The Cryosphere
The Cryosphere
TC
Articles | Volume 18, issue 10
Articles | Volume 18, issue 10
https://doi.org/10.5194/tc-18-4607-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-4607-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 10
Research article
 | 
08 Oct 2024
Research article |  | 08 Oct 2024

Exploring the potential of forest snow modeling at the tree and snowpack layer scale

Giulia Mazzotti, Jari-Pekka Nousu, Vincent Vionnet, Tobias Jonas, Rafife Nheili, and Matthieu Lafaysse

Supplement

https://doi.org/10.5194/tc-18-4607-2024-supplement

Data sets

Distributed sub-canopy datasets from mobile multi-sensor platforms (CH / FIN, 2018-2019) for hyper-resolution forest snow model evaluation G. Mazzotti et al. https://doi.org/10.16904/envidat.162

Forest canopy structure data for radiation and snow modelling (CH/FIN) G. Mazzotti et al. https://doi.org/10.16904/envidat.220

Model code and software

Procedure for new users of Crocus model M. Lafaysse et al. https://opensource.umr-cnrm.fr/projects/snowtools_git/wiki/Procedure_for_new_users

FSMCRO v1.0.0 (v1.0.0) G. Mazzotti https://doi.org/10.5281/zenodo.13881006

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Short summary
As many boreal and alpine forests have seasonal snow, models are needed to predict forest snow under future environmental conditions. We have created a new forest snow model by combining existing, very detailed model components for the canopy and the snowpack. We applied it to forests in Switzerland and Finland and showed how complex forest cover leads to a snowpack layering that is very variable in space and time because different processes prevail at different locations in the forest.
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