U.S. flag An official website of the United States government.
Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

i

Environmental and radar-derived predictors of tornado intensity within ongoing convective storms



Details

  • Journal Title:
    Journal of Operational Meteorology
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Analyses of Doppler radar data and environmental parameters for 300 tornado cases are used to propose an alternative framework for tornado intensity prediction during pretornadic stages of ongoing storms, conditional on tornadogenesis. This framework is founded on the robust relationship (R² = 0.69) between pretornadic mesocyclone width and the EF rating of the subsequent tornado. In contrast, the linear relationship between pretornadic mesocyclone intensity and EF scale is much weaker (R² = 0.29). Environmental information for each case was additionally used to explore relationships between environmental parameters and tornado intensity. Such relationships depend in part on how the tornado-intensity categories are distributed [i.e., nonsignificant (EF0–1) versus significant (EF2–5), or weak (EF0–1) versus strong (EF2–3) versus violent (EF4–5)]. Low-level shear parameters discriminate the environments of significant tornadoes from nonsignificant tornadoes, but not the environments of violent tornadoes from strong tornadoes. The converse is true for thermodynamic parameters. Operational implementation of this framework for thepurposes of impact-based warnings will require real-time, automated quantification of mesocyclone width in addition to intensity and other attributes. The information gained from the pretornadic analysis demonstrated in this study would allow an operational forecaster to be aware of—and communicate—information about potential tornado intensity in warning text to the public before a tornado develops to better protect life and property. Currently, these relationships are being utilized in machine learning models for binary prediction of non-significant versus significant tornado intensity where skill is being demonstrated.
  • Source:
    Journal of Operational Meteorology (2023)
  • DOI:
  • ISSN:
    2325-6184
  • Format:
    PDF
  • Publisher:
    National Weather Association
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA17OAR4590195
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
    urn:sha-512:20aae26923c912759b9861716bdf00f2a50ec7cd69f2506ca516c03f9af426fede109c6aaa5aafc5481d7396d28ba7c3a4c92c75c95f69dbd61d78032afc51ef
  • Download URL:
  • File Type:
    Filetype[PDF - 2.04 MB ]
PREVIOUS
ON THIS PAGE
Details
The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.
BACK TO TOP