understanding anomalous storms

Understanding anomalous

storms

Brody Fuchs

23 Mar 2017

Atmospheric Electricity Lecture

Quick review of non-inductive

charging and lightning

• Polar nature of water molecule means that charge can be transferred during collisions

• Charged particles (primarily) vertically separated by convective motions in the storm– Gravity pulls larger particles downward

– Convection pushes small particles upward

– Large scale separation produces strong electric fields

– Lightning is results from electrical breakdown of air

– Acts to neutralize charge separation/electric fields

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Takahashi (1978); Saunders and Peck (1998);

Pereyra and Avila (2000)

Charge acquired by graupel particle a function of

temperature and supercooled cloud water content

• Particle growing faster by deposition acquires positive charge upon collision

• Fundamentally, supercooled cloud droplets are accreted by larger particles which then freeze and release latent heat

• Alters the fundamental heat balance

• Can alter growth rates from vapor deposition

• Could be affected by other things such as cloud droplet size

Takahashi et al. (2017)

Charge polarity/magnitude depend on

experiment setup

• Lots of different results from different studies

• Largely dependent on experimental setup

• A few common themes

– Graupel charges positively at warm temperatures

– At colder temps, graupel charge is dependent on supercooled water content

• In theory, should be able to back out supercooled water content if we can get graupel charge polarity

Lightning as an investigative tool

• Electric fields result from collisions between graupel and ice crystals

• Lightning flash rate linked to vertical air motions, graupel mass

• Various microphysical and dynamical processes control amount of SCLW in mixed-phase

• We should be able to work backwards from lightning flash rate and charge structure to learn stuff about microphysics/dynamics

Williams (1985); Baker et al. (1995) ; Lang et al. (2000); Williams and Stanfill (2002);Williams et al. (2005); Carey and Buffalo (2007)

Storm charge structure and lightning

• “Normal” dipole/tripole• Vertically separated,

oppositely charged regions• ICs between mid-level

negative/upper-level positive

• CGs initiate between lower positive and mid-level negative

• Lower negative charge to ground

• Majority of storms around the US and globe have this charge structure

• How do we know this???

• Lower atmosphere is a weak conductor

• Continuous current flow from ionosphere to

Earth surface (can be thought of as capacitor)

• Would not be continuous unless there was a

continuous charging mechanism

• Upper positive charge in thunderstorms is

transported to the ionosphere (or

electrosphere) and negative charge is

transported to the Earth’s surface through

cloud-to-ground flashes

++ + +

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Rc

ABOUT 90% OF

CGS IN CONUS

ARE NEGATIVE

POLARITY

-+

-+

0 °C

-20 °C

-40 °C

Normal polarity, modest supercooled water

-CG flash

• Low level positive charge due to graupel charging at warm temps

• Mid level negative charge due to graupel charging at cooler temps and

modest supercooled water contents

• Upper positive from the ice crystals that collided with the mid level graupel

• Infer modest SCLW from –CGs, which likely from mid-level negative charge,

which is likely graupel -> therefore, SCLW must fall in the negative charging

zone

Cloud water content (g/m3)

Tem

per

atu

re (

°C)

Typical supercooled liquid water

contents (from our best estimates)

IC flash

Anomalous polarity, large supercooled water amounts

-+

? ? ?+CG flash

Cloud water content (g/m3)

Tem

per

atu

re (

°C)

• Mid level positive charge (likely on graupel)

• Corresponding negative ice crystals lofted to the top of the storm

• Not clear what charge (if any) resides near 0 °C, could be positive or

negative

• Higher fraction of +CG flashes, likely comes from mid-level positive, which

is likely comprised of graupel

• Additionally, these storms more likely to produce severe weather, also have

high IC:CG

Increase supercooled water content

over the threshold to get positive

graupel charging

IC flash

The problem

• Inference of supercooled water is very indirect

• We can’t get in situ measurements!

The payoff

• Lightning/charge structure/supercooled water are

functions of microphysics and dynamics

• Various lightning/charge quantities could inform us about

storm processes

– Entrainment

– Turbulence

– Updraft speeds?

– Mixed-phase processes

– Growth of graupel/hail

– Warm rain efficiency?

