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Journal of Geophysical Research – Atmospheres
Supporting Information for
Airborne quantification of upper tropospheric NOx production from lightning in deep
convective storms over the United States Great Plains
I. B. Pollack1, C. R. Homeyer2, T. B. Ryerson3, K. C. Aikin3,4, J. Peischl3,4, E. C. Apel5, T.
Campos5, F. Flocke5, R. S. Hornbrook5, D. J. Knapp5, D. D. Montzka5, A. J. Weinheimer5, D.
Riemer6, G. Diskin8, G. Sachse7, T. Mikoviny8, A. Wisthaler9, E. Bruning10, D. MacGorman11,
K. A. Cummings12, K. E. Pickering13, H. Huntrieser14, M. Lichtenstern14, H. Schlager14, and M.
C. Barth5
1
Atmospheric Science Department, Colorado State University, Fort Collins, CO, USA, 2School of Meteorology,
University of Oklahoma, Norman, Oklahoma, USA, 3Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, Colorado, USA, 4Chemical Sciences Division, Earth System Research Laboratory,
National Oceanic and Atmospheric Administration, Boulder, Colorado, USA, 5Atmospheric Chemistry Division,
National Center for Atmospheric Research, Boulder, CO, USA, 6Rosenstiel School of Marine and Atmopsheric
Science, University of Miami, Miami, FL, USA, 7NASA Langley Research Center, Hampton, Virginia, USA, 8Oak
Ridge Associated Universities (ORAU), Oak Ridge, TN, USA, 9Institut fuer Ionenphysik und Angewandte Physik,
Innsbruck, AUSTRIA, 10Department of Geosciences, Texas Tech University, Lubbock, TX, USA, 11NOAA/OAR
National Severe Storms Laboratory, Norman, Oklahoma, USA, 12Department of Atmospheric and Oceanic Science,
University of Maryland, College Park, MD, USA, 13Atmospheric Chemistry and Dynamics Laboratory, NASA
Goddard Space Flight Center, Greenbelt, MD, USA, 14Institut für Physik der Atmosphäre, Deutsches Zentrum für
Luft- und Raumfahrt (DLR), Oberpfaffenhofen, Germany
29
Contents of this file
30
Text S1 to S5
31
Figures S1 to S8
32
Table S1
33
34
35
Introduction
This supporting information provides a detailed description of an indicator for when the
36
aircraft were sampling in cloud (S1), a comparison of NO, NO2, CO, and O3 measurements
37
acquired from three different instrumented aircraft during the Deep Convective Clouds and
1
38
Chemistry (DC3) Experiment (S2), exemplary vertical profiles that provide supporting evidence
39
that NOx enhancements due to lightning were measured in the outflow region of DC3 storms (S3,
40
an account of information used from atmospheric soundings (S4), a comparison of results from
41
the flux calculation with and without incorporating storm speed (S5), and details for calculating
42
the sensitivity of P(NOx) to NOx productivity per type of lightning flash (S6). Also included are
43
time series of chemical tracers measured in the outflow (similar to Figure 4 in the paper) and
44
time series of lightning flash counts (similar to Figure 9 in the paper) for each storm considered
45
in the analysis.
46
47
Text S1.
