58
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] - [email protected], 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

1 [1] Central Institute for Meteorology and Geodynamics, Hohe Warte, Vienna [2] Deutsches Zentrum für Luft und Raumfahrt, Institut für Physik der Atmosphäre,

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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] - [email protected],H. Höller [2], H.-D. Betz [3] , K. Schmidt [2]

Convection Week 2011, Session 3

Thunderstorm Tracking and Nowcastingusing 3D Lightning and Radar Data in Southern Germany

2

PROJECT RegioExAKT www.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 AIRPORTHEAVY RAIN15 Juni 2007 40,5 l/m² zw. 18.00 –21.00 h

HAIL DAMAGE

Boeing 737, Geneva 15 August 2003

intense rainhaillightning strikeswind gustsetc.

MOTIVATION

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 parametercomprehensive discrimination of ‘cloud’ and ‘cloud-to-ground’ lightning

MOTIVATION

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 CG

IC IC

IC

LIGHTNING TYPES

MOTIVATION

5

high-precision lightning detection.

‚NORMAL STORM‘

cloud lightning

cloud-to- ground lightning

MOTIVATION

LINET 3D-Visualisierung

‚SEVERE STORM‘

6

THUNDERSTORM TRACKING and NOWCASTING

temporal evolution of LIGHTNING cell parameters

cell track

MUNICH AIRPORT

lightning-cell

14:45 15:00 15:15 15:30

total lightningcloud lightningcloud-to-groundlightning

time

MOTIVATION

7

cell track

MUNICH AIRPORT

lightning-cell

cell nowcasts

THUNDERSTORM TRACKING and NOWCASTING

14:45 15:00 15:15 15:30

total lightningcloud lightningcloud-to-groundlightning

time

now prognosis

temporal evolution of LIGHTNING cell parameters

MOTIVATION

8

GOAL:

to assess the usability of 3D total-lightning data forthunderstorm nowcasting

separately and in combination with other data sources (radar)

INTRODUCTION

INTRODUCTION

9

GOAL:

to assess the usability of 3D total-lightning data forthunderstorm nowcasting

separately and in combination with other data sources (radar)

INTRODUCTION

INTRODUCTION

identificationtracking

prediction

10

GOAL:

to assess the usability of 3D total-lightning data forthunderstorm nowcasting

separately and in combination with other data sources (radar)

INTRODUCTION

INTRODUCTION

identificationtracking

prediction

cell evolution

11

GOAL:

to assess the usability of 3D total-lightning data forthunderstorm 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

INTRODUCTION

12 INTRODUCTION

May – September 2008

RESEARCH DOMAIN and OBSERVATION PERIOD

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 3

DWD Radar Site Fürholzen (Munich)2D reflecitvity maps, low level scandomain [200 km x 200 km]resolution [1 km x 1 km], [5 min]

LINET lightning data, nowcast GmbH3D TOA method in VLF/LF regime, IC/CG discrimination

2D discharge event maps

cell clustering: time interval 3 min

minimum distance 6 km

ec-TRAM – tracking and monitoring of electrically charged convective cells

NOWCASTING APPROACH ec-TRAM

3METHOD

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

4METHOD

Rad-TRAM

[Kober,2009]

li-TRAM

[Meyer,2010]

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

4METHOD

ec-TRAM

[Meyer,2010]

Rad-TRAM

[Kober,2009]

li-TRAM

[Meyer,2010]

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

5METHOD

18

18

radar sites

x Fürholzen

x POLDIRAD

MUC Munich Airport

M Munich

R Regensburg

A Augsburg

P

F

25 June 2008

TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER

South Germany

Austria

CASE STUDY

19

19

20

15:3

0

15:4

5

16:0

0

16:1

5

16:3

0

16:4

5

17:0

0

17:1

5

17:3

0

17:4

5

18:0

0

18:1

5

18:3

00

100

200

300

400

500

[km

2]

LIFE CYCLE radcell AREA20080625 Nr 7

areamarginmerge

split

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

15

:30

15

:45

16

:00

16

:15

16

:30

16

:45

17

:00

17

:15

17

:30

17

:45

18

:00

18

:15

UTC timeCluster: time= 3 min, dist=3.0 km

0

100

200

300

400

500

600

[km

2],

[cn

t/ce

ll]

LIFE CYCLE licell with LIGHTNING FREQUENCY20080625 Nr 24

areaf(TOT)

f(IC)

f(CG)

margin

merge

split

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

[km

²], d

isch

arg

e fr

equ

ency

[cn

t/ce

ll]

25 June 2008

CASE STUDY

23

23

TEMPORAL EVOLUTION of ec-TRAM CELL PARAMETER

area

[km

²], d

isch

arg

e fr

equ

ency

[cn

t/ce

ll]

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

[km

²], d

isch

arg

e fr

equ

ency

[cn

t/ce

ll]

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

[km

²], d

isch

arg

e fr

equ

ency

[cn

t/ce

ll]

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

[km

²], d

isch

arg

e fr

equ

ency

[cn

t/ce

ll]

