Extended Abstract (580K)8R.4
MIGFA: The Machine Intelligent Gust Front Algorithm for NEXRAD
David J. Smalley, MIT Lincoln Laboratory, Lexington, MA; and B. J. Bennett and R. Frankel
The Machine Intelligent Gust Front Detection Algorithm (MIGFA) was originally developed for the detection of wind shear hazardous gains as observed by the FAA's Terminal Doppler Weather Radar (TDWR). The algorithm provides detection and forecast positions of features exhibiting sufficient wind shear to be of concern to terminal aviation operations. Many of these features would be of interest to the non-aviation meteorological community as well.
MIGFA for NEXRAD provides the opportunity to further make available its capabilities adding nationwide benefit to air terminals within view of a NEXRAD installation. The algorithm product provides a new capability for NEXRAD with automated detection of wind shear features useful to aviation interests, nowcasting of potential severe weather, and forecasting of convective development.
In this presentation, the functionality of MIGFA will be reviewed. Performance characteristics will be discussed. Examples of MIGFA output for different causalities such as sea breeze interactions, frontal passages, and convective outflows will be highlighted.
* This work was sponsored by the Federal Aviation Administration under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the U.S. Government.
Session 8R, Operational Radar Applications
Thursday, 27 October 2005, 3:30 PM-5:45 PM, Alvarado D
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