Spatial Distributions of Tornadic Near-Storm Environments by Convective Mode
Abstract
All tornado reports across the contiguous United States from 2003-2011 were filtered for the maximum damage rating on an hourly grid with 40-km horizontal spacing. Convective mode was assigned to each grid-hour tornado event via manual examination of full volumetric WSR-88D data, and supercell-related environmental parameters accompanied each grid-hour tornado event from the hourly objective analyses calculated and archived at the Storm Prediction Center. Only tornado events associated with right-moving supercells (RM) or quasi-linear convective systems (QLCS) were considered in this work, which resulted in a sample of 8837 tornado grid-hour events.
Spatial distributions of supercell-related parameters were constructed for the RM and QLCS tornado events. Sample sizes were increased by accumulating tornado events within a 120-km neighborhood to each 40-km grid box. All neighborhoods with ≥10 events were retained for percentile rank distributions of the supercell-related parameters, and then smoothed using a Gaussian kernel with a 120-km influence radius. Regional variations in buoyancy and lifting condensation level (LCL) are apparent-RM tornadoes are more common with greater buoyancy and higher LCL heights across the Great Plains compared to the Mississippi Valley region. QLCS tornadoes tend to be focused across the Ohio and Mississippi Valleys, in environments with weaker buoyancy and lower LCL heights. Vertical wind shear parameters are typically well within the parameter space associated with tornadic RM for both the RM and QLCS tornado events. The significant tornado parameter shows improved discrimination between weak and significant RM tornadoes, compared to individual kinematic or thermodynamic parameters.
Full Text: PDF
Citation:
Thompson, R. L., B. T. Smith, A. R. Dean, and P. T. Marsh, 2013: Spatial distributions of tornadic near-storm environments by convective mode. Electronic J. Severe Storms Meteor., 8 (5), 1-22.
Keywords:
supercells, storm environments, tornadoes, squall lines, operational forecasting, severe storms