2.1 Meteorological data

HALO was equipped with a wide range of in situ and remote sensing instruments. In addition to the scientific instruments installed for the measurement campaign, the Basic Halo Measurements and Sensor System (BAHAMAS) is part of HALO. BAHAMAS is installed permanently and provides meteorological and aircraft parameters along the flight trajectory (DLR, 2020).

The local tropopause information along the flight tracks of HALO was created using the Chemical Lagrangian Model of the Stratosphere (CLaMS) (e.g., Grooß et al., 2014). The underlying meteorological data are taken from ECMWF ERA-5 (Hersbach et al., 2020). In this work, the potential vorticity (PV)-based dynamical tropopause is used (e.g., Gettelman et al., 2011), taking 2 PVU (potential vorticity unit) for the dynamical tropopause. Since the PV tropopause is not physically meaningful in the tropics, the potential temperature level of 380 K was taken as the tropopause if the 2 PVU level lies above.

2.2 Halocarbons and SF₆

The Gas chromatograph for Observational Studies using Tracers (GhOST) is a two-channel gas chromatographic instrument. The first channel combines an isothermally operated gas chromatograph (GC) with an electron capture detector (ECD) to measure SF₆ and CFC-12 at a time resolution of 1 min (hereinafter referred to as GhOST-ECD). A similar setup was used during the SPURT campaign (Bönisch et al., 2009; Engel et al., 2006). The second channel is a combination of temperature programmed GC with a quadrupole mass spectrometer (QP-MS, hereinafter referred to as GhOST-MS). Because of very small mole fractions of the halocarbons, a cryogenic pre-concentration system is installed prior to the GC (Obersteiner et al., 2016; Sala et al., 2014). GhOST was operated successfully during several aircraft campaigns to mainly target brominated halocarbon species, as discussed in Keber et al. (2020). For the SouthTRAC campaign, the ionization mode was changed from negative chemical ionization (NCI) to electron impact ionization (EI) to record full mass spectra. For each substance, one molecular fragment is selected for which the chromatographic peak is not disturbed by other substances. Furthermore, the MS was operated in selected ion monitoring (SIM), scanning pre-selected mass fractions at a preset retention time window. A larger sample volume is needed in EI mode compared to NCI mode. The change of ionization decreased the time resolution from 4 to 6 min per measurement cycle, of which 147 s are needed for sampling air. The performance of the GhOST-MS channel for the chlorinated substances used in this work is shown in Table 1. Displayed are the precisions and detection limits measured shortly before the campaign in the laboratory. Additionally, based on in-flight calibration, precision during the flight can also be calculated. As the conditions in the airplane are more variable than in a laboratory, especially when changing the flight level, this affects the precision of the measurements. The frequency of calibration measurements during a flight is much lower than in the laboratory, making it less stable than the laboratory value. Therefore, precision drops for most of the substances by up to a factor of 4. The exceptions are CFC-11, CFC-113, and methyl chloroform. Methyl chloroform shows a significantly better precision during the campaign, whereas the precision of CFC-12 and CFC-113 measurements was much poorer. It is difficult to determine exactly what the poorer precisions of these two substances can be attributed to. The chromatographic peak of CFC-11 is very narrow, and variable environmental conditions (due to changes in altitude, pressure, and temperature in the cabin) have an influence on the peak shape. The amount of water in the analysis system is also important and is kept as low as possible by drying before pre-concentration. As the chromatographic peak of CFC-113 is close to the chromatographic peak of water, small changes in water can affect the chromatographic peak of CFC-113. CFC-12 and SF₆ with the GhOST-ECD channel were measured with a precision of 0.2 % and 0.64 %, respectively. The instrument was tested for nonlinearities and memory effect, and correction was done where necessary (see Sala et al., 2014, for details). Mixing ratios in this work are reported as dry mixing ratios on AGAGE (Advanced Global Atmospheric Gases Experiment) scales.

Table 1Chlorinated species measured with the GhOST-MS. The precisions and limit of detections (LODs) of GhOST were determined in the laboratory shortly before the SouthTRAC (ST) campaign, and mean precision was calculated during the flights.

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2.3 N₂O

Measurements of N₂O were performed with the University of Mainz Airborne Quantum Cascade Laser-spectrometer (UMAQS), which also provided data for CH₄, CO, CO₂, and OCS during SouthTRAC. The instrument is based on direct absorption spectroscopy using a continuous-wave quantum cascade laser with a sweep rate of 2 kHz (Müller et al., 2015). During SouthTRAC the instrument was calibrated in situ against two standards of different concentrations, which are compared against primary standards (NOAA) prior to and after campaign phases.

