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Displacement Data Assimilation

Research paper by W. Steven Rosenthal, Shankar C. Venkataramani, Arthur J. Mariano, Juan M. Restrepo

Indexed on: 05 Feb '16Published on: 05 Feb '16Published in: Physics - Data Analysis; Statistics and Probability



Abstract

We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information important. While the displacement transformation is not tied to any particular assimilation scheme, here we implement it within an ensemble Kalman Filter and demonstrate its effectiveness in tracking stochastically perturbed vortices.