4.4
Severe weather climatologies based on NEXRAD and other data from the Severe Weather Data Inventory (SWDI)

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 19 January 2010: 9:15 AM
B217 (GWCC)
Mark Phillips, University of North Carolina at Asheville, Asheville, NC; and S. Ansari and S. A. Del Greco

The Severe Weather Data Inventory (SWDI) at NOAA's National Climatic Data Center (NCDC) provides a searchable and downloadable database of several years of data critical to the detection and evaluation of severe weather. These datasets include:

  • NEXRAD Level-III point features describing general storm structure, hail, mesocyclone and tornado signatures
  • National Weather Service Storm Events Database
  • National Weather Service Local Storm Reports collected from storm spotters
  • National Weather Service Warnings
  • Lightning strikes from Vaisala's National Lightning Detection Network (NLDN)
SWDI data, which is available in several formats via ftp and REST web services, can be used to create severe weather climatologies from any of the above data sources. This presents an unprecedented opportunity to examine severe weather patterns on a national scale, especially when applied to the NEXRAD Level III point features --- storm structure, hail, mesocyclone, and tornado signatures. Climatology maps of these features have the potential to become an extremely valuable risk assessment tool.

There are, however, many challenges and questions involved in producing such climatologies. Since there are regions of the US not covered by any radar site, a lack of data in a region cannot be interpreted as an absence of events from that region. In addition, many regions are covered by more than one radar site, which means that the same event may be represented multiple times in SWDI data. Furthermore, NEXRAD Level-III point features do not represent confirmed events --- they represent signatures present in the original reflectivity data that indicate a likelihood of an event. When aggregated over an extended time period, however, the data may provide insights into severe weather patterns not detectable by other means.

This presentation will describe a new project whose goal is to produce meaningful climatology products from SWDI data. It will cover some of the successes and challenges, some techniques for addressing the challenges, and some ideas for assessing the validity of the resulting products.

Supplementary URL: http://www3.nemac.unca.edu/swdiclimatology