EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Linking detailed canopy structure and snow process model representations to explore the dynamics of snowpack properties and ground conditions

Giulia Mazzotti1,2, Jari-Pekka Nousu2,3, Tobias Jonas1, and Matthieu Lafaysse2
Giulia Mazzotti et al.
  • 1WSL Institute for Snow and Avalanche Research SLF, Davos, Davos Dorf, Switzerland (
  • 2Univ. Grenoble Alpes, Univ. de Toulouse, Météo-France, CNRS, CNRM, Centre d’Études de la Neige, Grenoble, France
  • 3Water, Energy and Environmental Engineering Research Unit, University of Oulu, Oulu, Finland

A large portion of boreal and alpine forests of the Northern Hemisphere hosts seasonal snowpacks over multiple months of the year. Rising temperatures and forest disturbances are causing rapid change to these environments; therefore, accurate prediction of forest snow is relevant for a variety of disciplines such as biogeochemistry, ecohydrology, cryospheric, and climate sciences. Research in each of these fields relies on process-based models that are usually discipline-specific, e.g., snow hydrology and land surface models. These models are intended for a broad range of spatiotemporal scales and consequently include canopy and snowpack process representations of varying complexity. Detailed snow physics models that resolve the microstructure of individual snow layers, motivated by avalanche forecasting and snow remote sensing, have existed for years. More recent advances in forest snow process representation and increasing availability of high-resolution canopy structure datasets have led to the development of snow-hydrology models capable of resolving tree-scale processes.

Here, we introduce a new model system that combines concepts from two such sophisticated models: the snowpack representation from Crocus, and the canopy representation from the Flexible Snow Model. We present multi-year simulations at 2-m resolution across sub-alpine and boreal forest landscapes. Spatially explicit simulations allow us to assess the spatio-temporal dynamics of snow properties, ground conditions and land surface states, and to unravel their distinct dependencies on canopy structure heterogeneities at a previously unfeasible level of detail. This work aims to inform and further promote the use of process-based modelling tools in interdisciplinary ecosystem research at the interface between snow and ecosystem science, and in support of environmental change impact studies, management practices and mitigation/adaptation strategies.

How to cite: Mazzotti, G., Nousu, J.-P., Jonas, T., and Lafaysse, M.: Linking detailed canopy structure and snow process model representations to explore the dynamics of snowpack properties and ground conditions, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13878,, 2023.