Meteorological Applications of Fully Polarimetric Doppler Radar

拟议的研究涉及极化捷变雷达传感的气象应用，即根据测量的散射或Mueller极化矩阵确定散射体(例如，水流星)集合的属性，如大小、形状和取向分布。有人认为，在进行时间平均和形成相关关系之前，应该对全极化数据进行处理，以便基于矢量波散射的物理洞察可以集中于识别极化参数的最佳组合。这项工作的目的是开发、测试和应用在相干和非相干散射区域中的新的极化数据处理算法。这些算法的目的是：1)提高现有降水估计器的精确度；2)提供云和降水现象的新“特征”，例如雨和冰雹的区别；3)改善对相干和非相干极化散射体制的概念理解和适用范围(散射矩阵与米勒矩阵描述)。

The proposed research is concerned with meteorological aplications of polarimetrically agile radar sensing, that is, determining properties of collections of scatterers (e.g. hydrometeors) such as size, shape, and orientation distributions from measured scattering or Mueller polarization matrices. It is argued that processing of fully polarimetric data should be done before time averages are made and correlations formed so that physical insight, based on vector wave scattering, can be focused on identifying an optimal combination of polarization parameters. The purpose of this work is to develop, test, and apply new polarimetric data processing algorithms in both, coherent and incoherent scattering regimes. The algorithms are aimed at 1) improving the accuracy of existing estimators of precipitation; 2) providing new "signatures" of cloud and precipitation phenomena e.g. rain vs. hail discrimination; 3) improving conceptual understanding and ranges of applicability of the coherent and incoherent polarimetric scattering regimes (scattering matrix vs. Mueller matrix description).