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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Scattering properties of modeled complex snowflakes andmixed-phase particles atmicrowave andmillimeter frequencies
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Scattering properties of modeled complex snowflakes andmixed-phase particles atmicrowave andmillimeter frequencies

机译:模拟的复杂雪花和混合相粒子在微波和毫米波频率上的散射特性

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A microphysically based algorithm (named Snow Aggregation and Melting (SAM)) that models snowflakes composed of a collection of hexagonal columns by simulating a random aggregation process is presented. SAM combines together pristine columns with multiple dimensions to derive complex aggregates constrained to size-mass relationship obtained by data collected from in situ measurements. The model also simulates the melting processes occurring for environmental temperatures above 0?C and thus define the mixed-phase particles structure. The single-scattering properties of the modeled snowflakes (dry and mixed phased) are computed by using a discrete dipole approximation (DDA) algorithm which allows to model irregularly shaped targets. In case of mixed-phased particles, realistic radiative properties are obtained by assuming snow aggregates with a 10% of melted fraction. The single-scattering properties are compared with those calculated through Mie theory together with Maxwell-Garnett effective medium approximation using both a homogeneous sphere and a layered-sphere models. The results show that for large-size parameters there are significant differences between the radiative properties calculated using complex microphysical and optical algorithms (i.e., SAM and DDA) and those obtained from simplified assumptions as the layered-sphere models (even when the radial ice density distribution of the aggregated snowflakes is perfectly matched). Finally, some applications to quantitative precipitation estimation using radar data are presented to show how the resulting differences in the basic optical properties would propagate into radar measurable. Large discrepancies in the derivation of the equivalent water content and snowfall rate from radar measurements could be observed when large-size parameters are accounted for.
机译:提出了一种基于微物理的算法(称为“雪凝结和融化”(SAM)),该算法通过模拟随机凝结过程来建模由六边形柱的集合组成的雪花。 SAM将具有多个维度的原始色谱柱组合在一起,以得出复杂的聚集体,这些聚集体受从现场测量收集的数据获得的尺寸质量关系的约束。该模型还模拟了环境温度高于0?C时发生的熔化过程,从而定义了混合相颗粒结构。建模雪花(干相和混合相)的单散射特性是通过使用离散偶极子近似(DDA)算法计算的,该算法可以对不规则形状的目标进行建模。对于混合相颗粒,通过假设雪凝块的熔化分数为10%,可以获得真实的辐射特性。将单散射特性与通过Mie理论以及使用均匀球体和分层球体模型的Maxwell-Garnett有效介质逼近计算出的那些特性进行了比较。结果表明,对于大尺寸参数,使用复杂的微物理和光学算法(即SAM和DDA)计算出的辐射特性与通过简化假设作为分层球体模型获得的辐射特性之间存在显着差异(即使径向冰密度聚集的雪花的分布完全匹配)。最后,介绍了使用雷达数据进行定量降水估算的一些应用,以显示基本光学特性的最终差异如何传播到可测量的雷达中。当考虑大尺寸参数时,可以观察到雷达测量得出的等效水含量和降雪率存在较大差异。

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