the utility of long-range lightning networks · 30 35 40 0 0.002 0.004 0.006 0.008 mixing ratio...
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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](https://reader033.vdocument.in/reader033/viewer/2022060502/5f1ba97d75d0ba6c47653f16/html5/thumbnails/1.jpg)
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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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
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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.
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Synoptic View
Time series of daily total lightning strikes
Synoptic View
Histogram of monthly mean lightning strikes.
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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
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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
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Rita
Central Sea-Level Pressure vs Lightning Rate
Rita
Aircraft radar reflectivity and lightning strikes
1513 UTC – 1533 UTC 21 September.
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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.
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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.
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" 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)
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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
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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
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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
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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
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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.