007: 1:30 PM-5:15 PM
208 (Henry B. Gonzalez Convention Center)
More
Chair:  Michele M. Rienecker, NASA/GSFC
Papers:
  1:30 PM
4.1
Ensemble data assimilation with the NCEP Global Forecast System
Jeffrey S. Whitaker, NOAA/ERL/CDC, Boulder, CO

  Recorded presentation
  1:45 PM
4.2
Using an ensemble data assimilation system for climate model development
Jeffrey Anderson, NCAR, Boulder, CO; and K. Raeder, T. Hoar, and N. Collins

  Recorded presentation
  2:00 PM
4.3
Recent development of global and regional local ensemble transform Kalman filters (LETKF) at JMA
Takemasa Miyoshi, Japan Meteorological Agency, Tokyo, Japan; and S. Yamane, Y. Sato, K. Aranami, and T. Enomoto

  Recorded presentation Poster PDF (1.2 MB)
  2:15 PM
4.4
The Canadian Meso4dvar continental analysis system: Pre-operational evaluations
Luc Fillion, MSC, Dorval, PQ, Canada; and M. Tanguay, Z. Liu, E. Lapalme, N. Ek, C. Page, and S. Pellerin

Poster PDF (892.1 kB)
  2:30 PM
4.5
Assessing observation impact using the adjoint of the GEOS-5 data assimilation system
Ronald Gelaro, NASA/GSFC, Greenbelt, MD; and Y. Zhu

  Recorded presentation
  2:45 PM
4.6
Issues in Assimilation of Lagrangian Data
Kayo Ide, University of California, Los Angeles, CA

  3:00 PM
4.6a
Coffee Break in Exhibit Hall

  3:30 PM
4.7
An alternative to bias correction in retrievals and direct radiances assimilation
Steven J. Fletcher, Colorado State University, Fort Collins, CO; and M. Zupanski

  Recorded presentation Poster PDF (80.4 kB)
  3:45 PM
4.8
Ensemble Kalman filter in the presence of model errors
Hong Li, Shanghai Typhoon Institute, Shanghai, China, Shanghai, China; and E. Kalnay, T. Miyoshi, and C. M. Danforth

  Recorded presentation Poster PDF (208.0 kB)
  4:00 PM
4.9
Comparing Local Ensemble Transform Kalman Filter with 4D-Var in a quasi-geostrophic model
Shu-Chih Yang, Univ. of Maryland, College Park, MD; and E. Kalnay

  4:15 PM
4.10
A hybrid ensemble transform Kalman filter(ETKF)-3DVAR data assimilation scheme for WRF
Xuguang Wang, School of Meteorology, University of Oklahoma, OK; and D. Barker, C. Snyder, and T. Hamill

  Recorded presentation
  4:30 PM
4.11
Four-dimensional variational assimilation without using the adjoint model
Hyo-Jong Song, Seoul National Univ., Seoul, South Korea; and G. H. Lim and H. S. Lee

  Recorded presentation Poster PDF (193.1 kB)
  4:45 PM
4.12
Predictor-corrector and morphing ensemble filters for the assimilation of sparse data into high-dimensional nonlinear systems
Jan Mandel, University of Colorado at Denver and Health Sciences Center, and National Center for Atmospheric Research, Denver, CO; and J. D. Beezley

http://www-math.cudenver.edu/~jmandel/papers/#ametsoc07

  Recorded presentation Poster PDF (661.1 kB)
  5:00 PM
4.13
Evaluating the ability of the Ensemble Transform Kalman Filter to predict the influence of observations on 3-6 day forecasts
Kathryn J. Sellwood, Univ. of Miami/RSMAS, Miami, FL; and S. J. Majumdar and D. Hodyss

  Recorded presentation Poster PDF (178.2 kB)
See more of: 11th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)
<< Previous Session | Next Session >>