48
Only data points collected when the aircraft are sampling in cloud are retained for further
49
analysis. Here, we follow the work of Ridley et al. [1996] and use increases in ice concentration,
50
which correspond with increases in lightning-produced NO, as an in-situ indicator for in-cloud
51
sampling by the aircraft. Each aircraft was outfitted with one or more in-situ cloud probes
52
during DC3, providing several different data products that can be used to define this cloud
53
indicator. Liquid water content and ice particles ranging from 25 to 800 m encountered by the
54
G-V were measured using a 2D-C cloud probe (Particle Measuring Systems, Inc.); particles
55
ranging from 2 to 50 m (nominally) were also measured with a cloud droplet probe (Droplet
56
Measurement Technologies). Particles up to 47 m (nominally) encountered by the Falcon
57
aircraft were measured using a Forward Scattering Spectrometer Probe (FSSP, Particle
58
Measuring Systems, Inc.). Ice water content and particles ranging from 10 to 3000 m were
59
measured aboard the DC-8 using a 2D-S probe (SPEC Inc.) [Lawson et al., 2006]. However,
60
cloud data products are measured and processed differently among the three aircraft (e.g.,
2
61
particle concentrations are processed using the “entire-in” algorithm by Heymsfield and Parrish
62
[1978] for the G-V and according to Lawson et al. [2011] for the DC-8, while a water content
63
parameter from the G-V is calculated using a spherical assumption with the density of water and
64
ice water content from the DC-8 is computed from particle projected areas as described in Baker
65
and Lawson [2006]). Therefore, we use different parameters to define when each aircraft had
66
penetrated the edge of the cloud. For the G-V, we use particle concentration > 1 L-1 from the 2D-
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C probe, and for the Falcon we use particle concentration > 1 cm-3 from the FSSP. In the
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absence of 2D-S data for all storms sampled prior to 29 May, a cloud indicator for the DC-8
69
aircraft was synthesized from forward-facing video camera footage; for storms on and after 29
70
May, the DC-8 cloud indicator is defined using a combination of video footage and ice water
71
content > 5 x 10-3 g m-3 (K. Froyd, Personal Communication, 2015). We observe little difference
72
(<2%) in the number of data points retained for further analysis when particle concentration
73
versus ice water content is applied, and thus the choice of cloud parameter for the cloud indicator
74
has little impact on the results of this analysis. Differences in the magnitude of the particle
75
concentrations measured by the different aircraft in a single storm, as shown in figure 3 of the
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main paper, figure S6, and figure S7, reflect differences in the range of particle sizes that can be
77
detected by each probe and the degree to which each aircraft penetrated the anvil cloud.
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Text S2.
Intercomparison of airborne trace gas sensors aboard the NASA DC-8 and NSF/NCAR
81
G-V aircraft were performed on several occasions throughout the DC3 deployment (e.g., 25
82
May, 30 May, 01 June, 05 June, and 17 June). Intercomparisons were often conducted within
83
the first hour of flight for a period of 20-30 minutes. The aircraft typically flew in close
3
84
proximity at two altitude levels (e.g., 7 and 12 km), with a coordinated ascent in between,
85
resulting in sufficient variability in measured mixing ratios for correlation analysis. Scatter plots
86
comparing NO, NO2, CO, and O3 measurements from all five DC-8 and G-V intercomparisons
87
are illustrated in Figure S1. The slopes from linear least-squares (LLS) [Press et al.,, 1988]
88
orthogonal distance regression (ODR) [Boggs et al., 1987] of these scatter plots provide a
89
measure of the average percent difference between measurements from the two aircraft, and
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result in differences of 2% for NO, 28% for NO2, 5% for CO, and < 1% for O3. Except for NO2,
91
all are within the combined uncertainties determined from addition of the individual
92
measurement uncertainties in quadrature. Differences in NO2 may be attributed to corrections
93
for thermal dissociation of methyl peroxy nitrate [Nault et al., 2015], which have been applied to
94
measurements acquired via laser-induced fluorescence aboard the DC-8.
95
Two intercomparisons between the DC-8 and DLR Falcon aircraft were conducted on 11
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June, with the coordinated portions of the flight performed at 2.1 km and 6.7 km. Scatter plots
97
for CO and O3 are shown in Figure S2. NO and NOx resulted in too little variability for accurate
98
correlation analysis, and are thus shown as a time series in Figure S3. While the average O3 and
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CO mixing ratios from the DC-8 and Falcon aircraft differ by < 3%, measurements of NO and
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NOx show less agreement. Larger mixing ratios of NO and NOx by an average of 0.1 and 0.2
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ppbv were measured by the Falcon aircraft; however, these difference are within the
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uncertainties and limits of detection reported for these measurements from the Falcon aircraft
103
during the intercomparison flight (e.g., ± 50 pptv uncertainty, and detection limits of 50 pptv for
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NO and 100 pptv for NOx). Although detection limits for NO and NOx are 20 pptv and 30 pptv,
105
respectively, for all other Falcon flights, detection limits were elevated during the
4
106
intercomparison flight due to excessively high temperatures in the aircraft cabin that caused an
107
unstable zero level in the instrument.
108
Here, we utilize the reported data from all three aircraft as it was archived in the final
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DC3 data set for this analysis, and assume a total uncertainty of 30% for NOx measured in storms
110
sampled by the G-V and DC-8 (e.g., storms on 18 May, 19 May, 25 May, 29 May 16 June, and
111
22 June), and an overall uncertainty of 55% for NOx measured in storms sampled by the Falcon
112
(e.g., storms on 30 May and 12 June).
