Choosing a universal mean wind for supercell motion prediction

Bunkers, Matthew J.; Barber, D. A.; Thompson, Richard L.; Edwards, Roger; Garner, Jonathan M.

doi:10.15191/nwajom.2014.0211

Cited by 26 publications

(34 citation statements)

References 32 publications

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“…This motivates an experiment to investigate the validity of using the Bunkers et al (2000) method for estimating storm motion within the context of the SSCRAM system. Given the established predictability of STP for significant FIG.…”

Section: B Statistical Results and Discussion For Tornadoesmentioning

confidence: 99%

“…This technique is used in the present study to determine a focus area for possible severe storm reports given initial storm motion, as it is applicable to high-impact severe supercell storms that are responsible for a considerable percentage of severe weather (Trapp et al 2005). Additional methods of estimating storm motion are presented in section 3, which provides further substantiation for the use of the Bunkers et al (2000) technique in this study. The use of the Bunkers et al (2014) technique for improving estimations of supercell motion based on pressure-weighted mean wind through a variable-layer depth dependent upon the base of the effective inflow layer and the most-unstable equilibrium-level height is not used in the present study.…”

Section: A Design Of Sscrammentioning

confidence: 98%

“…Yellow-outlined, lightning-containing, 40-km-wide grid boxes (numbered) are overlaid. White exes (x) indicate center points of the grid box at the initial time (hh:00) and future/downstream positions for analysis based upon the Bunkers et al (2000) right-moving supercell motion with surrounding search circles (in blue) extending outward to 40 km. This represents a cumulative total of 2 h of severe storm report collection forward in time from the lightning-associated grid box by considering two different search zones centered on points extrapolated forward in space from the initial lightning-associated center grid point.…”

Section: A Design Of Sscrammentioning

confidence: 99%

“…1, each lightning-containing grid box (as determined by gridded lightning data) represents a moving convective element that may or may not produce severe weather reports downstream (or even be sustained) and whose forward motion is estimated using the Bunkers et al (2000) right-moving supercell motion technique. This technique is used in the present study to determine a focus area for possible severe storm reports given initial storm motion, as it is applicable to high-impact severe supercell storms that are responsible for a considerable percentage of severe weather (Trapp et al 2005).…”

Section: A Design Of Sscrammentioning

confidence: 99%

“…The use of the Bunkers et al (2014) technique for improving estimations of supercell motion based on pressure-weighted mean wind through a variable-layer depth dependent upon the base of the effective inflow layer and the most-unstable equilibrium-level height is not used in the present study. Given the error inherent to this motion technique (Bunkers et al 2000), combined with the possibility of lightningproducing convection occurring with other convective modes, a radius of 40 km is applied as a search radius to query downstream severe storm reports. This radius is specifically chosen to match the grid length of the SPC Mesoanalysis dataset.…”

Section: A Design Of Sscrammentioning

confidence: 99%

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The Statistical Severe Convective Risk Assessment Model

Hart¹,

Cohen²

2016

Weather and Forecasting

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This study introduces a system that objectively assesses severe thunderstorm nowcast probabilities based on hourly mesoscale data across the contiguous United States during the period from 2006 to 2014. Previous studies have evaluated the diagnostic utility of parameters in characterizing severe thunderstorm environments. In contrast, the present study merges cloud-to-ground lightning flash data with both severe thunderstorm report and Storm Prediction Center Mesoscale Analysis system data to create lightning-conditioned prognostic probabilities for numerous parameters, thus incorporating null-severe cases. The resulting dataset and corresponding probabilities are called the Statistical Severe Convective Risk Assessment Model (SSCRAM), which incorporates a sample size of over 3.8 million 40-km grid boxes. A subset of five parameters of SSCRAM is investigated in the present study. This system shows that severe storm probabilities do not vary strongly across the range of values for buoyancy parameters compared to vertical shear parameters. The significant tornado parameter [where ''significant'' refers to tornadoes producing (Fujita scale) F2/(enhanced Fujita scale) EF2 damage] exhibits considerable skill at identifying downstream tornado events, with higher conditional probabilities of occurrence at larger values, similar to effective storm-relative helicity, both findings being consistent with previous studies. Meanwhile, lifting condensation level heights are associated with conditional probabilities that vary little within an optimal range of values for tornado occurrence, yielding less skill in quantifying tornado potential using this parameter compared to effective storm-relative helicity. The systematic assessment of probabilities using convective environmental information could have applications in present-day operational forecasting duties and the upcoming warn-onforecast initiatives.

