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管理的联合收割机研究与对从原始雷达数据得出降雨量估计值的算法的研究结合起来，以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、检索元数据和数据的客户图书馆以及用于质量控制、数据准备和生成降雨图的客户应用程序。 如果成功的话，结果将大大减少定位相关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。 该项目还将有助于降雨场生成过程的标准化，提高不同水文模型组结果的可比性。 该框架将包括一个雷达数据浏览器、一个降雨量产品地图显示器和一个分析器，该分析器允许叠加地理参考降雨场、数字高程模型和地面通道网络。 该系统的用户可采用标准和可定制的方法进行质量控制和生成降雨场。 计划开发的工具中包括一个软件，当一个以上的雷达覆盖一个地区时，该软件可以创建合并的降雨量产品。 如果成功，该项目将对水文科学产生潜在的影响，通过提供数据，这是动态水文的主要驱动力，以类似于天气数据提供给天气研究人员的方式。这反过来将有助于更好地预测土壤侵蚀、洪水和山崩，并改善环境资源管理。 由于元数据被纳入THREDDS目录，NEXRAD数据将通过DLESE（地球科学教育数字图书馆）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.