Under typical flight conditions at flight level, N₂O was measured with an overall uncertainty of 0.6 ppb relative to the calibration standards. The noise of the 1 Hz data was 0.1 ppb (1σ). Note that this is an upper limit since the data are corrected post-flight for drift effects based on the in-flight calibrations.

3.1 Air mass classification by in situ measurements

The maximum gradient of PV is a commonly used indicator to define the location of the vortex edge, also known as the Nash criterion (Nash et al., 1996). PV is a model-derived quantity. Although the underlying meteorological reanalyses have a fairly high resolution these days (e.g., Hersbach et al., 2020), small-scale features like vortex filaments with different chemical compositions may not be well resolved. In this work, an extended version of the vortex definition by Greenblatt et al. (2002) is used instead. The technique by Greenblatt et al. (2002) uses the tight correlation between N₂O and potential temperature to determine the inner edge of the vortex boundary. N₂O can be measured in situ with a high time resolution to reveal small-scale structures in the atmosphere. As already mentioned in Sect. 1, air inside the polar vortex has a substantially different composition regarding trace gases than air outside the vortex. A tracer like N₂O exhibits a horizontal gradient across the vortex edge in the stratosphere with lower mixing ratios inside the vortex and higher mixing ratios outside the vortex. In addition, N₂O has small variability inside the vortex on constant isentropic surfaces (variability of about 6 ppb Greenblatt et al., 2002). This is an indication of well-mixed air inside the polar vortex due to the long isolation in polar winter. The vertical profile of N₂O in the midlatitudes shows a weak gradient but a high variability as it is influenced by both tropical and polar air (Krause et al., 2018; Marsing et al., 2019). In between there is a transition region (vortex boundary region), which is influenced by the vortex as well as by midlatitudes. Towards tropopause altitudes, the transport barrier of the polar vortex disappears and a classification is not possible.

Based on the method of Greenblatt et al. (2002), one flight is chosen to generate a vortex reference profile. This flight should ideally be completely in the vortex. However, during the SouthTRAC campaign there was no flight that only sampled vortex air. In addition, there is an interest in not only distinguishing between vortex and non-vortex air, but also in assigning the campaign measurements to the vortex, vortex boundary region, and midlatitudes. For this reason, several flights were used to create reference profiles for the vortex and midlatitudes. The composition of the lowermost stratosphere is affected by diabatic descent inside and outside the polar vortex and quasi-isentropic mixing with air from lower latitudes. In addition, mixing at the extratropical tropopause affects the lowest 20–25 K above the local tropopause (Hoor et al., 2004, 2005). Therefore, classification was done with two vertical coordinates, potential temperature (Θ) and potential temperature above the local tropopause (ΔΘ).

The vortex reference profile (see Fig. 2) was generated from all flights that are assumed to contain measurements within vortex air. Data from these flights were pre-filtered by taking only the measurements polewards of 60^∘ S equivalent latitude (Butchart and Remsberg, 1986) and 20 K above the local tropopause. With an iterative filter procedure (see Appendix A) the lower envelope of the remaining measurements is obtained and is used to generate the vortex profile function (Werner et al., 2010). For the midlatitude profile (see Fig. 2), all flights were taken into account, focusing only on measurements between 40 and 60^∘ S equivalent latitude and again 20 K above the local tropopause. This time, the upper envelope of the measurements was evaluated by the iteration procedure to build a reference profile function for the midlatitudes. As an intermediate step to the final profiles, the measurements of the lower and upper envelope are binned in 5 K intervals of Θ or ΔΘ (see Fig. S2c and d). Mean values of the binned profiles are then used to generate a polynomial fit function for the vortex profile and the midlatitude profile (Fig. S3). The two reference profiles in Θ coordinates are displayed in Fig. 2a, and the two reference profiles in ΔΘ coordinates are displayed in Fig. 2b.

Figure 2Midlatitude and vortex profiles (black) of N₂O versus (a) potential temperature (Θ) and (b) potential temperature difference (ΔΘ) from the local PV tropopause. The vortex cutoff criterion (see main text for details) of 20 ppb is illustrated by the grey profile on the right side of the vortex profile. Midlatitude variability of 15 ppb is illustrated with the grey profile on the left side of the midlatitude profile. In between these is the vortex boundary region. The overlap region is declared for the area where the vortex cutoff and midlatitude variability cross. Additionally, N₂O measurements classified to the respective region are displayed. Vortex measurements are in red, vortex boundary region measurements are in green, midlatitude measurements are in blue, and overlapping measurements are in grey.

