The University of Iowa, Princeton University, NOAA's National Climatic Data Center (NCDC), and Unidata

The NEXRAD-ITR hydro project received funding from the National Science Foundation earlier this fall. The project aims to provide ready access to NEXRAD archives as well as the real-time information collected by NEXRAD weather radars to a broad community of users.

Use of the full resolution of NEXRAD information, especially in hydrology and hydrometeorology, is limited at this time because considerable expertise is required in weather radar, data quality control, formatting, and radar-rainfall algorithms. (Currently, the NEXRAD data are converted to operational products and used by forecasters in real time and then archived at NCDC.)

The project's goal is to provide professionals in the scientific, engineering, education, and public policy sectors with on-demand NEXRAD data and custom products that are at high spatial and temporal resolutions. The data and custom products will be of a quality suitable for scientific discovery in hydrology and hydrometeorology.

The development team includes experts in hydrology and hydrometerlogy namely, the lead PI Witold Krajewski (The University of Iowa) and Jim Smith (Princeton). Product from the NEXRAD-ITR project may serve CUAHSI observatories as well. Rainfall estimation algorithms developed as part of the project might eventually run at a future CUAHSI Hydrologic Information Center. Plans include a client-server architecture that will use data mining and SQL queries to a relational database for metadata.

Unidata's role in the project will a involve collection of level II data, running decoders to compute additional metadata, and adding the new metadata to catalogs as well as streaming it to subscribing sites on a new data feed. Unidata will then become a top-tier node for 3 sites, with operation eventually turned over to a CUAHSI center or observatory.

The team will develop a comprehensive framework to reach the goal that will address data dissemination, format conversions, terabyte-sized datasets management, rapid browsing and visualization, metadata selection and calculation, and integration with GIS.

The tools will perform comprehensive quality control and radar-rainfall estimation using a variety of algorithms. The algorithms that the user can select will range from "quick look" to complex and will include operational algorithms used by federal agencies. Users will be able to specify spatial and temporal resolution, ancillary products such as storm advection velocity fields, and estimation of uncertainty associated with rainfall maps. The data and tools will be provided to the community via the services and the infrastructure of Unidata and NCDC.

NIH plans will be presented at the AGU (on Thursday).

Anton Kruger, University of Iowa