Abstract
Intrinsic albedo is the bihemispherical reflectance of a substance with a smooth surface. Conversely, the apparent albedo is the bihemispherical reflectance of the same substance with a rough surface. For snow, the surface is often rough, and these two optical quantities have different uses: intrinsic albedo is used in scattering equations whereas apparent albedo should be used in energy balance models. Complementing numerous studies devoted to surface roughness and its effect on snow reflectance, this work analyzes a timeseries of intrinsic and apparent snow albedos over a season at a sub-alpine site using an automated terrestrial laser scanner to map the snow surface topography. An updated albedo model accounts for shade, and in situ albedo measurements from a field spectrometer are compared to those from a spaceborne multispectral sensor. A spectral unmixing approach using a shade endmember (to address the common problem of unknown surface topography) produces grain size and impurity solutions; the modeled shade fraction is compared to the intrinsic and apparent albedo difference. As expected and consistent with other studies, the results show that intrinsic albedo is consistently greater than apparent albedo. Both albedos decrease rapidly as ablation hollows form during melt, combining effects of impurities on the surface and increasing roughness. Intrinsic broadband albedos average 7 % greater than apparent albedos, with the difference being about 6 % in the near-infrared or 3–4 % if the average (planar) topography is known and corrected. Field measurements of spectral surface reflectance confirm that multispectral sensors see the apparent albedo but lack the spectral resolution to distinguish between darkening from ablation hollows versus low concentrations of impurities. In contrast, measurements from the field spectrometer have sufficient resolution to discern darkening from the two sources. Based on these results, conclusions are: 1) impurity estimates from multispectral sensors are only reliable for relatively dirty snow with high snow fraction; 2) a shade endmember must be used in spectral mixture models, even for in situ spectroscopic measurements; and 3) snow albedo models should produce apparent albedos by accounting for the shade fraction. The conclusion re-iterates that albedo is the most practical snow reflectance quantity for remote sensing.
Highlights
IntroductionSnow albedo plays an important role in Earth's climate and hydrology. For example, a small (1.5% to 3.0%) decrease in snow albedo over the Northern Hemisphere is twice as effective as a doubling of CO2 at raising global air temperature (Hansen and Nazarenko, 2004)
Intrinsic albedo is the bihemispherical reflectance of a substance with a smooth surface
As expected and consistent with other studies, the results show that intrinsic albedo is consistently greater than apparent albedo
Summary
Snow albedo plays an important role in Earth's climate and hydrology. For example, a small (1.5% to 3.0%) decrease in snow albedo over the Northern Hemisphere is twice as effective as a doubling of CO2 at raising global air temperature (Hansen and Nazarenko, 2004). MODIS measurements of snow albedo that comprise the National Solar Radiation Database have been found to be positively-biased because they fail to account for surface roughness (Gueymard et al, 2019) Both albedos should be studied, as apparent and intrinsic albedos have different uses. Most snow albedo models follow approaches developed four decades ago, based on radiative transfer (Warren, 1982) These models provide intrinsic albedos with lighting conditions controlled by snow properties and illumination angles for a 55 smooth surface; they have been modified to consider grain shape (Libois et al, 2013), slopes (Picard et al, 2020), snow structure (Kaempfer et al, 2007), direct and indirect effects of light-absorbing particles (Skiles and Painter, 2019;Picard et al., 2020), and vertical heterogeneity (Zhou et al, 2003). None of these studies have tracked the snow surface topography throughout a snow season, nor have they examined the effects of snow surface topography on spectral mixture analysis
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