Hydro-NEXRAD Radar-rainfall Estimation Algorithm Development, Testing And Evaluation

The Hydro-NEXRAD radar-rainfall estimation algorithms involve three main components: 1) preprocessing, 2) rain rate, and 3) rainfall accumulation. The preprocessing algorithm performs the quality control of reflectivity volume data and generates a hybrid scan. That is, reflectivity values for each azimuth and range bin are assigned from the several lowest elevation angles. It optionally estimates an azimuth-dependent vertical reflectivity profile and performs a correction for range effects. The rain rate algorithm converts the corrected reflectivity to rainfall intensity. The user can specify any power-law type empirical relationship between reflectivity and rainfall intensity. The last step of rainfall estimation is to integrate consecutive rate scans for specific time duration ranging from 15 minutes to daily. The algorithm mimics real-time calculations and involves advection correction. © 2007 ASCE

Multiple Radar Data Merging In Hydro-NEXRAD

The Hydro-NEXRAD merging algorithms include two options: (1) data-based merging; and (2) product-based merging. Data-based merging algorithm takes volume scan reflectivity data from all radars involved through preprocessing algorithm that performs volume data quality control, interpolates data to synchronize temporal scale between individual radars, and finally combines data onto a common geographic grid. Reflectivity values for a given location are assigned by a weighting function with respect to the distance from the radar. This single reflectivity field is then converted to rainfall amounts using a user-requested standard approach. In product-based merging algorithm reflectivity data from multiple radars are all converted to rainfall using the same, user-specified algorithm. These products are then combined into the final one using a weighting function that expresses the uncertainty of estimated rainfall amounts. © 2008 ASCE

Radar-rainfall Estimation Algorithms Of Hydro-NEXRAD

Hydro-NEXRAD is a prototype software system that provides hydrology and water resource communities with ready access to the vast data archives of the U.S. weather radar network known as NEXRAD (Next Generation Weather Radar). This paper describes radar-rainfall estimation algorithms and their modular components used in the Hydro-NEXRAD system to generate rainfall products to be delivered to users. A variety of customized modules implemented in Hydro-NEXRAD perform radar-reflectivity data processing, produce radar-rainfall maps with user-requested space and time resolution, and combine multiple radar data for basins covered by multiple radars. System users can select rainfall estimation algorithms that range from simple (\u27Quick Look\u27) to complex and computing-intensive (\u27Hi-Fi\u27). The \u27Pseudo NWS PPS\u27 option allows close comparison with the algorithm used operationally by the US National Weather Service. The \u27Custom\u27 algorithm enables expert users to specify values for many of the parameters in the algorithm modules according to their experience and expectations. The Hydro-NEXRAD system, with its rainfall-estimation algorithms, can be used by both novice and expert users who need rainfall estimates as references or as input to their hydrologic modelling and forecasting applications. © IWA Publishing 2011

Hydro-NEXRAD: An Updated Overview And Metadata Analysis

Hydro-NEXRAD is a prototype system that allows hydrologists to obtain user-specified rainfall data for their research. These data are based on observations collected by the national network of WSR-88D radars, known as NEXRAD. Users interact with Hydro-NEXRAD through a web-based interface that has map-based components for spatial navigation, calendar- and time series plot components for temporal navigation and a menu-based component for selection of processing options. Through the interface, users browse the Hydro-NEXRAD metadata and select data of interest. As the system is approaching the point of being fully operational, the authors and a group of test users have evaluated several aspects of the system. Metadata remains very important for the system functionality. Radar-based, basin-based and point (for selected set of rain gauge locations) metadata serve multiple purposes: 1) enable users to efficiently search for subsets of data (SQL query, visual inspection), 2) provide information on quality of the collected data archive (missing or corrupt data), 3) and have a scientific value (basin-based metadata has a potential to be used as a precipitation input to hydrologic models). The authors provide an updated overview of the Hydro-NEXRAD system. Additionally, the authors present the complete set of Hydro-NEXRAD metadata and discuss their possible applications. © 2008 ASCE

Towards better utilization of NEXRAD data in hydrology: An overview of hydro-NEXRAD

With a very modest investment in computer hardware and the open-source local data manger (LDM) software from UCAR\u27s Unidata Program Center, an individual researcher can receive a variety of NEXRAD Level III gridded rainfall products, and the unprocessed Level II data in real-time from most NEXRAD radars. Additionally, the National Climatic Data Center has vast archives of these products and Level II data. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte data sets: storing, compressing, and backing up. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for application in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms with variety of corrections, coordinate conversion and georeferencing, conversion to a convenient data format(s), and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. Thirdly, the amount of data present in a multi-year, multi-radar dataset is such that simple cataloging and indexing of the data is not sufficient. Rather, sophisticated metadata extraction and management techniques are required. The authors describe and discuss the Hydro-NEXRAD software system that addresses the above three challenges. With support from the National Science Foundation through its ITR program, the authors are developing a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. Through a flexible web interface users can search a large metadata database base, managed by a relational database, for subsets of interest. Well-chosen and documented defaults are provided for the flow from unprocessed NEXRAD data to basin-centered rainfall estimates at a desired space-time resolution. In addition to the web interface, there are web services that provide access to scripts and compiled programs. © 2007 ASCE

Towards Better Utilization of NEXRAD Data in Hydrology: An Overview of Hydro-NEXRAD

With a very modest investment in computer hardware and the open-source local data manager (LDM) software from University Corporation for Atmospheric Research (UCAR) Unidata Program Center, a researcher can receive a variety of NEXRAD Level III rainfall products and the unprocessed Level II data in real-time from most NEXRAD radars in the USA. Alternatively, one can receive such data from the National Climatic Data Center in Ashville, NC. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terabyte datasets. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for applications in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented steps that include quality control, removal of false echoes, rainfall estimation algorithms, coordinate conversion, georeferencing and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. The authors describe the Hydro-NEXRAD system that addresses the above challenges. With support from the National Science Foundation through its ITR program, the authors have developed a basin-centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. © IWA Publishing 2011