Evidence that Nitric Acid Increases Relative Humidity in Low-Temperature Cirrus
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1 Supporting Online Material for: Evidence that Nitric Acid Increases Relative Humidity in Low-Temperature Cirrus Clouds R. S. Gao, P. J. Popp, D. W. Fahey, T. P. Marcy, R. L. Herman, E. M. Weinstock, D. G. Baumgardner, T. J. Garrett, K. H. Rosenlof, T. L. Thompson, P. T. Bui, B. A. Ridley, S. C. Wofsy, O. B. Toon, M. A. Tolbert, B. Kärcher, Th. Peter, P. K. Hudson, A. J. Weinheimer, A. J. Heymsfield Materials and methods WB-57F in situ payload instruments During the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment, the WB-57F high-altitude aircraft provided measurements inside natural cirrus and its own contrail using an extensive suite of in situ and remote-sensing instruments for particles, trace gases, and meteorological parameters. Of importance here are the measurements of water vapor, total water, temperature, pressure, gas-phase and condensed HNO 3 ; number, size, shape, and surface area of ice particles; nitric oxide (NO), and CO 2. On the WB-57F aircraft, water vapor and total water are measured with the techniques described below. Temperature and pressure are measured with aircraft probes (S1). Gas-phase and condensed HNO 3 are measured with an accuracy of about ±20% using chemical ionization mass spectrometry (S2) and inertial separation of particles from the ambient sample. The precisions of the gas-phase and condensed phase
2 HNO 3 measurements are approximately 30 and 3 pptv, respectively. The sizes and number of ice particles are measured using aerosol spectrometers (S3). Particle surface area is derived from the aerosol spectrometer data and is also measured directly by laser scattering (S4). A particle imaging system with automated habit classification software was used to assess particle shapes (S5). Nitric oxide is measured by chemiluminescence (S6) and CO 2 by infrared absorption (S7). The following website contains more detail on the WB-57 instruments used here [ Cloud parameters Most of the cirrus sampled by the aircraft was produced in convective outflow and anvil dissipation in the upper troposphere (S8). Measured cloud parameters beyond those displayed in Figs. 1 3 and S1 include number density, volume-weighted mean diameter, and condensed fraction of total water. Table 1 shows the mean and standard deviation of these parameters as measured in the ten WB-57F flights included in Fig. 1. Images of the natural cirrus ice crystals associated with the data in Table S1 and Fig. 1 revealed that the large majority of particles had irregular shapes. Irregular shaped particles include fragments from single particles or aggregates, aggregates themselves, rimed crystals, or droplets that have frozen and undergone some subsequent growth. RHi accuracy The accuracy of the RHi values depends on several factors: the accuracies of the water vapor, pressure, and temperature measurements, the relation of saturation vapor
3 pressure with temperature, and the interference of cloud ice. Based on a propagation of the independent errors associated with these factors, the estimated uncertainty in the RH i measurements reported here is ±11%. Water vapor, temperature, and pressure are each measured with two different instruments. The two water instruments are the Harvard water vapor (HWV) instrument (S9) and the Jet Propulsion Laboratory Laser Hygrometer (JLH) (S10). The HWV instrument photodissociates water vapor using nm (Lyman-α) radiation and detects the resulting OH fluorescence at 315 nm. The JLH instrument monitors water vapor concentration in an open path through laser light absorption near 1370 nm. Based on laboratory calibration, both instruments agree within ± 7% over a range of pressure ( hpa) and water mixing ratio ( ppmv) and agree in flight with each other within ± 5% throughout the aircraft dataset. Because of the open path of the JLH instrument, evaporation of ice particles cannot contribute to the water vapor signal. A comparison of the two water instruments in cloud shows that the evaporation of ice particles in the HWV instrument is negligible for this study. The total water instrument (HTW) (S11) uses an isokinetic inlet followed by a 600-watt heater directly in the flow to efficiently evaporate ice particles. The resulting total water vapor (ambient water vapor and evaporated ice) is detected as described above for the HWV instrument. Cloud ice water content is determined by the difference of the HTW and HWV measurements. Both temperature measurements use platinum resistor sensors but located outside the aircraft at different fuselage locations. The two temperature measurements agree with
