… based on the Kalman filter in data assimilation, this paper also provides examples and classifies
the … of both the Kalman filter and its derivative algorithms in the field of data assimilation. …

… Assessment of the state of the environment with observational data is … on data assimilation
systems. One of the most popular algorithms for data assimilation is the ensemble Kalman filter…

… A Kalman filter based sequential estimator is presented in … costs associated with a complete
Kalman Filter application, two … work suggests that these Data Assimilation techniques, which …

… already providing us with large amounts of experimental data, thus opening the possibility to
learn … Data assimilation — the process by which we incorporate these data to our numerical …

… He, 2010a: Intercomparison of variational data assimilation and the ensemble Kalman
filter for global deterministic NWP. Part I: Description and single-observation experiments …

… frequency has essential influences on the performances of data assimilation, especially for
… of assimilation frequency on data assimilation and the imbalance caused by data insertion, …

… Data assimilation (… Kalman filter, and we prove that it is also the minimum variance linear
unbiased estimator. Here, we formulate and implement a multi-model ensemble Kalman filter (…

… Data assimilation is critical for providing … data assimilation method has been widely adopted
and developed by many operational centers. The hybrid ensemble–variational assimilation …

… developed a data assimilation (DA) methodology based on the ensemble Kalman filter (…
-field model from observational/experimental data. The DA methodology based on Bayesian …

… a new data assimilation filtering technique called a weak constrained ensemble Kalman filter
(… In the present study, a new constrained ensemble Kalman filter, which we refer to as weak …