Editorial Type:
Article
Article Type:
Research Article

Empirical Examination of the Factors Regulating Thunderstorm Initiation

Noah A. Lock University of Nebraska–Lincoln, Lincoln, Nebraska

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Adam L. Houston University of Nebraska–Lincoln, Lincoln, Nebraska

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Print Publication:
01 Jan 2014
DOI:
https://doi.org/10.1175/MWR-D-13-00082.1
Page(s):
240–258
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Abstract

Initiation is the part of the convective life cycle that is currently least understood and least well forecast. The inability to properly forecast the timing and/or location of deep convection initiation degrades forecast skill, especially during the warm season. To gain insight into what atmospheric parameters distinguish areas where storms initiate from areas where they do not initiate, over 55 000 thunderstorm initiation points over the central United States from 2005 to 2007 are found and a number of thermodynamic and kinematic parameters are computed from 20-km Rapid Update Cycle (RUC)-2 data. In addition to the initiation points, data are also collected at nearby locations where thunderstorms did not initiate (null points) for comparison. Thunderstorm identification and tracking are done using several tools within the Warning Decision Support Services–Integrated Information (WDSS-II) package and a thunderstorm tracking algorithm called Thunderstorm Observation by Radar (ThOR). The parameters being examined are intended to represent the four main factors governing the behavior of convection: buoyancy, dilution, lift, and inhibition. Statistical analysis of the data shows that there is no threshold of any single parameter that is consistently able to discriminate between initiation and noninitiation. However, case-by-case comparison of the values showed that lift is most often the factor that distinguishes the thunderstorm initiation environment from other areas.

Corresponding author address: Noah A. Lock, University of Nebraska–Lincoln, 214 Bessey Hall, Lincoln, NE 68588. E-mail: nlock@huskers.unl.edu

Abstract

Initiation is the part of the convective life cycle that is currently least understood and least well forecast. The inability to properly forecast the timing and/or location of deep convection initiation degrades forecast skill, especially during the warm season. To gain insight into what atmospheric parameters distinguish areas where storms initiate from areas where they do not initiate, over 55 000 thunderstorm initiation points over the central United States from 2005 to 2007 are found and a number of thermodynamic and kinematic parameters are computed from 20-km Rapid Update Cycle (RUC)-2 data. In addition to the initiation points, data are also collected at nearby locations where thunderstorms did not initiate (null points) for comparison. Thunderstorm identification and tracking are done using several tools within the Warning Decision Support Services–Integrated Information (WDSS-II) package and a thunderstorm tracking algorithm called Thunderstorm Observation by Radar (ThOR). The parameters being examined are intended to represent the four main factors governing the behavior of convection: buoyancy, dilution, lift, and inhibition. Statistical analysis of the data shows that there is no threshold of any single parameter that is consistently able to discriminate between initiation and noninitiation. However, case-by-case comparison of the values showed that lift is most often the factor that distinguishes the thunderstorm initiation environment from other areas.

Corresponding author address: Noah A. Lock, University of Nebraska–Lincoln, 214 Bessey Hall, Lincoln, NE 68588. E-mail: nlock@huskers.unl.edu
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  • Banacos, P. C., and D. M. Schultz, 2005: The use of moisture flux convergence in forecasting convective initiation: Historical and operational perspectives. Wea. Forecasting, 20, 351–366.

    • Search Google Scholar
    • Export Citation

  • Benjamin, S. G., and Coauthors, 2004: An hourly assimilation–forecast cycle: The RUC. Mon. Wea. Rev., 132, 495–518.

  • Coniglio, M. C., 2012: Verification of RUC 0–1-h forecasts and SPC mesoscale analyses using VORTEX2 soundings. Wea. Forecasting, 27, 667–683.

    • Search Google Scholar
    • Export Citation

  • Corfidi, S. F., S. J. Corfidi, and D. M. Schultz, 2008: Elevated convection and castellanus: Ambiguities, significance, and questions. Wea. Forecasting, 23, 1280–1303.

    • Search Google Scholar
    • Export Citation

  • Doswell, C. A., III, and E. N. Rasmussen, 1994: The effect of neglecting the virtual temperature correction on CAPE calculations. Wea. Forecasting, 9, 625–629.

    • Search Google Scholar
    • Export Citation

  • Doswell, C. A., III, and D. M. Schultz, 2006: On the use of indices and parameters in forecasting severe storms. Electronic J. Severe Storms Meteor., 1 (3). [Available online at http://www.ejssm.org/ojs/index.php/ejssm/article/viewArticle/11/12.]

    • Search Google Scholar
    • Export Citation

  • Glickman, T. S., Ed., 2000: Glossary of Meteorology. 2nd ed. Amer. Meteor. Soc., 855 pp.

  • Houston, A. L., and D. Niyogi, 2007: The sensitivity of convective initiation to the lapse rate of the active cloud-bearing layer. Mon. Wea. Rev., 135, 3013–3032.

    • Search Google Scholar
    • Export Citation

  • Johns, R. H., and C. Doswell, 1992: Severe local storms forecasting. Wea. Forecasting, 7, 588–612.

