… Comparison of empirical localization techniques for serial ensemble Kalman filters in a
simple atmospheric general circulation model, Mon. Weather Rev., 141, 4140–4153, 2014. …

… This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step
of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and …

… LWEnKF is compared with the ensemble Kalman filter (EnKF) and the local particle filter (PF). …
The local PF ensemble does not converge to the observed solution in an ample amount of …

… of the ensemble Kalman filter via shrinkage covariance matrix estimation. Our filter implementation
… and its implementation with the local ensemble transform kalman filter. Mon. Weather. …

… The ensemble Kalman filter (EnKF) is a recursive filter … The EnKF originated as a version of
the Kalman filter for large problems (… of ensemble forecasting. EnKF is related to the particle …

… Kalman filter (EnKF) is that the error statistics are calculated from an ensemble of the forward
model … In this study, we propose a local ensemble Kalman filter (LEnKF) to assimilate GNSS …

… Kalman gain estimate are known and hence exact Kalman gain resampling can be done. For
the general nonlinear case we introduce the resampling ensemble Kalman filter (… ensemble …

… filters exist, but they are computationally too expensive when working with high-dimensional
systems. The ensemble Kalman filter … mixture filter has the advantage of both a local Kalman …

… Filter (PF) and Ensemble Kalman Filter (EnKF) has been adopted (Interacting Particle-Ensemble
Kalman Filter, IP-EnKF) in which the EnKF estimates the response states as ensembles …

… The results are compared against those obtained using the local ensemble transform Kalman
filter (LETKF). Tests are performed for dense observations (100% and 50% of the model …