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Targeted Observation by Radars and UAS of Supercells: TORUS



Details

  • Journal Title:
    Bulletin of the American Meteorological Society
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Targeted Observation by Radars and Uncrewed Aircraft Aystems (UAS) of Supercells (TORUS) aimed to improve the conceptual model of supercell thunderstorms through advancing the understanding of the role of storm-generated airmass boundaries and coherent structures in the development of near-surface rotation. Research questions guiding the field phase of TORUS focused on left-flank vertical vorticity sheets, streamwise vorticity currents, left-flank convergence boundaries, and rear-flank internal surges. Research questions also aimed to address the relationship between inflow modification and supercell characteristics. Across three field seasons (2019, 2022, and 2023), data on 46 supercell thunderstorms were collected through coordinated deployments of radars, lidars, mobile mesonets, UAS, manned aircraft, radiosondes, and swarmsondes. More than 200 scientists and engineers (many of whom were students) participated in the TORUS field deployments. The scientific motivation for TORUS, experiment design, and examples of data/analysis are presented in this article. Significance Statement Targeted Observation by Radars and Uncrewed Aircraft Systems (UAS) of Supercells (TORUS) was a collaborative research project funded by the National Science Foundation and the National Oceanic and Atmospheric Administration to advance understanding of supercells. TORUS involved more than 200 scientists and engineers (many of whom were students) who led data collection on 46 supercell thunderstorms across three field seasons. This effort constituted the most deployments of UAS within supercells and, on 17 May 2019, likely yielded the longest continuous airborne multi-Doppler radar sampling of a Great Plains supercell ever conducted.
  • Source:
    Bulletin of the American Meteorological Society, 107(2), E249-E276
  • DOI:
  • ISSN:
    0003-0007 ; 1520-0477
  • Format:
    pdf
  • Publisher:
  • Document Type:
  • Rights Information:
    Other
  • Compliance:
    Library
  • Download URL:
  • File Type:
    Filetype[PDF - 4.90 MB]
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:9c8041334829fbbdbfdc240ff859bbbd03d9f8a6e758b278b97d9f5a361ed054889d4db03b1dfa7ede869202b110d4526979aaef33952e4063e9044917d1e991
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