Now showing items 1-10 of 35
An Ensemble Kalman Filter Implementation Based on Modified Cholesky Decomposition for Inverse Covariance Matrix Estimation
This paper develops an efficient implementation of the ensemble Kalman filter based on a modified Cholesky decomposition for inverse covariance matrix estimation. This implementation is named EnKF-MC. Background errors ...
An Efficient Implementation of the Ensemble Kalman Filter Based on Iterative Sherman Morrison Formula
(ELSEVIER SCIENCE BV, 2012-01-01)
Low-rank approximations for computing observation impact in 4D-Var data assimilation
(PERGAMON-ELSEVIER SCIENCE LTD, 2014-07-01)
A Parallel Implementation of the Ensemble Kalman Filter Based on Modified Cholesky Decomposition
This paper discusses an efficient parallel implementation of the ensemble Kalman filter based on the modified Cholesky decomposition. The proposed implementation starts with decomposing the domain into sub-domains. In each ...
A time-parallel approach to strong-constraint four-dimensional variational data assimilation
(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2016-05-15)
Efficient approximation of Sparse Jacobians for time-implicit reduced order models
Efficient Construction of Local Parametric Reduced Order Models Using Machine Learning Techniques
Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning ...
Ensemble Kalman filter implementations based on shrinkage covariance matrix estimation
(SPRINGER HEIDELBERG, 2015-11-01)
LIRK-W: Linearly-implicit Runge-Kutta methods with approximate matrix factorization
This paper develops a new class of linearly implicit time integration schemes called Linearly-Implicit Runge-Kutta-W (LIRK-W) methods. These schemes are based on an implicit-explicit approach which does not require a ...