92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Sunday, 22 January 2012
Tuning a Storm Tracking Algorithm for Automated, Severe Hail Warning Guidance
Hall E (New Orleans Convention Center )
Alex J. Wovrosh, Ohio University, Athens, OH; and T. Smith, V. Lakshmanan, G. J. Stumpf, and K. L. Ortega

During severe weather events, forecasters are often faced with the challenge of monitoring current and developing thunderstorms, determining if they are or will become severe, and warning the public that lie in the path of these storms. This multitasking is often burdensome to the forecaster and can even draw attention away from focus-demanding situations that pose extreme danger to life and property, such as when tornadoes are present. Other severe weather, such as severe hail, can be identified rather quickly, requiring less examination to determine if a one-inch diameter has been reached. An automated guidance for warning and tracking on severe hail would be a great asset to a forecaster, allowing for more focus to be given to those situations that prose the most danger to life and property. Here, a storm-tracking algorithm developed at NOAA's National Severe Storms Laboratory is fine-tuned to track storms most favorable for producing severe hail (i.e. Supercells), based on nine case studies for merged products obtained from WSR-88D units. Specifically, parameter thresholds for tracking radar reflectivity at -10C and VIL via storm centroids and image-based motion vectors were analyzed in 40 and 30 test trials across the nine days, respectively. Results presented here include the suite of parameter thresholds for centroid-based tracking (e.g. tracking storm cores between 30 and 60dBZ) and issues with image-based tracking per the current version of the tracking algorithm.

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