– Nowcasting

• So we have to try to understand lightning/charge

structures

Causal chain

Environment

Microphysics Dynamics

Charge transfer

Charge structures

Lightning

Boccippio et al. (2000); Williams et al. (2005); Fuchs et al. (2015)

Θw, Instability

CBH

IC:CG ratio

% +CGs

The thermodynamic argument

• 2 schools of thought about updraft strength

• Sun warms land more than oceans

– More instability

– Maybe not true? (Williams and Renno 1993)

– Higher cloud bases and shallow warm cloud

depths

• Greater land aerosol concentrations

– Aerosol invigoration of convection

• Simultaneous influences?

Thermodynamics vs. Aerosols

Lyons et al. (1998); Williams et al. (2002); Williams and Stanfill (2002); Andreae et al. (2004); Williams et al.

(2005); van den Heever et al. (2006); Rosenfeld et al. (2008); Stolz et al. (2015); Fuchs et al. (2015, 2017)

Freezing Height

CBH

WCD

CBH α surface dew point depression

My masters work• Investigate dependence of

storm characteristics on thermodynamics and aerosols

• ~ 4000 isolated convective storms from 4 distinct regions of US with NEXRAD and high-res lightning data

• Accurate total flash rates

• Infer gross charge structures

• Estimate supercooled water contents?

Boccippio et al. (2000); Williams et al. (2005); Fuchs et al. (2015)

Θw

Instability

CBH

CSU Lightning, Environmental, Aerosol and

Radar (CLEAR) Framework

• Designed by Lang and Rutledge (2011) to objectively analyze large amounts of data

• Objectively identifies cells based on reflectivity

• Used with – 3D mosaic (reflectivity only) data every 5 minutes

– Lightning mapping arrays (LMA) – flash counting

– Nat’l Lightning Detection Network (NLDN) CG data

– Environmental (RUC/RAP) analysis data

– Model CCN concentrations (GEOS-Chem)

• Combines data by attributing data to identified cells

Rison et al., (1999); Benjamin et al., (2004, 2006); King et al., (1999); Zhang et al., (2011); Lang and

Rutledge (2011); Pierce et al. (2013); Fuchs et al. (2015)

GLD 360/ WWLLN

NLDN

LMA

Different lightning processes

produce different

frequencies of radiation

Wavelength proportional to

characteristic size

Attenuation of radiation is

frequency-dependentCourtesy Walt Lyons

LMA operation

• Fancy system of radio antennas

• Detects sources within ~ 60-66 MHz band – Unused local analog television band (channel 3 or 4)

– Wavelength ~ 5 meters

• Time of arrival (TOA) from 6 or more stations– Redundant equations, higher accuracy

– Intersection of time-difference hyperbolas

• Decimated data – record most intense radiation within a time window (tens of ns)– Realtime output (smaller bandwidth)

• Full rate data- processed to provide all radiation sources

• VHF radiation produced by lightning channel propagation

Rison et al (1999); Thomas et al. (2002); Fuchs et al. (2015, 2017)

VHF Lightning MappersLMA LMA soon LDAR

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t1t2

t3

Ground

LMA time-of-arrival technique

VHF radiation α dI/dt

Cell

antenna

Radio antenna

Solar panel

Main

processor

IC flash

Lightning Mapping Arrays (LMAs)

• LMAs detect radiation produced by lightning propagation

• LMA sources grouped to make flashes

– Rates, areas and locations

• Higher detection efficiencies than LIS, OTD

– Implications for comparisons?

• Can be used to infer charge structures (LMA mode)

Temperature (°C)

0

-10

-20

-30

-40

Williams (1989); Rison et al (1999); Thomas et al. (2002); Fuchs et al. (2015)

LMA source

Use LMA mode as a crude way to represent charge structure

(or location of active positive charge)

Normal charge structure Anomalous charge structure

LMA mode-20 °C

Temperature (°C)

0

-10

-20

-30

-40

-40

°C

LMA charge inferenceLMA stations detect VHF radiation from propagation of lightning channel, more noisy in positive charge

Williams (1989)

(More common; typical LWCs) (Less common; large LWCs)

