期刊名称：Journal of Advances in Modeling Earth Systems
电子版ISSN：1942-2466
出版年度：2022
卷号：14
期号：1
页码：n/a-n/a
DOI：10.1029/2020MS002431
语种：English
出版社：John Wiley & Sons, Ltd.
摘要：Abstract Accurate snow albedo simulation is a prerequisite for climate models to produce reliable climate prediction. Climate models would benefit from schemes of snowpack radiative transfer that are responsive to changing atmospheric conditions. However, the uncertainties in the narrowband snow optical parameters used by these schemes have not been evaluated. Conventional methods typically compute these narrowband parameters as irradiance‐weighted averages of the spectral snow optical parameters, with the single scattering albedo being additionally weighted by the optically thick snowpack albedo. We first evaluate the effectiveness of the conventional methods as adopted by the widely used Community Land Model (CLM). Snow albedo calculations using the CLM narrowband optical parameters are relatively accurate for very thin snow (e.g., a bias of 0.01 for a 2‐cm snowpack). The error, however, becomes larger as snowpack thickens (with biases of up to 0.05 for semi‐infinite snowpack), because the snow radiative transfer is highly nonlinear and is most significant at wavelengths <1 μm. In this study, we propose a novel method to retrieve broadband optical parameters according to snow radiative transfer theory, reducing the albedo biases to <0.003 for 2 cm snowpacks and <0.005 for thick snowpacks. We find little impact in changing incident spectra on narrowband snow albedo. These newly derived narrowband optical parameters improve snow albedo accuracy by a factor of 10, allowing to trace the impacts of aerosol pollution in snow. The parameters are independent of which two‐stream approximation is used, and are thus applicable to sea ice, glaciers, and seasonal snow cover.
