TY  - JOUR
A1  - Reich, Sebastian
T1  - A Gaussian-mixture ensemble transform filter
T2  - Quarterly journal of the Royal Meteorological Society
N2  - We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions.
KW  - data assimilation
KW  - ensemble Kalman filter
KW  - nonlinear filtering
KW  - Gaussian mixtures
KW  - Gaussian kernel estimators
Y1  - 2012
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/36378
SN  - 0035-9009
VL  - 138
IS  - 662
SP  - 222
EP  - 233
PB  - Wiley-Blackwell
CY  - Malden
ER  -