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114
Text S3.
115
Vertical profiles of trace gases measured by the G-V and DC-8 aircraft in the latitude and
116
longitude region of each storm (e.g., the 19 May storm shown in Figure S4) illustrate evidence of
117
enhancements in NOx up to ~4 ppbv between 9 and 13 km m.s.l. due to lightning. These
118
observations are consistent with peak LNOx enhancements ranging between 1 and 19 ppbv
119
reported in previous studies of storms over the U.S. Great Plains [Dye et al., 2000; Luke et al.,
120
1992; Ridley et al., 1994; Ridley et al., 1996; Stith et al., 1999]. Large ratios of NOx/NOy and
121
NO/NO2 at high altitudes demonstrate recent production of NO by lightning, while large NOy/O3
122
ratios indicate fresh sources of NO or NOx and photochemically unprocessed air [Ridley et al.,
123
1996]. Thus, the observed NOx enhancements in the anvil are best explained by recent
124
production of NO by lightning. O3 enhancements within the cloud largely reflect
125
photochemically processed air and/or mixing with stratospheric air, as shown above for the 19
126
May storm.
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128
The vertical profiles in Figure S4 also demonstrate vertical transport of chemical tracers
from the planetary boundary layer into the upper troposphere by convection. Long-lived, low
5
129
solubility chemical tracers such as CO and CH4, and slightly more soluble tracers like acetone
130
and propanal, which do not have a stratospheric source, act as good indicators for convective
131
transport of anthropogenic species from the planetary boundary layer. Average enhancements in
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CO, CH4, and (acetone+propanal) measured in the anvil outflow of each storm between 9 and 13
133
km m.s.l. are roughly half of the average enhancements above the free tropospheric background
134
measured in the planetary boundary layer. Therefore, measured NOx enhancements would be
135
much smaller than the mixing ratios observed in the outflow if NOx had been solely transported
136
upward from the boundary layer by convection.
137
138
Text S4.
139
In-situ atmospheric soundings, obtained from radiosondes launched in the vicinity of
140
these storms (e.g., by the NCAR Mobile Integrated Sounding System in the Colorado region and
141
by NOAA’s National Severe Storms Laboratory in the Oklahoma region), provided vertical
142
profiles of temperature, pressure, relative humidity, and winds. Convective available potential
143
energy (CAPE), in units of m2 s-2, is determined for each storm using these parameters, and is
144
employed here as an indicator of the severity of convective activity and the potential strength of
145
each storm [Djuric, 1994; Bluestein, 1993]. The time, location, and CAPE determined from
146
soundings performed during each storm are summarized in Table 1. CAPE for two storms (e.g.,
147
one on 18 May and another on 12 June) occurring outside the realm of the in-field sounding
148
network are acquired from the National Weather Service radiosonde network (digested data
149
accessed from http://weather.uwyo.edu/upperair/sounding.html) from 00:00 UTC soundings
150
launched from Amarillo, TX (AMA site) and North Platte, NE (LBF site). A potential maximum
151
updraft velocity for each storm is calculated as
152
1993].
[Price and Rind, 1992; Bluestein,
6
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154
Text S5.
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Table S1 compares results for Pflux(NOx) with and without accounting for storm speed, s,
156
in equation (E5). As expected, the percent difference between Pflux(NOx) calculated with a only
157
and Pflux(NOx) calculated with (a -s) scales directly withs. However, since the difference
158
between wind speed and storm motion is directly related to the wind shear, one might question
159
whether the results in Figure 8 of the main paper are due to neglect of storm motion in the flux
160
calculation. Figure S5 shows a scatter plot of the percent difference in Pvol(NOx) and Pflux(NOx)
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for all storms except 29 May calculated with (a -s) versus the 0-6 km wind shear reported in
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Table 1 of the main paper. Linear regression of the data points in Figure S5 results in a negative
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slope similar to that in Figure 8 of the main paper, and suggests that 15% of the variance in the
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difference between the two methods (r2 = 0.15) can still be attributed to wind shear.
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Text S6.
The sensitivity of P(NOx) to NOx productivity per type of lightning flash is demonstrated
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by comparing the effects of assuming IC flashes and CG flashes produce equal amounts of NOx
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with the possibility that IC flashes could produce ten times less NOx than CG flashes. The
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percent differences in P(NOx) for each geographical region is calculated according to equation
171
(ES1), and are based on fIC/fCG ratios of 4.9 for Colorado, 4.1 for northern Texas, and 3.9 for
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Oklahoma [Boccippio et al., 2001].
