The Lightning Power Index Testing a new tool for predicting lightning density and the potential for

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The Lightning Power Index Testing a new tool for
predicting lightning density and the potential
for extreme rainfall in Mediterranean storms

• Barry Lynn (1, 2), Yoav Yair (1), Colin Price (3)
  and Efrat Morin (4)
• 1. Department of Life and Natural Sciences, The
  Open University of Israel
• 2. Weather-it-is, Efrat
• 3. Department of Geophysics and Planetary
  Sciences, Tel-Aviv University
• 4. Department of Geography, The Hebrew University
  of Jerusalem

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Talk Layout

• Introduction
• Existing Indices for Lightning Prediction
• K-Index (KI)
• Cloud Physics Thunder Parameter (CPTP)
• The Lightning Power Index (LPI)
• Case studies
• Israel Afula, 28.10.2006
• Greece Volos 9.10.2006
• Italy Emilia Romagna 8.9.2006
• Summary

This research is part of the FLASH project
supported by the FP6 Framework Program of the EU
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K Index (KI)

• The K index takes into account moist air at 700
  mb contributing to air mass thunderstorm
  development.
• The K index is defined as follows
• K T850 - T500 Td850 - (T700 - Td700)
• The risk of air mass thunderstorms is defined as
  follows
• K lt 15 0 Air mass thunderstorm
  probability15-20 lt20 Air mass
  thunderstorm probability21-25 20-40 Air
  mass thunderstorm probability26-30 40-60
  Air mass thunderstorm probability31-35
  60-80 Air mass thunderstorm probability36-40
  80-90 Air mass thunderstorm probabilityK gt40
  gt90 Air mass thunderstorm probability

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CPTP Cloud Physics Thunder Parameter (Bright et
al., 2005)
TEL is the equilibrium level temperature CAPE-20
is the CAPE between the 0C to -20C K 100 Jkg-1.

• Based on evidence for the correlations between
  the presence of ice in the mixed phase region and
  the level of electrification
• Convective updraft must be strong enough to
  ensure super-cooled liquid water is replenished
  and graupel is lifted above the charge-reversal
  temperature zone (-15C to -20C).
• CPTP produces a plan view depiction of where
  thermodynamics support thunderstorms given that a
  convective cloud can develop

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Thunderstorm charging requirements (Mason, 1953)

• Time available for electric field generation is
  30 minutes.
• Charge generation produces 20 to 30 Coulombs per
  flash.
• Charge separation occurs between the 0C and
  -40C levels in a region of radius 2 km.
• The main negative charge centre is between the
  -5C and
• -25C levels depending on the cloud physics, the
  main positive centre is a few km above the
  negative centre. The lower positive charge is
  close to the 0C level.
• Electric field development is associated with the
  development of precipitation in the form of soft
  hail (graupel), and the first lightning occurs
  within 12 to 20 minutes of the first radar
  detection of large particles.

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The Lightning Power Index

• Effective charge separation region within a
  developing thunderstorms is the volume between
  the freezing level and the -20C isotherms, where
  supercooled liquid water coexist with cloud ice,
  graupel pellets and snow crystals.
• Charge separation occurs via the non-inductive
  ice-grauple mechanism, in the presence of
  super-cooled liquid water (Takahashi, 1978
  Saunders and Peck, 1991).
• The electric charge build-up rate is directly
  proportional to the concentrations of the
  interacting particles and to the 4th power of the
  velocity gradient between them (Keith and
  Saunders, 1991)

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The Lightning Power Index

• The LPI calculates the flux of ice and water mass
  into and out of the charging zone (0 to -20C)
  within a convective cloud. It is the volume
  integral of the total mass of ice and liquid
  water, signifying the potential of the cloud to
  generate electric power.
• LPI 1/v ??? e w2 dx dy dz J
• where e 2(Qi Ql) 0.5 /(QiQl) W is
  the updraft
• Ql is the total liquid water mass.  Qi is the
  ice fractional content
• Qi 2 qg ((qs qg )0.5 /(qsqg) ) ((qi qg
  )0.5/ (qiqg))
• qs snow, qi cloud ice, qg graupel mass
  concentrations kg/m3
•  

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The WRF Model

• The WRF model simulations were done using a
  triple nest, beginning with a 27 km coarse grid
  outer mesh. The inner grids had 9, 3, and 1 km2
  grid resolution.
• The model grids were centered over the region of
  interest.
• The simulations were initialized using GFS
  Analysis data (no nudging was used).
• The simulations were from 18 to 24 hours,
  depending on location.
• Thompson bulk microphysics was used to explicitly
  simulate the hydrometeor fields.

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Sources of Data

• Lightning
• ZEUS European lightning detection network
• LPATS Israeli Electrical Company
• Rain
• SHAHAM radar (Israel)
• Israeli Meteorological Service (Rain gauge
  network)
• Notional Observatory of Athens (Greek network)
• Italian CNR satellite retrieval algorithms
• Model
• NCEP
• GFS

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Example 1 April 2006 Northern Israel
A good correlation exists between the locations
of lightning as measured by LPATS and the places
with the highest values of the Power Index
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Floods in Northern IsraelAfula

• FLASH Case Study 4
• 28 October 2006

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Flood in Israel 28.10.2006
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Lightning vs. Radar derived Rainfall
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Scale separation between convective and
stratiform rain - measured
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Model Results Flood in Israel 28.10.2006

• LPI vs. Model Rain Rate
• gt 10 mm/h

• LPI vs. Model Rain Rate
• 1-5 mm/h

Maximum LPI values are early by 0.5 h before
max rain
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Correlations between Lightning Power Index and
measured lightning and rain
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Floods in Central and Northern Greece

• FLASH Case study 14
• 9-10-11 October 2006

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Flood in Greece Volos 9.10.2006
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Flood in Greece Volos 9.10.2006

• LPI vs. model rain

• LPI vs. ZEUS lightning

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Model Results Flood in Greece Volos 9.10.2006

• LPI vs Rain Rate gt 10 mm/h

• LPI vs ZEUS lightning

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Floods in Northern ItalyEmilia Romagna

• FLASH Case Study 21
• 8-9 September 2006

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Flood in Northern Italy 8.9.2006
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Model Results Flood in Northern Italy Emilia
Romagna 8.9.2006

• LPI vs. model rain(gt 10 mm/h)

• LPI vs. ZEUS lightning

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Correlation between LPI and ZEUS lightning
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Conclusions

• The LPI is strongly correlated with (observed)
  cloud-to-ground lightning activity
• It correctly predicts the occurrence of major
  convective electrically-active cells
  (thunderstorms)
• There is a 30 minutes lead time of the maximum
  LPI from the peak in measured ground level
  rainfall rate
• The LPI gives a finer spatial and temporal
  resolution of lightning activity compared to KI
  and CPTP
• LPI values are calibrated against observed
  cloud-to-ground lightning activity to determine
  threshold values.

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Thank You!

• Questions?

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Lifted Index (LI)

• An air parcel is lifted from the surface with
  temperature and mixing ratios representative of
  the mean layer values of the lowest 100 mb of the
  atmosphere. This hypothetical parcel is then
  lifted dry adiabatically to the LCL and
  pseudo-adiabatically to 500 mb.
• The value of this index is the temperature of the
  environment subtracted from the temperature of
  the parcel at 500 mb.
• The risk of thunderstorms and severe weather
  activity is defined as follows
• LI gt 2 No significant activity
• 0 lt LI lt 2 Showers/thunderstorms possible
  (additional lift)-2 lt LI lt 0 Thunderstorms
  possible-4 lt LI lt -2 Thunderstorms more
  probable, but few, if any severeLI lt -4 Severe
  thunderstorms possible