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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >A parameterized multiple-scattering model for microwave emission from dry snow
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A parameterized multiple-scattering model for microwave emission from dry snow

机译:干燥雪中微波发射的参数化多重散射模型

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Snow water equivalent (SWE) is one of the key parameters for many applications in climatology, hydrology, and water resource planning and management. Satellite-based passive microwave sensors have provided global, long-term observations that are sensitive to SWE. However, the complexity of the snowpack makes modeling the microwave emission and inversion of a model to retrieve SWE difficult, with the consequence that retrievals are sometimes incorrect. Here we develop a parameterized dry snow emission model for analyzing passive microwave data, including those from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) at 10.65 GHz, 18.7 GHz, and 36.5 GHz for SWE estimation. We first evaluate a multiple-scattering microwave emission model that consists of a single snow layer over a rough surface by comparing model calculations with data from two field measurements, from the Cold Land Process Experiment (CLPX) in 2003 and from Switzerland in 1995. This model uses the matrix doubling approach to include incoherent multiple-scattering in the snow, and the model combines the Dense Media Radiative Transfer Model (DMRT) for snow volume scattering and emission with the Advanced Integral Equation Model (AIEM) for the randomly rough snow/ground interface to calculate dry snow emission signals. The combined model agrees well with experimental measurements. With this confirmation, we develop a parameterized emission model, much faster computationally, using a database that the more physical multiple-scattering model generates. For a wide range of snow and soil properties, this parameterized model's results are within 0.013 of those from the multiple-scattering model. This simplified model can be applied to the simulation of the microwave emission signal and to developing algorithms for SWE retrieval.
机译:雪水当量(SWE)是气候学,水文学和水资源规划与管理中许多应用程序的关键参数之一。基于卫星的无源微波传感器已经提供了对SWE敏感的全球长期观测。但是,积雪的复杂性使建模微波发射和模型反演难以检索SWE,结果有时检索不正确。在这里,我们开发了一个参数化的干雪发射模型,用于分析被动微波数据,包括来自高级微波扫描辐射计-地球观测系统(AMSR-E)在10.65 GHz,18.7 GHz和36.5 GHz进行SWE估计的数据。我们首先通过将模型计算与两次现场测量的数据(2003年冷陆过程实验(CLPX)和1995年瑞士的数据)进行比较,来评估由粗糙表面上的单个雪层组成的多散射微波发射模型。模型使用矩阵加倍方法在雪中包括非相干多重散射,并且该模型将用于雪量散射和排放的密集介质辐射传递模型(DMRT)与用于随机粗糙雪/高级积分方程模型(AIEM)结合在一起地面接口以计算干雪排放信号。组合模型与实验测量结果非常吻合。有了这一确认,我们将使用更加物理的多散射模型生成的数据库,以更快的计算速度开发出参数化的排放模型。对于大范围的雪和土壤属性,此参数化模型的结果与多重散射模型的结果相差0.013以内。这种简化的模型可以应用于微波发射信号的仿真以及用于SWE检索的开发算法。

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