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Monthly Weather Review The Hybrid Local Ensemble Transform Kalman Filter

48 Hybrid data assimilation methods combine elements of ensemble Kalman filters (EnKF) 49 and variational methods. While most approaches have focused on augmenting an 50 operational variational system with dynamic error covariance information from an EnKF, 51 we take the opposite perspective of augmenting an operational EnKF with information 52 from a simple 3D-Variational (3D-Var) method. We wish to determine which aspects of 53 the variational methods are necessary for successful application of a hybrid method. To 54 this end we have developed the Hybrid Local Ensemble Transform Kalman Filter 55 (Hybrid-LETKF), which improves analysis errors when using small ensemble sizes and 56 low observation coverage versus either LETKF or 3D-Var used alone. The results imply 57 that for small ensemble sizes, allowing a solution to be found outside of the space 58 spanned by ensemble members provides robustness in the hybrid method compared to 59 LETKF alone. Finally, the simplicity of the Hybrid-LETKF design implies that this 60 method can be applied operationally while requiring almost no modification to an 61 existing operational 3D-Var system. 62