Enhanced snow absorption and albedo reduction by dust-snow internal mixing: Modeling and parameterization
We extend a stochastic aerosol-snow albedo model to explicitly simulate dust internally/externally mixed with snow grains of different shapes and for the first time quantify the combined effects of dust-snow internal mixing and snow nonsphericity on snow optical properties and albedo. Dust-snow internal/external mixing significantly enhances snow single-scattering coalbedo and absorption at wavelengths of <1.0 mu m, with stronger enhancements for internal mixing (relative to external mixing) and higher dust concentrations but very weak dependence on snow size and shape variabilities. Compared with pure snow, dust-snow internal mixing reduces snow albedo substantially at wavelengths of <1.0 mu m, with stronger reductions for higher dust concentrations, larger snow sizes, and spherical (relative to nonspherical) snow shapes. Compared to internal mixing, dust-snow external mixing generally shows similar spectral patterns of albedo reductions and effects of snow size and shape. However, relative to external mixing, dust-snow internal mixing enhances the magnitude of albedo reductions by 10%-30% (10%-230%) at the visible (near-infrared) band. This relative enhancement is stronger as snow grains become larger or nonspherical, with comparable influences from snow size and shape. Moreover, for dust-snow external and internal mixing, nonspherical snow grains have up to similar to 45% weaker albedo reductions than spherical grains, depending on snow size, dust concentration, and wavelength. The interactive effect of dust-snow mixing state and snow shape highlights the importance of accounting for these two factors concurrently in snow modeling. For application to land/climate models, we develop parameterizations for dust effects on snow optical properties and albedo with high accuracy.
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https://n2t.org/ark:/85065/d7t156zv
eng
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2016-01-01T00:00:00Z
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2019-11-24T00:00:00Z
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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