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Liquid Particle Composition and Heterogeneous Reactions in aMountain Wave Polar Stratospheric Cloud

D. Lowe1, A. R. MacKenzie1, H. Schlager2, C. Voigt2, A. Dornbrack2, and M. J. Mahoney3

1Environmental Science Dept., Lancaster University, Lancaster, UK2Institutefor Atmospheric Physics, DLR, Oberpfaffenhofen, Germany3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA

Abstract. On the 8th February 2003, as part of theVINTERSOL-EuPLEx campaign,in-situ measurements ofthe chemical properties of the gas and condensed phaseswere made within mountain waves above the ScandinavianMountains using instruments onboard the M55-Geophysicaaircraft. We study these observations using dynamic-microphysical and equilibrium-aerosol-composition box-models run along quasi-lagrangian trajectories constructedfrom aircraft data and mesoscale back trajectories. Thecondensed-phaseNOy content predicted by our micro-physical model replicates the observations well, indicat-ing that the particles are principally supercooled ternary(H2O/HNO3/H2SO4) solution particles that are out of equi-librium with the surrounding gas phase. The dynamic andequilibrium models respectively produce 85 and 99 pptv ofCl2, the difference is due to the over-prediction of mass in thecondensed-phase by the equilibrium model. TheseCl2 lev-els are reasonable compared with the measured mixing ratiosof ClOx, however direct comparisons are not possible due tothe high solar zenith angles at this time. This work showsthat there is a significant difference in the predicted particledistributions, particle compositions, and chlorine activationbetween our microphysical model and the equilibrium calcu-lations commonly used in large-scale chemistry-transport orchemistry-climate models.

1 Introduction

Polar stratospheric clouds (PSCs) have long been recognisedto play an important role in the destruction of stratosphericozone via chlorine activation, dehydration and denitrifica-tion (for a detailed review and discussion see, for example,WMO, 2003, and references within). PSCs are, however,

Correspondence to: A. R. MacKenzie([email protected])

composed of a range of different particles, both solid andliquid, the combination of which governs their environmen-tal influence. Below the frost point solid type II particles canexist, composed of water ice. Up to several degrees abovethe frost pointHNO3-rich type I particles can form. Thesecan consist of solid nitric acid trihydrate (NAT) (Hanson andMauersberger, 1988) as observed by balloon-borne in-situmass spectrometry (Voigt et al., 2000a) — or possibly di-hydrate (NAD) (Worsnop et al., 1993). Additionally, super-cooled ternary solution (STS) droplets (Molina et al., 1993;Zhang et al., 1993) form 3–4 K above the ice frostpoint.

The heterogeneous chemical processes involved in chlo-rine activation have been extensively studied in laboratorywork (see, for example, Sander et al., 2003, and refer-ences within. A notable omission in these studies is notedin Section 4.1, however.). Whilst the majority of the chemi-cal constituents involved in these processes have been mea-sured on a range of scales, fromin-situ to global, mod-elling studies of chlorine activation have tended to focus onglobal/mesoscale effects, originally incorporating the hetero-geneous processes as empirical effects, which are comparedwith large-scale rather thanin-situ observations (e.g. Kuhlet al., 2004). Recent work has incorporated microphysicalPSC schemes into mesoscale chemical models (Drdla andSchoeberl, 2003; Mann et al., 2003). Microphysical modelshave previously been used to model chlorine activation, ini-tially considering just background aerosols and NAT PSCs(Jones et al., 1990; Lutman et al., 1994), but later consider-ing more complicated populations of particles (Drdla, 1996;Sessler et al., 1996; Carslaw et al., 1998). However thesemodels have never been compared with measurements ofchlorine within PSCs, mainly because most measurementsof PSCs have been remote rather thanin-situ.

Until recently the chemical compositions of PSC particleshave had to be inferred from gas-phase compositions and thepolarisation of lidar signals; however this has been changedby the development of balloon-borne mass spectrometers

© European Geosciences Union 2004

2 Lowe et al.: Mountain wave PSCs

(Schreiner et al., 1999), and aeroplane-borne chemilumines-cence instruments (Northway et al., 2002), designed to mea-sure theNOy content of the particle phase.

