Session 16A.3 Synoptic environments and convective modes associated with significant tornadoes in the contiguous United States

Thursday, 30 October 2008: 2:00 PM
North & Center Ballroom (Hilton DeSoto)
Richard L. Thompson, NOAA/NWS/NCEP, Norman, OK ; and J. S. Grams and J. Prentice

Presentation PDF (702.5 kB)

Operational forecasts of significant tornadoes have improved during the past several decades as a result of sophisticated numerical simulations of supercells and numerous field observations, as well as the development of several large proximity sounding samples and sounding-derived ingredients related to tornado environments. However, operational experience suggests that the anticipation of significant tornadoes beyond the day of the event can be difficult. Errors in numerical model forecasts make parameter evaluation problematic, leaving the forecaster with a more general view of the synoptic regime as the most reliable approach. As such, there is a tendency amongst the operational community to translate this synoptic regime information into various “rules of thumb” that pertain to the tornado threat. The purpose of this study is to compare a number of these rules of thumb, such as a tendency for violent tornadoes to accompany intense cyclones, to an actual distribution of conditions that does not rely on skewed recollections of forecaster experiences.

To this end, a sample of several hundred significant tornadoes (F2-F5 damage) was collected from 2000-2008. Information for each case included: 1) convective mode (from radar reflectivity mosaics) at the time of and after the tornadoes, 2) a subjective characterization of the synoptic flow regime (500 mb and MSL pressure fields) preceding each event, and 3) various mandatory pressure level data interpolated to the time and location of the tornadoes. The convective mode evolution allowed for multiple tornado cases during a larger tornado episode, such as discrete supercells and QLCS tornadoes. The intent is to calibrate many rules of thumb via a large sample size, and complement the ingredients-based approach to tornado forecasting.

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