… data assimilation systems. One of the most popular algorithms for data assimilation is the
ensemble Kalman filter, in which the forecast error covariance is estimated using an ensemble …

… forecasting model to indoor environment field. In this paper, all numerical operations
relating to data assimilation are based on a generic toolbox for data assimilation, OpenDA [20], …

… ) is examined in an idealized environment. Using a three-level, quasigeostrophic, T21
model and simulated observations, experiments are performed in a perfect-model context. By …

An ensemble Kalman filter may be considered for the 4D assimilation of atmospheric data.
In this paper, an efficient implementation of the analysis step of the filter is proposed. It …

… “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 performance of the ensemble Kalman filter (EnKF) for soil moisture estimation is
assessed by assimilating L-band (1.4 GHz) microwave radiobrightness observations into a land …

… scheme on the National Center for Environmental Prediction (NCEP) Global Forecast
System (GFS) model support this view.] Thus, we anticipate that we can approximate the …

… and (lower) assimilation runs using the ensemble square root Kalman filter, with updates every
… control simulations and (lower) assimilation runs using the ensemble square root Kalman …

… of the ensemble Kalman filter by comparing its distributional estimates to those of a less efficient
ensemble … about the ensemble Kalman filter’s performance in land surface applications. …

… Data assimilation for systems possessing many scales of … Coupled data assimilation (CDA)
distinctively appears as a … and then focus on CDA using the ensemble Kalman filter (EnKF), a …