These balloon-borne in-situ measurements positively iden-tified NAT (Voigt et al., 2000a) and STS (Voigt et al., 2000b)in mountain wave PSCs. More recently such measurementshave also been used to confirm the presence on HCl in STSparticles (Weisser et al., 2004). Because the balloons carry-ing these instruments follow quasi-lagrangian flight-paths themeasurements are highly suited to the creation of lagrangiantrajectories for 0-D models (Voigt et al., 2003). In addi-tion, in-situmeasurements of theNOy content of the particleand gas phases allowed the identification of very low num-ber densities of relatively large (5 µm radius) NAT particles(so-called “NAT-rocks”) during the SOLVE/THESEO 2000campaign (Fahey et al., 2001).

The microphysical studies mentioned above concentratedpurely on particle compositions, with no consideration of theheterogeneous reactions occurring on these particles. Thosestudies of these reactions which use a microphysical box-model (e.g. Carslaw et al., 1998) have not been able to makecomparisons of the model output within-situ measurementsof the changes in the mixing ratios of chlorine compoundspassing through the PSC event. One of the aims of theEuPLEx-VINTERSOL campaign is to study halogen activa-tion within PSCs. To this end the M-55 Geophysica aircraftwas fitted with instruments to makein-situ measurements ofparticle composition and a number of chlorine species. Carewas taken to fly the Geophysica parallel to the wind-directionclose to, or within, PSCs in order to allow quasi-lagrangianstudies of the evolution of these PSC properties to be made.Below we will examine one such flight from EuPLEx, com-paring the particle compositions with those calculated by ourmicrophysical model (Lowe et al., 2003), and with an equi-librium composition STS model such as commonly used inchemistry-transport models (e.g. Sessler et al., 1996). Weshall examine the differences inCl2 production between thetwo models, and qualitatively compare their output to themeasured mixing ratios ofClOx.

2 Meteorological Forecast and Flight Plan

The meteorological conditions above northern Scandinaviaon 8th February 2003 were favourable for the excita-tion and vertical propagation of mountain waves. Thesewaves formed mesoscale stratospheric temperature anoma-lies which extended from directly above to around 200 kmdownstream of the mountain range (Fig. 1). The hindcastsimulation from the MM5 mesoscale model indicates thepresence of two nearly parallel regions of low temperatureswith a peak-to-peak amplitude of about 12 K, whereas thecooling with respect to the upstream conditions amounts toabout 6 K.

Fig. 1. Hindcast of air temperature at 50 mbar for 1800 UTC,8/2/2003 from the MM5 mesoscale model. The red line indicatesthe flight path of the Geophysica.

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Fig. 2. Flight plan of the Geophysica aircraft on 8th February 2003.The green and blue sections roughly indicate where the aircraftpassed through PSCs.

Tropospheric excitation conditions varied on 8th Febru-ary 2003, so that the stratospheric mountain wave event onlylasted for about 6 hours. Therefore, and in contrast to for-mer documented events (Dornbrack et al., 1999, 2002), thecooling within the waves was limited to 6 K.

Based on the MM5 forecasts (Dornbrack et al., 1998) aflight plan was drawn up for the Geophysica to include sev-eral passes through these mountain waves parallel to the winddirection; on the day the flight path was fine-tuned using li-dar observations from the Falcon aircraft. The Geophysicapassed through a number of PSCs, the positions of which areindicated in Fig. 2.

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Lowe et al.: Mountain wave PSCs 3

3 Measurements

The Geophysica aircraft carries a wide-range of instruments,from lidar through to whole-air samplers (Stefanutti et al.,2004); in this study, however, we shall primarily use datafrom the SIOUX instrument — a chemiluminescence de-tector similar to that used by Northway et al. (2002) onthe ER-2 aircraft. We will also use temperature data fromthe JPL MTP (Microwave Temperature Profiler) instrument(Denning et al., 1989); totalH2O mixing ratios from theFISH (Fast In-Situ Hygrometer (Zoger et al., 1999);N2Omixing ratios from the HAGAR instrument (Stefanutti et al.,2004); and ClO, ClOOCl andClONO2 mixing ratios fromthe HALOX (HALogen OXide monitor) instrument (Bruneet al., 1989; von Hobe et al., 2004). Although the Geophysicacarried a FSSP aerosol spectrometer to measure the aerosolsize distribution (), it was not operational during the part ofthe flight discussed below.

