… “Data assimilation, as defined by Geir Evensen, refers to the … of data assimilation with
Kalman filters. … The book primarily addresses researchers in the field of data assimilation, for …

… The actual assimilations are performed using a pair of ensemble Kalman filters. With a view
toward the real-time constraints associated with operational atmospheric data assimilation, …

… However, the degree of suboptimality is relatively small and results presented here
indicate that the EnKF is a flexible and robust data assimilation option that gives satisfactory …

… of the ensemble Kalman filter approach for atmospheric data assimilation. Our scheme is …
Ensemble Kalman filters, in general, take the analysis resulting from the data assimilation to …

… Kalman filter are identical to those obtained from the maximum likelihood estimator. The
extended Kalman filter and the iterated Kalman filter … , the extended Kalman filter is equivalent to …

… An ensemble Kalman filter may be considered for the 4D assimilation of atmospheric data.
In this … An ensemble Kalman filter may be considered for the 4D assimilation of atmospheric …

… ABSTRACT In this paper, two data assimilation methods … : the ensemble Kalman filter and
the particle filter. Each of these … Kalman filter, consists to rely on the Ensemble Kalman Filter …

… method of data assimilation that is based on a simplification of the Kalman filter equations. …
central and most expensive aspect of the Kalman filter algorithm. In simulations with a linear…

… 67 Kalman filter for intermittent data assimilation (BERGEMANN and REICH, 2010a,b).
With this 68 choice for R and H one could also implement a standard ensemble Kalman filter (…

… This random vector is chosen from a Gaussian distribution with zero mean and data covariance
W . (In passing, I note that the analysis step used in the Kalman filter is not optimal for a …