1. Radar Climatology of Tornadoes in High Shear, Low CAPE Environments in the Mid-Atlantic and Southeast Jason Davis Matthew Parker North Carolina State University NC State-NWS CSTAR Workshop November 16, 2012 Acknowledgements: NOAA CSTAR grant ( NA10NWS4680007), AMS/NASA Earth Science Graduate Fellowship Program NWS collaborators, especially Justin Lane, Patrick Moore, Jonathan Blaes, and Hunter Coleman Andy Dean from SPC

2. Motivation Issuing accurate tornado warnings in high shear, low CAPE (HSLC) environments is a difficult challenge for forecasters.

3. Motivation Smaller and shallower storms compared to higher CAPE environments. Storm appearance on radar can vary markedly from the typical structures/signatures. Quick spin-ups. Previous radar studies of HSLC tornadoes have primarily been limited to case studies. – i.e. McAvoy et al. 2000, Lane and Moore 2006

4. Methods For this study, a high shear, low CAPE (HSLC) environment is defined as – SBCAPE < 500 J/kg – 0-6 km bulk shear > 35 kts Tornado reports taken from the SPC’s severe weather database (Smith et al. 2012). Shear and CAPE values determined from nearest grid point in hourly SPC mesoanalysis data (Thompson et al. 2012). 100 HSLC severe weather events were identified by area WFOs between January 2006 and April 2011.

5. Outline I.Regional climatology of HSLC tornadoes II.Climatology of convective modes for HSLC tornadoes. III.Climatology of mesocyclones/mesovortices for HSLC tornadoes. IV.Conclusions

6. Regional Climatology of HSLC Tornadoes

7. Convective Modes Climatology Results Based on data from Smith et al. (2012) convective mode database.

8. Convective Modes Climatology Results On days with HSLC tornadoes occurring in part of the domain, the high shear, high CAPE tornadoes in other areas of the domain have a greater percentage of supercells.

9. Regional climatology of convective modes

11. Climatology of HSLC Vortices-Methods Azimuthal shear used to measure the strength of the radar-observed rotation in mesocyclones/ mesovortices associated with tornadic and non- tornadic HSLC storms. – Gradient in radial velocity in the azimuthal direction.

12. Climatology of HSLC Vortices-Methods Warning Decision Support System-Integrated Information (WDSS-II) application (Lakshmanan et al. 2007) used to generate azimuthal shear using the linear least squares derivative method (Smith and Elmore 2004). A tracking algorithm was developed to track azimuthal shear maxima over time (see preprint). Only used cases when WSR-88D “super res” data was available (after summer 2008). Non-tornadic vortices found by using false alarm tornado warnings.

13. Tracking algorithm example

14. 83 tornadic vortices (yellow) and 84 non-tornadic vortices (red) tracked.

16. Vortices binned by range from radar

17. Preliminary Results t  -25mint  +25min

18. Comparing tornadic and non-tornadic vortices

19. Preliminary Results

20. Comparing tornadic and non-tornadic vortices

21. Preliminary Results

22. Comparing tornadic and non-tornadic vortices

23. Vortex Vertical Structure

27. Conclusions Greater relative frequency of QLCS HSLC tornadoes and lower relative frequency of discrete supercell HSLC tornadoes. Azimuthal shear discriminates well at the base scan between tornadic and non-tornadic vortices close to the radar, but not very well farther from the radar. This tendency is also apparent at higher tilts as well.

28. Future Work Further quantitative analyses of results, including – vortex lifetime and depth – differences between supercells and QLCSs. Find ways to apply these results to operations. Addition of more cases. Compare results to higher CAPE environments. Study of radar reflectivity signatures.

29. Conclusions Greater relative frequency of QLCS HSLC tornadoes and lower relative frequency of discrete supercell HSLC tornadoes. Azimuthal shear discriminates well at the base scan between tornadic and non-tornadic vortices close to the radar, but not very well farther from the radar. This tendency is also apparent at higher tilts as well.

30. References Lakshmanan, V., T. Smith, G. Stumpf, and K. Hondl, 2007: The Warning Decision Support System–Integrated Information. Wea. Forecasting, 22, 596–612. Lane J.D., and P.D. Moore, 2006: Observations of a non-supercell tornadic thunderstorm from terminal Doppler weather radar. Preprints, 23 rd Conf. Severe Local Storms, St. Louis, MO., P4.5. McAvoy, B. P., W. A. Jones, and P. D. Moore, 2000: Investigation of an unusual storm structure associated with weak to occasionally strong tornadoes over the eastern United States. Preprints, 20 th Conf. on Severe Local Storms, Orlando, FL, 182-185. Smith, B.T., R.L. Thompson, J.S. Grams, and C. Broyles, 2012: Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part I: Storm Classification and Climatology. Wea. Forecasting, 27, 1114-1135. Smith, T.M. and K. L. Elmore, 2004: The use of radial velocity derivatives to diagnose rotation and divergence. Preprints, 11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc., P5.6. Thompson, R.L., B.T. Smith, J.S. Grams, A.R. Dean, and C. Broyles: 2012 Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part II: Supercell and QLCS Tornado Environments. Wea. Forecasting, 27, 1136-1154.

31. Extra Slides

32. Tracking algorithm Predicted position of vortex at previous time t = t 0 – Δt based on estimated motion vector Position of vortex at initial time t = t 0 Vortex motion vector uncertainty Possible actual vortex position Tornado touchdown point, or center of false alarm warning.

34. Preliminary Results