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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 9
Hydrol. Earth Syst. Sci., 20, 3601–3618, 2016
https://doi.org/10.5194/hess-20-3601-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Sub-seasonal to seasonal hydrological forecasting

Hydrol. Earth Syst. Sci., 20, 3601–3618, 2016
https://doi.org/10.5194/hess-20-3601-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Sep 2016

Research article | 06 Sep 2016

Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts

Louise Crochemore et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (10 May 2016) by Ilias Pechlivanidis
AR by Louise Crochemore on behalf of the Authors (17 Jun 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (22 Jun 2016) by Ilias Pechlivanidis
RR by Anonymous Referee #2 (11 Jul 2016)
RR by Massimiliano Zappa (18 Jul 2016)
ED: Publish subject to minor revisions (Editor review) (19 Jul 2016) by Ilias Pechlivanidis
AR by Louise Crochemore on behalf of the Authors (29 Jul 2016)  Author's response    Manuscript
ED: Publish as is (14 Aug 2016) by Ilias Pechlivanidis
Publications Copernicus
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Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
This study investigates the way bias correcting precipitation forecasts can improve the skill of...
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