Snow is a fundamental component of the climate system. It is also an important part of the planet's hydrological cycle. Accordingly, the investigation of its light scattering properties is essential for remote sensing applications employed in the estimation of changes in the current amount of snowpack. These wide-scale environmental changes are key indicators of future climate events affecting global sustainability. Viewed in this context, computational simulations of light interactions with snow can be used to increase the effectiveness-to-cost ratio of remote sensing initiatives in this area. More specifically, by enabling a controlled assessment of the effects of snow granular structure and composition parameters on its light reflection and transmission profiles, these simulations can be instrumental in the high-fidelity interpretation of data remotely acquired from snow-covered landscapes that pose sizable challenges for field work. In order to contribute to these interdisciplinary research efforts, this paper presents a novel light transport model for snow that can predictively simulate the spectral and spatial distributions of light interacting with this ubiquitous particulate material. While the former radiometric responses are quantified in terms of hyperspectral reflectance and transmittance, the latter are quantified in terms of BSDF (bidirectional scattering distribution function). The proposed model employs a first-principles simulation approach that accounts for the positional dependence of the scattered light in the quantification of its spatial distribution. Thus, this distribution can also be expressed in terms of BSSDF (bidirectional surface-scattering distribution function). The predictive capabilities of the proposed model are quantitatively and qualitatively evaluated by comparing modeled results with measured data obtained from in situ experiments and phenomenological traits reported in the literature, respectively.

雪是气候系统的基本组成部分。它也是地球水文循环的重要组成部分。因此，对其光散射特性的研究对于估算当前积雪量变化所采用的遥感应用至关重要。这些广泛的环境变化是影响全球可持续性的未来气候事件的关键指标。在这种情况下，光与雪相互作用的计算模拟可用于提高该地区遥感计划的实效成本比。更具体地说，通过对雪粒状结构和组成参数对其光反射和透射剖面的影响进行受控评估，这些模拟有助于高保真解释从冰雪覆盖的景观中远程获取的数据，这给野外工作带来了巨大挑战。为了促进这些跨学科的研究工作，本文提出了一种新颖的雪光传输模型，该模型可以预测性地模拟与这种普遍存在的颗粒物质相互作用的光的光谱和空间分布。前者的辐射响应是根据高光谱反射率和透射率来量化的，而后者是根据BSDF（双向散射分布函数）来量化的。所提出的模型采用第一原理模拟方法，该方法考虑了散射光在其空间分布的量化中的位置依赖性。从而，该分布也可以用BSSDF（双向表面散射分布函数）表示。通过比较建模结果和从中获得的测量数据，定量和定性地评估了所提出模型的预测能力。文献中分别报道了原位实验和现象学特征。