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The Utility of Long-Range Lightning Networks A UH view Steven Businger Outline ! Pacific Lightning Detection Network (PacNet) ! Lightning, cloud ice, aerosol, rainfall relationships ! Lightning in Hurricanes ! Lightning data assimilation

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Page 1: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

The Utility of Long-Range

Lightning Networks

A UH view

Steven Businger

Outline

! Pacific Lightning Detection Network (PacNet)

! Lightning, cloud ice, aerosol, rainfall relationships

! Lightning in Hurricanes

! Lightning data assimilation

Page 2: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Long-range Lightning Detection

Ionosphere-earth wave guide allows VLF (5-25 kHz) emissions (sferics) from cloud to ground strikes to propagate thousands of km. Best propagation is over ocean and at night.

PacNet Sensor Sites

Currently 4 sensors installed at Dutch Harbor, Lihue, Kona and Kwajalein. Sensors in North-America and Japan contribute.

IMPACT ESP Sensor in Lihue, Kauai

Page 3: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Synoptic View

Like GOES, long-range lightning data provide a synoptic view over data-sparse oceans (left). Lightning strikes match broad pattern of rainfall from AMSR-E (right).

Synoptic View

Like GOES, long-range lightning data provide a synoptic view over data-sparse oceans.

Page 4: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Synoptic View

Time series of daily total lightning strikes

Synoptic View

Histogram of monthly mean lightning strikes.

Page 5: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

GOES 12 IR Image 9-21-05 1545Z; Lightning Overlaid from 15Z - 16ZMinimum Central Pressure 945 mb; 3 hours into Rapid Intensification

(30 Kts increase in M.S.W. in 24 hrs - John Kaplan HRD)

Rita

Lightning Signatures in

Tropical Cyclones

Katrina

Animation of lightning distribution in Katrina

Page 6: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Detection

Efficiency

The detection

efficiency (%) of the

long-range lightning

network must be

taken into account in

quantitative

applications of the

lightning strike data.

2005 Hurricanes Were

Unusually Active in Lightning

0

200

400

600

800

1,000

1,200

0-25 25-50 50-75 75-100 100-125 125-150 150-175 175-200 200-225 225-250 250-275 275-300

0130Z

0300Z

0730Z

0900Z

1330Z

1500Z

1630Z

1745Z

1930Z

2100Z

2230Z

Hurricane Jerry had highest previously published lightning rate with ~ 600 strikes within 60 km of eyewall

Rita had >1300 strikes within 50 km of eyewall

Page 7: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Rita

Central Sea-Level Pressure vs Lightning Rate

Rita

Aircraft radar reflectivity and lightning strikes

1513 UTC – 1533 UTC 21 September.

Page 8: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Rita

TRMM 87 GHz and Ice Product w/ lightning strikes

1506 UTC – 1617 UTC 21 September.

RitaAircraft radar reflectivity

TRMM ice product

and lightning strikes

1506 UTC – 1617 UTC 21

September.

Page 9: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Rita

Aircraft radar reflectivity and lightning strikes

1452 UTC 22 September.

Conceptual Model

During high lightning rates: eye wall is steep and eye is

small, vertical velocities and ice concentrations are large.

During low lightning rates: eye is large, eye wall is

sloped, vertical velocities are modest, and ice

concentrations are low.

Page 10: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

" Domain divided into 0.5˚ x 0.5˚ grid

" Lightning rates from Long-Range Network

" Rainfall rate from NASA AMSR-E and TMI sensors

" Lightning strokes occurring within ±15 min of satellite overpass time are counted

" Lightning count and average rainfall are computed over each square

Methodology to Determine Relationship

of Lightning to Rainfall

28 February 2004

Lightning - Convective Rainfall Relationship

Composite analysis of 15 storms in the central Pacific. Blue line is fitted function where R is rainfall rate and L lightning rate. Data points were obtained using cumulative probability matching technique (Calheiros and Zawadski 1987)

Page 11: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Lightning Data Assimilation

into a NWP Model

Two approaches:Four-Dimensional Data Assimilation (FDDA) of Moisture ProfilesLatent heating assimilation

NWP Model Description

PSU/NCAR Mesoscale Model (MM5) 40 vertical levels and 27-km grid spacingKain-Fritch convective parameterizationReisner graupel explicit moisture scheme

Model integration 60 hInitialization 00Z or 12Z

Initial conditions from GFS-model

Boundary conditions every 6 hours

Assimilation 8 h

Page 12: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

Moisture profiles

0

5

10

15

20

25

30

35

40

0 0.002 0.004 0.006 0.008

Mixing Ratio (kg/kg)

Sig

ma L

evel

No rain

1-3 mm/h

3-6 mm/h

>6 mm/h

Assimilation of Lightning Data" Compute lightning rates over 0.25º x 0.25º squares and 30 min time

window during the whole assimilation period" Use lightning-rainfall relationship to match lightning rate with moisture

profile." Radius of influence of observations in horizontal = 54 km" Time window of influence = ±15 min" Nudging every second time step if observed value is higher than

model computed value.

Lightning observations 09-12Z 12/19/2002

Observed Sea-level Pressure (left) and ETA 24-hr SLP and rainfall forecasts valid at 12 UTC 19 December 2002 (middle), show a 11mb forecast error in storm central pressure (12 hr forecast shows 9mb error).

972

983

North-East Pacific Low 19 December 2002

Page 13: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

972

L 983L 971

Reduced Forecast Error over the Eastern Pacific

Assimilation of lightning data results in a significantly improved forecast of storm central pressure.

Latent Heating Approach

Sample convective latent heating profiles over the NE Pacific storm for 1-2 mm/h and 5-6 mm/h rain rates.

Latent Heating (convective)

0

5

10

15

20

25

30

35

40

-200 -150 -100 -50 0 50 100 150

K/day

Mo

del Level

1-2 mm/h

5-6 mm/h

Rainfall rates derived from lightning observations are used to scale model’s latent heating profiles

Page 14: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

972

L 983

Reduced Forecast Error over the Eastern Pacific

Assimilation of lightning data results in a significantly improved forecast of storm central pressure.

L 976

Sea-Level Pressure 19-20 Dec. 2002

968

970

972

974

976

978

980

982

984

986

0 6 12 18 24

Time

SLP

(m

b)

FDDA

CTRL

OBS

LAT

Time Series of Storm Central

Sea-Level Pressure

Assimilation 8h

Page 15: The Utility of Long-Range Lightning Networks · 30 35 40 0 0.002 0.004 0.006 0.008 Mixing Ratio (kg/kg) Sigma Level No rain 1-3 mm/h 3-6 mm/h >6 mm/h Assimilation of Lightning Data

AcknowledgementsThe authors would like to thank ONR and NASA for support of PacNet.

References

Pessi, A.T., S. Businger, T. Cherubini, K. L. Cummins, and T. Turner, 2005: Toward the assimilation of lightning data over the Pacific Ocean into a mesoscale NWP model. 85th Annual AMS Meeting held in San Diego, CA.

Squires, K. and S. Businger, 2006: The Morphology of Eyewall Cloud to Ground Lightning Outbreaks in Two Category Five Hurricanes. MWR, in review.


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