Quantification of the radiative impact of light-absorbing particlesduring two contrasted snow seasons at Col du Lautaret (2058 m a.s.l., French Alps)

Abstract. The presence of light-absorbing particles (LAPs) in snow leads to a decrease in shortwave albedo, affecting the surface energy budget. Precisely quantifying the impacts of LAPs on snowpack evolution is crucial to characterise the spatio-temporal variability of snowmelt and assess snow albedo feedbacks in detail. However, the understanding of the impacts of LAPs is hampered by the lack of dedicated datasets, as well as the scarcity of models able to represent the interactions between LAPs and snow metamorphism. The present study aims to address both these limitations by introducing a survey of LAP concentrations over two snow seasons in the French Alps, as well as an estimation of their impacts based on the Crocus snowpack model that represents the complex interplays between LAP dynamics and snow metamorphism. First, we present a unique dataset collected at the Col du Lautaret (2058 m a.s.l; French Alps) for the two snow seasons 2016–2017 and 2017–2018. This dataset consists of spectral albedo measurements (manual and automated), vertical profiles of snow specific surface area (SSA), density, and concentrations of refractive Black Carbon (rBC), Elemental Carbon (EC) and mineral dust. Spectral albedo data are processed to estimate near-surface SSA and LAP absorption-equivalent concentrations near the surface of the snowpack. These estimates are then compared to chemical measurements of dust and BC concentrations, as well as to SSA measurements acquired by near-infrared reflectometry. Our dataset highlights large discrepancies between the two measurement techniques of BC concentrations, with EC concentrations being one order of magnitude higher than rBC measurements. In view of LAP absorption inferred from albedo measurements, the mass absorption efficiency (MAE) of BC used in our study (11.25 g m−2 at 550 nm) is more appropriate for EC measurements than for rBC ones. Second, we present ensemble snowpack simulations of ESCROC – the multi-physics version of the detailed snowpack model Crocus – forced with in-situ meteorological data as well as dust and BC deposition fluxes from the ALADIN-Climate atmospheric model. The results of these simulations are compared to the near-surface properties estimated from automatic albedo measurements, showing that the temporal variations of near-surface LAP concentration and SSA are correctly reproduced. The impact of dust and BC on our simulations is estimated by comparing this ensemble to a similar ensemble that does not account for LAPs. The seasonal radiative forcing of LAPs is 1.33 times higher for the 2017–2018 snow season than for the 2016–2017 one, highlighting a strong variability between these two seasons. However, the shortening of the snow season caused by LAPs are similar with 10 ± 5 and 11 ± 1 days for the first and the second snow seasons respectively. This counter-intuitive result is attributed to two small snowfalls at the end of the first season and highlights the importance to account for meteorological conditions to correctly predict the impact of LAPs. The strong variability of season shortening caused by LAPs in the multi-physics ensemble for the first season also points out the sensitivity of model-based estimations of LAP impact to modelling uncertainties of other processes. Finally, the indirect impact of LAPs (i.e. the enhancement of energy absorption due to acceleration of the metamorphism by LAPs) is negligible for the two years considered here, contrary to what was found in previous studies for other sites. This finding is mainly attributed to the meteorological conditions of the two studied snow seasons.