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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 7
Hydrol. Earth Syst. Sci., 22, 3575–3587, 2018
https://doi.org/10.5194/hess-22-3575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Integration of Earth observations and models for global water...

Hydrol. Earth Syst. Sci., 22, 3575–3587, 2018
https://doi.org/10.5194/hess-22-3575-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 02 Jul 2018

Research article | 02 Jul 2018

Assessment of a multiresolution snow reanalysis framework: a multidecadal reanalysis case over the upper Yampa River basin, Colorado

Elisabeth Baldo and Steven A. Margulis

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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: Publish subject to revisions (further review by editor and referees) (19 Feb 2018) by Matthias Bernhardt
AR by Elisabeth Baldo on behalf of the Authors (21 Mar 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (09 Apr 2018) by Matthias Bernhardt
RR by Anonymous Referee #3 (14 May 2018)
RR by Anonymous Referee #1 (14 May 2018)
RR by Anonymous Referee #2 (29 May 2018)
ED: Publish as is (06 Jun 2018) by Matthias Bernhardt
Publications Copernicus
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Short summary
Montane snowpacks are extremely complex to represent and usually require assimilating remote sensing images at very fine spatial resolutions, which is computationally expensive. Adapting the grid size of the terrain to its complexity was shown to cut runtime and storage needs by half while preserving the accuracy of ~ 100 m snow estimates. This novel approach will facilitate the large-scale implementation of high-resolution remote sensing data assimilation over snow-dominated montane ranges.
Montane snowpacks are extremely complex to represent and usually require assimilating remote...
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