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

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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.

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