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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.
Data sets

MERRA 2D IAU Diagnostic, Land Only States and Diagnostics Global Modeling and Assimilation Office https://doi.org/10.5067/YL8Z7MICQZF9

MERRA Simulated 2D Incremental Analysis Update (IAU) MERRA-Land reanalysis Global Modeling and Assimilation Office https://doi.org/10.5067/OQ6B1RHOHBI8

GLDAS Noah Land Surface Model L4 3 hourly 0.25 x 0.25 degree V2.0 M. Rodell and H. K. Beaudoing https://doi.org/10.5067/342OHQM9AK6Q

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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