Modélisation spatialisée de la neige en forêt

Sujet du stage :

At our mid-latitudes, forests of the montane and subalpine zones can have seasonal snow for several months per year. Therefore, accurate representation of snow under forest is important for any hydrological or land surface model applied to such areas. The snow cover evolution in forests can be very different from that seen in nearby open terrain, as trees affect all energy and mass exchange processes between the atmosphere and the underlying snowpack, for example through interception of snowfall in the canopy, shading of the snow surface from solar radiation and emission of thermal radiation by the trees. As forest-snow interactions are strongly dependent on the structure of the forest canopy, their magnitude can vary across scales of just a few meters, especially under discontinuous canopies. This small-scale process variability makes it challenging to parametrize models intended for coarse-resolution applications and evaluate them against point-scale observations (Rutter et al. 2009).

At CNRM, the forest-snow scheme MEB-Crocus (Boone et al. 2017) was recently implemented within the SURFEX Earth surface modelling platform for large scale applications (from about 50 km in General Circulation Models to hectometric resolution for the most-detailed configurations of Numerical Weather Prediction or hydrological modelling systems). By 2026, Météo-France plans to operate a new snow modelling system including MEB-Crocus at 250m resolution over all French mountains. The same modelling system is actively used in several research projects, concerned for example with snow and hydrological modelling over the Chartreuse mountain range in the French Alps (Pauze, 2024). MEB-Crocus has so far mainly been applied and evaluated against point-scale observations at few measurement sites, including Col de Porte in the French Alps (Vincent et al. 2018, Bouchet, 2022), 3 sites in the Canadian boreal forest (Napoly et al., 2020) and 2 sites in Finnish boreal forest (Nousu et al., 2024). Within the framework of a research internship in 2023 at CEN, MEB-Crocus was for the first time applied spatially to a 35 km2 domain in the Eastern Swiss Alps at target resolution and for hydrological years 2017-2023 (Courteaud, 2023). Simulation results were compared to simulations from the Swiss Operational Snow Hydrology Modelling System, FSM2oshd (Mott et al. 2023), which includes state-of-the-art forest snow process representations from Mazzotti et al. (2021), extensively tested and validated in the study area (e.g. Mazzotti et al., 2020). Driven with identical meteorological forcing, this model was used as benchmark for MEB-Crocus simulations. Substantial differences in modelled snow accumulation and patterns were found but could not be attributed to specific processes in the framework of that internship project.

Building on this existing work, the goal of this internship is to further explore the performance of MEB-Crocus at spatially distributed scales and 250m resolution. To this end, the analysis of existing MEB-Crocus and FSM2oshd simulations over the test domain in Switzerland will be expanded to consider individual processes, as well as the impact of vegetation datasets. This analysis will allow identifying model shortcomings, and potentially help suggesting improvements for future model development.

Overall, the work of the internship will include :

1) Analysis of model simulations focusing on differences between MEB-Crocus and FSM2oshd at the level of individual processes (sub-canopy radiations, canopy interception and unloading), aiming to explain resulting differences in SWE dynamics
2) Analysis of model differences as a function of topographic variables, forest density, and meteorological conditions
3) Performing additional model experiments with changed vegetation datasets to quantify the impact of process representation vs. vegetation input datasets.

We are looking for motivated candidates with a strong interest in cryospheric sciences and numerical modelling, proficient with the Python language and Linux environment. Students considering to pursue a PhD after the internship are particularly encouraged to apply, as opportunities are likely and participation in a scientific publication is envisaged.

References :

Boone, A., Samuelsson, P., Gollvik, S., Napoly, A., Jarlan, L., Brun, E., and Decharme, B. : The interactions between soil–biosphere–atmosphere land surface model with a multi-energy balance (ISBA-MEB) option in SURFEXv8 – Part 1 : Model description, Geosci. Model Dev., 10, 843-872, doi : 10.5194/gmd-10-843-2017, 2017.

Bouchet, A. : Observation et modélisation de la neige sous la forêt de l’observatoire nivo-météorologique du Col de Porte (1325 m, Chartreuse). Internship report, Université Grenoble-Alpes / Météo-France, 2022.

Courteaud, A. Comparaison de modèles opérationnels de neige en forêt à résolution intermédiaire en terrain alpin. Projet de Fin d’Études IENM / Météo-France, 2023

Mazzotti. G., Essery, R., Webster, C., Malle, J., and Jonas, T. : Process-level evaluation of a hyper-resolution forest snow model using distributed multi-sensor observations. Water Resources Research, 56, 9, doi : 10.1029/2020WR027572, 2020.

Mazzotti, G., Webster, C., Essery, R., and Jonas, T. : Increasing the Physical Representation of Forest‐Snow Processes in Coarse‐Resolution Models : Lessons Learned From Upscaling Hyper‐Resolution Simulations, Water Resources Research, 57, 5. doi : 10.1029/2020WR029064, 2021.

Mott, R., Winstral, A., Cluzet, B., Helbig, N., Magnusson, J., Mazzotti, G., Quéno, L., Schirmer, M., Webster, C., and Jonas, T. : Operational snow-hydrological modeling for Switzerland, Front. Earth Sci., 11, 1228158, https://doi.org/10.3389/feart.2023.1228158, 2023.

Napoly, A., Boone, A., and Welfringer, T. : ISBA-MEB (SURFEX v8.1) : model snow evaluation for local-scale forest sites, Geosci. Model Dev., 13, 6523–6545, doi : 10.5194/gmd-13-6523-2020, 2020.
 
Nousu, J.-P., Lafaysse, M., Mazzotti, G., Ala-aho, P., Marttila, H., Cluzet, B., Aurela, M., Lohila, A., Kolari, P., Boone, A., Fructus, M., and Launiainen, S. : Modeling snowpack dynamics and surface energy budget in boreal and subarctic peatlands and forests, The Cryosphere, 18, 231–263, https://doi.org/10.5194/tc-18-231-2024, 2024.

Pauze, T. : Vers une modélisation distribuée du manteau neigeux sous forêt sur le massif de la Chartreuse (Alpes, France). Internship report, Ecole Normale Supérieure / Météo-France, 2024.

Rutter, N. et al. : Evaluation of forest snow processes models (SnowMIP2), J. Geophys. Res., 114, doi : 10.1029/2008JD011063, 2009.