Articles | Volume 24, issue 4
https://doi.org/10.5194/npg-24-701-2017
https://doi.org/10.5194/npg-24-701-2017
Research article
 | 
01 Dec 2017
Research article |  | 01 Dec 2017

The Onsager–Machlup functional for data assimilation

Nozomi Sugiura

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Nozomi Sugiura on behalf of the Authors (06 Oct 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (19 Oct 2017) by Zoltan Toth
ED: Publish subject to minor revisions (further review by Editor) (19 Oct 2017) by Zoltan Toth
AR by Nozomi Sugiura on behalf of the Authors (26 Oct 2017)  Author's response    Manuscript
ED: Publish as is (26 Oct 2017) by Zoltan Toth
Download
Short summary
The optimisation of simulation paths is sometimes misleading. We can find a path with the highest probability by the method of least squares. However, it is not necessarily the route where the paths are most concentrated. This paper clarifies how we can find the mode of a distribution of paths by optimisation.