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Skillful Subseasonal Forecasts of Weekly Tornado and Hail Activity Using the Madden-Julian Oscillation

  • Cory F. Baggett
  • , Kyle M. Nardi
  • , Samuel J. Childs
  • , Samantha N. Zito
  • , Elizabeth A. Barnes
  • , Eric D. Maloney
  • Colorado State University
  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

In the United States, severe weather poses a threat to society, producing tornadoes and hail that can result in hundreds of casualties and billions of dollars in damages. Fortunately, skillful predictions of severe weather for short lead times of 0–8 days and longer lead times exceeding 1 month have been realized. However, this leaves a forecast gap at subseasonal to seasonal lead times of 2–5 weeks, when early-action decision making by stakeholders is typically made. Here we develop an empirical prediction model that fills this gap during March–June when severe weather is most prevalent across the United States. We demonstrate skillful weekly forecasts of opportunity with lead times of 2–5 weeks of environmental parameters favorable to severe weather, as well as actual tornado and hail activity. To attain this skill, we use as a predictor the current state of active phases of the Madden-Julian Oscillation, known to have physical teleconnections with future weather over the United States. The model has significant skill in regions such as the Plains and the Southeast, providing stakeholders with valuable extended forewarning.

Original languageEnglish
Pages (from-to)12,661-12,675
JournalJournal of Geophysical Research: Atmospheres
Volume123
Issue number22
DOIs
StatePublished - Nov 27 2018
Externally publishedYes

Keywords

  • hail
  • MJO
  • prediction
  • S2S
  • teleconnection
  • tornado

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