The Effects of Stochastic Rainfall Clustering on Radar Measurements

大气中雨滴和云滴的浓度可视为随时间和位置波动的随机变量。Jameson和Kostinski最近的工作表明，这些浓度的概率分布偏离了适用于纯随机分布的理论泊松定律。偏差是由液滴聚集成块或片状的趋势引起的。这种水滴的聚集对降水的发展和辐射在云和降水中的传播都有影响。这项研究的目的是(1)继续研究集群的定量特征；(2)评估集群对雨滴对雷达波的散射的影响；(3)确定这些影响对根据雷达测量估计降雨率的意义。这项工作还将试图确定，除了众所周知的米氏或瑞利散射外，星团是否还能解释云和降水的显著布拉格型散射。该方法结合了(1)对测量液滴大小和浓度的各种仪器的数据进行分析，以及(2)在早期关于聚集特征的工作的基础上进行的理论调查。

The concentrations of raindrops and cloud droplets in the atmosphere may be regarded as random variables that fluctuate with time and location. Recent work by Jameson and Kostinski has shown that these concentrations have probability distributions that deviate from the theoretical Poisson law that applies to purely random distributions. The deviations are caused by the tendency of drops to concentrate in clumps or patches. This clustering of drops has implications for precipitation development and for the propagation of radiation through clouds and precipitation. The objectives of this research are (1) to continue studies on quantitative characterization of clustering; (2) to evaluate the effects of clustering on the scattering of radar waves by raindrops; (3) to determine the significance of these effects on the estimation of rainfall rate from radar measurements. The work will also attempt to determine whether clustering can account for significant Bragg-type scattering by clouds and precipitation in addition to the well-understood Mie or Rayleigh scattering. The approach is a combination of (1) analysis of data from various instruments that measure drop sizes and concentrations and (2) theoretical investigations building on the earlier work on the characterization of clustering.