The SIOUX instrument (Schmitt, 2004; Voigt et al., 2004)located in the right wing pod of the aircraft M55 Geophys-ica has two inlets, which are especially designed for PSCmeasurements. Particle- and gas-phaseNOy (totalNOy) aredetected using a forward facing inlet. The measured particlenumber density is enhanced due to anisokinetic sampling ofthe particles, the enhancement factor is dependent on pres-sure and particle size. The rear facing inlet primarily mea-sures the gas phase; particles with diameters>0.2 µm areexcluded due to inertia. Inside the inlets the particles evapo-rate,NOy is catalytically reduced to NO, and the subsequentreaction of NO with ozone is measured with a chemiluminis-cence detector. Nitric acid content of the particles is derivedby subtracting the gas phaseNOy from the totalNOy andcorrecting for the particle enhancement. In this work, weuse an oversampling factor of 3.6 for particles smaller than0.3 µm at pressures near 50 mbar, derived from inlet simula-tions (Kramer and Afchine, 2004). The oversampling factorincreases for larger particles and decreases for lower pres-sures.

Measurements taken by the SIOUX instrument during thisflight are shown in Fig. 3. The discrepancies between the to-tal (red line) and gas-phase (black line)NOy occur when par-ticles are present. We shall concentrate on the second, North-ern, PSC event: denoted by the green lines in Figs. 2 and 3.The section of the flight that passes through this PSC was inthe direction of, and practically parallel to, the local wind;this allows us to use the flight to construct a quasi-lagrangiantrajectory. We have examined the earlier PSC event (the po-sition of which is shown by the blue line in Fig. 2), but thedata does not lend itself readily to the creation of a case studyand so will not be reported here.

To create trajectories for our model we shall use tempera-ture and pressure measurements made during the flight. In-situ measurements of these were made by the Geophysica’snavigational data system (UCSE) and the MTP instrument.Additionally the variations in temperature within 5 km of

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Fig. 3. Measured total (gas-phase plus 3.6×particle-phase; red line)and gas-phase (black line)NOy measured by the SIOUX instru-ment around the second PSC event on the flight on 8th February2003. The green lines denote the edges of the region of PSCsmarked by the green line in Figure 2.

Fig. 4. Comparison of the pressure altitude of the Geophysica-M55during the flight on the 8th February 2003 (black diamonds) withthe pressure altitudes of isentropic surfaces (coloured solid lines) at5 K intervals.

the flight path altitude can be reliably obtained using theMTP measurements — the estimated errors in temperaturerelative to radiosondes are±0.5 K at flight level, less than±1.0 K within 2.2 km of flight level, and less than±2.0 Kwithin 6 km of flight level. Using this data we compare thechanges in the aircraft pressure altitude with those of theisentropic surfaces within the mountain wave (Fig. 4). Beforethe mountain wave the aircraft flies just above the 455 K isen-

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trope, following its profile well. Within the mountain wave(t ≈18.27–18.5 hr), however, the aircraft drops about 10 K inpotential temperature, before returning to roughly follow the455 K isentrope again. These changes in potential tempera-ture mean that the aircraft trajectory is not ideal for study-ing the evolution of the PSC particles; in the work below wewill investigate this influence on our attempts to replicate theNOy observations.

Comparisons of the UCSE data with measurements fromthe MTP show that, on average over the whole campaign,TUCSE = TMTP − 1.14 K. For the 8th February flight thisdifference becomesTUCSE = TMTP − 1.63 K. The MTPdata are calibrated using measurements from radiosondeslaunched close to the flight path of the Geophysica and soare likely to be the most reliable temperature measurements;however the higher temporal resolution of the UCSE data isuseful for our work, and so we will use this for our trajec-tories, although with corrections to bring the temperature inline with the MTP measurements.

4 Model Details

We will use two box models to calculate the evolution of,and heterogeneous reactions on, the aerosol along a trajec-tory passing through the mountain wave. The first uses theparameterisation of Carslaw et al. (1995) to calculate thecomposition of STS in equilibrium with the gas-phase, fromwhich we calculate the aerosol surface area for a prescribedparticle number density. The second, MADVEC, describesthe dynamics of condensational growth of liquid PSC parti-cles, using the advection of mass components in radius-space(Pilinis, 1990) driven by differences between ambient par-tial pressures and the equilibrium vapour pressures parame-terised by Luo et al. (1995). This scheme allows us to treatparticle growth as the advection of mass in size-space usingfluid dynamical methods (see Lowe et al., 2003, for moredetails).

