Collaborative Research to Explore the Spatial/Temporal Statistical-Physical Structures of Rain in the Vertical Plane

探索垂直平面降雨时空统计物理结构的合作研究

• 批准号: 2001490
• 负责人: Michael Larsen
• 金额: $ 39.92万
• 依托单位: College of Charleston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2001490&HistoricalAwards=false
• 关键词: Collaborative; Research; Explore; Spatial; Temporal

A good understanding of rain in time and space is important for improved public safety and productivity. With regard to public safety, this means better water control designs for reducing the impact of flooding from smaller urban to larger regional scales as well as for improved spatial and temporal warnings of flooding in order to reduce damage and fatalities. With regard to productivity in rural areas, such information has the potential for reducing the impacts of soil erosion through the better design of field run-off and water storage. In more urban areas, productivity depends in part upon good wireless communication. However, the advent of 5G wireless networks will be more subject to signal loss due to rain, a loss that also depends upon the largely unknown spatial structure of rainfall particularly above the ground. All of these improvements, however, depend upon the proper translation of radar measurements and numerical model outputs to many different scales. This in turn requires that radar measurements above the ground as well as numerical model products be correctly transferred to what appears at the surface where people live. This, then, is a central objective of this project.More specifically with regard to the science, this project allows a more complete description of rain structure in a multi-dimensional context including height with the additional benefit of developing a better multi-dimensional understanding of drop interactions and evolution. Furthermore, the project is directed toward a more comprehensive investigation into the prevalence and the importance of statistical homogeneity in all three spatial dimensions as well as in time. Statistical homogeneity is important for the proper scaling of rainfall measurements, but, of course, not all rain is statistically homogeneous. However, it often appears that when the data are statistically heterogeneous, such data may be subdivided into statistically homogeneous sections which can then be properly treated analytically. This project develops this approach. In addition, wind tower measurements as well as simultaneous measurements between two 2DVD disdrometers will be used to explore further the reported deviations of drop fall speeds from their nominal terminal values both aloft and at the surface. This is potentially quite important for the proper understanding of the evolution of rain.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

对时间和空间中的降雨的良好理解对于提高公共安全和生产力至关重要。关于公共安全，这意味着更好的水控制设计，以减少从较小的城市到较大的区域范围的洪水影响以及改善洪水的空间和时间警告，以减少损害和死亡。关于农村地区的生产力，这种信息有可能通过更好地设计野外径流和储藏量来减少土壤侵蚀的影响。在更多的城市地区，生产力部分取决于良好的无线沟通。但是，5G无线网络的出现将更容易受到降雨的信号损失，这一损失也取决于降雨的很大未知的空间结构，尤其是在地面上方。但是，所有这些改进都取决于对雷达测量值的适当翻译和数值模型输出的适当翻译。反过来，这要求将雷达测量值在地面上方以及数值模型产品上方正确传输到人们所居住的地表。因此，这是该项目的核心目标。特别是关于科学，该项目允许在多维环境中对雨结构进行更完整的描述，包括高度，并具有进一步的好处，即开发更好的多维理解滴相互作用和进化。此外，该项目是针对对所有三个空间维度以及及时的统计同质性的普遍性和重要性进行更全面的调查。统计同质性对于适当的降雨量测量值很重要，但是，当然，并非所有降雨都是统计均匀的。但是，通常看来，当数据在统计上是异质的时，可以将这些数据细分为统计均匀的部分，然后可以通过分析对其进行正确处理。该项目开发了这种方法。此外，将使用两个2DVD拆卸仪之间的风塔测量值以及同时测量，以进一步探索降落速度与其标称末端值的偏高和表面上的降落速度的偏差。这对于正确理解降雨的演变非常重要。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评论标准来评估值得支持的。

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.

Improved Estimates of the Vertical Structures of Rain Using Single Frequency Doppler Radars

使用单频多普勒雷达改进降雨垂直结构的估计

• DOI: 10.3390/atmos12060699
• 发表时间: 2021
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Jameson, Arthur R.;Larsen, Michael L.;Wolff, David B.
• 通讯作者: Wolff, David B.

Preliminary Statistical Characterizations of the Lowest Kilometer Time–Height Profiles of Rainfall Rate Using a Vertically Pointing Radar

使用垂直指向雷达对最低公里时间降雨率高度剖面的初步统计特征

• DOI: 10.3390/atmos13040635
• 发表时间: 2022
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Jameson, Arthur R.;Larsen, Michael L.
• 通讯作者: Larsen, Michael L.

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

利用数据聚类算法自动识别层积云中的特征液滴尺寸分布

• DOI: 10.1175/aies-d-22-0003.1
• 发表时间: 2022
• 期刊: Artificial Intelligence for the Earth Systems
• 作者: Allwayin, Nithin;Larsen, Michael L.;Shaw, Alexander G.;Shaw, Raymond A.
• 通讯作者: Shaw, Raymond A.

Multivalent Surface Cations Enhance Heterogeneous Freezing of Water on Muscovite Mica

多价表面阳离子增强白云母上水的异质冻结

• DOI: 10.1021/acs.jpclett.0c02121
• 发表时间: 2020
• 期刊: The Journal of Physical Chemistry Letters
• 作者: Lata, Nurun Nahar;Zhou, Jiarun;Hamilton, Pearce;Larsen, Michael;Sarupria, Sapna;Cantrell, Will
• 通讯作者: Cantrell, Will