AOSC 620: Special
Lecture Lightning
R. Dickerson
North Dakota Thunderstorm Experiment
1
Lightning Nomenclature
Flash – the entire lightning process whether staying within the
cloud (intra-cloud) or striking the ground (cloud-to-ground).
Stroke – cloud-to-ground components only.
Leader – discharge creating a conductive channel.
Corona – composed of streamers and limited to the region
around an electrode. ~ambient temperature.
Plasma – gas with >1% ions or electrons.
2
>90%
Thanks to M. Uman
Rare but powerful
3
4
5
Global electric circuit – classic view
In fair weather the current is downward (positive ions
down and neg ions or electrons up) with a global current
of ~1kA.
Thunderstorms induce a current of neg charges
downward (lightning and precp) and positive charges
upwards from the tops of clouds.
6
7
Basics of negative cloud-to-ground lightning
Stepped leader
Length of steps ~50 m
Mean current 100-200 Amp
First return stroke
Peak current 30kA
Radius 1-2 cm
T ~30,000 K
Overall Flash
Duration ~250 ms
Strokes/flash 3-5
Charge transfer ~ 20 C
Energy 109-1010 J
8
Impact of Lightning-NO Production on Tropospheric
Photochemistry and Radiative Forcing
Dale J. Allen
University of Maryland
College Park, MD 20742
With contributions from:
K. Pickering, NASA-GSFC
H. Huntrieser, DLR
E. Bucsela, SRI
R. Pinder, EPA
M. Martini, PNNL
C. Liaskos, A. Ring, & Y. Li, UMCP
October 17, 2013
Photo of northeast Colorado STEREO storm
Courtesy of K. Pickering
Outline
• Lightning formation and the resulting production of nitrogen
oxide (LNOx)
• Impact of LNOx on atmospheric composition and radiative
forcing
• Parameterization of LNOx production in global/regional models
– Estimation of LNOx production per flash
– Relation between flash rate and meteorological variables
– Specification of vertical distribution of LNOx
• Impact of LNOx on air quality and nitrogen deposition
• “When LNOx is not enough.”
– Why was UT NOx so high during the INTEX field campaign?
– Why do models underestimate tropospheric NO2 columns at rural
locations?
Lightning initiation...
Lightning is most common in clouds that contain
both water and ice (-10 to -40°C)
-40°C
-10°C
In these clouds, strong updrafts carry water
droplets upward where they collide with ice
crystals, forming graupel and transferring a
positive charge to the ice crystals and a
negative charge to the graupel.
As the relatively heavier graupel falls, an
increasingly negative charge builds up in the
lower portion of the cloud until the electrical
potential becomes sufficient to initiate a
lightning discharge or leader from the lower
portion of the cloud. This leader and subsequent
branches may travel upward (intracloud flash) or
downward to the surface (cloud-to-ground flash).
O2
N2
N2
N2
N2
N2
O2
N2
O2
N2
O2 N2
N2
Air is ~78%N2 and ~21% O2
N2 + O2  NO + NO
Zel’dovich mechanism
(Zel’dovich and Raizer
1966)
Lightning stroke  high T &
high P
N2 + O ↔ NO + N
(1)
N + O2 ↔ NO + O
(2)
N2 + O2 ↔ 2(NO)
(2b)
Reaction rate (1) is a strong
function of temperature.
NO is “frozen out” when
lightning channel cools
rapidly.
NO from Lightning
Copyright © 2013 R. R.
Dickerson & Z.Q. Li
13
Lightning, Reminder
In the absence of industrial processes, lightning is a major source of
odd nitrogen (NOx) and thus nitrate (NO3-) in the atmosphere. Even today,
lightning is a major source of NOx in the upper free troposphere.
