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: 1230087
• 负责人: Arthur Jameson
• 金额: $ 46.57万
• 依托单位: RJH Scientific Incorporated
• 依托单位国家: 美国
• 项目类别: Standard 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=1230087&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.

降水粒子分布的特征尺度和结构一般在远大于1公里的尺度上进行探索，但由于若干原因，在小得多的尺度上描述其变异性是重要的。其中包括需要：（1）优化对简单雨量器和雨量计观测结果的解释，并根据需要将这些测量结果转换为更大的尺度，以验证数值天气预报和洪水警报;（2）更好地理解多维背景下的水滴相互作用和演变，而不仅仅是垂直降水的经典时间依赖处理（这通常被认为足以表示雨滴碰撞、聚合和分裂等过程）;（3）更完整地描述雷达发射的微波如何与雨相互作用;和（4）最终的连接，也许翻译的1-D观测液滴尺寸分布到更大的2-D域。通过结合使用2-D视频disdrometer与光学disdrometers的网络阵列，通过它的研究人员将计算成对的相关函数在雨中，以获得任何给定的降水场的水平几何形状的改进措施，尺度降水结构。 雨滴仪观测（其水平间距可随时调整）还将允许对各种距离进行检查，以确定雨滴大小分布的可能比例、自相似性和功能结构，从而更好地与遥感器对大面积降水量的测量相联系。 这项工作的主要目的是收集和分析从厘米（使用二维视频disdrometer观察）到几十到一百米或更长的水平尺度上的降雨时间序列观测。 更广泛的影响将通过潜在的贡献来改善洪水预测和监测，以及更好的过程相关的土壤侵蚀，通过支持动手的学生参与，并通过改善观测基础设施在本科机构服务代表性不足的群体。