Collaborative Research: ITR-(ASE+ECS)-(dms+sim): A Comprehensive Framework for Use of Next Generation Weather Radar (NEXRAD) Data in Hydrometeorology and Hydrology

该项目将把对大型实时数据流的管理研究与从原始雷达数据得出降雨量估计的算法研究结合起来，开发一个信息技术框架，用于分析NEXRAD雷达网的降雨量数据。它包括研究和开发用于NEXRAD原始数据馈送的元数据、存档的NEXRAD数据和衍生数据产品、用于检索元数据和数据的客户端库，以及用于质量控制、数据准备和生成降雨图的客户端应用程序。如果成功，结果将大大减少查找相关NEXRAD数据并将其转换为可用于驱动水文模型的降雨场所需的时间和精力。该项目还将有助于标准化雨场生成过程，增加不同水文模型组结果的可比性。该框架将包括一个用于雷达数据的浏览器、一个降雨产品地图显示，以及一个允许覆盖地理参考雨量场、数字高程模型和地表渠道网络的分析器。该系统的用户将可使用标准和可定制的方法进行质量控制和生成雨量场。计划开发的工具中包括当一个以上的雷达覆盖一个地区时创建合并降雨产品的软件。如果成功，该项目将以类似于气象研究人员获得天气数据的方式提供作为动态水文学主要驱动力的数据，从而对水文科学产生潜在影响。这反过来将有助于更好地预测土壤侵蚀、洪水和山体滑坡，并改善环境资源管理。由于元数据被包括在THREDDS目录中，NEXRAD数据将可以通过地球科学教育数字图书馆DLESE访问。

This project will combine research on the management of large, real-time, data streams with research on algorithms for deriving rainfall estimates from raw radar data, to develop an information technology framework for use in the analysis of rainfall data from the NEXRAD radar network. It includes research on and the development of metadata for the NEXRAD raw data feed, archived NEXRAD data and derived data products, client libraries for retrieving metadata and data, and client applications for quality control, data preparation, and the generation of rainfall maps. If successful, the results should greatly reduce the time and effort required to locate relevant NEXRAD data and to convert it to rainfall fields that can be used to drive hydrologic models. The project will also help standardize the process of rainfall field generation, increasing the comparability of results from different hydrological modeling groups. The framework will include a browser for radar data, a map display of rainfall products, and an analyzer that permits the overlaying of geo-referenced rainfall fields, digital elevation models, and surface channel networks. Standard and customizable methods will be available for quality control and rainfall field generation by users of the system. Included in the tools planned for development is software to create merged rainfall products when more than one radar covers a region. If successful, the project will have a potential impact on hydrological science by providing the data that is the primary driver of dynamic hydrology in a fashion similar to the way weather data is available to weather researchers. This, in turn, will facilitate better prediction of soil erosion, flooding and landslides as well as improve environmental resource management. Because metadata is being included in THREDDS catalogs, NEXRAD data will become accessible through DLESE, the Digital Library for Earth Science Education.