A Multi-Parameter Approach to Lightning Prediction

1. A Multi-Parameter Approach to Lightning Prediction Gail Hartfield NOAA/NWS Raleigh, North Carolina 2011 American Meteorological Society Annual Meeting, Seattle, WA

2. Much value can be gained from a skillful forecast of lightning activity. • Accurate lightning prediction remains challenging • Process still poorly understood • Incomplete metrics (only CGs are detected over much of U.S.) • Improved near-term modeling and observations are promising • Predictions could have enormous benefits for the weather enterprise and related/dependent groups • Aviation • Utilities • Recreation/outdoor activities U.S. Lightning Deaths, 2000-2009 Map courtesy of Ronald Holle, Vaisala, Inc., and B.Curran and M. Bragaw, and NASA MSFC Lightning Imaging Sensor (LIS) Science Team

3. Several groups are working toward lightning prediction in different ways. • Research into improved understanding (e.g. LMA applications) (e.g. SPoRT/NASA, NWS, NSSL) • Flow regime analysis and climatologies (e.g. FSU, TAMU) • “First strike” radar-based detection (NSSL, NCSU) • Occurrence of any lightning (e.g. Patrick AFB/KSC) • Lightning threat parameters in convection-allowing models (e.g. NSSL, SPoRT/NASA) • Focus on occurrence of excessive lightning (high density, or HD, lightning) with an ingredients-based method (e.g. NWS Raleigh) Strike density climatology

4. WFO Raleigh’s Analysis and Prediction of the Potential for Excessive Lightning (APPEL) project: (Experimental forecasts based on application of peer-reviewed lightning research) (Climatology + case studies of events with high density lightning) Comprised of a forecast component and an analysis component

5. Our goal: to produce a skillful 3-24 hr outlook of lightning activity. • Approach: a multi-parameter, ingredients-based checklist (thresholds based on past research and local cases) with forecaster input • Why a checklist? • Can use preferred model • Not a “black box” • Forecaster can apply experience and weigh parameters accordingly • Focus: catch the “big” lightning days, and include this info in the morning Hazardous Weather Outlook • Have completed two seasons (May-Sept) of forecasting

6. Checklist components and thresholds were based on past studies of environmental conditions preceding excessive lightning events. • Helps assess two critical components for lightning production: • Available moisture(the presence of graupel is essential for electrification) • Instability(especially aloft) (the greater the buoyancy, the more vigorous the updrafts) Moisture and instability Instability and CAPE “shape” Multi-parameter indices from SPC Precip. water Subjective assessments of forcing and moisture

7. Forecasters have several tools at their disposal to help fill out the checklist: AWIPS procedures Local WRF model BUFKIT forecast soundings

8. Forecasters have several tools at their disposal to help fill out the checklist: SPC NAM-based “perfect prog” forecast SPC SREF-based calibrated probabilities of >100 CGs New this year: NSSL WRF-based total lightning threat

9. Lightning activity forecast results for 2009: • Enhanced lightning threat added to the Hazardous Weather Outlook (HWO) on 24 of 153 days • Several noted the extreme nature of expected lightning (“…will be nearly continuous…as much as one strike every few seconds…”) • Enhanced wording included for 3 of the 4 greatest lightning density days • Local media has begun to incorporate lightning prediction into broadcasts “IN ADDITION...SUFFICIENT INSTABILITY IS PRESENT AT MID AND UPPER LEVELS OF THE ATMOSPHERE TO SUPPORT AN UNUSUALLY LARGE AMOUNT OF LIGHTNING THIS AFTERNOON AND EVENING.” “STRONG THUNDERSTORMS MAY PRODUCE FREQUENT LIGHTNING...IN SOME CASES ONE STRIKE EVERY 10 SECONDS.” • BUT… there were a few problems: • Forecaster experience and confidence varied • Inclusion in HWO somewhat inconsistent by forecaster and situation • Extra duties took time

10. Challenges remain with this technique. • Is it ideal to apply mesoscale characteristics to the storm scale? • How do we weigh dynamic and thermodynamic contributions to ascent? • Both parameterized and convection-allowing models are used, and these must be evaluated properly • Can be inconsistency among forecasters • Our latest efforts: • Complete detailed areal climatology (to help define a “significant” day) • Case studies and composites (to improve pattern recognition capabilities and increase understanding of HD lightning events) • Initial operational evaluation of NSSL WRF-based lightning threat OUCH!

