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

了解降雨的时间和空间对提高公共安全和生产力非常重要。在公共安全方面，这意味着更好的治水设计，以减少洪水从小城市到大区域的影响，以及改善洪水的时空预警，以减少损失和死亡。关于农村地区的生产力，这种资料有可能通过更好地设计田地径流和水储存来减少土壤侵蚀的影响。在更多的城市地区，生产力部分依赖于良好的无线通信。然而，5G无线网络的出现将更容易受到降雨造成的信号损失的影响，这种损失还取决于很大程度上未知的降雨空间结构，尤其是地面上的降雨。然而，所有这些改进都取决于雷达测量和数值模式输出到许多不同尺度的适当转换。这反过来又要求地面上的雷达测量以及数值模型产品正确地转移到人们居住的地面上。因此，这是该项目的中心目标。更具体地说，在科学方面，该项目允许在多维环境下更完整地描述雨的结构，包括高度，以及对雨滴相互作用和进化有更好的多维理解的额外好处。此外，该项目旨在对所有三个空间维度和时间的统计同质性的普遍性和重要性进行更全面的调查。统计上的均匀性对于降雨测量的适当缩放很重要，但是，当然，并非所有的雨在统计上都是均匀的。然而，通常情况下，当数据在统计上是异质的，这些数据可以被细分为统计上同质的部分，然后可以适当地进行分析处理。本项目开发了这种方法。此外，将使用风塔测量以及两个2DVD disdrometer之间的同时测量来进一步探索报道的高空和地面下降速度与其标称终端值的偏差。这对于正确理解雨的演变可能是非常重要的。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.