摘要:
雪深( snow depth,SD)和雪水当量( snow water equivalent,SWE)是气候水文研究中的重要参数,在雪灾监测中尤为重要。首先,简要介绍了被动微波遥感SD和SWE反演算法的物理基础———积雪微波辐射传输模型,分析了不同微波频段、不同特点的积雪微波辐射和散射特性。然后,根据前人的研究从数学角度将反演算法分为线性亮温梯度法和基于先验知识法,总结了2类算法的优势和局限性:线性亮温梯度法相对简单、速度快,一般只适用于特定的研究区;先验知识法需要获取研究区的样本数据,并反复训练才能达到较好的精度,但对样本的独立性及其均值差异显著性的要求较高。最后,重点介绍了我国风云三号微波成像仪( FY-3 MWRI)的全球SD和SWE反演算法和针对中国区域的改进算法,并对未来的研究热点进行了展望。
Abstract:
Snow depth ( SD ) and snow water equivalent ( SWE ) are key parameters in hydrology and climate research,especially in the snowstorm monitoring. In this paper,the authors first provided a brief background of the physical basis of the SD and SWE inversion algorithm, i. e. , the snow microwave radiative transfer model, and discussed the snow microwave radiation and scattering in different microwave frequencies. After that, the former snow estimation inversion algorithms were reviewed, which can be categorized into two types: linear brightness temperature gradient and prior knowledge-based from mathematical methods. The advantages and limitations of the two algorithms were summarized. The linear brightness temperature gradient method is easier and runs faster,but it only suits specific study areas. For the establishment of a prior knowledge-based model,researchers need to obtain the sample data and repeated training so as to achieve higher accuracy. However, the model requires the independence and significant mean difference of the samples. The SD and SWE inversion algorithms for Fengyun-3 microwave radiation imager ( FY-3 MWRI) were described,which are composed of global business algorithm and improved regional algorithm for China. Finally, the research focuses in this aspect were predicted.
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