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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 4
Hydrol. Earth Syst. Sci., 21, 2163–2185, 2017
https://doi.org/10.5194/hess-21-2163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 2163–2185, 2017
https://doi.org/10.5194/hess-21-2163-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 Apr 2017

Research article | 20 Apr 2017

Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada

Jefferson S. Wong et al.
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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 revisions (further review by Editor and Referees) (31 Dec 2016) by Jan Seibert
AR by Jefferson Wong on behalf of the Authors (19 Jan 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (20 Jan 2017) by Jan Seibert
RR by Anonymous Referee #1 (23 Jan 2017)
RR by Anonymous Referee #3 (20 Feb 2017)
ED: Publish subject to minor revisions (further review by Editor) (21 Feb 2017) by Jan Seibert
AR by Jefferson Wong on behalf of the Authors (28 Feb 2017)  Author's response    Manuscript
ED: Publish as is (16 Mar 2017) by Jan Seibert
Publications Copernicus
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Short summary
This study was conducted to quantify the spatial and temporal variability of the errors associated with various gridded precipitation products in Canada. Overall, WFDEI [GPCC] and CaPA performed best with respect to different performance measures, followed by ANUSPLIN and WEDEI [CRU]. Princeton and NARR demonstrated the lowest quality. Comparing the climate model-simulated products, PCIC ensembles generally performed better than NA-CORDEX ensembles in terms of reliability in four seasons.
This study was conducted to quantify the spatial and temporal variability of the errors...
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