Quantifying the Radiative Impact of Light-Absorbing Particles on Alpine Snowpack Dynamics

Light-absorbing particles (LAPs) such as black carbon, mineral dust, and organic carbon, when deposited on snow, reduce its surface albedo and increase the absorption of solar radiation. This enhanced absorption accelerates snowmelt and alters snowpack dynamics, particularly during the melt season. Field studies have measured seasonal concentrations of LAPs and confirmed their presence and significant effects on snow albedo. Even small quantities of LAPs can measurably reduce reflectance, particularly in the visible spectrum, and lead to earlier melt-out. A snowpack modeling assessment that isolates the individual and combined effects of each particle type under controlled scenarios can improve our understanding of their specific roles in snowpack evolution. Identifying the contribution of different LAPs to albedo reduction and snowpack dynamics is essential for alpine snow hydrology, where snowmelt timing governs runoff generation and water availability, and helps anticipate how LAPs-driven changes may amplify with climate change and reshape mountain hydrological regimes.

We first developed a one-layer energy budget snowpack model based on HyS (De Michele et al., 2013) and applied it over 18 hydrological years (2005–2023) at the Col de Porte experimental site in the French Alps, using local meteorological forcing. The model, referred to as HyS 3.0, was evaluated against long-term in situ measurements of snow depth and snow water equivalent (SWE), confirming its ability to accurately reproduce seasonal snow accumulation and melt dynamics. Due to its simplicity and low computational cost, HyS 3.0 is also well-suited for hydrological applications and sensitivity testing.

To assess the radiative effects of LAPs, we used field measurements of them along with spectral albedo data from two alpine sites Col de Porte (2014) and Col du Lautaret (2016–2018), capturing contrasting snow conditions. These datasets were used to evaluate BioSNICAR radiative transfer model performance, which computes snow albedo based on impurity concentration, grain size, and snow layer structure. After validation, BioSNICAR was used to generate a suite of LAP scenarios with varying concentrations and compositions. The resulting albedo changes were then used as input to HyS 3.0 to simulate the snowpack response under each scenario.

Results from these simulations revealed measurable changes in snowpack behavior, particularly in melt-out timing and snow specific surface area (SSA), compared to clean-snow conditions. This highlights both the direct radiative and indirect metamorphic effects of LAPs on seasonal snow evolution.

This work is supported by the “Light-Absorbing ParticleS in the Cryosphere and Impact on Water ResourcEs (LAPSE)” project, funded by MUR under the PRIN22 program.