Combined effect of algae and dust on snow spectral and broadband albedo

Di Mauro, B.; Garzonio, R.; Ravasio, C.; Orlandi, V.; Baccolo, G.; Gilardoni, S.; Remias, D.; Leoni, B.; Rossini, M.; Colombo, R.

doi:10.1016/j.jqsrt.2024.108906

Cited by 6 publications

(2 citation statements)

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“…More importantly it induces fast structural changes of the microstructure (Colbeck, 1982;Brun et al, 1989), usually leading to a rapid decrease in SSA and thus in albedo . Impurities, whether they are of mineral, organic, or biological origin, can also greatly affect the absorption in the visible and drive both the albedo and the penetration (Chevrollier et al, 2022;Réveillet et al, 2022;Di Mauro et al, 2024). At last, the illumination characteristics (angular and spectral distributions) also play a role because the snow reflectance depends on the wavelength and the incidence angle.…”

Section: Introductionmentioning

confidence: 99%

“…13 shows a comparison of different dust types (different origins and sizes) and models. The concentration is 100 µg g −1 , which is realistic in alpine snow Di Mauro et al, 2024). The agreement is again fairly good between TARTES and SNICAR-ADv3 which results from the similar MAE values for the "Libya PM2.5" and "Algeria PM.25" dusts ( 400 nm =110 and 73 m 2 kg −1 ) used in TARTES, compared to the values for Sahara used in SNICAR-ADv3 (Flanner et al, 2021, table 2, figure 3).…”

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confidence: 99%

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Simulation of snow albedo and solar irradiance profile with the two-stream radiative transfer in snow (TARTES) v2.0 model

Picard,

Libois

2024

Preprint

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Abstract. The Two-streAm Radiative TransfEr in Snow (TARTES) model computes the spectral albedo and the profiles of spectral absorption, irradiance and actinic fluxes for a multi-layer plane-parallel snowpack. Each snow layer is characterized by its specific surface area, density, and impurities content, in addition to shape parameters. In the landscape of snow optical numerical models, TARTES distinguishes itself by taking into account different shapes of the particles through two shape parameters, namely the absorption enhancement parameter B and the asymmetry factor g. This is of primary importance as recent studies working at the microstructure level have demonstrated that snow does not behave as a collection of equivalent ice spheres, a representation widely used in other models. Instead, B and g take specific values that do not correspond to any simple geometrical shape, which leads to the concept of "optical shape of snow". Apart from this specificity, TARTES combines well established radiative transfer principles to compute the scattering and absorption coefficients of pure or polluted snow, and the δ-Eddington two-stream approximation to solve the multi-layer radiative transfer equation. The model is implemented in Python, but conducting TARTES simulations is also possible without any programming through the SnowTARTES web application, making it very accessible to non-experts and for teaching purposes. Here, after describing the theoretical and technical details of the model, we illustrate its main capabilities and present some comparisons with other common snow radiative transfer models (AART, DISORT-Mie, SNICAR-ADv3) as a validation procedure. Overall the agreement on the spectral albedo, when in compatible conditions (i.e. with spheres), is usually within 0.02, and is better in the visible and near-infrared compared to longer wavelengths of the solar domain.

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