A skill assessment of techniques for real-time diagnosis and short-term prediction of tornado intensity using the WSR-88D
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A skill assessment of techniques for real-time diagnosis and short-term prediction of tornado intensity using the WSR-88D

  • 2016

  • By Gibbs, Justin
  • Source: J. Operational Meteor, 4(13), 170-181.
Filetype[PDF-893.55 KB]


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Details:

  • Journal Title:
    Journal of Operational Meteorology
  • Personal Author:
    Gibbs, Justin
  • NOAA Program & Office:
    NWS (National Weather Service)
  • Description:
    Recent advancements in the science of tornado detection have allowed the National Weather Service (NWS) Warning Decision Training Division to incorporate real-time tornado intensity estimation into guidance available to NWS forecasters. This guidance focuses specifically on differentiating between strong/violent (EF2+) and weak (EF0–1) tornadoes. This study evaluates the skill of a portion of that guidance, specifically the quantification of the relationship between rotational velocity signatures and the height of tornadic debris signatures (TDSs) with observed EF-scale tornado damage.

    The guidance is found to be sufficiently skillful at diagnosing tornado intensity. Perhaps most usefully, when attempting to differentiate between weak and strong/violent tornadoes in real-time, skill scores peak at the threshold of 20.57 m s–1 (40 kt) of rotational velocity when the velocity couplet is combined with a TDS. Skill sufficient for operational decision making also is evaluated and found in other permutations of rotational velocity, with and without a TDS, and the guidance regarding the height of the TDS. Beyond realtime diagnosis, several subjectively analyzed radar parameters show skill within the dataset at differentiating between strong/violent and weak tornadoes with lead times of 2–3 volume scans.

  • Source:
    J. Operational Meteor, 4(13), 170-181.
  • DOI:
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

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