Articles | Volume 23, issue 11
https://doi.org/10.5194/hess-23-4717-2019
https://doi.org/10.5194/hess-23-4717-2019
Research article
 | 
19 Nov 2019
Research article |  | 19 Nov 2019

Hyper-resolution ensemble-based snow reanalysis in mountain regions using clustering

Joel Fiddes, Kristoffer Aalstad, and Sebastian Westermann

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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 minor revisions (further review by editor) (19 Sep 2019) by Carlo De Michele
AR by Joel Fiddes on behalf of the Authors (01 Oct 2019)  Author's response    Manuscript
ED: Publish as is (10 Oct 2019) by Carlo De Michele
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Short summary
In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.