McKenna W. Stanford University of South Alabama Meteorology Weather-Ready Nation

1. Utility of 0-3 km Bulk Shear Vectors as a Predictor for Quasi-Linear Convective System (QLCS) Tornadoes McKenna W. Stanford University of South Alabama Meteorology Weather-Ready Nation National Weather Service, Springfield, MO David Gaede, Jason Schaumann, & John Gagan NOAA’s National Weather Service

2. Outline • Introduction/Objectives • Background • Methodology • Criteria & Recognition • Results • Statistical Analyses • Application to Protection of Life & Property • Next Steps • Summary • Acknowledgements • References

3. Introduction/Objectives • McKenna W. Stanford • University of South Alabama • Meteorology, Major • Mathematics, Minor • National Weather Service, Springfield, MO WFO • Weather-Ready Nation • Personal Motivation: My interest in severe convective storms and aspirations to investigate them and improve warning strategies for destructive events aided in my selection of this project. • Objective: Statistically verify identified predictors for QLCS tornadoes and improve Tornado Warning lead times in order to satisfy NOAA’s objective for “reduced loss of life, property, and disruption from high-impact events.”

4. Co-Collaborators • Contributors to this project included: • David Gaede, Mentor, Science & Operations Officer • Jason Schaumann, Co-Mentor, Senior Forecaster • John Gagan, Co-Mentor, Senior Forecaster

5. QLCS Background • Quasi-Linear Convective Systems (QLCSs) • Produce large swaths of wind damage • Descending rear-inflow jets (RIJs) • Embedded microbursts & macrobursts • Localized swaths of (E)F-0 to (E)F-1 wind damage can occur • Can contain embedded tornadoes • Usually (E)F-0 to (E)F-1 damage • Documented damage intensity up to (E)F-4

6. QLCS vs. Supercell Moore, OK – KTLX 20 May 2013 Sunset Hills, MO – KLSX 31 December 2010 Photo Courtesy of NWS St. Louis Photo Courtesy of FEMA

7. Motivation for Research • Much research has been conducted involving environments and physical processes related to supercell tornadoes versus those of QLCSs • Warning skill and lead times for QLCS tornadoes remains poor • Most warning decision forecasters issue Tornado Warnings after mesovortex development • Recent studies have shown the average lead time for this technique is only around 5 minutes • Can also result in high False Alarm Rates (FAR) - “ crying wolf ”

8. Additional Disadvantages to Current Tornado Warning Strategies • Due to the quick nature of mesovortex genesis, mesovoritices can form in between radar volume scans • Radar beam will overshoot features at distances greater than 40 nautical miles (nm) from the radar • Where does the 0.5° tilt reach 1 km AGL? • How do we resolve these issues?

9. Alternative Methodology to Anticipate QLCS Tornadogenesis • Schaumann and Przybylinski (2012) examined several QLCS events to identify three co-existing ingredients, both physical properties and radar characteristics, that present an increased likelihood for mesovortex genesis and rapid intensification • (1) A portion of the QLCS in which the system cold pool and ambient low-level shear are nearly balanced or slightly shear dominant AND • (2) The 0-3 km line-normal bulk shear magnitudes are equal to or greater than 15 m s-1 (30 knots) AND • (3) A rear-inflow jet (RIJ) or enhanced outflow causes a surge or bow in the line • The intent of this study is to verify this three-ingredients method and provide statistical significance to its practice

10. Methodology – Case Selection • Period of study: 2005-2011 • 31 cases • Warm & cold season

11. Mesovortex Identification GR2Analyst Software

12. Surge Identification Surge on rear flank of leading convective line Surge on forward flank of leading convective line GR2Analyst Software GR2Analyst Software

13. Determining Balance Regime 0-3 km Bulk Shear Vectors 0.5° Z • Five Different Regimes • Shear Dominant • Slightly Shear Dominant • Balanced • Slightly Cold Pool Dominant • Cold Pool Dominant Shear Dominant Cold Pool Dominant Balanced Balanced & Slightly Shear Dominant are regimes necessary in three-ingredients method

14. Determining 0-3 km Bulk Shear Vector Magnitude & Direction 4-Panels Courtesy of Chad Gravelle, Ph.D.

15. Determining 0-3 km Line-Normal Shear Magnitude Updraft-Downdraft Convergence Zone (UDCZ) Δu Θ Δu = sin(θ)m m Δu = line-normal magnitude of 0-3 km bulk shear Θ= angle between convective line and 0-3 km bulk shear vector m= magnitude of 0-3 km bulk shear vector

16. Performance of Three-Ingredients Method • 67Mesovortices • 64 Non-Mesovortex Surges • 52% of identified mesovorticies produced at least one report of winds ≥ 50 knots and/or a tornado • Verification for three-ingredients method • Probability of Detection (POD) – 79% • False Alarm Rate (FAR) – 23%

