Algorithm for retrieval of the effective snow grain size and pollution amount from satellite measurements
Algorithm for retrieval of the effective snow grain size and pollution amount from satellite measurements
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DOI：
10.1016/j.rse.2011.06.001
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发表时间：
2011-10
影响因子：
13.5
通讯作者：
E. Zege;I. Katsev;A. Malinka;A. Prikhach;G. Heygster;H. Wiebe
中科院分区：
文献类型：
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作者：
E. Zege;I. Katsev;A. Malinka;A. Prikhach;G. Heygster;H. Wiebe
本文提出了一种从卫星观测数据反演有效雪粒度和污染量的算法。以及我们以前的版本（Zege等人，2008年，1998年），新的算法是基于渐近辐射传输理论内的雪反射率的解析解。SGSP算法不使用任何关于雪粒形状的假设，并允许雪包双向反射分布函数（BRDF）。该算法包括一个新的大气校正程序，允许雪BRDF。此SGSP算法已被彻底验证与计算机模拟。研究了它对大气模式的敏感性。结果表明，由于气溶胶和分子大气模型中的不确定性的雪特征检索的不准确性是可以忽略不计的，相比，由于测量误差至少为气溶胶负载典型的极地地区。SGSP的显着优势，传统的算法，它使用先验假设粒子形状和（或）不允许的BRDF的个人雪包，是发达的检索仍然工作在低太阳高度，这是典型的极地地区。
We present an algorithm for retrieval of the effective Snow Grain Size and Pollution amount (SGSP) from satellite measurements. As well as our previous version (Zege et al., 2008, 1998), the new algorithm is based on the analytical solution for snow reflectance within the asymptotic radiative transfer theory. The SGSP algorithm does not use any assumptions on snow grain shape and allows for the snow pack bidirectional reflectance distribution function (BRDF). The algorithm includes a new atmospheric correction procedure that allows for snow BRDF. This SGSP algorithm has been thoroughly validated with computer simulations. Its sensitivity to the atmosphere model has been investigated. It is shown that the inaccuracy of the snow characteristic retrieval due to the uncertainty in the aerosol and molecular atmosphere model is negligible, as compared to that due to the measurement errors at least for aerosol loads typical for polar regions. The significant advantage of the SGSP over conventional algorithms, which use a priori assumptions about particle shape and (or) not allow for the BRDF of the individual snow pack, is that the developed retrieval still works at low sun elevations, which are typical for polar regions.