Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2545-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-2545-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 May 2020
Research article |
| 15 May 2020
| 15 May 2020
Snow processes in mountain forests: interception modeling for coarse-scale applications
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
David Moeser
USGS New Mexico Water Science Center, Albuquerque, NM, USA
Michaela Teich
Austrian Federal Research Centre for Forests, Natural Hazards and Landscape (BFW), Innsbruck, Austria
Department of Wildland Resources, Utah State University, Logan, UT, USA
Laure Vincent
Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France
Yves Lejeune
Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Études de la Neige, Grenoble, France
Jean-Emmanuel Sicart
Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Institut des Géosciences de l’Environnement (IGE) – UMR 5001, 38000 Grenoble, France
Jean-Matthieu Monnet
Université Grenoble Alpes, INRAE, LESSEM, 38402 St-Martin-d'Hères, France
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Cited
16 citations as recorded by crossref.
- Operational snow-hydrological modeling for Switzerland R. Mott et al. https://doi.org/10.3389/feart.2023.1228158
- The Challenges of Simulating SWE Beneath Forest Canopies are Reduced by Data Assimilation of Snow Depth E. Smyth et al. https://doi.org/10.1029/2021WR030563
- Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities J. Lundquist et al. https://doi.org/10.1002/hyp.14274
- Large‐diameter trees affect snow duration in post‐fire old‐growth forests M. Teich et al. https://doi.org/10.1002/eco.2414
- Evaluating the Effects of UAS Flight Speed on Lidar Snow Depth Estimation in a Heterogeneous Landscape F. Sullivan et al. https://doi.org/10.3390/rs15215091
- Modelling of snow interception on a Japanese cedar canopy based on weighing tree experiment in a warm winter region T. Katsushima et al. https://doi.org/10.1002/hyp.14922
- Toward climate change refugia conservation at an ecoregion scale C. Balantic et al. https://doi.org/10.1111/csp2.497
- Revisiting Forest Effects on Winter Air Temperature and Wind Speed—New Open Data and Transfer Functions M. Klein et al. https://doi.org/10.3390/atmos12060710
- Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set J. Sicart et al. https://doi.org/10.5194/essd-15-5121-2023
- Modeling Forest Snow Using Relative Canopy Structure Metrics C. Moeser et al. https://doi.org/10.3390/w16101398
- Improved Snow-Covered Forest Bidirectional Reflectance Model Incorporating Canopy-Intercepted Snow and Atmospheric Effects S. Chen et al. https://doi.org/10.1109/TGRS.2024.3427818
- ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites A. Napoly et al. https://doi.org/10.5194/gmd-13-6523-2020
- Influence of Slope Aspect and Vegetation on the Soil Moisture Response to Snowmelt in the German Alps M. Schaefer et al. https://doi.org/10.3390/hydrology11070101
- Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt F. Avanzi et al. https://doi.org/10.5194/gmd-15-4853-2022
- Disturbance history and canopy structure drive growing season albedo dynamics in boreal forests I. Aba et al. https://doi.org/10.1016/j.jag.2026.105108
- Object-based ensemble estimation of snow depth and snow water equivalent over multiple months in Sodankylä, Finland D. Brodylo et al. https://doi.org/10.5194/tc-19-6127-2025
16 citations as recorded by crossref.
- Operational snow-hydrological modeling for Switzerland R. Mott et al. https://doi.org/10.3389/feart.2023.1228158
- The Challenges of Simulating SWE Beneath Forest Canopies are Reduced by Data Assimilation of Snow Depth E. Smyth et al. https://doi.org/10.1029/2021WR030563
- Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities J. Lundquist et al. https://doi.org/10.1002/hyp.14274
- Large‐diameter trees affect snow duration in post‐fire old‐growth forests M. Teich et al. https://doi.org/10.1002/eco.2414
- Evaluating the Effects of UAS Flight Speed on Lidar Snow Depth Estimation in a Heterogeneous Landscape F. Sullivan et al. https://doi.org/10.3390/rs15215091
- Modelling of snow interception on a Japanese cedar canopy based on weighing tree experiment in a warm winter region T. Katsushima et al. https://doi.org/10.1002/hyp.14922
- Toward climate change refugia conservation at an ecoregion scale C. Balantic et al. https://doi.org/10.1111/csp2.497
- Revisiting Forest Effects on Winter Air Temperature and Wind Speed—New Open Data and Transfer Functions M. Klein et al. https://doi.org/10.3390/atmos12060710
- Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set J. Sicart et al. https://doi.org/10.5194/essd-15-5121-2023
- Modeling Forest Snow Using Relative Canopy Structure Metrics C. Moeser et al. https://doi.org/10.3390/w16101398
- Improved Snow-Covered Forest Bidirectional Reflectance Model Incorporating Canopy-Intercepted Snow and Atmospheric Effects S. Chen et al. https://doi.org/10.1109/TGRS.2024.3427818
- ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites A. Napoly et al. https://doi.org/10.5194/gmd-13-6523-2020
- Influence of Slope Aspect and Vegetation on the Soil Moisture Response to Snowmelt in the German Alps M. Schaefer et al. https://doi.org/10.3390/hydrology11070101
- Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt F. Avanzi et al. https://doi.org/10.5194/gmd-15-4853-2022
- Disturbance history and canopy structure drive growing season albedo dynamics in boreal forests I. Aba et al. https://doi.org/10.1016/j.jag.2026.105108
- Object-based ensemble estimation of snow depth and snow water equivalent over multiple months in Sodankylä, Finland D. Brodylo et al. https://doi.org/10.5194/tc-19-6127-2025
Saved (final revised paper)
Latest update: 15 Aug 2026
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.
Snow retained in the forest canopy (snow interception) drives spatial variability of the...