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(ES1)
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7
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References
176
Baker, B. A., and R. P. Lawson (2006), Improvement in determination of ice water content from
177
two-dimensional particle imagery: Part I: Image to mass relationships, J. of Appl. Meteor.
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Boccippio, D. J., et al. (2001), Regional differences in tropical lightning distributions, J. Appl.
Meteorol., 39(12), 2231-2248, doi:10.1175/1520-0450(2001)040<2231:Rditld>2.0.Co;2.
Boggs, P. T., et al. (1987), A stable and efficient algorithm for nonlinear orthogonal distance
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Dye, J. E., et al. (2000), An overview of the Stratospheric-Tropospheric Experiment: Radiation,
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Aerosols, and Ozone (STERAO)-Deep Convection experiment with results for the July
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10, 1996 storm, J. Geophys. Res-Atmos., 105(D8), 10023-10045,
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Heymsfield, A. J., Parrish, J. L. (1978), A Computational Technique for Increasing the Effective
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Lawson, R. P. et al. (2006), The 2D-S (stereo) probe: Design and preliminary tests of a new
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airborne, high speed, high resolution particle imaging probe, J. Atmos. Oceanic Technol.,
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Lawson, R. P. (2011), Effects of ice particles shattering on the 2D-S probe, Atmos. Meas. Tech.,
4, 1361-1381, doi:10.5194/amt-4-1361-2011.
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States, 2, Trace gas profiles and distributions, J. Geophys. Res., 97, 20647-20670.
8
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Nault, B. A., et al. (2015), Measurements of CH3O2NO2 in the upper troposphere, Atmos. Meas.
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Press, W. H., et al. (1988), Numerical recipes in C, Cambridge University Press, Cambridge.
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Ridley, B. A., et al. (1994), Distributions of NO, NOx, NOy, and O-3 to 12-Km altitude during
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9
Figure S1. Scatter plots of NO, NO2, CO, and O3 measurements from the DC-8 and G-V
aircraft. Data points represent measurements from all five intercomparisons between
these two aircraft; results of LLS correlation analysis (solid black lines) are reported in
the text boxes.
10
Figure S2. Same as Figure S1 for intercomparison of measurements from the DC-8 and
Falcon aircraft.
11
Figure S3. Time series of CO, O3, NO, and NOx, measurements from a 20-minute
intercomparison at 2.1 km (a) and a 12-minute intercomparison at 6.7 km (b) between the
DC-8 and Falcon aircraft on 11 June.
12
Figure S4. Vertical profiles of NOx (black for DC-8, gray for G-V), CO (red for DC-8,
pink for G-V), O3 (blue for DC-8, cyan for G-V), select hydrocarbons (green/purple), and
ratios of NOx/NOy (black), NOy/O3 (blue), and NO/NO2 (red for DC-8 and pink for G-V)
sampled by the aircraft in the spatial region of the 19 May storm. Shaded areas represent
the vertical extent of the anvil.
13
% difference in P(NOx) (volume-flux)
100
80
60
40
20
0
0
10
20
30
-1
Shear (m s )
Figure S5. Same as Figure 8 in the main paper except the percent difference in P(NOx) is
calculated using Pflux(NOx) (a - s) from Table S1.
14
Figure S6. Same as Figure 3 in the paper for the remaining storms in the Oklahoma
region.
15
Figure S7. Same as Figure 3 in the paper, but for storms in the Colorado region.
16
Figure S8. Same as Figure 6 in the paper, but for storms in the Colorado region.
17
Table S1. Results of the flux calculations, in units of moles flash-1, with and without
subtracting the storm velocity, vs, from the measured wind speed, va. The reported
percent difference refers to the difference in Pflux(NOx), va - vs and Pflux(NOx), va and scales
directly with vs.
Date
vs (m s-1) Pflux(NOx), va - vs Pflux(NOx), va % diff
19 May
8
265 ± 79
407 ± 131
35
25 May
17
45 ± 10
84 ± 19
46
29 May
10
110 ± 15
141 ± 19
22
16 June
2
192 ± 33
205 ± 36
6
18 May
11
50 ± 9
73 ± 12
32
22 June
15
67 ± 7
131 ± 15
49
18