Cold-season tornadoes: Climatological and meteorological insights

Samuel J. Childs, Russ S. Schumacher, John T. Allen

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Tornadoes that occur during the cold season, defined here as November-February (NDJF), pose many societal risks, yet less attention has been given to their climatological trends and variability than their warm-season counterparts, and their meteorological environments have been studied relatively recently. This study aims to advance the current state of knowledge of cold-season tornadoes through analysis of these components. A climatology of all (E)F1-(E)F5 NDJF tornadoes from 1953 to 2015 across a domain of 25°-42.5°N, 75°-100°W was developed. An increasing trend in cold-season tornado occurrence was found across much of the southeastern United States, with a bull's-eye in western Tennessee, while a decreasing trend was found across eastern Oklahoma. Spectral analysis reveals a cyclic pattern of enhanced NDJF counts every 3-7 years, coincident with the period of ENSO. La Niña episodes favor enhanced NDJF counts, but a stronger relationship was found with the Arctic Oscillation (AO). From a meteorological standpoint, the most-tornadic and least-tornadic NDJF seasons were compared using NCEP-NCAR reanalysis data of various severe weather and tornado parameters. The most-tornadic cold seasons are characterized by warm and moist conditions across the Southeast, with an anomalous mean trough across the western United States. In addition, analysis of the convective mode reveals that NDJF tornadoes are common in both discrete and linear storm modes, yet those associated with discrete supercells are more deadly. Taken together, the perspectives presented here provide a deeper understanding of NDJF tornadoes and their societal impacts, an understanding that serves to increase public awareness and reduce human casualty.

Original languageEnglish
Pages (from-to)671-691
Number of pages21
JournalWeather and Forecasting
Volume33
Issue number3
DOIs
StatePublished - Jun 1 2018

Keywords

  • Climatology
  • Data mining
  • Mesoscale systems
  • Oscillations
  • Reanalysis data
  • Statistical techniques

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