21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction


Data Assimilation on the NASA fvGCM with the Local Ensemble Transform Kalman Filter

Elana Klein, University of Maryland, College Park, MD; and H. Li, J. Liu, I. Szunyogh, B. Hunt, E. Kalnay, E. J. Kostelich, and R. Todling

The Local Ensemble Transform Kalman Filter (LETKF) applies the Ensemble Transform Kalman Filter technique (Bishop et al. 2001) to locally update the analysis ensemble members. By performing data assimilation on each local patch (following the LEKF approach of Ott et al, 2002, 2004), LETKF can utilize the low-dimensional subspace to reduce the required ensemble size. LETKF has been implemented to assimilate simulated observations on the operational NCEP model, with comparable results to those obtained using LEKF (Szunyogh et al., 2004), but with a speed-up of 3-5. In the NASA fvGCM model, the LETKF is applied to assimilate simulated model variables and rawinsonde observations. The results from this scheme will be compared with those obtained from the results with the operational NCEP model and the operational fvGCM PSAS scheme. We ultimately plan to assimilate real observations at the observation time (Hunt et al, 2004), estimate and correct model errors present in the fvGCM model, and assimilate AIRS observations.

Poster Session 1, Conference Posters
Monday, 1 August 2005, 5:30 PM-7:00 PM, Regency Ballroom

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