1. 1 [1] Central Institute for Meteorology and Geodynamics, Hohe Warte, Vienna [2] Deutsches Zentrum für Luft und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Deutschland [3] Physics Department, University of Munich, Germany Vera Meyer [1] - vera.meyer@zamg.ac.at, H. Höller [2], H.-D. Betz [3], K. Schmidt [2] Convection Week 2011, Session 3 Thunderstorm Tracking and Nowcasting using 3D Lightning and Radar Data in Southern Germany

2. 2 PROJECT RegioExAKTwww.regioexakt.de Regional Risk of Convective Extreme Weather Events: User-oriented concepts for optimised thunderstorm nowcasting, with focus on the needs of Munich Airport Coordinator: Dr. Nikolai Dotzek MUNICH AIRPORT HEAVY RAIN 15 Juni 2007 40,5 l/m² zw. 18.00 –21.00 h HAIL DAMAGE Boeing 737, Geneva 15 August 2003 intense rain hail lightning strikes wind gusts etc. MOTIVATION

3. 3 LINET - Lightning Detection Network -‘total lightning’ detection -2008 app. 100 sensors in Central Europe -magnetic field measurements -TOA (time of arrival) method -event-height parameter comprehensive discrimination of ‘cloud’ and ‘cloud-to-ground’ lightning MOTIVATION

4. 4 Abbreviations IC (cloud lightning) in-cloud, inter-cloud, intra-cloud, cloud-to-air CG (cloud-to-ground) cloud – to – ground TL (total lightning) sum (IC + CG) 0 °C -15 °C CG IC LIGHTNING TYPES MOTIVATION

5. 5 high-precision lightning detection. ‚NORMAL STORM‘ cloud lightning cloud-to- ground lightning MOTIVATION LINET 3D-Visualisierung ‚SEVERE STORM‘

6. 6 THUNDERSTORM TRACKING and NOWCASTING temporal evolution of LIGHTNING cell parameters cell track MUNICH AIRPORT lightning-cell 14:45 15:00 15:1515:30 total lightning cloud lightning cloud-to-ground lightning time MOTIVATION

7. 7 cell track MUNICH AIRPORT lightning-cell cell nowcasts THUNDERSTORM TRACKING and NOWCASTING 14:45 15:00 15:1515:30 total lightning cloud lightning cloud-to-ground lightning time nowprognosis temporal evolution of LIGHTNING cell parameters MOTIVATION

8. 8 GOAL: to assess the usability of 3D total-lightning data for thunderstorm nowcasting separately and in combination with other data sources (radar) INTRODUCTION

9. 9 GOAL: to assess the usability of 3D total-lightning data for thunderstorm nowcasting separately and in combination with other data sources (radar) INTRODUCTION identification tracking prediction

10. 10 GOAL: to assess the usability of 3D total-lightning data for thunderstorm nowcasting separately and in combination with other data sources (radar) INTRODUCTION identification tracking prediction cell evolution

11. 11 GOAL: to assess the usability of 3D total-lightning data for thunderstorm nowcasting separately and in combination with other data sources (radar) - develop a nowcasting method based on lightning information - develop a method to compare lightning-cell information with information from other data sources (radar) verify lightning-cell properties in case-studies evaluate the statistical information content of 3D lightning information INTRODUCTION

12. 12 INTRODUCTION May – September 2008 RESEARCH DOMAIN and OBSERVATION PERIOD

13. 13 METHOD ec-TRAM – tracking and monitoring of electrically charged convective cells combines cell informations from independently tracked lightning- and radar-cells NOWCASTING APPROACH ec-TRAM

14. 14 3 DWD Radar Site Fürholzen (Munich) 2D reflecitvity maps, low level scan domain [200 km x 200 km] resolution [1 km x 1 km], [5 min] LINET lightning data, nowcast GmbH 3D TOA method in VLF/LF regime, IC/CG discrimination 2D discharge event maps cell clustering:time interval3 min minimum distance6 km ec-TRAM – tracking and monitoring of electrically charged convective cells NOWCASTING APPROACH ec-TRAM 3 METHOD

15. 15 NOWCASTING APPROACH ec-TRAM combines the cell informations of lightning cells and radar cells cell assignment via spatial overlap cell identification parameter (optimized) lightning cell:threshold of 1 event lightning data:amplitude |A| > 2.5 kA radar cell: threshold of 33 dBZ radar-cells lightning-cell 4 METHOD Rad-TRAM [Kober,2009] li-TRAM [Meyer,2010]

16. 16 NOWCASTING APPROACH ec-TRAM cell assignment via spatial overlap cell identification parameter lightning cell:threshold of 1 event radar cell: threshold of 33 dBZ radar-cells lightning-cell ec-cells combines the cell informations of lightning cells and radar cells 4 METHOD ec-TRAM [Meyer,2010] Rad-TRAM [Kober,2009] li-TRAM [Meyer,2010]

