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首页> 外文期刊>Geoscientific Model Development >snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation
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snowScatt 1.0: consistent model of microphysical and scattering properties of rimed and unrimed snowflakes based on the self-similar Rayleigh–Gans approximation

机译:Snowscatt 1.0:基于自我类似的瑞利GAN近似的边缘和无义雪花的微物理和散射特性的一致模型

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More detailed observational capabilities in the microwave (MW) range and advancements in the details of microphysical schemes for ice and snow demand increasing complexity to be included in scattering databases. The majority of existing databases rely on the discrete dipole approximation (DDA) whose high computational costs limit either the variety of particle types or the range of parameters included, such as frequency, temperature, and particle size. The snowScatt tool is innovative in that it provides consistent microphysical and scattering properties of an ensemble of 50?000 snowflake aggregates generated with different physical particle models. Many diverse snowflake types, including rimed particles and aggregates of different monomer composition, are accounted for. The scattering formulation adopted by snowScatt is based on the self-similar Rayleigh–Gans approximation (SSRGA), which is capable of modeling the scattering properties of large ensembles of particles. Previous comparisons of SSRGA and DDA are extended in this study by including unrimed and rimed aggregates up to centimeter sizes and frequencies up to the sub-millimeter spectrum. The results generally reveal the wide applicability of the SSRGA method for active and passive MW applications. Unlike DDA databases, the set of SSRGA parameters can be used to infer scattering properties at any frequency and refractive index; snowScatt also provides tools to derive the SSRGA parameters for new sets of particle structures, which can be easily included in the library. The flexibility of the snowScatt tool with respect to applications that require continuously changing definitions of snow properties is demonstrated in a forward simulation example based on the output of the predicted particle properties (P3) scheme. The snowScatt tool provides the same level of flexibility as commonly used T-matrix solutions, while the computed scattering properties reach the level of accuracy of detailed discrete dipole approximation calculations.
机译:微波(MW)的更详细的观察能力在冰和雪需求的微微物理方案的细节中和进步,增加了散射数据库中的复杂性。大多数现有数据库依赖于离散的偶极近似(DDA),其高计算成本限制了各种粒子类型或包括频率,温度和粒度的参数范围。 Snowscatt工具是创新性的,因为它提供了用不同物理粒子模型产生的50Ω·000雪花骨料集合的一致的微专业和散射性能。考虑了许多不同的雪花类型,包括引发颗粒和不同单体组合物的聚集体。 Snowscatt采用的散射制剂基于自相似的瑞利GANs近似(SSRGA),其能够建模大型颗粒的散射特性。在本研究中,通过将未遮光的和边缘聚集体延长到厘米尺寸和频率直到亚毫米频谱的比较,延长了SSRGA和DDA的比较。结果一般揭示了SSRGA方法对于主动和无源MW应用的广泛适用性。与DDA数据库不同,SSRGA参数集可用于在任何频率和折射率下推断散射性能; Snowscatt还提供了用于导出新的粒子结构集的SSRGA参数的工具,这可以很容易地包含在库中。在基于预测粒子特性(P3)方案的输出的前向仿真示例中,在正模(P3)方案的输出中,在前向仿真示例中说明了SnowScatt工具关于需要连续改变雪属性定义的应用的应用。 SnowScatt工具提供与常用的T矩阵解决方案相同的灵活性,而计算的散射属性达到详细离散偶极近似计算的精度水平。

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