17. 0-3 km Bulk and Line-Normal Shear for all Mesovortices Mean Line-Normal Shear– 33 kts Mean Bulk Shear – 37 kts

18. 0-3 km Line-Normal Shear for all Mesovortices & Non-Mesovortex Surges Mean Line-Normal Shear for Non-Mesovortex Surges– 26 kts Mean Line-Normal Shear for Mesovortices– 33 kts

19. Three-Ingredients Method for all Mesovortices • Average Surge Genesis to Wind Damage Lead Time – 21 minutes • Average Surge Genesis to Tornado Lead Time • – 18 minutes

20. Tornado Warning Baseline • Government Performance Requirements Act (GPRA) goals for 2013 • Probability of Detection (POD) – 72% • False Alarm Rate (FAR) – 70% • Tornado Warning Lead Time – 13 minutes

21. Three-Ingredients Method for Mesovortex Tornadoes • Scenario: If a Tornado Warning is issued as soon as all three ingredients are met… • New Warning Decision Strategyvs. Current • 18 minutelead time is a substantial increase over the average of 5 minutescurrently offered by warning decision forecasters issuing Tornado Warnings upon the actual genesis of mesovortices

22. Future Work • SLS Manuscript and Poster • Ernest F. Hollings Scholar Research • Formal Research • Conduct NOAA/NWS Training • Interactive Webinars • Work with Warning Decision Training Branch

23. Summary Mesovortex genesis and strong intensification is favored… • In a portion of the QLCS in which the cold pool and ambient low-level shear are nearly balanced or slightly shear-dominant AND • Where 0-3 km line-normal bulk shear magnitudes are equal to or greater than 30 knots AND • Where a rear-inflow jet (RIJ) or enhanced outflow causes a surge or bow in the line.

24. Summary (cont) • 52% of 67 identified mesovorticies produced at least one report of winds ≥ 50 knots and/or a tornado • Utilization of the three-ingredients method for issuing Tornado Warnings would greatly exceed 2013 GPRA goals • POD – 90% • Lead Time – 18 minutes

25. Summary (cont) • Results of utilizing the three-ingredients method offers a substantial and efficient means to reduce the loss of life, property, and disruption from high-impact events through the issuance of more accurate and timely warnings

26. Acknowledgements • Staff at Springfield WFO • Chad Gravelle, Ph.D. for providing the 4-panel RUC files • Ryan Kardell, Meteorological Intern, Springfield WFO for providing several programs used to collect and interrogate data

27. Questions?

28. References • Atkins, N. T., J. M. Arnott, R. W. Przybylinski, R. A. Wolf, and B. D. Ketcham, 2004: Vortex structure and evolution within bow echoes. Part I: Single-Doppler and damage analysis of the 29 June 1998 derecho. Mon. Wea. Rev., 132, 2224-2242. • _____, C. S. Bouchard, R. W. Przybylinski, R. J. Trapp, and G. Schmocker, 2005: Damaging surface wind mechanism within the 10 June 2003 Saint Louis bow echo during BAMEX. Mon. Wea. Rev., 133, 2275-2296. • _____, and M. St. Laurent, 2009a: Bow Echo Mesovortices. Part I: Processes That Influence Their Damaging Potential. Mon. Wea. Rev., 137, 1497–1513. • _____, and M. St. Laurent, 2009b: Bow Echo Mesovortices. Part II: Their Genesis. Mon. Wea. Rev., 137, 1514–1532. • Burgess, D. W., 1974: Study of a right moving thunderstorm utilizing new single Doppler radar evidence. Masters Thesis, Dept. of Meteor., University of Oklahoma, Norman, OK. 77 pp. • _____, and B. F. Smull, 1990: Doppler radar observations of a bow echo with a long-track severe windstorm. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, AB, Canada, Amer. Meteor. Soc., 203-208. • Bryan, G. H., D. Ahijevych, C. Davis, S. Trier, and M. Weisman, 2005: Observations of cold pool properties in mesoscale convective systems during BAMEX. Preprints, 11th Conf. on Severe Local Storms, Albuquerque, Nm, Amer. Meteor. Soc., JP5J. 12.

