A Moment Matching Ensemble Filter for Nonlinear Non-Gaussian Data Assimilation

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A Second-Order Exact Ensemble Square Root Filter for Nonlinear Data Assimilation (2015, methodology): “Here, localization is mainly applied as a dimension reduction technique, as discussed by Lei and Bickel (2011), since a filter solely based on theBayesianweights cannot work directly in high-dimensional spaces due to the curse of dimensionality.”
A local particle filter for high-dimensional geophysical systems (2015, methodology): “The L96 system has frequently been used to demonstrate PF and other data assimilation algorithms for the geosciences (Nakano et al., 2007; van Leeuwen, 2010; Lei and Bickel, 2011; Penny, 2014).”
A Localized Particle Filter for High-Dimensional Nonlinear Systems (2016, methodology): “Localization strategies have already been adopted in several non-Gaussian filters, including the local–local Gaussian mixture filter (Bengtsson et al. 2003), the rank histogram filter (Anderson 2010), and the moment-matching filter (Lei and Bickel 2011).”
An Iterative EnKF for Strongly Nonlinear Systems (2012, methodology): “2010), merging the EnKF and particle filters (Hoteit et al. 2008; Stordal et al. 2011; Lei and Bickel 2011), try-”