Measurements of light-absorbing particles in snow across the Arctic, North America, and China: effects on surface albedo

Using field observation, we perform radiative transfer calculations on snowpacks in the Arctic, China, and North America to quantify the impact of light-absorbing particles (LAPs) on snow albedo and its sensitivity to different factors. For new snow, the regional-averaged albedo reductions caused by...

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Bibliographic Details
Main Authors: Dang, Cheng, Warren, Stephen G., Fu, Qiang, Doherty, Sarah J., Sturm, Matthew
Format: Article in Journal/Newspaper
Language:English
Published: Journal of Geophysical Research [in revision] 2017
Subjects:
Online Access:http://hdl.handle.net/1773/39741
Description
Summary:Using field observation, we perform radiative transfer calculations on snowpacks in the Arctic, China, and North America to quantify the impact of light-absorbing particles (LAPs) on snow albedo and its sensitivity to different factors. For new snow, the regional-averaged albedo reductions caused by all LAPs in the Arctic, North America, and China are 0.009, 0.012, and 0.077, respectively, of which the albedo reductions caused by black carbon (BC) alone are 0.005, 0.005, and 0.031, corresponding to a positive radiative forcing of 0.06, 0.3, and 3 Wm-2. The albedo reduction for old melting snow is larger by a factor of 2 than for the same particulate concentrations in new snow; this leads to 3 – 8 times larger radiative forcing, in part due to higher solar irradiance in the melting season. These calculations used ambient snowpack properties; if all snowpacks were instead assumed to be optically thick, the albedo reduction would be 20-50% larger for new snow in the Arctic and North America and 120-300% larger for old snow. Accounting for non-BC LAPs reduces the albedo reduction by BC in the Arctic, North America, and China by 32%, 29% and 70% respectively for new snow and 11%, 7% and 51% for old snow. BC-in-snow albedo reduction computed using two-layer model agrees reasonably with that computed using multi-layer model. Biases in BC concentration or snow depth often lead to nonlinear biases in BC-induced albedo reduction.