29. References (cont) • Corfidi, S., F., J. H. Merritt, and J. M Fritsch,1996: Predicting the movement of mesoscale convective complexes.Wea. Forecasting, 11, 41-46. • ____, J. H. Merritt, and J. M Fritsch,1996: Predicting the movement of mesoscale convective complexes. Wea. Forecasting, 11, 41-46. • ____, 1998: Forecasting MCS mode and motion. Preprints, 19th Conf. on Severe Local Storms, Minneapolis, MN, Amer. Meteor. Soc., 626–629. • ____, 2003: Cold Pools and MCS Propagation: Forecasting the Motion of Downwind-Developing MCSs. Wea. Forecasting, 18, 997–1017. • Distance Learning Operations Course (WDTB) • Doswell, C. A. III, 2000: "A Primer on Vorticity for Application in Supercells and Tornadoes". Cooperative Institute for Mesoscale Meteorological Studies, Norman, Oklahoma. • Engerer, N. A., D. J. Stensrud, and M. C. Coniglio, 2008: Surface characteristics of observed cold pools. Mon. Wea. Rev., 136, 4839–4849. • Forbes, G. S., and R. M. Wakimoto, 1983: A concentrated outbreak of tornadoes, downbursts and microbursts, and implications regarding vortex classification. Mon. Wea. Rev., 111, 220-235.

30. References (cont) • Funk. T. W., K. E. Darmofal, J. D. Kirkpatrick, V. L. DeWald, R. W. Przybylinski, G. K. Schmocker, and Y. -J. Lin, 1999: Storm reflectivity and mesocyclone evolution associated with the 15 April 1994 squall line over Kentucky and southern Indiana. Wea. Forecasting, 14, 976-993. • Houze, R. A., Jr., S. A. Rutledge, M. I. Biggerstaff and B. F. Smull, 1989: Interpretation of Doppler weather radar displays of midlatitude mesoscale convective systems. Bull. Amer. Meteor. Soc., 70, 608-619. • Jorgensen, D. P., and B. F. Smull, 1993: Mesovortex circulations seen by airborne Doppler radar within a bow-echo mesoscale convective system. Bull. Amer. Meteor. Soc., 74, 2146-2157. • Markowski, P. M., Y. Richardson, E. Rasmussen, J. Straka, R. Davies-Jones, and R. J. Trapp, 2008: Vortex lines within low-level mesocyclones obtained from pseudo-dual-Doppler radar observations. Mon. Wea. Rev., 136, 3513-3535. • Przybylinski, R. W., 1995: The bow echo: Observations, numerical simulations, and severe weather detection methods. Wea. Forecasting, 10, 203-218.

31. References (cont) • _____, Y. –J., Lin, C. A. Doswell III, G. K. Schmocker, T. J. Shea, T. W. Funk, K. E. Darmofal, J. D. Kirkpatrick, and M. T. Shields, 1996: Storm reflectivity and mesocyclone evolution associated with the 15 April 1994 derecho, Part I: Storm structure and evolution over Missouri and Illinois. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 509-515. • _____, G. K. Schmocker, and Y. –J. Lin, 2000: A Study of Storm and Vortex Morphology during the ‘Intensifying Stage’ of Severe Wind Mesoscale Convective Systems. Preprints, 20th Conf. on Severe Local Storms, Savannah, GA, 6.4. • Rotunno, R.J., J. B. Klemp, and M. L. Weisman, 1988:A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463-485. • Trapp, R. J., E. D. Mitchell, G. A. Tipton, D. A. Effertz, A. I. Watson, D. L. Andra, and M. A. Magsig, 1999: Descending and non-descending tornadic vortex signatures detected by WSR-88D’s. Wea. and Forecasting, 14, 625-639. • _____, and M. L. Weisman, 2003: Low-level mesovortices within squall lines and bow echoes. Part II: Their genesis and implications. Mon. Wea. Rev., 131, 2804–2823. • _____, S. A. Tessendorf, E. S. Godfrey, and H. E. Brooks, 2005: Tornadoes from squall lines and bow echoes. Part I: Climatological distribution. Wea. Forecasting, 20, 23–34. • Weisman, M. L. and R. W. Przybylinski, 1999: Mesoscale convective systems: Squall lines and bow echoes, COMET CBL module, UCAR.

32. References (cont) • _____, and R. J. Trapp, 2003: Low-level mesovortices within squall lines and bow echoes. Part I: Overview and dependence on environmental shear. Mon. Wea. Rev., 131, 2779–2803. • Schaumann, J. S., and R. W. Przybylinski, 2012: Operational Application of 0-3 km Bulk Shear Vectors in Assessing QLCS Mesovortex and Tornado Potential. Preprints, 26th Conf. on Severe Local Storms, Nashville, TN, Amer. Meteor. Soc., 9.10. • Schmidt, J. M., and W. R. Cotton, 1989: A High Plains squall line associated with severe surface winds. J. Atmos. Sci., 46, No. 3, 281-302. • Rasmussen, E. N., 2003: Refined supercell and tornado forecast parameters. Wea. Forecasting, 18, 530-535. • Thompson, R. L., R. Edwards, J. A. Hart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 1243-1261.