The Onsager--Machlup functional for data assimilation
Abstract
When taking the model error into account in data assimilation, one needs to evaluate the prior distribution represented by the Onsager--Machlup functional. Through numerical experiments, this study clarifies how the prior distribution should be incorporated into cost functions for discrete-time estimation problems. Consistent with previous theoretical studies, the divergence of the drift term is essential in weak-constraint 4D-Var (w4D-Var), but it is not nec essary in Markov chain Monte Carlo with the Euler scheme. Although the former property may cause difficulties when implementing w4D-Var in large systems, this paper proposes a new technique for estimating the divergence term and its derivative.
Cite
@article{arxiv.1703.06663,
title = {The Onsager--Machlup functional for data assimilation},
author = {Nozomi Sugiura},
journal= {arXiv preprint arXiv:1703.06663},
year = {2017}
}
Comments
Reprint from Nonlin. Processes Geophys. (ver.5). 12 pages, 5 figures