4 each other and with balloon-borne temperature measurements within ± 0.5 K throughout the dataset. The uncertainty in the ambient pressure measurements of ± 0.3 hpa is negligible for the RH i calculations. The saturation water vapor pressure over ice as a function of temperature is from Wexler (S12) and has an accuracy of about 2% (S13). Contrail RHi observations Evidence of the rapid approach to an equilibrium RH i value in a contrail is shown in Fig. S1. The initial ambient RH i in contrail air is known, because the observed contrail was both produced and sampled by the WB-57F aircraft (S14). Fig. S1 shows that the average contrail RH i value of approximately 131% was approached systematically from lower and higher ambient RH i values. For lower ambient values, the addition of combustion water to the contrail air parcels increased RH i. For higher ambient values, ambient water vapor was reduced by contrail particle growth. The low variability of RH i values about the mean is strong evidence that equilibrium conditions are reached in a time period less than the contrail age. In addition, the low variability is an upper limit for the precision of the RH i measurements. HNO 3 condensed phases In general, a HNO 3 /H 2 O binary liquid solution or one of several solid hydrates is formed when HNO 3 co-condenses with water (S15). The stable condensed phases were identified with the Aerosol Inorganic Model (AIM), which uses minimization of the Gibbs free energy for the total moles present [see AIM Model I was used to calculate the
5 distribution of the species H +, NO 3 -, and H 2 O between the liquid, solid, and vapor phases for specified conditions of temperature and species total amounts (S16, S17). The AIM model shows that the supercooled HNO 3 -H 2 O binary solution, nitric acid trihydrate (NAT), and ice are the only thermodynamically stable condensed phases for the range of HNO 3 and H 2 O values associated with the data in Fig. 1. Both the supercooled HNO 3 - H 2 O binary solution and nitric acid trihydrate (NAT) have been shown to co-exist with ice in laboratory studies (S18-S22). Microphysical model studies have shown that NAT coatings can form on contrail particles in low temperature exhaust plumes (S23). The AIM model calculations used here do not include sulfuric acid composition. Sulfuric acid is likely present in many of the cloud and contrail particles sampled. Although sulfur is unlikely to make a significant difference in the interpretation of the role of HNO 3 in cloud particles, its potential role is not evaluated here. Ice particle equilibrium -ice particles existing in a metastable equilibrium state (mass balance) with water vapor would in general be characterized by a complex habit. This state would evolve to a new equilibrium as the -ice crystals undergo a metamorphosis to reach the minimum surface energy state just as snow flakes do after they reach the surface (S24). During metamorphosis, ice crystals lose their variety of facets and the associated microscopic inhomogeneities in growth and supersaturation. In the lowest energy state, ice crystals are simple hexagonal prisms (S25). The metamorphism stage in a typical cirrus cloud is likely never completed before the cloud state is changed or the cloud evaporates.
6 Adsorbed HNO 3 on -ice prevents RH i from reaching equilibrium values found in laboratory studies with homogeneous pure ice samples. Impurities at the low trace levels noted here for HNO 3 cannot alter RH i at equilibrium in the minimum surface energy state as a consequence of detailed balance and, hence, RH i must return to 100% in this state.
