Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2723-2020
https://doi.org/10.5194/gmd-13-2723-2020
Methods for assessment of models
 | Highlight paper
 | 
18 Jun 2020
Methods for assessment of models | Highlight paper |  | 18 Jun 2020

Towards an objective assessment of climate multi-model ensembles – a case study: the Senegalo-Mauritanian upwelling region

Juliette Mignot, Carlos Mejia, Charles Sorror, Adama Sylla, Michel Crépon, and Sylvie Thiria

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 Juliette Mignot on behalf of the Authors (15 Apr 2020)  Author's response   Manuscript 
ED: Publish subject to minor revisions (review by editor) (29 Apr 2020) by Paul Halloran
AR by Juliette Mignot on behalf of the Authors (08 May 2020)  Author's response   Manuscript 
ED: Publish subject to technical corrections (14 May 2020) by Paul Halloran
AR by Juliette Mignot on behalf of the Authors (15 May 2020)  Manuscript 
Download
Short summary
The most robust representation of climate is usually obtained by averaging a large number of simulations, thereby cancelling individual model errors. Here, we work towards an objective way of selecting the least biased models over a certain region, based on physical parameters. This statistical method based on a neural classifier and multi-correspondence analysis is illustrated here for the Senegalo-Mauritanian region, but it could potentially be developed for any other region or process.