N2 + O2  2NO
How can this happen? Let’s calculate the Gibbs Free Energy for the reaction for
298 K and again for 2000 K.
G° = – nRT ln (Keq)
Gf° = Hf° 0.0 for N2 and O2 Gf° (NO) = 20.7 kcal mole-1
Hf° (NO) = 21.6 kcal mole-1
R = 1.98 cal mole-1 K-1
G° = 2*(20.7) = 41.4 kcal mole-1
Keq = exp (– 41.4E3/1.98*298)
= 3.4 E-31
Copyright © 2011 R. R. Dickerson
æ P2 ö
Keq = ç NO ÷
è PN 2 PO2ø
14
G° = 2*(20.7) = 41.4 kcal mole-1
æ P2 ö
Keq = ç NO ÷
è PN 2 PO2ø
= exp (-G°/RT) = 3.4 E-31
Assume PN2 = 0.8 atm; PO2 = 0.2 atm
PNO = - Keq × 0.8× 0.2
= 2.3E-16 atm
(pretty small)
Let’s try again at a higher temperature (2000 K).
Remember H and φ are independent of temperature.
GT ≈ H° – Tφ°
41.4 = 43.2 – 298 φ°
φ° = +6.04E-3 kcal mole-1 K-1
GT ≈ 43.2 – 2000* 6.04E-3
= 31.12 kcal mole-1
Copyright © 2013 R. R.
Dickerson & Z.Q. Li
15
G(2000) ≈ 31.12 kcal mole-1
Keq = = PNO2/PN2*PO2 = exp (-GT/RT)
= exp (-31.12E3/1.98*2000)
= 3.87E-4
If the total pressure is 1.00 atm
PNO = 7.9E-3 atm
= [0.79% by volume]
You can show that the mole fraction of NO at equilibrium is nearly
independent of pressure. Try repeating this calculation for 2500 K; you
should obtain Keq = 3.4E-3 and [NO] = 2.3%.
In high temperature combustion, such as a car engine or power plant,
NO arises from similar conditions.
Copyright © 2013 R. R.
Dickerson & Z.Q. Li
16
Where does G(T) = 0?
GT ≈ H° – Tφ°
41.4 = 43.2 – 298 φ°
φ° = +6.04E-3 kcal mole-1 K-1
GT ≈ 43.2 – T* 6.04E-3 = 0
T ≈ 7000 K
But at 7000K N2, NO, and O2, forced by entropy, all begin to decompose to
their constituent atoms. Project left to the student: Calculate the Keq for
NO = N + O
At 7000 K.
With 20% O2 in the atmosphere, the maximum [NO is ~10%
Copyright © 2013 R. R.
Dickerson & Z.Q. Li
17
BL
Climatological OTD/LIS 0.5° x 0.5° Flash Rate Distribution (Flashes km-2 yr-1)
Courtesy of GHCC lightning team
Constructed using 1995-2000 data from the Optical Transient Detector (global coverage)
& 2000-2011 data from the Lightning Imaging Sensor (Equatorward of 35°) [GHCC]
Why is this LNOx important ?
LNOx indirectly affects local air quality and global climate
through its influence on ozone and hydroxyl radical (OH)
[OH is often referred to as the troposphere’s detergent]
NOx [NO+NO2]:
• Is a primary pollutant found in photochemical smog
• Is a precursor for tropospheric ozone formation
TROPOSPHERIC OZONE:
• Is the third most important GHG
• Impacts the Earth’s radiation budget
and can cause changes in
atmospheric circulation patterns
• Toxic to humans, plants & animals
Photo courtesy of University of California at Berkley
*(review by Schumann and Huntrieser, ACP, 2007)
Global NOx sources
[TgN a-1]
53*
< 1
NOx = NO+NO2
30-60
(source: Lee et al., AE, 1997)
< 1
Ozone production efficiency (OPE) in the PBL as a function of
NOx mixing ratio assuming full oxidation of NMHCs
[Liu et al., 1987]
Note decrease in OPE for high values of NOx.
Most LNOx production occurs at altitudes where NOx amounts are
low and OPE is high. Therefore the LNOx source is more important
than one might infer based on its % of the total NOx source.
