Articles | Volume 27, issue 3
Nonlin. Processes Geophys., 27, 453–471, 2020
https://doi.org/10.5194/npg-27-453-2020
Nonlin. Processes Geophys., 27, 453–471, 2020
https://doi.org/10.5194/npg-27-453-2020

Research article 17 Sep 2020

Research article | 17 Sep 2020

Applications of matrix factorization methods to climate data

Dylan Harries and Terence J. O'Kane

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 Dylan Harries on behalf of the Authors (23 Jul 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (31 Jul 2020) by Zoltan Toth
RR by Anonymous Referee #2 (04 Aug 2020)
RR by Anonymous Referee #1 (06 Aug 2020)
ED: Publish subject to technical corrections (07 Aug 2020) by Zoltan Toth
Download
Short summary
Different dimension reduction methods may produce profoundly different low-dimensional representations of multiscale systems. We perform a set of case studies to investigate these differences. When a clear scale separation is present, similar bases are obtained using all methods, but when this is not the case some methods may produce representations that are poorly suited for describing features of interest, highlighting the importance of a careful choice of method when designing analyses.