11. 2002-2010 data analysis reveals year-to-year variations. (Large scale flow pattern differences?) Area of study • For 2002-2010: • Average lightning days per year: 100 • Lightning on top 10 days, on average, accounts for 49.9% of yearly total lightning • Most electrically active systems were multicell clusters and • dynamically driven convective lines = RAH CWA = Verification area Data source: NLDN

12. Lightning analysis for June 2002-September 2010 reveals yearly maxima from late June through late August. 2005 2006 2002 2003 2004 2009 2007 2008 2010 Area of study = RAH CWA = Verification area Data source: NLDN Data analysis courtesy of Jeremy Gilchrist and Whitney Rushing, NCSU

13. Lightning analysis for June 2002-September 2010 reveals yearly maxima from late June through late August. Area of study Data source: NLDN

14. 28 July 2005 (most all-time): 39,754 strikes in central NC CGs, 1200 UTC 28 Jul to 1200 UTC 29 Jul

15. Comparing top HD lightning days with average days in 2010: Suggests high potential for strong instability and vigorous updrafts Gauges potential for “fat” CAPE and strong instability in the mixed phase layer aloft Indicates presence of sufficient graupel and graupel flux Parameters from RUC-based SPC mesoanalyses, within 100 km of convection, within 2 hours of onset

16. Findings consistent with past research • Guidelines for potential high-density events: • MUCAPE > 3000 J/kg • MLCAPE > 2000 J/kg • PW > 150% of normal & positive PW flux • Blended TPW products have been helpful

17. Findings consistent with past research • Guidelines for potential high-density events: • MUCAPE > 3000 J/kg • MLCAPE > 2000 J/kg • PW > 150% of normal & positive PW flux • Blended TPW products have been helpful Typical PW for 2010 high-density lightning days Blended TPW imagery, available on the web and on NWS AWIPS systems PW climatology courtesy of NWS Rapid City, SD

18. Composites of precipitable water and surface lifted index, 2010 top 10 high-density (l.) and 10 average (median, r.) lightning days PW=35-45 mm PW=45-55 mm Greatest lightning days Average lightning days LI= -3 to -3.5 C LI= -1 to -2 C

19. 5 August 2010: 10,642 CG strikes in central NC 2 people struck by lightning in Raleigh (struckbylightning.org) CGs, 1200 UTC 5 Aug to 1200 UTC 6 Aug

20. 5-6 August 2010 NSSL WRF lightning threat 05/0300 UTC 05/2000 UTC 06/0000 UTC Hourly CG strikes KRAX 88D reflectivity

21. 25 July, 2010 9,497 CG strikes Local WRF-NMM, 1 km refl, 0400 UTC (16h fcst) SPC WRF, 1 km refl, 0400 UTC (16h fcst) CGs, 25 Jul – 26 Jul, 1200-1200 UTC KRAX 88D, reflectivity, 0334 UTC NSSL WRF lightning threat, 0400 UTC (28h fcst)

22. Conclusions & future plans • What we know: • NSE analysis for HD lightning days supports past research and measurements •  Confirms importance of graupel flux and strong updrafts for lightning production • Skillful lightning prediction can be done • WRF-, NAM-, and SREF-based output very helpful •  Augment NSE parameters • Forecaster intervention may improve upon purely automated methods • Working together and sharing findings are critical for success • What’s coming up: • Resumption of forecasts in May 2011 • Continued operational evaluation of WRF-based lightning threat fields • Creation of an experimental “ensemble” parameter for each model • Verification of automated methods vs. human-based method NWS Raleigh Lightning Team: Jonathan Blaes (NWS), Morgan Brooks (NWS), Jeremy Gilchrist (NCSU), Whitney Rushing (NCSU), Gail Hartfield (NWS – gail.hartfield@noaa.gov)

24. Extra slides

25. Yearly CG strike statisticsWFO RAH CWA

27. Average lightning days (r., compared to top days, l.) had lower heights aloft and more ridging over the Southeast. 500 mb mean heights/anomalies, top 10 days of 2010 500 mb mean heights/anomalies, average days of 2010

28. 500 mb composites of top 2009 & 2010 days indicates a mid level trough to our northwest (but signal is weak). 500 mb mean heights/anomalies, top 10 days of 2010 (80044 CG strikes) 500 mb mean heights/anomalies, top 10 days of 2009 (79813 CG strikes) CGs similar for both years, but 2010 was hotter (more CAPE?) and 2009 cases appear more dynamic (compensating for lower CAPE?)