17. 17 example: ec-TRAM nowcasting map (detail) with cell contours, tracks and prognoses of an electrically charged ‚ec-cell‘. radar cell: Reflectivity map (blue shaded) cell track (white line), actual cell contour (white polygons), cell prognoses for 10 minutes (dark grey polygons), and 20 minutes (light grey polygons) lightning cell: discharge events clustered for 3 minutes (green crosses) actual cell (red polygon) cell track ec-cells NOWCASTING APPROACH ec-TRAM 5 METHOD

18. 18 radar sites x Fürholzen xPOLDIRAD MUC Munich Airport M Munich RRegensburg AAugsburg P F 25 June 2008 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER South Germany Austria CASE STUDY

19. 19

20. 20 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER 25 June 2008 Example rad-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] CASE STUDY

21. 21 25 June 2008 CASE STUDY TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER Example li-TRAM: temporal evolution of selected parameters lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell]

22. 22 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER Example ec-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell] area [km²], discharge frequency [cnt/cell] 25 June 2008 CASE STUDY

23. 23 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER area [km²], discharge frequency [cnt/cell] onset Example ec-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell] CASE STUDY

24. 24 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER area [km²], discharge frequency [cnt/cell] cell splitting Example ec-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell] CASE STUDY

25. 25 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER area [km²], discharge frequency [cnt/cell] intensification Example ec-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell] CASE STUDY

26. 26 TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER area [km²], discharge frequency [cnt/cell] decease Example ec-TRAM: temporal evolution of selected parameters radar-cell: - cell area[km²] lightning-cell: - cell area[km²] - TL [cnt/cell] - CG [cnt/cell] - IC [cnt/cell] CASE STUDY

27. 27 VERIFICATION of LIGHTNING-CELL PROPERTIES in CASE-STUDIES lifetime series of ec-cell parameters were complemented with 3D polarimetric radar data (POLDIRAD) - not shown lightning-cell parameters were found to - evolve reasonably according to the current state of knowledge - be in very good agreement with other case studies [Klemp1987, Williams 1989 and 1999, Goodman 1988, Carey 1996, Lopez 1997, Mazur 1998, Altaraz 2003, Motley 2006,...]  reflect the actual storm dynamic (intensification / weakening)  li-TRAM has reasonable, consistent tracking performances (comparable to rad-TRAM) [Meyer, 2010] VERIFICATION

28. 28 Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS 2 CASE STUDIES

29. 29 Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] I 2 3 cell growth PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS 2 CASE STUDIES

30. 30 Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] mature stage PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

31. 31 Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] 4 5 6 E cell dissipation PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS 2 CASE STUDIES

32. 32 Lifetime = 145 min 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] 2 CASE STUDIES

33. 33 Lifetime = 145 min 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] 2 3 4 5 I cell growth PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] 2 CASE STUDIES

34. 34 Lifetime = 145 min 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] mature stage PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] 2 CASE STUDIES

35. 35 Lifetime = 145 min 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] -2 E -4 -5 -6 cell dissipation -3 PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS Lifetime = 40 min 30 May 2008 lightning-cell No 137 cell area [km²] lightning frequency per cell [cnt/cell] 2 CASE STUDIES

36. 36 cell area [km²] lightning frequency per cell [cnt/cell] TL fit 1 + 2 TL mean IC mean PARAMETER MEANS lightning frequency versus cell area -10 km² area intervals -10 200 completely assessed lightning-cell entries TL fit 1 + 2 TL MEAN IC MEAN CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS LIGHTNING-STATISTICS

37. 37 cell area [km²] lightning frequency per cell [cnt/cell] TL fit 1 + 2 TL mean IC mean TL fit 1 + 2 TL MEAN IC MEAN 160 km² CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS LIGHTNING-STATISTICS

38. 38 cell area [km²] IC mean discharge height per cell [km] cell area [km²] lightning frequency per cell [cnt/cell] TL fit 1 + 2 TL MEAN IC MEAN fit 1 + 2 IC MEAN height CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS 160 km² LIGHTNING-STATISTICS

39. 39 cell area [km²] IC mean discharge height per cell [km] cell area [km²] lightning frequency per cell [cnt/cell] 160 km² fit 1 + 2 IC mean height 160 km² TL fit 1 + 2 TL MEAN IC MEAN fit 1 + 2 IC MEAN height CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS NO ARTIFACT of the ALGRITHM LIGHTNING-STATISTICS

40. 40 CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS cell area [km²] IC mean discharge height per cell [km] cell area [km²] lightning frequency per cell [cnt/cell] 160 km² TL fit 1 + 2 TL mean IC mean fit 1 + 2 IC mean height 160 km² NO INFORMATION about TEMPORAL CELL EVOLUTION TL fit 1 + 2 TL MEAN IC MEAN fit 1 + 2 IC MEAN height 9 LIGHTNING-STATISTICS

41. 41 Lifetime = 40 min Lifetime = 145 min 30 May 2008 lightning-cell No 137 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] cell area [km²] lightning frequency per cell [cnt/cell] I E E I CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS 10 LIGHTNING-STATISTICS

42. 42 Lifetime = 40 min Lifetime = 145 min 30 May 2008 lightning-cell No 137 25 May 2008 lightning-cell No 6 cell area [km²] lightning frequency per cell [cnt/cell] cell area [km²] lightning frequency per cell [cnt/cell] I E E I CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS 10 LIGHTNING-STATISTICS