7 Contrail producing leg In contrail RH i = 131% RH i (%) NO (ppbv) Figure S1. RH i values as a function of nitric oxide (NO) for measurements on the contrail-producing (black diamonds) and contrail-sampling (red circles) legs on the flight of July 13, The persistent contrail was both produced and sampled by the WB-57F aircraft in the altitude range of 14 to 15 km (S14). There is an approximate one-to-one correspondence between data points (each a 1-s average) on the producing and sampling legs. The RH i changes because of ice formation and the addition of combustionproduced water. The background NO values are near a constant value of 700 pptv. NO values above 700 pptv measured on the contrail-sampling leg unambiguously indicate contrail air because NO is continuously emitted by the WB-57F aircraft engines. Measurements of engine-emitted CO 2 were also used to identify contrail air. The blue horizontal lines represent the average RH i value of 131% found inside the contrail. Ice particle formation by homogeneous nucleation is expected to limit RH i to values below 160%. The highest RH i values found on the contrail producing leg are approximately 180%, further suggesting that the RH i data might be overestimated by ~13%.
8 Table S1. Cloud properties measured by the WB-57F for the flights used in Fig. 1. Temperature Concentration Volume-weighted Surface area Ice / (total (K) * (# cm-3) mean diameter density water) (µm) (µm2 cm-3) * Note: Values are means found in 5K temperature bins. Temperatures indicate mean bin value.
9 References S1. S. G. Scott, T.P. Bui, K. R. Chan, S. W. Bowen, J. Atmos. Ocean. Tech., 7, 525 (1990). S2. J. A. Neuman et al., Rev. Scien. Instrum. 71, 3886 (2000). S3. D. Baumgardner, H. Jonsson, W. Dawson, D. O'Connor, R. Newton, Atmos. Res., 59, 251 (2002). S4. H. Gerber, Y. Takano, T. J. Garrett, P. V. Hobbs, J. Atmos. Sci., 57, 3021 (2000). S5. R. P. Lawson, A. J. Heymsfield, S. M. Aulenbach T. L. Jensen, Geophys. Res. Lett., 25, 1331 (1998). S6. Ridley, B. A. et al., J. Geophys. Res., 99, (1994). S7. K. A. Boering et al., Geophys. Res. Lett., 21, 2567 (1994). S8. A. J.Heymsfield, G. M. McFarquhar, in Cirrus, D. K. Lynch, K. Sassen, D. O. Starr, G. Stephens Eds, (Oxford Univ. Press, Oxford, UK, 2002), chap. 4. S9. E. M. Weinstock et al., Rev. Sci. Instrum., 65, 3544 (1994). S10. R. D. May, J. Geophys. Res., 103, (1998). S11. Weinstock, E. M., et al., in preparation (2003). S12. A. Wexler, J. Res. Nat. Bur. Stand.-A, 81A(1), 5 (1977). S13. J. Marti, K. Mauersberger, Geophys. Res. Lett., 20, 363 (1993). S14. R. S. Gao et al., J. Geophys. Res., in preparation (2003). S15. Molina, M. J. et al., Science, 261, 1418 (1993). S16. K. S. Carslaw, S. L. Clegg, P. Brimblecombe, J. Phys. Chem. 99, (1995). S17. M., S. Massucci, L. Clegg, P. Brimblecombe, J. Phys. Chem. 103A, 4209 (1999). S18. D. R. Hanson, A. R. Ravishankara, J. Geophys. Res., 96, 5081 (1991).
10 S19. A. M. Middlebrook, B. G. Koehler, L. S. McNeil, M. A. Tolbert, Geophys. Res. Lett., 19, 2417 (1992). S20. M. A. Zondlo, S. B. Barone, M. A. Tolbert, Geophys. Res. Lett., 24, 1391 (1997). S21. M. A. Zondlo, S. B. Barone, M. A. Tolbert, J. Phys. Chem., 102, 5735 (1998). S22. J. P. D. Abbatt, Geophys. Res. Lett., 24, 1479 (1997). S23. B. Kärcher, Geophys. Res. Lett., 23, 1933 (1996). S24. E. J. Langham, in Handbook of Snow: Principles, processes, management, and use, D. M. Gray, D. H. Male, Eds, (Pergamon Press Canada Ltd, Ontario, Canada, 1981). S25. H. R. Pruppacher, J. D. Klett, Microphysics of Clouds and Precipitation, (Reidel Publishing Co., Holland, 1978).
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