29. 500 mb composite of top days indicates a mean weak mid level trough to our west. 500 mb mean heights, top 10 days 2002-2010 500 mb mean heights, top 10 days of 2010

30. Partial bibliography for the Analysis and Prediction of the Potential for Excessive Lightning (APPEL) project • Keller, D. L., 2004: Forecasting cloud-to-ground lightning data with AFWA-MM5 model data using the "Bolt of Lightning Technique" (BOLT) algorithm. Preprints,22nd Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., CD preprints. • Hondl, K. and M. Eilts, 1994: Doppler radar signatures of developing thunderstorms and their potential to indicate the onset of cloud-to-ground lightning. Mon. Wea. Rev., 122, 1818–1836. • Wolf, P., 2006: Anticipating the Initiation, Cessation, and Frequency of Cloud-to-Ground Lightning Utilizing WSR-88D Reflectivity Data (local study, WFO JAX). • Shafer, P.E., 2005: Developing Gridded Forecast Guidance for Warm Season Lightning over Florida Using the Perfect Prognosis Method and the Weather Research & Forecast Model (doctoral prospectus). • Bothwell, P., 2005: Development of an operational statistical scheme to predict the location and intensity of lightning. Preprints, Amer. Meteor. Soc. Annual Meeting, 2005. • Deierling, W. and W. A. Petersen, J. Latham, S. M. Ellis, H. J. Christian Jr. and J. Walters, 2006: Total lightning frequency in relation to ice masses and ice mass flux estimates. Preprints, Amer. Meteor. Soc. Annual Meeting, 2006. • Shafer, P.E. and H. Fuelberg, 2005: A statistical procedure to forecast the daily amount of warm season lightning in south Florida. Preprints, Amer. Meteor. Soc. Annual Meeting, 2005. • Cope, A., 2006: Toward better use of lightning data in operational forecasting. Preprints, Amer. Meteor. Soc. Annual Meeting, 2006. • Blanchard, D.O., 1998: Assessing the vertical distribution of convective available potential energy (CAPE). Wea. Forecasting, Sep. 1998. • Jayaratne, R. and E. Kuleshov, 2006: The relationship between lightning activity and surface wet bulb temperature and its variation with latitude in Australia. Meteorology and Atmospheric Physics, 91, pp.17-24. • Petersen, W. A. and S. Rutledge, 2001: Regional variability in tropical convection: observations from TRMM. Journal of Climate, Sep. 2001. • Petersen, W. A., 1997: Multi-Scale Process Studies in the Tropics: Results from Lightning Observations. Doctoral thesis, Colo. St. Univ., 1997. • Van Den Broeke, M. and D. Schultz, R. Johns, J. Evans, and J. Hales, 2004: Cloud-to-Ground Lightning Production in Strongly Forced, Low-Instability Convective Lines Associated with Damaging Wind. Wea. Forecasting, Aug. 2005. • MacGorman, D.R., and W.D. Rust, 1998: The Electrical Nature of Storms. Oxford University Press, 422 pp. • Bright, D.R. and M. S. Wandishin, R. E. Jewell, and S. J. Weiss, 2005: A physically based parameter for lightning prediction and its calibration in ensemble forecasts. Preprints, Amer. Meteor. Soc. Annual Meeting, 2005. • Kehrer, K. and B. Graf and W. Roeder, 2008: Global Positioning System (GPS) precipitable water in forecasting lighting at Spaceport Canaveral. Wea. Forecasting, Apr. 2008. • Lambert, W. and D. Sharp, S. Spratt, and M. Volkmer, 2006: Using cloud-to-ground lightning climatologies to initialize gridded lightning threat forecasts for east central Florida. Preprints, Amer. Meteor. Soc. Annual Meeting, 2006. • Murphy, M. and C. E. Konrad, 2005: Spatial and temporal patterns of thunderstorm events that produce cloud-to-ground lightning in the interior southeastern United States. Monthly Weather Review, 133, 1417-1430. • Williams, E. and V. Mushtak, D. Rosenfeld, S. Goodman, and D. Boccippio, 2005: Thermodynamic conditions favorable to superlative thunderstorm updraft, mixed phase microphysics, and lightning flash rate. Atmos. Research, 76, 2005. • McCaul, Jr., E. and K. LaCasse, S. Goodman, and D. Cecil, 2008: Use of high-resolution WRF simulations to forecast lightning threat. Preprints, Amer. Meteor. Soc. Annual Meeting, 2008. • Deierling, W. and W. A. Petersen, J. Latham, S. M. Ellis, and H. J. Christian Jr., 2005: Towards the relationship between total lightning activity and downward as well as upward ice mass fluxes in thunderstorms. Preprints, Amer. Meteor. Soc. Annual Meeting, 2005. • Mazany, R. and S. Businger, S. Gutman, and W. Roeder, 2002: A lightning prediction index that utilizes SPS integrated precipitable water vapor. Wea. Forecasting, Oct. 2002. • Livingston, E. and J Nielsen-Gammon and R. Orville, 1996: A climatology, synoptic assessment, and thermodynamic evaluation for cloud-to-ground lightning in Georgia: a study for the 1996 Summer Olympics. Bull. Amer. Meteor. Soc., 77, Jul. 1996. • Burrows, W. and C. Price and L. Wilson, 2004: 1 to 2 day prediction of the probability of lightning occurrence over Canada and the northern United States in the warm season. Canadian Meteorological and Oceanographic Society Annual Meeting, 2004.