  • Lahowetz, J., A. Houston, G. Limpert, A. Gibbs, and B. L. Barjenbruch, 2010: A technique for developing a U.S. climatology of thunderstorms: The ThOR algorithm. Extended Abstracts, 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., 16B.1. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176174.htm.]

  • Lakshmanan, V., T. Smith, K. Hondl, G. Stumpf, and A. Witt, 2006: A real-time, three- dimensional, rapidly updating, heterogeneous radar merger technique for reflectivity, velocity, and derived products. Wea. Forecasting, 21, 802–823.

    • Search Google Scholar
    • Export Citation

  • Lakshmanan, V., A. Fritz, T. Smith, K. Hondl, and G. Stumpf, 2007a: An automated technique to quality control radar reflectivity data. J. Appl. Meteor. Climatol., 46, 288–305.

    • Search Google Scholar
    • Export Citation

  • Lakshmanan, V., T. Smith, G. Stumpf, and K. Hondl, 2007b: The Warning Decision Support System–Integrated Information. Wea. Forecasting, 22, 596–612.

    • Search Google Scholar
    • Export Citation

  • Lakshmanan, V., K. Hondl, and R. Rabin, 2009: An efficient, general-purpose technique for identifying storm cells in geospatial images. J. Atmos. Oceanic Technol., 26, 523–537.

    • Search Google Scholar
    • Export Citation

  • Lee, B. D., R. D. Farley, and M. R. Hjelmfelt, 1991: A numerical case study of convection initiation along colliding convergence boundaries in northeast Colorado. J. Atmos. Sci., 48, 2350–2366.

    • Search Google Scholar
    • Export Citation

  • Mecikalski, J., and K. Bedka, 2006: Forecasting convective initiation by monitoring the evolution of moving cumulus in daytime GOES imagery. Mon. Wea. Rev., 134, 49–78.

    • Search Google Scholar
    • Export Citation

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360.

  • Moncrieff, M. W., and M. J. Miller, 1976: The dynamics and simulation of tropical cumulonimbus and squall lines. Quart. J. Roy. Meteor. Soc., 102, 373–394.

    • Search Google Scholar
    • Export Citation

  • NCDC, cited2010: North American Regional Reanalysis (NARR) data for 2005–2007. [Available online at http://nomads.ncdc.noaa.gov/data.php?name=access#narr_datasets.]

  • NCDC, cited2011a: Rapid Update Cycle (RUC) 20 km grid for 2005–2007. [Available online at http://ruc.noaa.gov/.]

  • NCDC, cited2011b: Level-II NEXRAD data for 2005–2007. [Available online at http://has.ncdc.noaa.gov/pls/plhas/HAS.FileAppSelect?datasetname=6500.]

  • Peckham, S. E., and L. J. Wicker, 2000: The influence of topography and lower-tropospheric winds on dryline morphology. Mon. Wea. Rev., 128, 2165–2189.

    • Search Google Scholar
    • Export Citation

  • Purdom, J. F. W., 1982: Subjective interpretations of geostationary satellite data for nowcasting. Nowcasting, K. Browning, Ed., Academic Press, 149–166.

  • Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463–485.

  • Stull, R. B., 1985: A fair-weather cumulus cloud classification scheme for mixed-layer studies. J. Climate Appl. Meteor., 24, 49–56.

    • Search Google Scholar
    • Export Citation

  • Thompson, R. L., R. Edwards, J. Hart, K. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 1243–1261.

    • Search Google Scholar
    • Export Citation

  • Thompson, R. L., C. M. Mead, and R. Edwards, 2007: Effective storm-relative helicity and bulk shear in supercell thunderstorm environments. Wea. Forecasting, 22, 102–115.

    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated convective storms on wind shear and buoyancy. Mon. Wea. Rev., 110, 504–520.

    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., and W. E. Schreiber, 1986: Initiation of convective storms at radar-observed boundary-layer convergence lines. Mon. Wea. Rev., 114, 2516–2536.

    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., G. B. Foote, N. A. Crook, J. C. Fankhauser, C. G. Wade, J. D. Tuttle, C. K. Mueller, and S. K. Kreuger, 1992: The role of boundary-layer convergence zones and horizontal rolls in the initiation of thunderstorms: A case study. Mon. Wea. Rev., 120, 1785–1815.

    • Search Google Scholar
    • Export Citation

  • Xue, M., and W. J. Martin, 2006: A high-resolution modeling study of the 24 May 2002 dryline case during IHOP. Part II: Horizontal convective rolls and convective initiation. Mon. Wea. Rev., 134, 172–191.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., and E. N. Rasmussen, 1998: The initiation of moist convection at the dryline: Forecasting issues from a case study perspective. Wea. Forecasting, 13, 1106–1131.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., T. J. Lee, and R. A. Pielke Sr., 1997: Convective initiation at the dryline: A modeling study. Mon. Wea. Rev., 125, 1001–1026.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., E. N. Rasmussen, M. S. Buban, Y. P. Richardson, L. J. Miller, and R. M. Rabin, 2007: The “triple point” on 24 May 2002 during IHOP. Part II: Ground radar and in situ boundary layer analysis of cumulus development and convection initiation. Mon. Wea. Rev., 135, 2443–2472.

    • Search Google Scholar
    • Export Citation
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