The Local Ensemble Transform Kalman Filter and its implementation on the NCEP global model at the University of Maryland

This paper describes the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme and its implementation on the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model at the University of Maryland. Numerical results are shown for both simulated observations and observations of the real atmosphere. The role of flow-dependent information in data assimilation is discussed based on the results of the numerical experiments. Preliminary assimilation results with AMSU-A radiance observations are also presented.

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