Environmental and Radar-Derived Predictors of Tornado Intensity within Ongoing Convective Storms

Michael F. Sessa, Robert J. Trapp

Research output: Contribution to journalArticlepeer-review


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 the purposes 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.

Original languageEnglish (US)
Pages (from-to)49-71
Number of pages23
JournalJournal of Operational Meteorology
StatePublished - 2023

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science
  • Management Science and Operations Research


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