DOI: 10.5061/dryad.z8w9ghx9t
title: Low-level updraft intensification in response to environmental wind profiles

description: Supercell storms can develop a “dynamical response” whereby upward
 accelerations in the lower troposphere amplify as a result of rotationally
 induced pressure falls aloft. These upward accelerations likely modulate a
 supercell’s ability to stretch near-surface vertical vorticity to achieve
 tornadogenesis. This study quantifies such a dynamical response as a
 function of environmental wind profiles commonly found near supercells.
 Self-organizing maps (SOMs) were used to identify recurring low-level wind
 profile patterns from 20,194 model-analyzed, near-supercell soundings. The
 SOM nodes with larger 0–500 m storm-relative helicity (SRH) and streamwise
 vorticity (ωs) corresponded to higher observed tornado probabilities. The
 distilled wind profiles from the SOMs were used to initialize idealized
 numerical simulations of updrafts. In environments with large 0–500 m SRH
 and large ωs, a rotationally induced pressure deficit, increased dynamic
 lifting, and a strengthened updraft resulted. The resulting
 upward-directed accelerations were an order of magnitude stronger than
 typical buoyant accelerations. At 500 m AGL, this dynamical response
 increased the vertical velocity by up to 25 m s–1, vertical vorticity by
 up to 0.2 s–1, and pressure deficit by up to 5 hPa. This response
 specifically augments the near-ground updraft (the midlevel updraft
 properties are almost identical across the simulations). However,
 dynamical responses only occurred in environments where 0–500 m SRH and ωs
 exceeded 110 m2 s–2 and 0.015 s–1, respectively. The presence vs. absence
 of this dynamical response may explain why environments with higher 0–500
 m SRH and ωs correspond to greater tornado probabilities.
description: The soundings through April 2012 are derived from the Rapid
 Update Cycle model whereas later soundings are derived from the Rapid
 Refresh model. The base-state profiles were combined with the Storm
 Prediction Center’s mesoscale surface objective analysis (SFCOA), and the
 resulting profiles were interpolated to height above ground level from 0
 km to 12 km in 50 m intervals. There were four variations of the
 interpolated wind profiles created: unaltered winds (ground-relative),
 winds rotated to align the 0 – 6 km vector wind difference with the
 abscissa (ground-relative rotated), winds converted to storm-relative
 (storm-relative), and winds converted to storm-relative and then rotated
 to align the 0 – 6 km vector wind difference with the abscissa
 (storm-relative rotated). These wind profile suites were then placed into
 self-organizing map algorithms (SOMs) trained on 0 – 500 m zonal and
 meridional wind profiles that returned four different lattices. The
 lattices consisted of the 16 most recurring 0 - 500 m wind profile
 patterns in the set of 20,194 profiles; the ground-relative and
 storm-relative rotated variations were used in Cloud Model 1 (CM1)
 simulations to analyze vertical velocity, relative vertical vorticity, and
 pressure perturbations within a simulated updraft evolving in each of
 these wind profiles. A total of 33 wind profiles (16 ground-relative, 16
 storm-relative rotated, and one quiescent) were combined with a common dry
 adiabatic thermodynamic profile and then initialized and maintained by a
 constant, artificial vertical velocity tendency. The pressure perturbation
 fields were decomposed into buoyant, dynamic linear, and dynamic
 non-linear components, and associated vertical perturbation pressure
 gradient accelerations were analyzed to identify and quantify the
 supercell low-level dynamical response. Processing the dataset in this way
 allowed the authors to identify and quantify the supercell low-level
 dynamical response as a function of low-level (0 – 500 m) environmental
 wind profiles.
description: There is a general ReadMe file (README.txt) located within the
 included .tar files (data is hosted by Dryad and software is hosted
 by Zenodo). While there is a list of information about the 20,194 SPC
 soundings in the data .tar file (located in the “input_soundings_SOM”
 directory and named “SPC_Dataset_Information.txt”), the actual soundings
 themselves are not provided. Additionally, the Bunkers storm motion
 estimates, mixed-layer convective available potential energy (MLCAPE),
 mixed-layer convective inhibition (MLCIN), and mixed-layer lifted
 condensation level (MLLCL) for each of the 20,194 environments are not
 provided. Please contact the authors of the dataset entry and related
 journal article for more information.