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是在远大于 1 公里的维度上进行探索的，但由于多种原因，在小得多的尺度上表征其变化性非常重要。其中包括需要：（1）根据验证数值天气预报和洪水警报的需要，优化对简单雨量计和测速仪观测结果的解释，并将此类测量结果转换为更大的尺度； （2）更好地理解多维背景下的水滴相互作用和演化，而不仅仅是垂直降水的经典时间相关处理（通常被认为足以表示雨滴碰撞、合并和分裂等过程） ; (3) 更完整地描述雷达发射的微波如何与雨水相互作用； (4) 将液滴尺寸分布的一维观测结果最终连接到更大的二维域。该项目的智力优点源于通过结合使用二维视频测速仪对小规模降水结构进行量化与光学测距仪网络阵列结合使用，研究人员将通过该阵列计算降雨中的成对相关函数，以得出任何给定降水场水平几何形状的改进测量值。 测速仪观测（其水平间隔可以很容易地调整）也将允许检查大范围的距离，以了解可能的尺度、自相似性和液滴尺寸分布的功能结构，以便更好地与覆盖大面积降水的遥感器测量相连接。 这项工作的首要目标是收集和分析水平尺度降雨量的时间序列观测结果，范围从厘米（使用二维视频测速仪观测）到几十米甚至一百米或更远。 更广泛的影响将通过对改进洪水预测和监测以及更好的土壤侵蚀相关流程的潜在贡献来实现，通过支持学生的实践参与，并通过改善服务于代表性不足群体的本科机构的观测基础设施。

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.