4.1 Heterogeneous Chemical Reactions

To the box models we have added parameterisations of het-erogeneous reactions for the release ofCl2 andHOCl:

ClONO2 + H2O(l)→ HOCl + HNO3(aq), (1)

ClONO2 + HCl(aq)→ Cl2 + HNO3(aq), (2)

HOCl + HCl(aq)→ Cl2 + H2O(l). (3)

No gas-phase homogeneous reactions have yet been incorpo-rated into the box models; so we do not currently model thephotolytic conversion ofCl2 into ClO, or the re-combinationof ClO andNO2 to form ClONO2. The first of these pro-cesses would not be relevant for these test-cases, due to thehigh solar zenith angles. The second process could slightlyincrease the yield ofClOx and HOCl from Reactions 1 &

2 since HCl is initialised in excess ofClONO2 (see Section5.2); therefore the yields reported below are lower limits.

There are no parameterisations for the rates of Reactions1–3 on STS; instead we will use the parameterisations for bi-nary sulphate solutions calculated by Shi et al. (2001). Theirparameterisations are based on the water activity of the bi-nary solution — which is dependent on the atmospheric con-ditions rather than the composition of the solution. To usetheir solution we simply insert the water activity of the STSdroplets.

This method may, however, lead to an over estimation ofthe production rates ofCl2 andHOCl during our test-cases.Hanson (1998) has compared measured uptake coefficientsfor Reactions 1–3 on ternaryHNO3/H2SO4 solutions withthe calculated coefficients for binary sulphate solutions of thesame water activity. He found that the uptake coefficients forternary solutions were typically 30–50% less than would beexpected for binary solutions with the same water activity.In addition we should note that the uptake coefficients givenby the parameterisation of Shi et al. (2001) are, generally,greater than those used by Hanson (1998), which will in-crease any over-prediction in production rates (see Shi et al.,2001, Figure 6, for comparison).

In both box-models we will treatClONO2, HOCl andHCl as purely gas-phase species; principally because the cal-culations of Shi et al. (2001) use the gas-phase concentrationof HCl, and include terms to account for the depletion ofHCl in the condensed-phase. However, because of the rela-tively small saturation ratios ofHCl, this assumption of equi-librium is not unreasonable. Any gains or losses ofH2O orHNO3 are applied to the condensed phase, however these arenot large enough to make any significant difference to parti-cle compositions.

5 Test Case Settings

5.1 Trajectories

Synoptic-scale back trajectories (based on ECMWF-analysis; http://badc.nerc.ac.uk/data/ecmwf-trj/) from thestart of the second PSC event show that the temperature ofthe air-parcel was above 200 K for a period of at least 10–120 hours before the mountain wave event (Fig. 5a). As suchwe can assume that any PSC particles observed within themountain wave event are less than 10–15 hours old.

We have used two methods to generate trajectories for ourmodels. In the first we have combined a 6 hour MM5 back-trajectory (Wernli and Davis, 1997) with adapted tempera-ture and pressure measurements from the Geophysica aircraft(Fig. 5b). To account for the differences between the aircraftand wind speeds we have multiplied the timescale of the air-craft data by the ratio of the aircraft speed to wind speedat each data point. This increases the time taken by a fac-tor of 7–8. To account for differences between UCSE and



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Fig. 5. (a) Temperature profile of the synoptic-scale (black line)back trajectory; the quasi-lagrangian trajectory used for the modelruns is included for comparison (red line). (b) The quasi-lagrangiantrajectory (combined red and green line) compared with the MTPtemperature profile along the flight path (black line). The first (red)section of the trajectory is generated from a hindcast made using theMM5 model. The second (green) section is generated from the Geo-physica flight data, the temperature isTUCSE + 1.5 K. Maximumcooling rates during the compositeTUCSE + 1.5 K are 0.04Ks−1

over 5 secs and 0.004Ks−1 over 900 secs.

MTP (see Section 3), we add 1.5 K toTUCSE. This producesa good fit to the magnitude of the MTP data (compare thegreen (TUCSE + 1.5 K) and black (MTP) lines in Fig. 5b),allowing us to retain the higher temporal resolution of theUCSE data.

