Collaborative Research: Testing a Dynamical-Hortonian Scaling Theory for Flood Events on Whitewater Basin, Kansas

合作研究：测试堪萨斯州白水盆地洪水事件的动态霍顿尺度理论

• 批准号: 0450320
• 负责人: Witold Krajewski
• 金额: $ 41.35万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0450320&HistoricalAwards=false
• 关键词: Collaborative; Research; Testing; Dynamical; Hortonian

AbstractMultifractal and multiscaling analyses of spatial rainfall have become a standard tool to study its statistical and physical properties. Almost all of the related studies are based on radar rainfall (RR) fields. However, very little is known about the effects of the uncertainties in RR on the estimation of multifractal parameters. Among the basic systematic factors that could affect the results of multifractal analyses are the selection of the Z-R relationship, the reflectivity threshold, and the dependence on the range from the radar. In addition, the effects of the random errors in RR products need to be investigated as well. In this study the authors examine the impacts of systematic and random errors on the inferred multifractal properties of rainfall. In investigating the effects of random errors, the approach followed is to express the radar rainfall fields as a product of the true rainfall and the error process, assumed to be multiplicative, lognormally distributed and characterized by two different spatial correlation functions (highly correlated and uncorrelated). This study indicates that, for some of the factors, the sensitivity of the results on the RR errors is high and might even dominate the outcome of the multifractal analyses.7. Kruger, A., R. Lawrence, E.C. Dragut, and J. Koladi, Building a Terabyte NEXRAD radar database for hydrometeorology research, Computers & Geosciences, 2004 (in review.)AbstractThe management and processing of terabyte-scale data sets is time-consuming, costly, and an impediment to research. Researchers need rapid and transparent access to their data, unencumbered by the technical challenges of data management. We describe a database and architecture that manages over 12 TB of Archive Level II data produced by the United States National Weather Service's network of WSR-88D weather radars. This work offers geoscientists an innovative, automatic system for archiving and analyzing radar data that isolates them from the complexities of data storage and retrieval. Data access transparency is achieved by using a relational database to store metadata on the raw data, enabling simple SQL queries to retrieve data subsets of interest. The second component is a distributed web platform to cost-effectively distribute data across web servers for access. This work demonstrates how massive data sets can be effectively queried and managed.8. Kruger, A., and K. Kanukurthy, A cell phone-based data logger and network for monitoring environmental variables, IEEE Transactions on Instrumentation and Measurement, 2005 (near submission) AbstractThe authors designed a data logger for interfacing with rain gauges to measure rainfall. Data is stored in SRAM and packaged along with other meteorological data such as temperature and humidity measured by on-board sensors and transmitted using a cell modem. Equipped with a real time clock-calendar, ADC, 53 programmable I/O lines, two USART modules, I2C bus, SPI bus, ISP and boot loading capabilities, onboard Flash, RAM etc., the data logger provides unique capabilities not found in commercially available products. The data logger could be modified with little effort for interfacing with other systems involving data acquisition, storage and transmission. The data logger was designed from the ground up to operate as part of a network, allowing for flexible data transmission, flexible power management, and accurate onboard clocks.

摘要空间降雨的多重分形和多尺度分析已成为研究其统计和物理特性的标准工具。 几乎所有的相关研究都是基于雷达降雨（RR）场。 然而，很少有人知道RR的不确定性对多重分形参数估计的影响。 影响多重分形分析结果的基本系统因素包括Z-R关系的选择、反射率阈值以及对雷达距离的依赖性。 此外，还需要研究RR产品中随机误差的影响。 在这项研究中，作者研究的影响，系统和随机误差推断的多重分形性质的降雨。 在研究随机误差的影响时，所采用的方法是将雷达降雨场表示为真实降雨量和误差过程的乘积，假设其为乘法、对数正态分布，并具有两种不同的空间相关函数（高度相关和不相关）。 本研究表明，对于某些因素，RR误差对结果的敏感性很高，甚至可能主导多重分形分析的结果. Kruger，A.，R.劳伦斯，E.C. Dragut和J. Koladi，建立用于水文气象研究的太比特NEXRAD雷达数据库，计算机地球科学，2004年（综述中）。摘要TB级数据集的管理和处理是一项耗时、昂贵的研究工作。 研究人员需要快速、透明地访问他们的数据，不受数据管理技术挑战的阻碍。 我们描述了一个数据库和体系结构，管理超过12 TB的存档级别II的数据由美国国家气象局的WSR-88 D天气雷达网络。 这项工作为地球科学家提供了一个创新的自动系统，用于归档和分析雷达数据，将其与数据存储和检索的复杂性隔离开来。 数据访问透明性是通过使用关系数据库在原始数据上存储元数据来实现的，允许简单的SQL查询检索感兴趣的数据子集。 第二个组件是一个分布式Web平台，用于在Web服务器上以经济高效的方式分发数据以供访问。 这项工作展示了如何有效地查询和管理海量数据集。Kruger，A.，和K. Kanukurthy，一个基于手机的数据记录器和网络监测环境变量，IEEE交易仪器和测量，2005年（近提交）摘要作者设计了一个数据记录器接口与雨量计测量降雨量。 数据存储在SRAM中，并与其他气象数据（如由机载传感器测量的温度和湿度）一起沿着打包，并使用蜂窝调制解调器进行传输。 配备一个真实的时钟-日历、ADC、53条可编程I/O线、两个USART模块、I2C总线、SPI总线、ISP和靴子加载功能、板载Flash、RAM等，数据记录器提供了在商业上可获得的产品中没有的独特能力。 数据记录仪可以很容易地进行修改，以便与其他涉及数据采集，存储和传输的系统进行接口。 该数据记录仪从一开始就被设计为作为网络的一部分运行，允许灵活的数据传输，灵活的电源管理和准确的板载时钟。