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In general, it cannot be assumed that a single N₂O vortex profile can be representative for the entire winter. Subsidence of the vortex air by several kilometers due to radiative cooling (Schoeberl and Hartmann, 1991) leads to a changing N₂O profile throughout the polar winter. In the lower stratosphere of the Southern Hemisphere, descent generally stops around mid-October (Manney et al., 1994). However, N₂O data of the SouthTRAC flights did not reveal strong diabatic descent during the time of the campaign (below Θ=400 K). Therefore, only one reference vortex profile was generated for the campaign.

A vortex and midlatitude reference N₂O data set (N₂O_vor and N₂O_mid) can be calculated from Θ or ΔΘ by using the fit function for the vortex and midlatitude profiles for every measurement point of the UMAQS instrument for all flights. The following then applies for each N₂O measurement: if the mixing ratio is below the respective N₂O_vor plus the prescribed vortex cutoff, then it is assigned to the vortex. Otherwise, if the mixing ratio is above the respective N₂O_mid minus the associated variability, then it is assigned to the midlatitudes. Mixing ratios above the respective N₂O_vor plus the prescribed vortex cutoff and below the respective N₂O_mid minus the associated variability are assigned to the boundary region. Measurements for which the respective N₂O_vor plus the prescribed vortex cutoff and the N₂O_mid minus the associated variability overlap cannot be uniquely classified and are assigned to both the vortex and the midlatitudes in later analysis. For the prescribed vortex cutoff, the value of 20 ppb proposed by Greenblatt et al. (2002) was used. The associated variability of the midlatitude profile was set to 15 ppb, as the variability in N₂O in the midlatitudes is roughly 10 % (Strahan et al., 1999).

3.2 Overview of the sample regions

In 2019, extraordinary meteorological conditions led to a sudden rise in stratospheric temperatures over Antarctica. This minor sudden stratospheric warming (minor SSW) event affected the shape, location, and strength of the polar vortex. From mid-August to early September 2019, the polar vortex was displaced and weakened towards the eastern South Pacific and South America (Safieddine et al., 2020; Wargan et al., 2020). The SouthTRAC campaign flights took place from early September to early October and in the first half of November; thus, they took place shortly after the minor SSW event and captured the late winter evolution of the Antarctic polar vortex.

Figure 3 displays an overview of air mass classification of the local flights of the SouthTRAC campaign (classification in Θ coordinates). Measurements below 20 K of ΔΘ are not classified and are not taken into account here. There are no N₂O measurements available from flight ST08 on 11 September, and thus no classification was possible. Vortex air sampling varies from flight to flight depending on the objective of each flight. The vortex and boundary regions were sampled in both phases of the campaign. The first phase includes some flights that predominantly sampled the vortex or vortex boundary region (e.g., flight ST15 on 29 September or flight ST16 on 30 September). In general, vortex air represents about 23 % of flight time in the stratosphere and vortex boundary air about 14 %. More than half (56 %) of the flight time in the stratosphere was in midlatitude air. The use of the ΔΘ coordinates for the air mass classification leads to similar percentage division (not shown here).

Figure 3Air sampling statistics of the SouthTRAC campaign. (a) The number of classified measurements. Each column represents a single scientific flight. Stacked bars indicate vortex (red), vortex boundary (green), midlatitudes (blue), and undefined (grey) amounts. (b) Percentage of each region in the total of all measurements in the scope of the classification (above ΔΘ of 20 K).

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4.1 Up-sampling GhOST-MS measurements

The GhOST-MS measurements have a time resolution of 6 min of which the enrichment and therefore the sampling of air takes around 147 s. With a maximum cruising speed of around 258 m/s, this means that air is sampled along a distance of approximately 38 km per measurement during enrichment. This could lead to a rather coarse resolution where fine structures like filaments and small-scale dynamical perturbations are sometimes not well resolved.