Upper positive

Mid-level negative

Time-Height

Looking north

Looking eastPlan view

Vertical distribution

Sample LMA lightning flash

Flash algorithm - DBSCAN• Most common clustering algorithm and most cited

in literature

• Finds regions of high density (in space and time)

• Groups clusters of sources into flashes

• No assumed distributions

• Free parameters

• Search radius

• Minimum points

• Relatively small sensitivities

• ~ 10% differences in flash rates

• < 15% difference with other algorithms

• Have to do subjective/manual analysis

~ 2

0 k

m

Fuchs et al. (2015)

Cell lightning flashes

Points are LMA sources

colored by time (in the 5

minute window)

Black ‘x’s are the

identified flashes by the

algorithm

Lots of data!!!

Flash products

• Flash rates

• More accurate than NLDN, IC:CG ratio– Satellite

– Field change

• Accurate measure of storm intensity

• Lat/lon/altitude of every flash

• Area of flash– Convex hull area

– Useful for NOx production studies

• With multiple flash products and charge structures, should be able to do some good investigating

Regional comparison

• Colorado has the highest flash rates

• And most anomalous storms (mid-level positive)

– Indicative of large SCLW and strong updrafts

Fuchs et al. (2015)

Environment and flash rates

Aerosol impacts• N40 = CCN proxy from GEOS-Chem

• Highest flash rates and mixed-phase

reflectivities for N40 < 1200 cm-3

• Drop-off at high N40

– Shortwave absorption?

– Decreased riming efficiency?

3 dB

Rosenfeld et al. (2008); Mansell and Ziegler (2013); Fuchs et al. (2015)

• No “clean” cases

• Hypothesize less aerosol impacts in

US

– Thermodynamics stronger

– CCN concentrations too high for

invigoration

• Does not rule out all aerosol impacts

– Charge structures? IN?

• What about CO?

Unique Colorado behavior

• Semi-arid

• High CBH

• Shallow WCD

• Unclear aerosol impacts

• Perhaps insufficient time for warm-phase aerosol impacts

• Aerosol impacts depend on warm cloud residence time?

??

?

Fuchs et al. (2015)

Summary

• Shorter warm cloud residence time results

in less warm phase precip fallout

• More in mixed-phase

• Results in more supercooled water,

graupel, collisions

• More likely to produce anomalous/high

flash rate storms

• Less CCN impacts

STILL LACKING THE

DIRECT MICROPHYSICAL

AND DYNAMICAL

EVIDENCE!!!

Fuchs et al. (2015)

Depletion of liquid water in a parcel

Let’s do something about this

• The lack of direct relationships is a problem

• Let’s use the automated case study system

on cases where we have polarimetric

radar/dual-Doppler coverage and LMA

coverage

• One of our PhD papers does just that

• Comparison of 2 populations

– 10 normal polarity cases from Alabama

– 6 anomalous polarity cases from Colorado

– Limited mainly to DC3 cases for now

Causal chain

Environment

Microphysics Dynamics

Charge transfer

Charge structures

Lightning

CLEAR updates

• Generalize to be able to take in any type of data

• Integrated with CSU-radartools (available on Github)

– Compiles years of CSU work on polarimetric retrievals

• Compute sophisticated storm metrics

• Keeps same simplicity to compile stats on many storm samples

• Also currently being used to compare WRF modeled storm to observed storm with radar

Fuchs et al. (2017)

Brief aside: polarimetric radar

• Transmits and receives in horizontal and vertical polarized radiation

• Information about size, shape, orientation, phase of hydrometeors in a volume

• Reflectivity (Z) – Measure of size/ concentration

• Differential reflectivity (ZDR) – Oblateness, sensitive to median drop size

• Specific differential phase (Kdp) – liquid water, drop oblateness, more sensitive to smaller drops than ZDR

• Correlation coefficient (ρhv) – Homogeneity of hydrometeors

• Linear depolarization ratio (LDR) – Indicative of canted particles and wet growth (only for alternating transmission mode)

Eumetcal.org; Bringi and Chandrasekar (2001); Doviak and Zrnic (1993)

