18th Conference on Probability and Statistics in the Atmospheric Sciences

4.6

An implementation of the Local Ensemble Transform Kalman Filter on the NCEP GFS

Istvan Szunyogh, University of Maryland, College Park, MD; and E. J. Kostelich and G. Gyarmati

The accuracy and computational efficiency of the recently proposed Local Ensemble Transforms Kalman Filter data assimilation and ensemble generation scheme is investigated on a state-of-the-art operational numerical weather prediction model using both simulated and real observations. The model selected for this purpose is the T62 horizontal- and 28-level vertical-resolution 2004 version of the Global Forecast System (GFS) of the National Centers for Environmental Prediction. .

Session 4, Ensemble Forecasting
Tuesday, 31 January 2006, 8:45 AM-11:45 AM, A304

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