Articles | Volume 22, issue 12
https://doi.org/10.5194/hess-22-6591-2018
https://doi.org/10.5194/hess-22-6591-2018
Research article
 | 
21 Dec 2018
Research article |  | 21 Dec 2018

On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark

Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen

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) (18 Dec 2017) by Maria-Helena Ramos
AR by Diana Lucatero on behalf of the Authors (13 Aug 2018)  Author's response   Manuscript 
ED: Publish subject to technical corrections (28 Oct 2018) by Maria-Helena Ramos
AR by Diana Lucatero on behalf of the Authors (05 Nov 2018)  Manuscript 
Download
Short summary
The present study evaluates the skill of a seasonal forecasting system for hydrological relevant variables in Denmark. Linear scaling and quantile mapping were used to correct the forecasts. Uncorrected forecasts tend to be more skillful than climatology, in general, for the first month lead time only. Corrected forecasts show a reduced bias in the mean; are more consistent; and show a level of accuracy that is closer to, although no higher than, that of ensemble climatology, in general.