Physics‐Based Narrowband Optical Parameters for Snow Albedo Simulation in Climate Models. (13th January 2022)

• Record Type: Journal Article
• Authors: Wang, Wenli; He, Cenlin; Moore, John; Wang, Gongxue; Niu, Guo‐Yue
• Is Part Of: Journal of advances in modeling earth systems. Volume 14:Number 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-13
• Subjects: snow -- albedo -- modeling -- radiative transfer -- Mie scattering -- narrowband; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2020MS002431
• Languages: English
• ISSNs: 1942-2466

Abstract

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. Plain Language Summary: Snow albedo describes how much sunlight is reflected at the snow surface, which depends on how deep the sunlight penetrates the snowpack. Radiative transfer schemes describe sunlight absorption with snow optical depth. Snow radiative transfer schemes used in climate models make approximations using narrow‐band snow optical properties for computational efficiency. A conventional way to derive the narrowband parameters is to average the wavelength‐dependent values weighted by the incident solar spectrum. This approach produces snow albedo biases of up to 0.01 for shallow snowpacks and biases of up to 0.05 for thick snow. Such precision is not accurate enough for resolving the strongly positive snow‐climate feedback when albedo decreases due to light‐absorbing particles. This can amount to 0.01 over some "hot spots, " which are climatically significant and have received increasing attention. Here, we provide a new set of narrowband optical parameters that improve the snow albedo accuracy by a factor of 10. Key Points: The semi‐empirical method used by Community Land Model to calculate narrowband snow optical parameters can produce errors that grow with snow mass The albedo errors stem from the relatively small biases in narrowband optical parameters that are amplified by nonlinear radiative transfer We propose a new set of narrowband snow optical parameters based on snow radiative transfer theory to improve albedo calculation accuracy