RADAR

CLOUD

Polarimetric Retrievals

• Different hydrometeor species have different polarimetric signatures

– Raindrops: high ZDR, moderate-high Z, T > 0 C

– Pristine ice crystals: high ZDR, low Z, cold T

– Graupel: 0 ZDR, moderate-high Z, T < 0 C

– Hail: 0 ZDR, high Z

• Can use these differences to infer dominant species in a radar grid volume

• Can calculate other things like rain rates, graupel ice masses

Bringi and Chandrasekar (2001) and references therein

Charge structure/lightning characteristics

• Median flash rates ~ 10 flashes/min

• Mainly in line with larger sample from Fuchs et al. (2015)

• Limited by storms that were within DD lobes

More CAPE in AL

Similar NCAPE

Much higher surface T in CO

Similar adibaticwater content

Higher LCL heights in CO

Shallower WCDs in CO

Higher PW in AL Similar mid-level RH

Similar shear

Archetypal normal

AL caseMain updraft

LMA sources near

the top of the

updraft, graupel

HID

Hail, big drops in

main updraft

Modest flash rates

Robust upper

positive develops

after 2020Z

Vertical ice mass

mainly below 7 km

Modest updraft

speeds

Archetypal

anomalous CO case• Main updraft

• LMA sources on the

periphery of the strong

updraft

• Mostly LDG in the

updraft, also modest dBZ

• Higher flash rates, but

not super high

• Consistent mid-level

positive charge until

2243Z

• Shift in charge structure

after that

• Vertical ice mass

correlates with LMA

sources

• Much stronger updrafts

Quick case study summary

• Rain/hail/HDG in the updraft of the AL storm, also high dBZ, not the case in CO

• LMA sources (i.e. positive charge) near the top of the updraft in AL, not collocated with ice mass

• LMA sources (i.e. positive charge) on the periphery of strong updraft in CO, collocated with ice mass

• Stronger, larger updrafts in CO case

• Let’s see if these differences hold up in the larger sample

Bulk microphysical quantities

• Just picked a few typical

microphysical intensity

metrics, esp those related to

lightning

• In AL cases

• Larger graupel volume

• Larger mixed-phase 30

dBZ volume

• Larger hail volume

• Similar maximum graupel

heights

Updraft speed characteristicsMost vertical velocities near 0

Stronger updrafts more common in CO, also peak

updrafts higher as well

Updraft volumes

Larger UV5 and UV10 in CO anomalous cases

Most normal AL cases don’t have updrafts greater than 10 m/s

Updraft area with height

Picked -20 C because that’s

where most of the charging

is likely occurring

Much wider updrafts in CO

cases, gets wider with height,

peaks between -20 and -30 C

Location of LMA sources w.r.t. dynamics

• Collocate LMA sources

in a storm with w and

horizontal gradient of w

• w and wH CFAD

contours also overlaid

• AL cases have most

LMA sources near 0

vertical motion and near

0 wH

• LMA sources in CO

cases also occur in

relatively weak w, but

tend to occur in nonzero

wH

• Similar to the cases we

looked at

• CFAD wH contours in

CO suggest that the

strong updrafts are

broad

Collocation of LMA sources and ice mass

• Recall the cases, AL ice mass did not correlate with ice mass, but CO case did

• Nearly all of the ice mass due to graupel

• High correlation between ice mass/LMA would suggest that graupel carries positive

charge

• Colorado anomalous cases indicate that the graupel is the positive charge carrier

• In Alabama graupel is not the positive charge carrier

Warm cloud residence time

• Recall hypothesis from Fuchs et al. (2015)

• Short warm cloud residence time in CO cases > limited loss of water before

reaching mixed-phase > lots of SCLW > positive graupel charging

• Shorter times would likely result in smaller cloud drops, acts in same direction

• Using 95th percentile of updraft speed, CO time is about 3 minutes!, AL is about 12

minutes, if use 90th percentile, factor 4 remains constant

• Would likely talk to aerosol impacts

Summary of statistics

• Colorado anomalous cases had stronger, broader

updrafts than Alabama cases

• Similar instability and adibatic water

• Much higher CBH/shallower WCD

• Led to a much shorter warm cloud residence time

in CO cases, increased ability to transport cloud

water to mixed-phase region

• Ice mass correlations provide more direct

evidence of positive graupel charging, which is

likely due to large supercooled water content

• Raises some questions…

Questions/future work

• Why are Colorado updrafts much stronger

even though they live in similar

environments?