43. 43 FREQUENCY DISTRIBUTION of LIFE-TIMES LIGHTNING-STATISTICS lightning-cell lifetime [min] frequency [-] long-lived cellsshort-lived cells

44. 44 LIFETIME REGIMES LIGHTNING-STATISTICS short-lived[ 15 min – 75 min ] ‚SINGLE CELLS‘ - lowly organized - simply structured:1 updraft + 1 downdraft - simple life-cycles:growth – short maturity – decease long-lived [ ≥ 80 min ] ‚MULITCELLS‘, ‚SUPERCELLS‘ - highly organized - complexly structured - complex life-cycles: growth – elongated (fluctuating) maturity – decease

45. 45 relative frequency cell area [km²] lightning frequency per cell [cnt/cell] total lightning short -lived long-lived cells RELATIVE AMOUNT to STATISTICAL MEAN CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS LIGHTNING-STATISTICS

46. 46 cell area [km²] lightning frequency per cell [cnt/cell] total lightning cell type growth decease CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS short-lived cells short- lived DISCUSSION

47. 47 cell area [km²] lightning frequency per cell [cnt/cell] total lightning cell type long-lived cells maturity CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS long-lived cells growth decease DISCUSSION

48. 48 cell area [km²] Lightning frequency per cell [1/km²] TL fit 1 + 2 TL mean IC mean SCATTER! total lightning cell area [km²] IC mean discharge height per cell [km] fit 1 + 2 IC mean height SCATTER! CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS DISCUSSION

49. 49 cell area [km²] lightning frequency per cell [cnt/cell] long-lived cell type long-lived cells short-lived INFORMATION about STORM TYPE (lifetime, intensity) and TEMPORAL EVOLUTION! CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS DISCUSSION

50. 50 THUNDERSTORM TRACKING and NOWCASTING cell track MUNICH AIRPORT lightning-cell cell nowcasts 14:45 15:00 15:1515:30 total lightning cloud lightning cloud-to-ground lightning time nowprognosis temporal evolution of LIGHTNING cell parameters Ad MOTIVATION

51. 51 cell area [km²] IC mean discharge height per cell [km] cell area [km²] lightning frequency per cell [cnt/cell] TL fit 1 + 2 TL MEAN IC MEAN fit 1 + 2 IC MEAN height 3D information from 2D cell tracking! CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS DISCUSSION

52. 52 GOAL: to assess the usability of 3D total-lightning data for thunderstorm nowcasting separately and in combination with other data sources (radar) CONCLUSION 11 CONCLUSION and OUTLOOK 3D lightning information with in-cloud and cloud-to-ground lightning discrimination provides useful information about the storm dynamic and developement and have the capacity to nowcast cell trends from the cell history

53. 53 - test the usability of (specified) normalized cell life-cycles to derive trend prognoses - use cell trends from cell history to add trend prognoses to local prognoses - test the quality of trend prognoses - investigate cell parameter correlations with other data sources (3D radar, satellite,... ) OUTLOOK 11 CONCLUSION and OUTLOOK

54. 54 - parameterization of TL frequency with IC/CG ratio and mean IC height for modelling [Price and Rind 1992, Allen and Pickering 2002] - simulation of thunderstorm life-cycles with realistic discharge characteristics OTHER possible APPLICATIONS CONCLUSION and OUTLOOK ?160 km²?

55. 55 cell area [km²] IC mean discharge height per cell [km] cell area [km²] lightning frequency per cell [cnt/cell] 160 km² TL fit 1 + 2 TL mean IC mean fit 1 + 2 IC mean height 160 km² THANK YOU vera.meyer@zamg.ac.at

56. 56 Literature K. Kober and A. Tafferner. Tracking and nowcasting of convective cells unsing remote sensing data from radar and satellite. Meteorologiesche Zeitschrift, 10(1):75-84, 2009 V. Meyer, H. Höller, K.Schmidt, and H.-D. Betz. Temporal evolution of total lightning and radar parameters of thunderstorms in southern Germany and its benefit for nowcasting. Proceedings: 5th European Conference on Severe Storms, 2009 V. Meyer (2010): Thunderstorm Tracking and Monitorin on the Basis of Three Dimenional Lightning Data and Conventional and Polarimetric Radar Data. Dissertation, LMU München: Faculty of Physics http://edoc.ub.uni-muenchen.de/12102/ vera.meyer@zamg.ac.at

57. 57 POLARIMTRIC INFORMATION POLDIRAD RHI 20080625, hydrometeorclassifications, 16:42h, azimuth = 52 ° sounding munich: 0 ° at 3.5 km, Tropopause at 10 km

58. 58 area [km²], discharge frequency [cnt/cell] 25 June 2008 example: radar-cell: -cell area[km²] lightning-cell: -cell area[km²] - TL[cnt/cell] - CG[cnt/cell] - IC[cnt/cell] polar. radar data - hydrometeors ZEITLICHE ENTWICKLUNG VON ec-ZELL PARAMETERN dBZ cell graupel/hail heavy rain light rain H = 4 km ground