Articles | Volume 18, issue 4
https://doi.org/10.5194/nhess-18-1261-2018
https://doi.org/10.5194/nhess-18-1261-2018
Research article
 | 
27 Apr 2018
Research article |  | 27 Apr 2018

Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

Paul W. Miller and Thomas L. Mote

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Atkins, N. T. and Wakimoto, R. M.: Wet microburst activity over the southeastern United States: implications for forecasting, Weather Forecast., 6, 470–482, https://doi.org/10.1175/1520-0434(1991)006<0470:WMAOTS>2.0.CO;2, 1991. 
Benjamin, S. G., Dévényi, D., Weygandt, S. S., Brundage, K. J., Brown, J. M., Grell, G. A., Kim, D., Schwartz, B. E., Smirnova, T. G., Smith, T. L., and Manikin, G. S.: An hourly assimilation–forecast cycle: the RUC, Mon. Weather Rev., 132, 495–518, https://doi.org/10.1175/1520-0493(2004)132<0495:AHACTR>2.0.CO;2, 2004. 
Black, A. W. and Mote, T. L.: Characteristics of winter-precipitation-related transportation fatalities in the United States, Weather Clim. Soc., 7, 133–145, https://doi.org/10.1175/WCAS-D-14-00011.1, 2015. 
Black, A. W., Villarini, G., and Mote, T. L.: Effects of rainfall on vehicle crashes in six U.S. states, Weather Clim. Soc., 9, 53–70, https://doi.org/10.1175/WCAS-D-16-0035.1, 2017. 
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Short summary
The likelihood of severe weather events in synoptically weakly forced thunderstorm (WFT) environments is best characterized by lapse-rate-based parameters. These measures, also among the most accurate model-derived variables, are posited to best capture the subtle convective environmental differences that favor WFT severity. Forecasters should consider weighting their WFT forecasts in favor of lapse-rate-based parameters over others that may be more sensitive to model biases.
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