Abstract
The original kernel-driven bidirectional reflectance distribution function (BRDF) models were developed based on soil-vegetation systems. To further improve the ability of the models to characterize the snow surface scattering properties, a snow kernel was derived from the asymptotic radiative transfer (ART) model and used in the kernel-driven BRDF model framework. However, there is a need to further evaluate the influence of using this snow kernel to improve the original kernel-driven models in snow albedo retrieval applications. The aim of this study is to perform such an evaluation using a variety of snow BRDF data. The RossThick-Roujean (RTR) model is used as a framework for taking in the new snow kernel (hereafter named the RTS model) since the Roujean geometric-optical (GO) kernel captures a neglectable hotspot effect and represents a more prominent dome-shaped BRDF, especially at a small solar zenith angle (SZA). We obtained the following results: (1) The RTR model has difficulties in reconstructing the snow BRDF shape, especially at large SZAs, which tends to underestimate the reflectance in the forward direction and overestimate reflectance in the backward direction for various data sources. In comparison, the RTS model performs very well in fitting snow BRDF data and shows high accuracy for all data. (2) The RTR model retrieved snow albedos at SZAs = 30°–70° are underestimated by 0.71% and 0.69% in the red and near-infrared (NIR) bands, respectively, compared with the simulation results of the bicontinuous photon tracking (bic-PT) model, which serve as “real” values. However, the albedo retrieved by the RTS model is significantly improved and generally agrees well with the simulation results of the bic-PT model, although the improved model still somewhat underestimates the albedo by 0.01% in the red band and overestimates the albedo by 0.05% in the NIR band, respectively, at SZAs = 30°–70°, which may be negligible. (3) The albedo derived by these two models shows a high correlation (R2 > 0.9) between the field-measured and Polarization and Directionality of the Earth's Reflectances (POLDER) data, especially for the black-sky albedo. However, the albedo derived using the RTR model is significantly underestimated compared with the RTS model. The RTR model underestimates the black-sky albedo (white-sky albedo) retrievals by 0.62% (1.51%) and 0.93% (2.08%) in the red and NIR bands, respectively, for the field-measured data. The shortwave black-sky and white-sky albedos derived using the RTR model for the POLDER data are underestimated by 1.43% and 1.54%, respectively, compared with the RTS model. These results indicate that the snow kernel in the kernel-driven BRDF model frame is more accurate in snow albedo retrievals and has the potential for application in the field of the regional and global energy budget.
Highlights
Snow albedo plays a crucial role in earth-atmosphere systems through its effects on the regional and global energy budget [1,2,3,4,5,6,7]
The new snow kernel improved snow bidirectional reflectance distribution function (BRDF) model has been compared with full radiative transfer simulations performed using SCIATRAN [40], and the results show that the model more accurately characterizes the anisotropic properties of snow, especially in forward directions
The equivalent grain radius is 0.1 mm, the b parameter is 1, and the snow density is 0.1 g/cm3. This aims to display the difference of these two kernel-driven models in fitting snow BRDF simulation data at three typical solar zenith angle (SZA) (i.e., SZAs = 0◦, 40◦ and 70◦) by the bicontinuous photon tracking (bic-PT) model
Summary
Snow albedo plays a crucial role in earth-atmosphere systems through its effects on the regional and global energy budget [1,2,3,4,5,6,7]. Snow with a high albedo value determines the amount of solar energy absorbed at the surface, which has a powerful positive feedback effect on climate change [1,3,4,6]. Snow albedo is a fundamental component of the surface energy balance and has a critical effect on the climate system and hydrological studies [8]. The required absolute accuracy of surface albedo is approximately 0.02–0.05 within 5–10 years for climate models [9,10,11,12], and Barry recommends that the demanded accuracy of 0.02 for the snow albedo is reasonable [7,11]. The intrinsic reflectance anisotropy of the snow surface must first be considered to retrieve snow albedo with a high retrieval accuracy [13], which can be quantified by the bidirectional reflectance distribution function (BRDF) [14]. An accurate description of snow forward-scattering properties is essential for snow reflectance models in estimating snow albedo
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