[Grewe, 2007]
UT NOx in summer increases by 61-75% when LNOx is added
Calculations use output from NASA GMI model and assume LNOx
source of 500 moles per flash in extratropics [Allen et al., 2010]
UT ozone over US in summer increases by 20-33% due to LNOx
Contribution of
lightning-NO
to UT O3
increases from
June-August
and is especially
large during
August 2006
Calculations made using NASA GMI model and assume an extratropical
LNOx source of 500 moles per flash
NASA’s Chemistry and Climate Model (NASA CCM)
•
Global modeling system for evaluating the impact of anthropogenic and/or
natural perturbations on atmospheric composition & climate.
•
Includes NASA GCM, NASA Global Modeling Initiative CTM, and GOCART
aerosol module. It can be run in a free-running mode or in a replay mode
where analysis increments are used to simulate particular time periods.
•
The GMI CTM, which can also be run off-line using met fields from the
GEOS-4 or GEOS-5 GCM/DAS. It solves for the distribution of trace gases
in the atmosphere using a stratospheric or combined stratospheretroposphere chemical mechanism.
•
The GOCART aerosol module can also be run off-line or within the CCM
framework. When combined with the GMI CTM, it can be used to evaluate
the impact of aerosols on atmospheric chemistry and climate.
•
In order to investigate the sensitivity of atmospheric composition to
LNOx production, 4 “replay” CCM simulations (no LNOx, HalfLNox,
stdLNOx , and DoubleLNOx.) were run for 2006 & 2007. Magnitude of
LNOx source in these runs was 0.0, 2.5, 5.0, and 10.0 Tg N / yr
corresponding to ~0, 125, 250, and 500 moles per flash.
•
We begin by looking at the impact on ozone and OH.
Zonally-averaged ozone and OH for September 2007
as a function of magnitude of LNOx source
Upper-tropospheric ozone (OH) amounts in the tropics increase by nearly
50% (100%) as the global LNOx source is increased from a lower bound of
125 moles per flash (“Half LNOx”) to an upper bound of 500 moles per
flash (“Double LNOx”). C. Liaskos et al. (JGR, 2015).
Change in zonally-averaged ozone relative to standard simulation
Change in zonally-averaged OH relative to standard simulation
Sensitivity of radiative forcing from ozone to magnitude and spatial pattern
of lightning-NO production (NASA-GSFC CCM December 2007)
2.5 Tgs
5.0 Tgs
Co-located
With
Climatological
LNOx source
5.0 Tgs
Co-located
With
Convection
10.0 Tgs
Note: RF by NO2 itself is relatively minor due to its short lifetime.
Changes in RF from methane due to LNOx are not considered here.
Instantaneous radiative forcing (IRF) from ozone due to North American (NA)
anthropogenic emissions (left) and NA lightning-NO production (right)
for Jun 1-Jul 17 (top) and Jul 18-Aug 31 (bottom) of 2004. Calculated by
Martini et al. [2011] using University of Maryland CTM (UMD-CTM).
Ratio of IRF from ozone due to North American LNOx
vs. IRF from ozone due to North American anthropogenic emissions
IRF ratios calculated using UMD-CTM
for Jun 1 – Jul 17, 2004 [Martini et al., 2011]
Requirements for Specifying Lightning NO
Production in Global/Regional Chemical
Transport and Climate Models
1) Estimates of NO production per IC and CG flash
(DeCaria et al., 2000; 2005; Ott et al. (2007; 2010)
2) Flash rate distribution as a function of space and time
that is consistent with the driving model’s convection
(e.g., Allen and Pickering, 2002; Allen et al., 2010).
3) Vertical distribution of LNOx at the end of storm (e.g.,
Pickering et al., 1998; Ott et al., 2010).
Table 1. Sample of previous investigations of lightning NOx production for individual storms
Method
Moles NO/flash (Notes)
Reference
Theoretical
Laboratory
Theoretical/lab/ltng. obs.
