Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

ABSTRACT: The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the

SUBMITTER: Kelly D 

PROVIDER: S-EPMC4553757 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature