• AMS Council, 2008: Enhancing weather information with probability forecasts. Bull. Amer. Meteor. Soc., 89, 10491053.

  • Brooks, H., C. Doswell III, and M. Kay, 2003: Climatological estimates of local daily tornado probability for the United States. Wea. Forecasting, 18, 626640, https://doi.org/10.1175/1520-0434(2003)018<0626:CEOLDT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cross, R. N., D. S. Ladue, T. Kloss, and S. Ernst, 2019: When uncertainty is certain: The creation and effects of amiable distrust between emergency managers and forecast information in the southeastern United States. 14th Symp. on Societal Applications, Phoenix, AZ, Amer. Meteor. Soc., TJ3.3, https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/352381.

    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, and D. W. Burgess, 1988: On some issues of United States tornado climatology. Mon. Wea. Rev., 116, 495501, https://doi.org/10.1175/1520-0493(1988)116<0495:OSIOUS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fundel, V. J., N. Fleischhut, S. M. Herzog, M. Göber, and R. Hagedorn, 2019: Promoting the use of probabilistic weather forecasts through a dialogue between scientists, developers and end-users. Quart. J. Roy. Meteor. Soc., 145, 210231, https://doi.org/10.1002/qj.3482.

    • Search Google Scholar
    • Export Citation
  • Joslyn, S., and S. Savelli, 2010: Communicating forecast uncertainty: Public perception of weather forecast uncertainty. Meteor. Appl., 17, 180195, https://doi.org/10.1002/met.190.

    • Search Google Scholar
    • Export Citation
  • Krocak, M. J., and H. E. Brooks, 2018: Climatological estimates of hourly tornado probability for the United States. Wea. Forecasting, 33, 5969, https://doi.org/10.1175/WAF-D-17-0123.1.

    • Search Google Scholar
    • Export Citation
  • Krocak, M. J., and H. E. Brooks, 2019: Testing and verifying potential severe timing forecasts in the Hazardous Weather Testbed. Ninth Conf.on Transition of Research to Operations, Phoenix, AZ, Amer. Meteor. Soc., 8B.3, https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/350019.

    • Search Google Scholar
    • Export Citation
  • Lanicci, J. M., and T. T. Warner, 1991: A synoptic climatology of the elevated mixed-layer inversion over the southern Great Plains in spring. Part I: Structure, dynamics, and seasonal evolution. Wea. Forecasting, 6, 181197, https://doi.org/10.1175/1520-0434(1991)006<0181:ASCOTE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Morss, R. E., J. L. Demuth, and J. K. Lazo, 2008: Communicating uncertainty in weather forecasts: A survey of the U.S. public. Wea. Forecasting, 23, 974991, https://doi.org/10.1175/2008WAF2007088.1.

    • Search Google Scholar
    • Export Citation
  • National Research Council, 2006: Completing the Forecast: Characterizing and Communicating Uncertainty for Better Decisions Using Weather and Climate Forecasts. National Academies Press, 124 pp., https://doi.org/10.17226/11699.

  • NOAA Storm Prediction Center, 2019a: SPC products page. NOAA, accessed 12 September 2019, https://www.spc.noaa.gov/misc/about.html.

  • NOAA Storm Prediction Center, 2019b: WCM Page. NOAA, accessed 13 June 2019, https://www.spc.noaa.gov/wcm/.

  • Rothfusz, L. P., R. Schneider, D. Novak, K. Klockow, A. E. Gerard, C. Karstens, G. J. Stumpf, and T. M. Smith, 2018: FACETs: A proposed next-generation paradigm for high-impact weather forecasting. Bull. Amer. Meteor. Soc., 99, 20252043, https://doi.org/10.1175/BAMS-D-16-0100.1.

    • Search Google Scholar
    • Export Citation
  • Savelli, S., and S. Joslyn, 2012: Boater safety: Communicating weather forecast information to high-stakes end users. Wea. Climate Soc., 4, 719, https://doi.org/10.1175/WCAS-D-11-00025.1.