However, as discussed above (see Section 3), the trajectoryfollowed by the aircraft within the gravity wave was not isen-tropic. To study what influence this will have on modellingthe observations we will also use four isentropic trajectories— along the 445 K, 450 K, 455 K and 460 K surfaces (seeFig. 4) — derived from the MTP data.

5.2 Model Initialisation

We initialise our microphysical aerosol model with 4.5 ppmvH2O, 9.0 ppbvHNO3, 0.5 ppbvH2SO4, and a log-normalparticle distribution with mode radius 0.063 µm, width 1.8,

and number density of 10cm−3. TheH2O andHNO3 mix-ing ratios are approximations taken, respectively, from FISHand SIOUX data immediately before the second PSC event.The H2SO4 mixing ratio and particle number density arebased on standard values for this part of the stratosphere.

To initialise the chlorine compounds within our model wewill use the scheme of Schauffler et al. (2003), which is basedon data collected during the SOLVE campaign in January–March 2000. Using this scheme we calculate the total in-organic chlorine based on theN2O content of the air parcel(determined by HAGAR to be approximately 135 ppb withinthe second PSC event), then remove the measured amountsof ClOx andClONO2 (from HALOX) to obtain an amountof HCl. Hence we calculate a total inorganic chlorine mix-ing ratio of 2800 ppt, 300 pptClOx, 500 pptClONO2 and2000 pptHCl. The ClOx data are uncertain by 30%. Al-though the results are sensitive to these uncertainties, the rel-ative magnitudes of the results are less so, and thus neitherare our conclusions.

6 Results

6.1 Particle Composition

In Figure 6 the particle-phaseNOy content of our micro-physical model (green, cyan, purple and yellow lines, asidentified in the legend) is compared with that measured bythe SIOUX instrument (black line). We see that the modelruns along the 450 K, 455 K and 460 K isentropes producequite low particle-phaseNOy contents, whereas that pro-duced by the 445 K model run is much higher — with a max-imum of 0.4 ppbvNOy in the particle-phase, compared with>0.5 ppbv from the SIOUX data and≤0.2 ppbv for the othermodel runs. The greater differences between the output fromthe 445 K and 450 K model runs, as opposed to, for example,the 450 K and 455 K runs, occur because these two trajec-tories straddle the narrow range of temperatures over whichthe liquid aerosol particles change composition from binarysulphate to ternary solutions.

Although the 445 K model run is the best at replicatingthe magnitude of the SIOUX measurements, it does not fullycapture some of the rapid changes inNOy content mea-sured by the SIOUX instrument. As discussed above, thesechanges occur as the aircraft crosses isentropic levels, sosampling air-parcels with different temperature histories. Tosimulate this we have calculated the expected particle-phaseNOy content along theTUCSE + 1.5 K trajectory by inter-polating between the neighbouring two isentropic trajecto-ries based on the calculated potential temperature for theTUCSE + 1.5 K trajectory (where the trajectory passes out-side of this range of potential temperatures, e.g. at timet ≈ 0.9 hr, we simply use the value for the nearest isentropictrajectory). The result is shown by the red line in Figure 6a,and it retains the maximumNOy content of 0.4 ppbv of the



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Fig. 6. (a)NOy content of the condensed phase for our non-equilibrium model along the isentropes measured by the MTP instrument (green,cyan, purple and yellow lines, as identified in the legend), combinedNOy content along the aircraft trajectory from the isentrope data (redline), and measured by the SIOUX instrument (black line). (b) The temperature profiles along the isentropic trajectories (green, blue, cyanand purple lines as identified in the legend in Fig. 6a), as well as theTUCSE + 1.5 K temperature profile. Note that, because of the methodwe use to expand the timescale, the relationship between model time and the equivalent UT is not linear.

445 K model run, although for the majority of the mountainwave event theNOy content is closer to the 450 K model run.

In Figure 7 we compare the resulting particle-phaseNOy

content from the combination of the isentropic trajectorieswith that resulting from simply running our microphysicalmodel along theTUCSE + 1.5 K trajectory. TheNOy con-tent of TUCSE + 1.5 K model run (blue line) is of a sim-ilar magnitude to that calculated from the isentropic mod-els (red line), although its maximumNOy content is slightlyless. However both of these models are better than the equi-librium calculations (grey line) at capturing the magnitudeof the SIOUX measurements. The equilibrium calculationsgreatly over-predict the particle-phaseNOy content beforetime t ≈ 1.0 hr, reaching a maximum of 1.5 ppbv at timet ≈ 0.9 hr. After timet ≈ 1.0 hr the equilibrium calculationscapture the magnitudes of the SIOUX measurements well.

