Articles | Volume 19, issue 2
https://doi.org/10.5194/tc-19-769-2025
https://doi.org/10.5194/tc-19-769-2025
Research article
 | 
20 Feb 2025
Research article |  | 20 Feb 2025

Improving large-scale snow albedo modeling using a climatology of light-absorbing particle deposition

Manon Gaillard, Vincent Vionnet, Matthieu Lafaysse, Marie Dumont, and Paul Ginoux

Related authors

Saharan dust impacts on the surface mass balance of Argentière Glacier (French Alps)
Léon Roussel, Marie Dumont, Marion Réveillet, Delphine Six, Marin Kneib, Pierre Nabat, Kevin Fourteau, Diego Monteiro, Simon Gascoin, Emmanuel Thibert, Antoine Rabatel, Jean-Emmanuel Sicart, Mylène Bonnefoy, Luc Piard, Olivier Laarman, Bruno Jourdain, Mathieu Fructus, Matthieu Vernay, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2025-1741,https://doi.org/10.5194/egusphere-2025-1741, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Radar-based high-resolution ensemble precipitation analyses over the French Alps
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025,https://doi.org/10.5194/amt-18-1731-2025, 2025
Short summary
Quantifying radiative effects of light-absorbing particle deposition on snow at the SnowMIP sites
Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova
The Cryosphere, 19, 1313–1334, https://doi.org/10.5194/tc-19-1313-2025,https://doi.org/10.5194/tc-19-1313-2025, 2025
Short summary
Northern Hemisphere in situ snow water equivalent dataset (NorSWE, 1979–2021)
Colleen Mortimer and Vincent Vionnet
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-602,https://doi.org/10.5194/essd-2024-602, 2025
Revised manuscript under review for ESSD
Short summary
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024,https://doi.org/10.5194/tc-18-5685-2024, 2024
Short summary

Related subject area

Discipline: Snow | Subject: Numerical Modelling
Quantifying radiative effects of light-absorbing particle deposition on snow at the SnowMIP sites
Enrico Zorzetto, Paul Ginoux, Sergey Malyshev, and Elena Shevliakova
The Cryosphere, 19, 1313–1334, https://doi.org/10.5194/tc-19-1313-2025,https://doi.org/10.5194/tc-19-1313-2025, 2025
Short summary
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024,https://doi.org/10.5194/tc-18-5685-2024, 2024
Short summary
Modelling snowpack on ice surfaces with the ORCHIDEE land surface model: application to the Greenland ice sheet
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024,https://doi.org/10.5194/tc-18-5067-2024, 2024
Short summary
Exploring the decision-making process in model development: focus on the Arctic snowpack
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024,https://doi.org/10.5194/tc-18-4671-2024, 2024
Short summary
Exploring the potential of forest snow modeling at the tree and snowpack layer scale
Giulia Mazzotti, Jari-Pekka Nousu, Vincent Vionnet, Tobias Jonas, Rafife Nheili, and Matthieu Lafaysse
The Cryosphere, 18, 4607–4632, https://doi.org/10.5194/tc-18-4607-2024,https://doi.org/10.5194/tc-18-4607-2024, 2024
Short summary

Cited articles

Armstrong, R. and Brun, E.: Snow and climate: physical processes, surface energy exchange and modelling, J. Glaciol., 55, 384–384, https://doi.org/10.3189/002214309788608741, 2009. a
Baladima, F., Thomas, J. L., Voisin, D., Dumont, M., Junquas, C., Kumar, R., Lavaysse, C., Marelle, L., Parrington, M., and Flemming, J.: Modeling an extreme dust deposition event to the French alpine seasonal snowpack in April 2018: Meteorological context and predictions of dust deposition, J. Geophys. Res.-Atmos., 127, e2021JD035745, https://doi.org/10.1029/2021JD035745, 2022. a, b
Baron, M.: Modelling soil thermal regimes in high altitue open environement of the french Alps : effect of wind-induced snow transport and vegetation, PhD thesis, Universite Grenoble Alpes, Grenoble, France, 2023 (in French). a
Beres, N. D., Sengupta, D., Samburova, V., Khlystov, A. Y., and Moosmüller, H.: Deposition of brown carbon onto snow: changes in snow optical and radiative properties, Atmos. Chem. Phys., 20, 6095–6114, https://doi.org/10.5194/acp-20-6095-2020, 2020. a
Bessagnet, B., Menut, L., Colette, A., Couvidat, F., Dan, M., Mailler, S., Létinois, L., Pont, V., and Rouïl, L.: An evaluation of the CHIMERE Chemistry Transport Model to simulate dust outbreaks across the Northern Hemisphere in March 2014, Atmosphere, 8, 251, https://doi.org/10.3390/atmos8120251, 2017. a
Download
Short summary
This study presents an efficient method to improve large-scale snow albedo simulations by considering the spatial variability in light-absorbing particles (LAPs) like black carbon and dust. A global climatology of LAP deposition was created and used to optimize a parameter in the Crocus snow model. Testing at 10 global sites improved albedo predictions by 10 % on average and over 25 % in the Arctic. This method can enhance other snow models' predictions without complex simulations.

Share