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Incorporating UH Occurrence Time to Ensemble-Derived Tornado Probabilities

Authors :
Adam J. Clark
Scott R. Dembek
Burkely T. Gallo
Israel L. Jirak
Richard L. Thompson
Bryan T. Smith
Source :
Weather and Forecasting. 34:151-164
Publication Year :
2019
Publisher :
American Meteorological Society, 2019.

Abstract

Probabilistic ensemble-derived tornado forecasts generated from convection-allowing models often use hourly maximum updraft helicity (UH) alone or in combination with environmental parameters as a proxy for right-moving (RM) supercells. However, when UH occurrence is a condition for tornado probability generation, false alarm areas can occur from UH swaths associated with nocturnal mesoscale convective systems, which climatologically produce fewer tornadoes than RM supercells. This study incorporates UH timing information with the forecast near-storm significant tornado parameter (STP) to calibrate the forecast tornado probability. To generate the probabilistic forecasts, three sets of observed climatological tornado frequencies given an RM supercell and STP value are incorporated with the model output, two of which use UH timing information. One method uses the observed climatological tornado frequency for a given 3-h window to generate the probabilities. Another normalizes the observed climatological tornado frequency by the number of hail, wind, and tornado reports observed in that 3-h window compared to the maximum number of reports in any 3-h window. The final method is independent of when UH occurs and uses the observed climatological tornado frequency encompassing all hours. The normalized probabilities reduce the false alarm area compared to the other methods but have a smaller area under the ROC curve and require a much higher percentile of the STP distribution to be used in probability generation to become reliable. Case studies demonstrate that the normalized probabilities highlight the most likely area for evening RM supercellular tornadoes, decreasing the nocturnal false alarm by assuming a linear convective mode.

Details

ISSN :
15200434 and 08828156
Volume :
34
Database :
OpenAIRE
Journal :
Weather and Forecasting
Accession number :
edsair.doi...........565a26d79912d33f26cd69615c38d8fa
Full Text :
https://doi.org/10.1175/waf-d-18-0108.1