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Estimation of Snow Water Equivalent from Passive Microwave Remote Sensing Data (SSM/I) in Tibetan Plateau

机译:藏高原无源微波遥感数据(SSM / I)估算雪水

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So far, there is not an operational algorithm to estimate the snow water equivalent from passive microwave remote sensing data (SSM/I) in the Tibetan Plateau. In this study the SSM/I brightness temperature data in January 1993 are used to estimate SWE at this region. The frequencies of SSM/I data are used to retrieval snow depth are 19 and 37GHz in horizontal polarization. The results have shown all existing algorithms overestimated the snow depth in the Tibetan plateau. This paper analyzed the reasons of overestimation of snow depth from several aspects, such as the water content of snowpack, large water bodies (e.g. lakes), and the abnormal field snow depth data. After eliminating some futile data (including the passive microwave brightness temperature values and snow depth data in the weather stations), an improved algorithm has been established to retrieval the snow depth from the difference of 19 and 37GHz brightness temperature in horizontal polarization. Here, snow density is obtained by a time function of fresh snow density. The snow depth and density were converted to the snow water equivalent, and are regarded as the ground truth. In finally, the TB vertically polarized differences of 19 and 37GHz are regressed with the SWE. Using the statistical method, a simple and practical algorithm is developed to estimate the snow water equivalent from the differences of 19 and 37GHz in vertical polarization.
机译:到目前为止,没有操作算法,可以估计藏高高原的被动微波遥感数据(SSM / I)的雪水等同于雪水。在本研究中,1993年1月的SSM / I亮度温度数据用于估计该地区的SWE。 SSM / I数据的频率用于检索雪深度是水平极化的19和37GHz。结果表明了所有现有的算法高估了藏高原中的雪深。本文分析了从几个方面的雪深度高估的原因,例如积雪的含水量,大水体(例如湖泊)和异常场雪深度数据。在消除了一些徒劳的数据(包括天气站中的被动微波亮度温度值和雪深)之后,已经建立了一种改进的算法,以从水平极化中的19和37GHz亮度温度的差异检索雪深。在这里,通过新雪密度的时间函数获得雪密度。雪深和密度被转换为雪水等价物,并被视为实际的真理。最后,用SWE回归19和37GHz的TB垂直极化差异。使用统计方法,开发了一种简单实用的算法,以估算垂直极化中19和37GHz的差异的雪水。

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