Articles | Volume 20, issue 9
https://doi.org/10.5194/hess-20-3601-2016
https://doi.org/10.5194/hess-20-3601-2016
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

Viewed

Total article views: 5,713 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,489 2,101 123 5,713 124 124
  • HTML: 3,489
  • PDF: 2,101
  • XML: 123
  • Total: 5,713
  • BibTeX: 124
  • EndNote: 124
Views and downloads (calculated since 24 Feb 2016)
Cumulative views and downloads (calculated since 24 Feb 2016)

Cited

Saved (final revised paper)

Saved (preprint)

Latest update: 20 Nov 2024
Download
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.