P3.4 the Local Ensemble Kalman Filter of the University of Maryland

The time has come when ensemble-based Kalman filter data assimilation schemes can be considered for implementation on operational weather forecast systems in the foreseeable future. For the first time, an ensemble Kalman filter has been reported to break even with a sophisticated operational 3DVar system (Houtekamer et al 2004), to outperform the NCEP 3D-Var in reconstructing the state of the mid-troposphere from surface pressure observations (Whitaker et al. 2004), and to be efficient in assimilating simulated and real Dopplerradar observations of convective systems (Snyder and Zhang 2003; Zhang et al 2004; Dowell et al 2004). The present paper reports on the current status of the 4-dimensional Local Ensemble Kalman Filter data assimilation system (4D LEKF) developed by our interdisciplinary team at the University of Maryland. Our plan has been to develop a largely model independent analysis system through completation of the following tasks: