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

Crochemore, Louise; Ramos, Maria-Helena; Pappenberger, Florian

doi:10.5194/hess-20-3601-2016

Articles | Volume 20, issue 9

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

https://doi.org/10.5194/hess-20-3601-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 20, issue 9

Research article

|

06 Sep 2016

Research article |

| 06 Sep 2016

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

Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger

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Cumulative views and downloads (calculated since 24 Feb 2016)

Month	HTML	PDF	XML	Total
Feb 2016	77	40	0	117
Mar 2016	85	64	2	151
Apr 2016	41	14	0	55
May 2016	35	21	0	56
Jun 2016	32	13	0	45
Jul 2016	21	5	0	26
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Oct 2025	38	31	2	71
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Latest update: 09 Nov 2025

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.