    • Search Google Scholar
    • Export Citation
  • Skinner, P. S., and Coauthors, 2018: Object-based verification of a prototype warn-on-forecast system. Wea. Forecasting, 33, 12251250, https://doi.org/10.1175/WAF-D-18-0020.1.

    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., D. M. Wheatley, N. T. Atkins, R. W. Przybylinski, and R. Wolf, 2006: Buyer beware: Some words of caution on the use of severe wind reports in postevent assessment and research. Wea. Forecasting, 21, 408415, https://doi.org/10.1175/WAF925.1.

    • Search Google Scholar
    • Export Citation
  • Verbout, S. M., H. Brooks, L. M. Leslie, and D. M. Schultz, 2006: Evolution of the U.S. tornado database: 1954–2003. Wea. Forecasting, 21, 8693, https://doi.org/10.1175/WAF910.1.

    • Search Google Scholar
    • Export Citation
  • Wilson, K. A., P. L. Heinselman, P. S. Skinner, J. J. Choate, and K. E. Klockow-McClain, 2019: Meteorologists’ interpretations of storm-scale ensemble-based forecast guidance. Wea. Climate Soc., 11, 337354, https://doi.org/10.1175/WCAS-D-18-0084.1.

    • Search Google Scholar
    • Export Citation
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An Analysis of Subdaily Severe Thunderstorm Probabilities for the United States

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  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • 2 NOAA/OAR/National Severe Storms Laboratory, and School of Meteorology, University of Oklahoma, Norman, Oklahoma
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Abstract

One of the challenges of providing probabilistic information on a multitude of spatiotemporal scales is ensuring that information is both accurate and useful to decision-makers. Focusing on larger spatiotemporal scales (i.e., from convective outlook to weather watch scales), historical severe weather reports are analyzed to begin to understand the spatiotemporal scales that hazardous weather events are contained within. Reports from the Storm Prediction Center’s report archive are placed onto grids of differing spatial scales and then split into 24-h convective outlook days (1200–1200 UTC). These grids are then analyzed temporally to assess over what fraction of the day a single location would generally experience severe weather events. Different combinations of temporal and spatial scales are tested to determine how the reference class (or the choice of what scales to use) alters the probabilities of severe weather events. Results indicate that at any given point in the United States on any given day, more than 95% of the daily reports within 40 km of the point occur in a 4-h period. Therefore, the SPC 24-h convective outlook probabilities can be interpreted as 4-h convective outlook probabilities without a significant change in meaning. Additionally, probabilities and threat periods are analyzed at each location and different times of year. These results indicate little variability in the duration of severe weather events, which allows for a consistent definition of an “event” for all locations in the continental United States.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Makenzie J. Krocak, makenzie.krocak@noaa.gov

Abstract

One of the challenges of providing probabilistic information on a multitude of spatiotemporal scales is ensuring that information is both accurate and useful to decision-makers. Focusing on larger spatiotemporal scales (i.e., from convective outlook to weather watch scales), historical severe weather reports are analyzed to begin to understand the spatiotemporal scales that hazardous weather events are contained within. Reports from the Storm Prediction Center’s report archive are placed onto grids of differing spatial scales and then split into 24-h convective outlook days (1200–1200 UTC). These grids are then analyzed temporally to assess over what fraction of the day a single location would generally experience severe weather events. Different combinations of temporal and spatial scales are tested to determine how the reference class (or the choice of what scales to use) alters the probabilities of severe weather events. Results indicate that at any given point in the United States on any given day, more than 95% of the daily reports within 40 km of the point occur in a 4-h period. Therefore, the SPC 24-h convective outlook probabilities can be interpreted as 4-h convective outlook probabilities without a significant change in meaning. Additionally, probabilities and threat periods are analyzed at each location and different times of year. These results indicate little variability in the duration of severe weather events, which allows for a consistent definition of an “event” for all locations in the continental United States.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Makenzie J. Krocak, makenzie.krocak@noaa.gov
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