The snow cover and the atmosphere interact strongly through the energy and matter transfers across their interface. The main interaction and the most well-known, results from the strong difference in albedo between snow and other surface types. For this reason, the extent of the snow-covered areas on Earth is systematically monitored, and the presence of snow is explicitly accounted for in numerical models for weather and climate forecasts. However, the internal properties of the snow cover such as the grain size, albedo, density and thermal conductivity are generally overlooked. Yet, these properties vary significantly over time, influenced by atmospheric conditions and, in return, they have a strong impact on the atmosphere, notably through the radiative budget. Many process chains thus form snow-climate feedback loops. Although, the principle of these interactions is known, their quantification is poor due to the lack of long-term observations on the internal properties of the snowpack. The goal of this project is to fill this deficit by 1) developing a new generation of instruments (MONISNOW) capable of observing the physical properties of the snow and of monitoring their evolution in the changing climate of the XXIst century, then by 2) exploiting these new observations to improve the formulations of snow metamorphism and of energy and matter fluxes across the surface. The ultimate goal is to integrate these improvements into general circulation models, which will provide a far better quantification of certain snow-climate feedback loops. The new-generation MONISNOW instruments will be capable of continuously measuring the grain size, surface roughness, spectral albedo, solar energy penetration depth, as well as temperature and thermal conductivity profiles. Together, these measurements form a coherent dataset to characterize the variables driving the energy fluxes and snow metamorphism. The main challenge of the project is to design the instrument for measuring in situ at several depths within the snowpack the grain size and density, and how they evolve. This instrument will use an optical sounding method, benefiting from the recent but recognized expertise of the project team. This development will require preliminary laboratory experiments and simulations with an optical model that will be refined as the project progresses. The instruments will be deployed in the Antarctic, the Alps and in Canada to cover a wide range of climate conditions. The MONISNOW data will be invaluable input for improving the Crocus modeling of metamorphism as well as energy and matter fluxes. The Crocus model was developed 20 years ago by the Centre d’Etude de la Neige (snow research center), and its metamorphism scheme is currently undergoing a major overhaul. With this data, the scheme will be tested with unprecedented accuracy because it will provide 1) a comprehensive variable set, and 2) the continuous evolution of these variables over time. In parallel, we will refine the formulation of the radiation budget and metamorphism near the surface, while taking into account the impact of the surface states (roughness, frost), the penetration of solar energy and the water vapor transfers. These processes that take place at the snow-atmosphere interface have strong mutual interactions and are involved in many snow-climate feedback loops. These improvements of the Crocus snow model, which is now an inherent part of the surface schemes of Météo-France will open the way for further refinements of climate simulations in snow-covered regions.

The vast majority of stars are born in associations or clusters rather than in isolation. To understand the general rules that govern how stars form, it is therefore crucial to decode fully the formation and evolution of young stellar clusters. This is the main goal of this project, which will focus more specifically on the early dynamical evolution of stellar systems. To pursue these objectives, we propose to bring together theoretical and observational expertise drawn from two research groups well established in their respective field: the Stellar Formation group in Grenoble, which has a vast experience in young cluster observations; and the Galaxy team in Strasbourg, which has strong expertise in N-body numerical simulations. Thanks to the recruitment of an ANR postdoc, this project will allow to develop a new expertise on numerical simulation at LAOG that is essential to interpret the observations of young stellar clusters.