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The Cryosphere An interactive open-access journal of the European Geosciences Union
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TC | Volume 12, issue 3
The Cryosphere, 12, 891–905, 2018
https://doi.org/10.5194/tc-12-891-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 12, 891–905, 2018
https://doi.org/10.5194/tc-12-891-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Mar 2018

Research article | 12 Mar 2018

Improving gridded snow water equivalent products in British Columbia, Canada: multi-source data fusion by neural network models

Andrew M. Snauffer et al.
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Status: closed
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
AR by Andrew Snauffer on behalf of the Authors (12 Dec 2017)  Author's response    Manuscript
ED: Publish as is (02 Jan 2018) by Claude Duguay
Publications Copernicus
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Short summary
Estimating winter snowpack throughout British Columbia is challenging due to the complex terrain, thick forests, and high snow accumulations present. This paper describes a way to make better snow estimates by combining publicly available data using machine learning, a branch of artificial intelligence research. These improved estimates will help water resources managers better plan for changes in rivers and lakes fed by spring snowmelt and will aid other research that supports such planning.
Estimating winter snowpack throughout British Columbia is challenging due to the complex...
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