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Proceedings Paper

Snow reflectivity inversion using Wiscombe-Warren model
Author(s): Ji Liang; Jian Wang; Lizong Wu
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Paper Abstract

Snow reflectivity is a particularly important factor in hydrological model, meteorological model and remote sensing applications. In order for the model to make realistic predictions, the Wiscombe-Warren (WW) model must account for the extreme anisotropy of scattering by snow particles. This is done by using the delta-Eddington approximation and MIE theory for multiple scattering. Measurements of snow reflectivity on wavelength, the solar zenith angle, the ratio of diffuse to direct solar incidence, the effective snow grain size, the snowpack thickness and equivalent depth of liquid water can be interpreted in terms of multiple scattering radiative transfer theory. This paper applies the WW model to inverse snow albedo on the Qilian Mount region, and several discussions of related issues, including (1) inversed the snow reflectivity in the case of the different snow grain sizes, snow thickness, and solar zenith using WW model; (2) it is carried out to evaluate the parameter sensitivity to the snow reflectivity through simulating with the WW model; (3) it is carried out to validate the accuracy of the inversed reflectivity using the WW model through contrast with the measurements of snow reflectance. We found that the great mass of the simulative snow albedo have been less than the measurements of snow reflectance which the snow grain sizes range from 200 to 400μm through comparison of the simulative albedo using WW model with multiply MIE scattering and measurements of snow reflectance from Qilian mountain in China on March 17, 2008.

Paper Details

Date Published:
PDF: 10 pages
Proc. SPIE 7475, Remote Sensing of Clouds and the Atmosphere XIV, 74751B; doi: 10.1117/12.830315
Show Author Affiliations
Ji Liang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Jian Wang, Cold and Arid Regions Environmental and Engineering Research Institute (China)
Lizong Wu, Cold and Arid Regions Environmental and Engineering Research Institute (China)


Published in SPIE Proceedings Vol. 7475:
Remote Sensing of Clouds and the Atmosphere XIV
Richard H. Picard; Klaus Schäfer; Adolfo Comeron; Evgueni I. Kassianov; Christopher J. Mertens, Editor(s)

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