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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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HESS | Articles | Volume 22, issue 3
Hydrol. Earth Syst. Sci., 22, 1957–1969, 2018
https://doi.org/10.5194/hess-22-1957-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 1957–1969, 2018
https://doi.org/10.5194/hess-22-1957-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 23 Mar 2018

Research article | 23 Mar 2018

Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment

Sanjeev K. Jha et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to revisions (further review by editor and referees) (23 Jan 2018) by Luis Samaniego
AR by Sanjeev Jha on behalf of the Authors (31 Jan 2018)  Author's response    Manuscript
ED: Publish as is (09 Feb 2018) by Luis Samaniego
Publications Copernicus
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Short summary
The output from numerical weather prediction (NWP) models is known to have errors. River forecast centers in Canada mostly use precipitation forecasts directly obtained from American and Canadian NWP models. In this study, we evaluate the forecast performance of ensembles generated by a Bayesian post-processing approach in cold climates. We demonstrate that the post-processing approach generates bias-free forecasts and provides a better picture of uncertainty in the case of an extreme event.
The output from numerical weather prediction (NWP) models is known to have errors. River...
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