Collaborative Research: Characterization of the Two-dimensional/Temporal Mosaic of Drop Size Distributions and Spatial Variability (Structure) in Rain

合作研究：雨中液滴尺寸分布和空间变化（结构）的二维/时间镶嵌特征

• 批准号: 1230240
• 负责人: Michael Larsen
• 金额: $ 32.54万
• 依托单位: College of Charleston
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1230240&HistoricalAwards=false
• 关键词: Collaborative; Research; Characterization; Two; dimensional

Characteristic scales and structures of precipitation particle distributions have generally been explored over dimensions considerably larger than 1 km, yet for several reasons it is important to characterize their variability on far smaller scales. These include the need to: (1) optimize interpretation of observations made by simple rain gages and disdrometers and the translation of such measurements to much larger scales, as needed for validation of numerical weather forecasts and flood warnings; (2) better understand drop interactions and evolution in a multi-dimensional context rather than just the classical time dependent treatment in the vertical for falling precipitation (as has often been considered adequate for representation of processes including raindrop collision, coalescence and break-up); (3) achieve a more complete description of how radar-emitted microwaves interact with rain; and (4) ultimate connection and perhaps translation of 1-D observations of drop size distributions to larger 2-D domains.The intellectual merit of this project derives from quantification of small-scale precipitation structures via combined use of a 2-D video disdrometer in conjunction with a networked array of optical disdrometers, through which investigators will calculate pair-correlation functions in rain to derive improved measures of any given precipitation field's horizontal geometry. Disdrometer observations (whose horizontal separation may be readily adjusted) will also allow examination a wide range of distances for possible scaling, self-similarity and functional structures of drop size distributions so as to better connect with remote-sensor measurements of precipitation covering large areas. The over-arching objective of this work is to collect and analyze time-series observations of rainfall over horizontal scales ranging from centimeters (as observed using a 2-D video disdrometer) up to several tens to perhaps a hundred meters or more. Broader Impacts will come through potential contributions to improved flood prediction and monitoring as well as better processes relevant to soil erosion, through support of hands-on student involvement in, and through improved observational infrastructure at an undergraduate institution serving underrepresented groups.

降水颗粒分布的特征尺度和结构通常已经在远大于1公里的尺度上进行了探索，但由于若干原因，在更小的尺度上表征它们的变异性是很重要的。这包括需要：(1)优化对简单雨量计和分差仪观测结果的解释，并将这些测量结果转化为更大的尺度，以验证数值天气预报和洪水警报的需要；(2)更好地理解雨滴在多维背景下的相互作用和演变，而不仅仅是在垂直方向上对降水进行经典的时间依赖处理（通常被认为足以表示雨滴碰撞、合并和破碎等过程）；(3)更完整地描述雷达发射的微波如何与雨相互作用；(4)液滴尺寸分布的一维观测结果与更大的二维区域的最终联系和可能的转换。这个项目的智力价值来自于对小规模降水结构的量化，通过结合使用二维视频disdimeter和网络光学disdimeter阵列，研究人员将计算降雨中的成对相关函数，以获得任何给定降水场水平几何形状的改进测量。disdimeter观测（其水平间距可随时调整）也将允许检查大范围距离内雨滴大小分布的可能尺度、自相似性和功能结构，以便更好地与覆盖大面积降水的遥感测量相结合。这项工作的首要目标是收集和分析在水平尺度上的降雨时间序列观测，范围从厘米（使用二维视频分差仪观察到的）到几十米到可能100米或更大。通过对改善洪水预报和监测以及改善与土壤侵蚀有关的过程的潜在贡献，通过支持学生亲自参与，以及通过改善为代表性不足的群体服务的本科机构的观测基础设施，将产生更广泛的影响。

项目成果

Refinements to Data Acquired by 2-Dimensional Video Disdrometers

对二维视频测距仪采集的数据进行改进

• DOI: 10.3390/atmos11080855
• 发表时间: 2020
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Larsen, Michael L.;Blouin, Christopher K.
• 通讯作者: Blouin, Christopher K.