• Local generation of charge vs. advection?

• Vertical W gradients/LMA sources in AL

• Look into turbulence measures? Flash size

• What about normal polarity storms in

Colorado?

Lightning flash

characteristics

Lightning response to charge structure

• Don’t only study charge structures to learn about storm processes

• Lightning obviously responds to charge structure

• With multiple years of LMA data in a few regions, let’s create a climatology of flashes

• Colorado, Washington DC, and Alabama

• See what we see!

DC flash characteristics12 million flashes analyzed from 2007-2014

FLASH

DENSITY*

IC/CG RATIO MEDIAN FLASH AREA

Azimuthally integrated

Decreasing detection

Fuchs et al. (2016)

IC/CG RATIO* MEDIAN FLASH

AREA

AL flash characteristics40 million flashes analyzed from 2008-2014


FLASH

DENSITY*


Fuchs et al. (2016)

Alabama and DC summary• AL flash densities ~ 30-40 flash km-2 yr-1

– ~ 4-5 IC:CG

– Inside and near network

• DC flash densities ~ 18 flash km-2 yr-1

– 3-4 IC:CG

– Inside and near network

• Both within 50% of the satellite estimates from Cecil et al. (2014)

• Different detection and data collection methods

• Satellite estimate in Colorado around 20-25 flash km-2 yr-1…

Cecil et al. (2014); Boccippio et al. (2001)

??

Colorado flash characteristics10 million flashes analyzed from 2012 and 2014


FLASH

DENSITY*

IC/CG RATIO* MEDIAN FLASH

AREA


Fuchs et al. (2016)

How is Colorado lightning different?

Colorado Alabama

• Much larger IC:CG values (up to 25!)

• Similar calculated flash areas despite much higher points/flash

– Colorado is most sensitive network to date

– Physical flashes may actually be smaller than in AL/DC

• Flash height

• But this is only initiation, satellites can detect more than that!

Fuchs et al. (2016)

Lightning flash channels

Flash extent density/Flash channels

• Important quantity– What GLM will observe

– Spatial extent and location of the flash

– Amount of N2 and O2 exposed to channel heating

• Gives more information about the flash than just a single fractal area

• There are issues with this– Grid box size sensitivity

– 2D versus 3D

– Flashes with few points

– LMA detection

~ 1

0 k

m

~ 10 km

Flash channel calculation

• Impose a grid over

each flash identified

by the algorithm

• Any grid box/cube

that contains an LMA

source is considered

to have contained a

segment of the flash

• Binary = 1 or 0

• Add them up for all

flashes in a

volume/cell

Fuchs and Rutledge (2017)


Regional flash channel distributions• Most Alabama/DC channels

around 8-10 km

• Colorado much lower in the

storm, similar to Fuchs et al.

(2016)

• Flashes that start low in CO

tend to stay low

• Much larger values in

Colorado than other regions

• Flash channels at higher

reflectivities in Colorado

• Perhaps tougher for

satellites to detect

• Hopefully be able to test this

during GLM Cal/Val

• Could impact downstream

NOx and ozone production


Flash channels and charge structure

• Lowest median channel

heights in CO

• Lightning follows strong

positive charge (LMA mode)

• Lower altitude flashes

coincident with warm

positive charge

• Colorado has the largest

fraction of anomalous storms

– They also produce a lot

of lightning

• Implications for scattering of

photons??

Why is Colorado different?

• High cloud bases, shallow WCD

• Strong updrafts, high SCLW contents

– Positive charge to graupel/hail

• More turbulence, smaller flashes?

• More low-altitude IC flashes

– More difficult for optical detectors?

Temperature (°C)

0

-10

-20

-30

-40

Alabama storms Colorado storms

Fuchs et al. (2015, 2016, 2017)

WHERE ARE SIMILAR THERMODYNAMIC

ENVIRONMENTS TO COLORADO??

• May have implications on our understand of

global lightning distributions?

understanding anomalous storms

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