Articles | Volume 24, issue 5
Hydrol. Earth Syst. Sci., 24, 2545–2560, 2020
https://doi.org/10.5194/hess-24-2545-2020
Hydrol. Earth Syst. Sci., 24, 2545–2560, 2020
https://doi.org/10.5194/hess-24-2545-2020

Research article 15 May 2020

Research article | 15 May 2020

Snow processes in mountain forests: interception modeling for coarse-scale applications

Nora Helbig et al.

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Interactive discussion

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) (22 Nov 2019) by Ryan Teuling
AR by Nora Helbig on behalf of the Authors (20 Dec 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (07 Jan 2020) by Ryan Teuling
RR by Anonymous Referee #2 (06 Feb 2020)
RR by Anonymous Referee #1 (06 Feb 2020)
ED: Publish subject to revisions (further review by editor and referees) (06 Feb 2020) by Ryan Teuling
AR by Nora Helbig on behalf of the Authors (26 Feb 2020)  Author's response    Manuscript
ED: Publish subject to minor revisions (further review by editor) (07 Mar 2020) by Ryan Teuling
AR by Nora Helbig on behalf of the Authors (13 Mar 2020)  Author's response    Manuscript
ED: Publish as is (29 Mar 2020) by Ryan Teuling
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Short summary
Snow retained in the forest canopy (snow interception) drives spatial variability of the subcanopy snow accumulation. As such, accurately describing snow interception in models is of importance for various applications such as hydrological, weather, and climate predictions. We developed descriptions for the spatial mean and variability of snow interception. An independent evaluation demonstrated that the novel models can be applied in coarse land surface model grid cells.