Aircraft data, cloud model
Aircraft data, cloud model
Aircraft data, cloud model
Aircraft data, cloud model
Aircraft data
Aircraft data
Aircraft data
Satellite (GOME)
Satellite (SCIAMACHY)
Satellite (OMI)
Satellite (OMI)
Satellite (OMI)
1100 (CG), 110 (IC)
103
484 (CG), 35 (IC)
345-460 (STERAO-A)
360 (STERAO-A, EULINOX)
590-700 (CRYSTAL-FACE)
500 (Mean midlatitude)
500 – 600 (SCOUT-O3/ACTIVE)
70-210 (TROCCINOX)
121 – 385 (SCOUT-O3/ACTIVE)
70 – 179 (AMMA)
32-240 (Sub-Tropical)
33 – 50 (global, mostly marine)
87-246 (TC4 – tropical marine)
174 (TC4 mean)
440 (Central US, Gulf of Mex.)
72 – 92 (DC3)
Price et al., 1997
Wang et al., 1998
Koshak et al., 2013
DeCaria, et al., 2005
Ott et al., 2007; 2010
Ott et al., 2010
Ott et al., 2010
Cummings et al., 2013
Huntrieser et al. 2008
Huntrieser et al., 2009
Huntrieser et al., 2011
Beirle et al., 2006
Beirle et al., 2010b
Bucsela et al., 2010
Bucsela et al., 2010
Pickering et al., in prep
Pickering et al., in prep
Specification of NO production per flash
Summary of Five Midlatitude and Subtropical Storms
Orville et al., 2002
Means: 500 moles/flash
0.94 ratio
For global rate of 44
flashes/sec, this implies
~9 Tg N/yr (a bit high)
Ott et al., 2010, JGR
OMI-based estimation of LNOx production per flash
1.
2.
3.
Use back trajectories to determine if enhanced OMI NO2 columns can be
associated with upstream flashes.
Portion of column due to LNOx (VLNOx) is determined by subtracting the
sum of the measured stratospheric slant column and estimated
tropospheric background slant column from the measured total slant
column and dividing the resulting “lightning” slant column by an air mass
factor (AMF) appropriate for a region impacted by convection.
Symbolically,
VLNOx = ( Stotal – Vstrat ·Astrat – Vtrop_background ·Atrop ) / ALNOx
Production per flash can then be estimated by dividing the moles of NO
due to LNOx by the number of upstream flashes.
•
Note: AMFs for NO2 are determined using Goddard Modeling Initiative
(GMI) CTM output and the TOMS radiative transfer model (TOMSRAD).
•
Note: The tropospheric background is estimated using OMI measurements
from surrounding days with minimal lightning activity.
OMI LNOx for May 30, 2012 during DC3 field mission. Large maximum is
evident over southern Appalachians downwind of previous day’s storms over
Oklahoma [14.0 Mmoles LNOx within box]
Back trajectories suggest transport times of 9 – 18 hours; mean = 16.1 hours
Total (CG + IC) contributing flashes along trajectories = 181,743
1.4 x 107 moles/181,743 flashes = 77 moles LNOx/flash
Example over the Gulf of Mexico
“Observed” flashes (World Wide
Lightning Location Network,
WWLLN, after adjusting for
detection efficiency) during 6-hrs
before OMI overpass
OMI-based estimate of
lightning-NO production
per flash
Cloud radiance fraction
OMI sees enhanced
LNOx over western
portion of cloud system
but low values over
eastern portion
Remaining Issues
• VLNOx distribution is usually noisy and occasionally negative in regions
where OMI shows high cloud radiance fractions (CRFs). Therefore, we
will try screening out regions with CRF > ~50%.
• Flash rate detection efficiencies from the World Wide Lightning Location
Network (WWLLN) are 5-15% over much of the globe including Africa
where flashes are most plentiful. Therefore, we are investigating other
lightning networks (ENTLN, GLD360) and focusing on regions with DEs
greater than 15%.
• Tropospheric background is difficult to pin down. Is it best defined using
OMI data alone or is model output needed (ratios of simulations with and
without LNOx)? What is the impact of day-to-day variation in biomass
burning on this background?
