Articles | Volume 19, issue 4
https://doi.org/10.5194/tc-19-1527-2025
https://doi.org/10.5194/tc-19-1527-2025
Research article
 | 
07 Apr 2025
Research article |  | 07 Apr 2025

Separating the albedo-reducing effect of different light-absorbing particles on snow using deep learning

Lou-Anne Chevrollier, Adrien Wehrlé, Joseph M. Cook, Norbert Pirk, Liane G. Benning, Alexandre M. Anesio, and Martyn Tranter

Data sets

Hyperspectral reflectance measurements A. Wehrlé and L. Chevrollier https://doi.org/10.5281/zenodo.14639602

Model code and software

Snowlaps Python package v0.1.0 A. Wehrlé et al. https://doi.org/10.5281/zenodo.14639602

jmcook1186/biosnicar-py: 2.2 (2.2) J. M. Cook et al. https://doi.org/10.5281/zenodo.15118252

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Short summary
Light-absorbing particles (LAPs) are often present as a mixture on snow surfaces and are important to disentangle because their darkening effects vary but also because the processes governing their presence and accumulation on snow surfaces are different. This study presents a novel method to retrieve the concentration and albedo-reducing effect of different LAPs present at the snow surface from surface spectral albedo. The method is then successfully applied to ground observations on seasonal snow.
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