We consider stochastic differential equations of type dx= f (x, t) dt+ Ω1/2dw (t)(1.1) where x
(t)∈ RN, Ω∈ RN× N is a symmetric positive semi-definite matrix, and w (t) denotes 9 N …

A suboptimal algorithm for data assimilation based on the ensemble Kalman filter (EnKF) is
proposed. An advantage of the algorithm is that it does not require an additional calculation …

Ensemble-based data assimilation methods related to the fundamental theory of Kalman
filtering have been explored in a variety of mostly non-operational data assimilation contexts …

Atmospheric Data Assimilation with an Ensemble Kalman Filter: Results with Real
Observations in: Monthly Weather Review Volume 133 Issue 3 (2005) Jump to Content …

In this paper, two data assimilation methods based on sequential Monte Carlo sampling are
studied and compared: the ensemble Kalman filter and the particle filter. Each of these …

The ensemble Kalman filter (EnKF) has been proposed as a Monte Carlo, derivative-free,
alternative to the extended Kalman filter, and is now widely used in sequential data …

We have investigated a method to substantially reduce the analysis computations within the
Local Ensemble Transform Kalman Filter (LETKF) framework. Instead of computing the …

Reducing Correlation Sampling Error in Ensemble Kalman Filter Data Assimilation in:
Monthly Weather Review Volume 144 Issue 3 (2016) Jump to Content Jump to Main …

ABSTRACT A hybrid data assimilation approach combining nudging and the ensemble
Kalman filter (EnKF) for dynamic analysis and numerical weather prediction is explored here …

Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation in:
Monthly Weather Review Volume 140 Issue 7 (2012) Jump to Content Jump to Main Navigation …