Atmospheric Radar Research Seminar Series presents...
Consistent Clustering of Radar Reflectivities Using Strong-Point Analysis - A Prelude to Storm Tracking
Benjamin Root
The University of Oklahoma School of Meteorology
29 January 2009, 1:00 PM
National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK
Directions to the NWC (.pdf, 60 kb)
Tracking features in a time-series of images requires a consistent and stable clustering algorithm. If the clustering algorithm cannot produce similar results for similar images, in other words, the clustering output does not change continuously with changes in the input images, then any object-based tracking algorithms will be severely hindered. Similarly, another important issue with clustering algorithms is the impact of input parameters on resulting clusters. The clustering algorithm becomes difficult to use if a user cannot easily fine-tune the parameters to the desired results.
The purpose of this project is to introduce SPA and to showcase its efficacy as applied to radar reflectivity data. This project also shows the independence of the algorithm from any particular source of radar data. The SPA is demonstrated using a wide range of events from localized thunderstorms to squall-lines to large-scale synoptic events. Also, the sources of radar data come from different radar stations, both geographically and technologically. The purpose of which is to demonstrate the versatility of SPA in being able to produce relevant clusters for whatever kinds of shapes and sizes of the features.