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

VERIFICATION of LIGHTNING-CELL PROPERTIESin 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

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

2 CASE STUDIES

29

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

I

2

3

cell growth

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

2 CASE STUDIES

30

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

mature stage

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

31

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

4

5

6

E

cell dissipation

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

2 CASE STUDIES

32

Lifetime = 145 min

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

2 CASE STUDIES

33

Lifetime = 145 min

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

23

45I

cell growth

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

2 CASE STUDIES

34

Lifetime = 145 min

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

mature stage

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

2 CASE STUDIES

35

Lifetime = 145 min

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

-2

E

-4-5

-6

cell dissipation

-3

PARAMETER CORRELATIONS of 2 LIGHTNING-CELL TRACKS

Lifetime = 40 min

30 May 2008lightning-cell No 137

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

2 CASE STUDIES

36

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

TL fit 1 + 2

TL fit 1 + 2

TL meanIC mean

PARAMETER MEANS

lightning frequency versus cell area

-10 km² area intervals-10 200 completely assessedlightning-cell entries

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

LIGHTNING-STATISTICS

37

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

TL fit 1 + 2

TL fit 1 + 2

TL meanIC mean

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN

160 km²

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

LIGHTNING-STATISTICS

38

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN fit 1 + 2

IC MEAN height

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

160 km²

LIGHTNING-STATISTICS

39

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

160 km²

fit 1 + 2IC mean height

160 km²

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN fit 1 + 2

IC MEAN height

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

NO ARTIFACT of the ALGRITHM

LIGHTNING-STATISTICS

40

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

160 km²

TL fit 1 + 2

TL fit 1 + 2

TL meanIC mean fit 1 + 2

IC mean height

160 km²

NO INFORMATION about TEMPORAL CELL EVOLUTION

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN fit 1 + 2

IC MEAN height

9LIGHTNING-STATISTICS

41

Lifetime = 40 min Lifetime = 145 min

30 May 2008lightning-cell No 137

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

I

EE

I

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

10LIGHTNING-STATISTICS

42

Lifetime = 40 min Lifetime = 145 min

30 May 2008lightning-cell No 137

25 May 2008lightning-cell No 6

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

I

EE

I

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

10LIGHTNING-STATISTICS

43

FREQUENCY DISTRIBUTION of LIFE-TIMES

LIGHTNING-STATISTICS

lightning-cell lifetime [min]

fre

que

ncy

[-] long-lived cellsshort-lived cells

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

rela

tive

fre

que

ncy

cell area [km²]cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

total lightning

short-lived

long-lived cells

RELATIVE AMOUNT to STATISTICAL MEAN

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

LIGHTNING-STATISTICS

46

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell] total lightning

cell type

growth

decease

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

short-lived cells

short-lived

DISCUSSION

47

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell] total lightning

cell type

long-lived cells

maturity

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

long-lived cells

growth

decease

DISCUSSION

4848

cell area [km²]

Lig

htn

ing

freq

ue

ncy

pe

r ce

ll [1

/km

²]

TL fit 1 + 2

TL fit 1 + 2

TL meanIC mean

SCATTER!

total lightning

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

fit 1 + 2IC mean height

SCATTER!

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

DISCUSSION

49

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

long-livedcell type

long-lived cells

short-lived

short-lived

INFORMATION about STORM TYPE (lifetime, intensity) and TEMPORAL EVOLUTION!

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

DISCUSSION

50

THUNDERSTORM TRACKING and NOWCASTING

cell track

MUNICH AIRPORT

lightning-cell

cell nowcasts

14:45 15:00 15:15 15:30

total lightningcloud lightningcloud-to-groundlightning

time

now prognosis

temporal evolution of LIGHTNING cell parameters

Ad MOTIVATION

51

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

TL fit 1 + 2

TL fit 1 + 2

TL MEANIC MEAN fit 1 + 2

IC MEAN height

3D informationfrom

2D cell tracking!

CORRELATION STATISTICS of LIGHTNING-CELL PARAMETERS

DISCUSSION

52

GOAL:

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

CONCLUSION

11CONCLUSION 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

- 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

11CONCLUSION and OUTLOOK

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

cell area [km²]IC m

ea

n d

isch

arg

e h

eig

ht p

er c

ell

[km

]

cell area [km²]

ligh

tnin

g fr

equ

ency

pe

r ce

ll [c

nt/c

ell]

160 km²

TL fit 1 + 2

TL fit 1 + 2

TL meanIC mean fit 1 + 2

IC mean height

160 km²

THANK YOU

[email protected]

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 Physicshttp://edoc.ub.uni-muenchen.de/12102/

[email protected]

57

57

POLARIMTRIC INFORMATION

POLDIRAD RHI 20080625, hydrometeorclassifications, 16:42h, azimuth = 52 °

sounding munich: 0 ° at 3.5 km, Tropopause at 10 km

58

area

[km

²],

dis

char

ge

freq

uen

cy [

cnt/

cell

]

25 June 2008example:

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 cellgraupel/hail

heavy rainlight rain H = 4 km

ground