LNOx production per flash is sensitive to environment; Storms with substantial wind
shear produce more NO per flash (e.g., tropical (low-shear) vs non-tropical systems)
c)
04 February 2005, 18 UTC
Wind
200 hPa
(~12 km)
Tropical
d)
18 February 2005, 21 UTC
Subtropical
Plot taken from Jan 2011 AMS presentation by Heidi Huntrieser
NO production per flash varies with flash component length which in
Comparison of "flash component" lengths in tropical and subtropical TS
turn varies with vertical wind shear
(Huntrieser et al., ACP, 2008)
2x
larger
1.6 km
3.1 km
TROCCINOX: subtropical flash component length = 2x tropical
Institut für Physik der Atmosphäre
Flash rates in the NASA GMI model are parameterized in terms of UT mass flux.
How well does this approach capture observed flashes?
Number to right of year shows total flash rate (flashes s-1) over region shown.
Spatial distributions of “observed” flashes are well captured
by mass-flux based parameterization. Magnitudes ~20% low.
Vertical distribution of LNOx production is expected to show
mid-trop peak due to CG flashes and UT peak due to IC flashes.
Here is the LMA-based distribution that was used as a guide for
partitioning LNOx production in CMAQ
Segment altitude distribution of
CG+IC flashes in vicinity of North
Alabama Lightning Mapping Array
(LMA) [Koshak et al., 2010]
EPA’s /Community Multi-scale Air Quality (CMAQ) CTM
•
Regional photochemical model that solves the constituent continuity equation.
In this study, it was run offline using meteorological fields from WRF.
•
CMAQ was originally designed to help regional air quality planners predict the
distribution of surface layer ozone and particulate matter.
•
•
These simulations use the CB05 chemical mechanism.
Calculates biogenic emissions of isoprene and monoterpenes using BEIS.
•
The lightning-NO algorithm used in these simulations was released
operationally in March 2011.
•
Simulations of 2006 air quality performed at EPA as part of this NASA Air
Quality Decision Support Project and the AQ Model Evaluation International
Initiative (AQMEII)
http://aqmeii.jrc.ec.europa.eu/doc/AQMEII_activity_description.pdf
•
These 2006 simulations use chemical boundary conditions from GEMS
(European-led assimilation effort)
http://ozone.meteo.be/meteo/view/en/1550484-GEMS.html
•
Bias between modeled and OMI tropospheric NO2 column for
CMAQ simulations without (top) and with (bottom) LNOx.
Adding LNOx
reduces mean
negative bias
for summer 2006
from 35-45% to 10-20%
Comparison uses
OMI DOMINO
product
However, an
interesting
urban/rural
bias remains …
Even after adjusting the OMI vertical column using a priori information from CMAQ,
CMAQ has a high-bias over urban areas and a low-bias over rural areas (summer)
.
Low-bias over rural areas suggests that the chemical lifetime of NO2 [Henderson et al., 2011;
Canty et al., 2015] and/or the medium-range transport of NOx [Gilliland et al., 2008] is
underestimated. Of course bias is also sensitive to magnitude of mostly rural LNOx & soil-NOx.
Does LNOx affect air quality?
Mean summer 2006 enhancement of
8-hr maxO3 due to LNOx
O3 enhancement (ppbv) calculated using
CMAQ assuming 500 mole per flash source)
Impact of LNOx on wet deposition of nitrate
Adding LNOx
eliminates
low-bias
Adding LNOx &
adjusting
for precip
bias leads
to better fit
Adjusting
for precip
Bias leads
To better fit
Eastern US: Longitudes east of 100W
How well does CMAQ simulate the wet deposition of nitrate (OxN)
and ammonium (redN) as measured by the NADP network?
oxN Biases
NE: +5%
SE: +19%
West –(5-10)%
Note: Adding LNOx causes
Wetdep(OxN) 50%↑
Totdep(OxN) 22%↑
redN biases
NE: +20%
SE: +40%
West: -(20-25)
Totdep(N) 11%↑
How much do uncertainties in chemistry contribute to
models’ inability to capture the high amounts of UT
NOx measured during INTEX-A
(An upper bound)
• CMAQv4.7.1 with CB-05 chemistry and AERO5 aerosols was
used to simulate the summer of 2004.
