DS0101 -

dEposition, BecOmiNg and impact of light absorbing Impurities in snow – EBONI

Submission summary


Snow cover is a key component of our weather and climate system, in particular through its high ability to reflect sunlight (albedo). Light absorbing impurities in snow such as soot and mineral dust decrease the albedo causing an acceleration of snow metamorphism and melt. Currently, the effect of light absorbing impurities in snow is only partially understood and investigated, as most of the past studies were focused on the direct radiative effect of impurity and only of a few of them were dedicated to the study of the non-direct radiative impact such as direct impact on snow metamorphism. Consequently, the deposition, evolution and impact of impurities in snow are not accurately taken into account in any snow model. The EBONI project aims at better understanding these processes through intensive field and laboratory measurement campaigns, focusing on soot and dust. This crucial knowledge will be transferred to a detailed snow model in order to better quantify and forecast the effect of light absorbing impurities in snow.
Thus the EBONI project aims to implement a detailed snow model able to accurately quantify the radiative and non-radiative impacts of light absorbing impurities in snow enabling the representation of the complex feedbacks between snow, climate and impurities. EBONI is divided into three research actions. Action 1 aims to better understand the effect of light absorbing impurities in snow through intensive measurement campaigns and controlled experiments. Action 2 is dedicated to the implementation of the observed processes in the detailed snow model Crocus and action 3 will use the improved snow model to quantify the impact of impurities on snow melt timing, snowpack stability, run-off, glacier surface mass balance in the French Alps. Lastly, this model will benefit to the simulations of the Greenland Ice Sheet surface mass balance and of its potential contribution to global sea level rise. The EBONI project consequently enables to transfer the knowledge acquired at the micro-scale to the regional-scale effects of impurities in snow and to operational forecasting systems.
The project will cover 48 months and will be mainly conducted at the Centre d’Etudes de la Neige (CNRM, Grenoble, France). It is based on the state-of-the art snow model Crocus and key developers of the model based at CEN are involved in the project. It offers a great opportunity to strengthen interactions between snow researchers at CEN and LGGE (Laboratoire de Glaciologie et de Géophysique de l’Environnement, Grenoble, France) especially within the framework of OSUG (Observatoire des Sciences de l’Univers de Grenoble).
The budget for this proposal is 300 keuros. This includes a 3-year PhD fellowship for actions 1 and 2, and a 18-month research engineer position to facilitate actions 2 and 3. The PI M. Dumont will be 75% involved (36 months) and 7 other permanent researchers from CEN will be involved for a total of 37 more months. The PI has recently taken responsibility as research team leader and the EBONI project will thus crucially contribute to the emergence and growth of the research axes she proposed.
This project addresses questions of direct interest for the society and the media. Our results will therefore be communicated to the public, including through dedicated web pages but also through innovative communication means via Météo-France and CNRS channels.

Project coordination

Marie Dumont (Centre National de la Recherche Scientifique/Centre National de Recherches Météorologiques)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

CNRS/CNRM Centre National de la Recherche Scientifique/Centre National de Recherches Météorologiques

Help of the ANR 299,602 euros
Beginning and duration of the scientific project: October 2016 - 48 Months

Useful links

Explorez notre base de projets financés

 

 

ANR makes available its datasets on funded projects, click here to find more.

Sign up for the latest news:
Subscribe to our newsletter