منابع مشابه
Localization techniques for ensemble transform Kalman filters∗
Ensemble Kalman filter techniques are widely used to assimilate observations into dynamical models. The dimension of phase is typically much larger than the number of ensemble members which leads to inaccurate results in the computed covariance matrices. These inaccuracies lead, among others, to spurious long range correlations which can be eliminated by Schur-product-based localization techniq...
متن کاملOn the stability and the uniform propagation of chaos properties of Ensemble Kalman-Bucy filters
The Ensemble Kalman filter is a sophisticated and powerful data assimilation method for filtering high dimensional problems arising in fluid mechanics and geophysical sciences. This Monte Carlo method can be interpreted as a mean-field McKean-Vlasov type particle interpretation of the Kalman-Bucy diffusions. In contrast to more conventional particle filters and nonlinear Markov processes these ...
متن کاملMorphing Ensemble Kalman Filters
A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. The ensemble members are represented as the composition of one common state with a spat...
متن کاملMorphing Ensemble Kalman Filters By JONATHAN
A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. The ensemble members are represented as the composition of one common state with a spat...
متن کاملThe Hybrid Local Ensemble Transform Kalman Filter
Hybrid data assimilation methods combine elements of ensemble Kalman filters (EnKF) and variational methods. While most approaches have focused on augmenting an operational variational system with dynamic error covariance information from an EnKF [1][2][4][5][8], we take the opposite perspective of augmenting an operational EnKF with information from a simple 3D-Variational (3D-Var) method [7]....
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ژورنال
عنوان ژورنال: Quarterly Journal of the Royal Meteorological Society
سال: 2013
ISSN: 0035-9009
DOI: 10.1002/qj.2186