• Three simulations: 1) standard chemistry without lightning-NO,
2) standard chemistry with lightning-NO, and 3) updated
chemistry with lightning-NO
• Updated chemistry: Main change: Organic nitrate (ON) yield
from the oxidation of paraffins (PAR) was reduced from 15% to
3%. This decrease in ON production reduces NO consumption,
increases the NOx lifetime, and is in better agreement with
observations (Henderson et al., 2011).
Comparison of GMI-calc NOx with INTEX-A DC-8 Flight 5
GMI with
No Light
GMI with
lightning
Lightning-NO
emissions
appear
responsible
for observed
16 EST peak
in UT NOx;
However,
magnitude of
peak is
underestimated
by GMI
simulation
Comparison of GMI-calc ozone with INTEX-A DC-8 Flight 5
GMI with
No Light
GMI with
Lightning
Lightning-NO
emissions
appear
responsible
for observed
16 UT peak
in ozone.
Vertical
extent of
peak is
overestimated
by GMI
simulation.
Comparison of GMI-calc NOx profiles with INTEX-A profiles
GMI-calc
NOx profiles
with or without
lightning-NO
greatly
underestimate
observed UT
NOx amounts.
Hudman et
al. [2007]
found a similar
bias using
GEOS-CHEM.
250 mole per flash lightning source used here
Lightning-NO
increases
UT NOx by
75-100 pptv
(X4 increase)
Adjusting chemistry increases UT NOx by
20-30 pptv reducing model biases by 5-16%
if data are unbiased and by 10-33% if data
are assumed to be 30% too high. Simulation
could be re-run using chemistry modifications
from Canty et al. (2013).
However, a
120-500 pptv
bias remains
(60-300 pptv
if assume MPN
interference)
NO2 measurements taken by R. Cohen. Black line with asterisks shows
measured mean assuming 30% interference from MPN [Browne et al., 2011]
Comparison of GMI-calc ozone profiles with INTEX-A profiles
GMI-calc
O3 profiles
for sims
with
lightning-NO
agree
reasonably
well with
INTEX-A
O3 profiles
despite the
low-bias in
NOx.
Summary
• Upper tropospheric ozone (OH) amounts in the tropics increase
by nearly 50% (100%) as the global LNOx source is increased
from a lower bound of 125 moles per flash to an upper bound of
500 moles per flash.
• Cloud-to-ground and intracloud flashes produce ~same amount
of NO per flash. However, flashes from storms with midlatitude
characteristics usually produce more NO than storms with
tropical characteristics possibly due to wind-shear driven
differences in flash channel length.
• LNOx is responsible for 60-75% (20-33%) of upper tropospheric
NOx (ozone) over the United States during the summer time.
Therefore, it must be included in simulations when comparing
with satellite data; however, the magnitude of the LNOx source
is likely too low to resolve model/OMI differences in
tropospheric NO2. Look to the chemistry.
Summary (continued)
•Observations of LNOx from OMI can be used in conjunction with flash
rate information to reduce uncertainties in production per flash. The
method must be used with caution due to uncertainties introduced by
retrievals in partly cloud scenes, biomass burning, and relatively low
detection efficiencies.
•Lightning-NO must be included in simulations that evaluate wet
deposition. Over the U.S., it increases wet deposition of nitrate by 50%
and total deposition of nitrogen by 11% in CMAQ. It also changes a
30% low-bias with respect to NADP deposition to a 2% high-bias.
•Ozone with a LNOx source does reach the surface, especially over the
southwestern U.S. where boundary layers are high. According to
CMAQ, on poor AQ days (8-hr max ozone>60 ppbv), LNOx contributes
>6.5 ppbv to 8hr-ozone at 10% of western sites and 3% of eastern sites
•Uncertainty in the LNOx spatial distribution and magnitude, contribute
to uncertainties in the RF from ozone. Additional simulations that
examine the methane RF for different LNOx sources are warranted.