Articles | Volume 13, issue 5
https://doi.org/10.5194/cp-13-421-2017
https://doi.org/10.5194/cp-13-421-2017
Research article
 | 
08 May 2017
Research article |  | 08 May 2017

Reconstructing paleoclimate fields using online data assimilation with a linear inverse model

Walter A. Perkins and Gregory J. Hakim

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
ED: Publish subject to minor revisions (review by Editor) (02 Mar 2017) by Joel Guiot
AR by Walter Perkins on behalf of the Authors (19 Mar 2017)  Author's response   Manuscript 
ED: Publish as is (23 Mar 2017) by Joel Guiot
AR by Walter Perkins on behalf of the Authors (31 Mar 2017)
Download
Short summary
We examine the skill of a novel data assimilation approach to paleoclimate reconstruction that uses linear climate model forecasts. Many reconstruction studies forego the use of forecasts from climate models due to their high computational expense and relatively low skill. We show that the use of simpler linear models can improve reconstruction skill for both global mean temperature and spatial fields. Improvements displayed seem to be related to dynamical constraints from the forecasts.