Addressing the Problems of Spatial Resolution and Adequate Sampling in Clustered Clouds and Rain

解决云雨中的空间分辨率和充分采样问题

• 批准号: 0242418
• 负责人: Arthur Jameson
• 金额: $ 24万
• 依托单位: RJH Scientific Incorporated
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0242418&HistoricalAwards=false
• 关键词: Addressing; Problems; Spatial; Resolution; Adequate

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 complicates the problem of distinguishing between actual time and space variability of quantities such as the rainfall rate and the drop-size distribution, and the variability arising naturally from samples containing small numbers of drops. The main objective of this project is to develop new sampling criteria for counting drops and estimating their concentration that will identify real meteorological variability and avoid the artifacts arising from small samples. Another objective is to devise new data analysis techniques to sample clouds that are clumpy in structure and to characterize their structure. Attention will also be given to developing sampling criteria for the proper description of drop-size distributions. The approach is a combination of (1) analysis of data from various instruments that measure drop sizes and concentrations and (2) theoretical investigations based on Monte Carlo simulation. The work will contribute fundamentally to cloud physics by defining accurate methods for measuring and describing the spatial and temporal structure of rain and clouds.

大气中的雨滴和云滴的浓度可能被认为是随着时间和位置波动的随机变量。 詹姆森（Jameson）和科斯汀斯基（Kostinski）最近的工作表明，这些浓度具有偏离适用于纯粹随机分布的理论泊松定律的概率分布。 偏差是由于滴倾向集中在团块或斑块中引起的。 滴剂的这种聚类使区分数量的实际时间和空间变异性（例如降雨速率和降量尺寸分布）的问题变得复杂，以及自然来自包含少量滴剂的样品产生的变异性。 该项目的主要目的是制定新的采样标准来计数降低并估算其浓度，以确定实际的气象变异性，并避免由小样本引起的伪像。 另一个目的是将新的数据分析技术设计为样品云的结构块并表征其结构。 还将注意开发采样标准以正确描述滴分布。 该方法是（1）分析来自各种仪器的数据的组合，这些数据测量了滴度大小和浓度，以及（2）基于蒙特卡洛模拟的理论研究。 这项工作将通过定义测量和描述雨水和云的空间结构的准确方法来从根本上促进云物理。