P8R.14 WSR-88D radar data services at the National Oceanic and Atmospheric Administration's National Climatic Data Center

Thursday, 27 October 2005
Alvarado F and Atria (Hotel Albuquerque at Old Town)
Stephen A. Del Greco, NOAA/NESDIS/NCDC, Asheville, NC; and S. Ansari

The National Oceanic and Atmospheric Administration's National Climatic Data Center ingests and archives, on average, 85 terabytes of Weather Surveillance Radar-1988 Doppler (known as NEXRAD) data and products annually. The NCDC archives hold over 1,000 terabytes of NEXRAD. Implementation of new radar technologies, such as dual polarization may increase the growth of the radar digital archive by a factor of 26. Annual data receipt of approximately 85 terabytes may, in 3 to 5 years, increase to 2,080 terabytes per year or 4,160 terabytes per year with backup.

These data are in high demand globally by both the public and private sectors. As much as one terabyte of data have been accessed monthly through the NCDC radar resources web page. In an effort to provide better support to these end users, NCDC has developed visualization tools for browsing and displaying these data. The NCDC NEXRAD Interactive Viewer and Data Exporter load NEXRAD volume scan data, known as Level-II and derived products, known as Level-III, into an OPEN GIS compliant environment. The applications are launched via Java Web Start and run on the client machine while accessing the data remotely from the archive at the NCDC. The NEXRAD Interactive Viewer provides tools for custom data overlays, animations and basic queries. The export of images and movies is provided in multiple formats. The NEXRAD Data Exporter allows for data export in both vector polygon (Shapefile, GML, Well-Known Text) and raster (GeoTIFF, ESRI Grid, HDF, NetCDF, GrADS) formats.

Future plans include using data mining techniques on NEXRAD data. NCDC is experimenting with two independent data mining engines in an effort to identify mesocyclone signatures (developed by NOAA NSSL & UAH). Mining tools will be used in an effort to extract unique parameters from level II data archives that may lead to the identification of specific weather phenomena and building specialized spatial data sets.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner