global lightning observations

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Global Lightning Observations. Streamers, sprites, leaders, lightning : from micro- to macroscales. Remote detection of lightning - information provided LIS and OTD - what they are and how they work Results from global observations Next generation Change ?. + + + + + + + +. + + + + - PowerPoint PPT Presentation

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Global Lightning Observations

Streamers, sprites, leaders, lightning: from micro- to macroscales

•Remote detection of lightning - information provided

•LIS and OTD - what they are and how they work

•Results from global observations•Next generation•Change ?

A schematic of grauple - ice crystal charge A schematic of grauple - ice crystal charge transfer in a thunderstormtransfer in a thunderstorm

Lightning production is related to microphysical and dynamic cloud processes. Lightning production is related to microphysical and dynamic cloud processes.

Ice interactions seem to play the major role in thunderstorm electrification.Ice interactions seem to play the major role in thunderstorm electrification.

Particularly rebounding collisions of graupel and ice crystals – Non-inductive Particularly rebounding collisions of graupel and ice crystals – Non-inductive charging mechanism.charging mechanism.

Necessary conditions for thunderstorm electrification: a) strNecessary conditions for thunderstorm electrification: a) strong enough enough up-draft to grow precipitation size ice. b) ice-graupel collisions in the up-draft to grow precipitation size ice. b) ice-graupel collisions in the

presence of waterpresence of water

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Lightning Connection to Thunderstorm Updraft,

Storm Growth and Decay

• Total Lightning —responds to updraft velocity and concentration, phase, type of hydrometeors — integrated flux of particles

• WX Radar — responds to concentration, size, phase, and type of hydrometeors- integrated over small volumes

• Microwave Radiometer — responds to concentration, size, phase, and type of hydrometeors — integrated over depth of storm (85 GHz ice scattering)

• VIS / IR — cloud top height/temperature, texture, optical depth

Why observe lightning?(Forecasting)

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Time

TornadotimeLightning

Radar

pp

Flux HypothesisFlux HypothesisHypothesis:Hypothesis: Lightning Lightning

frequency frequency ((F)F) proportional to product proportional to product

of upward non of upward non precipitation ice mass precipitation ice mass

flux flux (I) (I) and precipitation and precipitation ice mass flux ice mass flux (p)(p)

FF = c* = c*pp**IISupported by simple Supported by simple

calculations (Blyth et al. calculations (Blyth et al. 2001) and lightning 2001) and lightning

model results (Baker et model results (Baker et al. 1995, 1999).al. 1995, 1999).

Positive chargePositive charge

Negative chargeNegative charge

Positive chargePositive charge

Positive chargePositive charge

Negative chargeNegative charge

TemperatureTemperature

Positive chargePositive charge

Char

ging

zon

eCh

argi

ng z

one

FF

STEPS Results – 6 June 2000

‘Garden Variety’ Single Cell Storm

Non- Precipitation ice mass flux [g s-1 m-2] * 1011

Ligh

tnin

g p

er r

ada r

vol

u me

tim

e

Precipitation ice mass flux [g s-1 m-2] * 1012

How good is the apparent correlation between lightning and IWP and how does it vary

between regimes?

Method• Create land, ocean, coastal data mask

• Create scatter plot of data in previous figure (0.5 x 0.5o grid) for each partitionResult• Noisy, but clear correlations above sample noise floor in flash density

• Eyeball says best fit lines would be very similar

Clarify Signal: Ocean, Coast and Land IWP Binned by Flash Density

• When averaged, correlation is very strong, best fit lines independent of regime. • ~95% (75%) of oceanic (coast) flash density distribution in sampling noise (low flash density; <.007 fl/km2/day = 0.2 fl/km2/mo), low IWP (~.01-.02 kg/m2). Sampling + DE threshold + occurrence!• Similar functional relationships between rain (Iiquid) – lightning vary by regime.

(All rain certain pixels with detectable IWP included)

TRMM PR IMP

Sample “Virtual radar” retrieval

Truth

Retrieval

(radar)

(µwave + lightning)

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GPROF(cloud model)

Instrument designChristian et al, J. Geophys. Res., 1989

• Fast lens, narrowband filter at 777.4 nm

• 128 x 128 CCD array, 500 fps imaging

• Frame-to-frame subtraction isolates lightning transients against bright daytime background

Measurement: Spatial Discrimination

8 km nominal spatial resolution optimizes the lightning-to-background S/N ratio.

8 km

8 km

Measurement:Temporal Discrimination

CCD integration interval is set to 2 ms to minimize pulse splitting between frames and minimize

integration of background signal

Measurement: Spectral Filtering

Narrow band interference filter passes only light from 1nm wide oxygen mutiplet

Optical Transient Detector( launched April, 1995 )

Lightning Imaging Sensor( launched November, 1997 )

Lightning Detection from Low Earth Orbit

LIS on TRMM

•Lower orbit, smaller Field of View, tropical inclination

History: LIS (1997-present)

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High Resolution Full Climatology Annual Flash Rate

Global distribution of lightning from a combined nine years of observations of the NASA OTD (4/95-3/00) and LIS (1/98-12/04) instruments

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Climatology: Diurnal cycle

( Local hour )

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Climatology: Diurnal cycle

( UTC Hour )

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Global lightning is modulated on annual & diurnal time scales, as well as seasonally

and interannually

Lightning Responsive to Interannual

Variability

Winter 1997-98 (El Niño)

Winter 1998-99 (La Niña)

Flash Rate Density-Congo

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Flash Rate Density-India

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LIS Ocean Overpass

LIS Land Overpass

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Major Points for Severe Weather

• Primary lightning signature is high flash rates and the “jump”

• Lightning flash rate is correlated storm intensity - higher rate implies stronger storm.

• Evolution of the lightning activity follows the updraft. Increasing activity means the storm intensifying; decreasing activity means the updraft is weakening.• A jump in lightning activity is associated with a pulse in updraft intensity

• These signatures, in conjunction with other NWS assets can be used to:

• Separate intensifying from weakening storms• Identify storms in process of going severe• Quickly determine the most intense storms in a complex system• Improved warning times • Reduced false alarms rates

Lightning Sensing from GEO

•Climate Monitoring

•Storm Development

• Ice-phase precipitation estimates

•Severe Weather Now-casting

•Data assimilation and model inputs

•Atmospheric chemistry

GLM : Field of View at GOES West and East

•GOES W (75ºW) GOES E (135ºW)

• OTD climatology indicates lightning density• Range rings indicate limits of 10, 15, 20, & 50 km pixel

footprint

GEO -East

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•Questions ?

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