The results from the combined isentropic andTUCSE + 1.5 K microphysical model runs are, withinour limitations, reasonable simulations of the SIOUX mea-surements. The mountain waves seen on the 8th February2003 were not stable, so trajectories based on the aircraft

data will not be perfect simulations of the actual isentropictrajectories. Additionally we have used mixing ratios basedon averaged measurements within the mountain wave, whichis again a simplification of reality.

6.2 Heterogeneous Chemical Reactions

Using the microphysical model run, and the equilibrium cal-culations, along theTUCSE + 1.5 K trajectory we shall nowexamine the rates of the heterogeneous reactions during themodel runs. These reactions depend on the particle surfacearea available, and so we shall begin by examining the rela-tionship between the particle-phaseNOy contents shown inFigure 7 and the aerosol surface areas generated by the twodifferent methods.

The relationship between particle-phaseNOy content andsurface area is partly dependent on the particle composi-tion. During theTUCSE + 1.5 K model run our microphysi-cal model shows a size-dependence of the changes in particlecomposition (Fig. 8a), which are not seen in the equilibriumcalculations (Fig. 8b). We see that the composition of our



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Fig. 7. NOy content of the condensed phase for our microphysical model (blue line) and equilibrium calculations (grey line) along theTUCSE + 1.5 K trajectory, compared with those measured by the SIOUX instrument (black line) and calculated along theTUCSE + 1.5 Ktrajectory using the data from the isentropic trajectories shown in Figure 6 (red line).

microphysical model changes more slowly than that of theequilibrium code, as would be expected. In addition we notethat theHNO3 mass fractions in the equilibrium model reach36–38%, while those of the microphysical model reach, atmost, 22–24% — these compositional differences betweenthe models are due mainly to the resistance toHNO3 dif-fusion through the gas phase to the particle surfaces. As aresult the large differences in theNOy content of the con-densed phase seen in Fig. 7 are not as pronounced whenlooking at the differences in the total mass of the condensedphase between the two different methods. This can be seenin Fig. 9b, where we compare the total aerosol volumes fromthe equilibrium (red line) and dynamic (blue line) models.The differences between the two models are less than thatseen in theNOy data in Figure 7. The difference is even lesspronounced for the aerosol surface areas (Fig. 9a) because,unlike aerosol volume, particle surface areas are not linearlyrelated to aerosol mass.

The production ofCl2 and HOCl during the model run areshown in Fig. 10. The equilibrium code produces about 15%moreCl2 than the microphysical model (99 pptv, comparedwith 85 pptv). This difference is principally due to the greateraerosol surface area seen in the equilibrium model (Fig. 9a).The HALOX instrument measuredClOx (ClO + 2Cl2O2)concentrations of around 300 pptv during this section of theflight; however, at this time, the solar zenith angle was about110◦. At such large zenith angles it is not straightforward toattempt to relate the measuredClOx with the predictions ofCl2 production from the model.

7 Conclusions

On the 8th February 2003, during the EuPLEx campaign,in-situ measurements of condensed-phaseNOy were madewithin mountain wave PSCs. Using dynamic microphysical,and equilibrium composition, models running along quasi-lagrangian trajectories — generated using flight data fromthe Geophysica, MM5 back-trajectories and MTP data — wehave investigated the second, Northern, PSC event. We foundthat the particle-phaseNOy measurements could be best rep-resented by interpolating theNOy content calculated by ourmicrophysical model along the isentropic trajectories createdusing the MTP data. However theNOy content predicted byour microphysical model using theTUCSE + 1.5 K trajectoryis comparable to that calculated using the MTP trajectories.Equilibrium calculations along theTUCSE + 1.5 K trajectoryoverpredict the particle-phaseNOy content in the first sec-tion of the mountain wave by up to a factor of 3, althoughthey are better at capturing the shape of the later measure-ments. These simulations of the mountain wave event arelimited by the short-lived and non-stationary nature of themountain waves, as well as by our assumptions of the homo-geneity of the mixing ratios of atmospheric gases. Bearingthese caveats in mind, we conclude that the fit of the dy-namic model to the measurements is reasonable, althoughwe must be careful in making direct comparisons with thedata. Within the simulated mountain wave our models pro-duce 85–99 pptvCl2 (170–198 pptv Cl), which is a similarmagnitude to the measuredClOx mixing ratios. Unfortu-nately the solar zenith angle during this period is such that wecannot make any direct comparisons between modelled andmeasuredClOx production; it would, however, be viable tomake this comparison with measurements taken within sim-ilar mountain wave events occuring in sun light.