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Section: B Statistical Results and Discussion For Tornadoesmentioning

confidence: 99%

Section: A Design Of Sscrammentioning

confidence: 98%

Section: A Design Of Sscrammentioning

confidence: 99%

Section: A Design Of Sscrammentioning

confidence: 99%

Section: A Design Of Sscrammentioning

confidence: 99%

See 3 more Smart Citations

The Statistical Severe Convective Risk Assessment Model

Hart¹,

Cohen²

2016

Weather and Forecasting

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Tropical Cyclone Outer Size Impacts the Number and Location of Tornadoes

Paredes

Schenkel

Edwards

et al. 2021

Geophysical Research Letters

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Landfalling tropical cyclones (TCs) often produce tornadoes in addition to other hazards. Most tornadoes occur during the afternoon within 100-500 km of the TC center during the 48-h period before and after landfall (Novlan & Gray, 1974;Schultz & Cecil, 2009). Compared to their non-TC counterparts, TC tornadoes typically: 1) are less damaging (Edwards, 2010;Edwards, 2012), 2) are produced by "miniature" supercells (Spratt et al., 1997;Edwards et al., 2012), and 3) occur in strong vertical wind shear and sufficient thermodynamic instability concentrated over a shallow lower-tropospheric layer (McCaul, 1991;McCaul & Weisman, 1996). These favorable kinematic conditions are due to the TC warm-core structure and surface friction (Novlan & Gray, 1974;Gentry, 1983), while favorable thermodynamic environments are associated with weak convective inhibition and CAPE typical of the tropics (McCaul, 1991;Molinari et al., 2012). Moreover, recent work has shown that ambient deep-tropospheric vertical wind shear (VWS; i.e., the difference between the 850-and 200-hPa ambient winds) is a key factor controlling the number and TC-relative azimuthal location of tornadoes (Schenkel et al., 2020;Schenkel et al., 2021). However, we lack a complete understanding of the factors controlling the number and TC-relative radial location of tornadoes. One understudied factor that may impact the number and TC-relative radius of tornadoes is the outer size of the TC (McCaul, 1991). Indeed, TC outer size is crucial in describing the scale and magnitude of hazards (Lin et al., 2014;Chavas et al., 2017), and is the focus of this study.

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Lightning and Radar Characteristics of Tornadic Cells in Landfalling Tropical Cyclones

Schenkel,

Calhoun,

Sandmæl

et al. 2023

JGR Atmospheres

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Tropical cyclone (TC) tornadoes are often associated with lower‐skill forecasts compared to midlatitude supercellular tornadoes. Forecasts may be improved through a greater understanding of their lightning and radar signatures. This study investigates the lightning and radar characteristics of TC tornadic cells for comparison with TC non‐tornadic cells (i.e., strongly rotating cells without tornadoes) and non‐TC tornadic cells using three lightning networks and radar data. These results show that the majority of TC tornadic and non‐tornadic cells are not associated with lightning, although the former subset occurs with lightning more often. TC tornadic cases typically have lightning maximized to its northeast, whereas the non‐tornadic subset is associated with a lower density of flashes that are more symmetrically distributed. TC tornadic mesocyclones also show stronger low‐level rotation and convergence at the time of tornado occurrence compared to non‐tornadic cases. Hourly trends in rotation and convergence show stronger increases before tornado occurrence in both variables for TC tornadic mesocyclones, yielding small, nonsignificant differences with non‐TC tornadic mesocyclones during tornado occurrence. Finally, analysis of lightning throughout the TC shows that tornadic cells often occur on the downwind edge of a broad lightning maximum, whereas non‐tornadic cases occur in the middle of a weaker lightning maximum, with these maxima propagating away from the TC in both subsets.

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Choosing a universal mean wind for supercell motion prediction

Cited by 26 publications

References 32 publications

The Statistical Severe Convective Risk Assessment Model

The Statistical Severe Convective Risk Assessment Model

Tropical Cyclone Outer Size Impacts the Number and Location of Tornadoes

Lightning and Radar Characteristics of Tornadic Cells in Landfalling Tropical Cyclones

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