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The differences in total aerosol mass between the twomodels are less than the differences in condensed-phaseNOy

would suggest, because of the lowerHNO3 mass fractionsof the dynamic model — which is due to a hysteresis effectin the evolution in composition of STS particles (Meilingeret al., 1995). The differences in the total aerosol surface ar-eas are even smaller, because the mean particle radii of thedynamic model are smaller than those of the equilibriummodel; consequently the equilibrium model only converts15% moreCl2 than the dynamic model. The differences inaerosol mass between the models, and so the differences inCl2 production, are very trajectory dependent. In this par-ticular test case the average temperature within the mountainwave is 0.5–1.0 K aboveTSTS (the narrow (∆T <1 K) tem-perature range at which the liquid aerosols change from aprimarily binary sulphuric to a ternary composition). Thedrops in temperature belowTSTS are too brief for conden-

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Fig. 9. Comparisons of the total aerosol (a) surface area and (b) vol-ume produced from the equilibrium (red lines) and dynamic (bluelines) models in theTUCSE + 1.5 K test case.

sation of large amounts ofHNO3 to occur, so overall thedynamic model produces smaller aerosol masses than theequilibrium model. As the average temperature decreases soshould the differences in mass between the models. Hencethis 15% difference inCl2 production between the two mod-els is not fixed; though more research is required to deter-mine the range of ratios which could be expected for typicalstratospheric mountain wave events.

The differences inCl2 production, due to surface area dif-ferences, between the two models are less than the reductionswe could expect if we used parameterisations for Reactions1–3 designed for ternary solutions. It is not clear from thefew data points collated by Hanson (1998) whether the mag-nitude of the reduction inClONO2 uptake coefficients varieswith theHNO3 content of the solution. Because of the hys-teresis effect — where the liquid PSC particles closely fol-low the composition curve of the binary sulphate solution



−6 −4 −2 0

020

4060

8010

0

Time [hr]

Cl 2

mix

ing

ratio

[ppt

v]

(a)

−6 −4 −2 0

1e−0

41e

−02

1e+0

0

Time [hr]

HO

Cl m

ixin

g ra

tio [p

ptv]

(b)

Fig. 10. Production of (a)Cl2 and (b) HOCl during theTUCSE + 1.5 K model runs shown in Fig. 7. The blue line indicatesthe output from our microphysical model, the red line that from theequilibrium code.

upon cooling, and follow that of the binary nitric acid so-lution upon warming (see Meilinger et al., 1995) — such acomposition dependence of Reactions 1–3 would lead to agreater decrease of the rates in the equilibrium model than inthe dynamic model, possibly to the point of eliminating, oreven reversing, the differences between the models. There istherefore a need for more laboratory studies of the heteroge-neous reaction rates on ternary sulphuric/nitric solutions andmore airbourne measurements of condensedNOy simultane-ous with measurements of gas-phaseClOx.

Acknowledgements.Our thanks to Fred Stroh and Marc von Hobefor providing the HALOX data and for help with interpretation,Michael Volk for providing the HAGAR data and for help with in-terpretation, and Cornelius Schiller for providing the FISH data.Work performed at Lancaster University was supported by EU con-tract number EVK2-CT-2001-00119. Work performed at the Jet

Propulsion Laboratory, California Institute of Technology, was car-ried out under a contract with the National Aeronautics and SpaceAdministration. The ECMWF forecast and operational analyseswere provided in the framework of the ECMWF special project”Influence of non-hydrostatic mountain waves on the stratosphereabove Scandinavia” by one of the authors (A. D.). We thank HeiniWernli (University of Mainz, Germany) for his trajectory code. Themesoscale numerical simulations were performed on the NEC SX6super computer of the German Climate Research Center (DKRZ) inHamburg, Germany.

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