Measuring CFC-12 in both the ECD and MS channels of the instrument allows the measurements of the organic source gases to be up-sampled by using the better-resolved measurements of CFC-12 from the ECD channel. Measurements of CFC-12 in the ECD channel not only have a higher time resolution of 1 min, but they also have better precision than data from the MS channel. As shown in Fig. 4, the correlation between CFC-12 measurements of the two channels for all flights is linear over the whole range of mixing ratios, with a coefficient of determination of R² = 0.968. Firstly, for each organic source gas, a linear or polynomial fit function is calculated based on the correlation with CFC-12 measurements in the GhOST-MS channel for all flights (correlations contained in the supporting information). Secondly, these fit functions are then used together with the CFC-12 measurements of the ECD channel to calculate the up-sampled mixing ratios of the organic source gases. Flight ST14 from 26 September in Fig. 5 is an example to demonstrate the benefits of the up-sampling. Displayed are the original measurements of CFC-11 of the MS channel as well as the up-sampled CFC-11 values. The background colors indicate to which region the samples can be assigned (classification in Θ coordinates), as described in Sect. 3. The up-sampled values show higher variability and follow the classification well by region. Especially with the sharp gradients, e.g., at 04:10 and 05:50 UTC in Fig. 5, the original lower-resolution data did not capture the transitions well between the regimes compared to the up-sampled data. In the following, the up-sampled data are used for further evaluation.

Figure 4Correlation between CFC-12 measured in the GhOST-MS channel and in the GhOST-ECD channel.

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Figure 5CFC-11 measured in the GhOST-MS during flight ST14 on 26 September 2019. Original data are shown in red, and measurements up-sampled using CFC-12 from the ECD channel are shown in black. Background colors indicate in which region the samples were taken using the air mass classification in Θ coordinates.

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4.2 Semi-direct and indirect calculation of inorganic chlorine

Organic chlorine (CCl_y) can be calculated directly from the up-sampled GhOST-MS measurements. Thus, Cl_y can be calculated from Eq. (1) if the mixing ratios of the major chlorine-containing substances at the stratospheric entry point (Cl_total) are known.

Air enters the stratosphere predominantly through the tropical tropopause layer (TTL). During transport into and within the stratosphere, an air parcel exhibits irreversible mixing and cannot be regarded as conserved (Hall and Plumb, 1994). Instead, an air parcel in the stratosphere consists of a multitude of components with different transit times, representing their travel times since they entered the stratosphere. The distribution of the transit times is called the age spectrum G, and the first moment is the mean age Γ (Hall and Plumb, 1994). The concept of the age spectrum can be used to determine mean age values based on observations of chemically inert tracers in the stratosphere. For this purpose, in addition to the age spectrum, tropospheric time series of the inert tracers are required (Engel et al., 2002). This was done for the SouthTRAC campaign by using SF₆ measurements of the GhOST-ECD and tropospheric time trends taken from the AGAGE (Advanced Global Atmospheric Gases Experiment) Network (Prinn et al., 2018). Since only the mean age is given, a width parameterization is used to derive the age spectrum by using the ratio of moments (${\mathrm{\Delta }}^{\mathrm{2}}/\mathrm{\Gamma }$). Hauck et al. (2019) showed that the ratio of moments undergoes seasonal variability and is probably much larger than previously implemented values (e.g., Engel et al., 2002; 0.7 years). A ratio of moments of 1.25 years is chosen here. The age spectrum, together with the tropospheric time trend of the substances of interest, can be used to calculate the stratospheric mixing ratio that would be present without chemical degradation, which thus represents the entry mixing ratio. In the following, Cl_y derived from the difference between the estimated entry mixing ratios and observed CCl_y from the in situ measurements (see Eq. 1) is referred to as the semi-direct calculation of Cl_y.

For the case where measurements of all major chlorine-containing substances are not available, Cl_y has in the past been calculated indirectly based on correlations derived from previous measurement campaigns. This also applies to Cl_y from the Northern Hemisphere used later in this paper (see Sect. 4.4). For instance Wetzel et al. (2015) and Marsing et al. (2019) used Cl_y based on a correlation derived from two balloon flights inside the Arctic polar vortex in 2009 and 2011 from a cryogenic whole-air sampler (Engel et al., 2002). In order to account for tropospheric trends, the correlations between CFC-12 and the other long-lived substances were adapted with a modified method described in Plumb et al. (1999) using the mean arrival time Γ^* to derive a correlation function valid for the respective time when the correlation is applied. Plumb et al. (1999) showed that the age spectrum of an inert tracer is not well suited to describe the propagation of chemically active tracers into and through the stratosphere. They introduced a modified age spectrum, called the normalized arrival time distribution G^*, which combines chemical loss and transport. The mean arrival time Γ^* represents the first moment of this distribution. The mean arrival time Γ^* for all the relevant chlorine substances can be parameterized in terms of stratospheric lifetime τ and mean age Γ (Plumb et al., 1999). Using G^* instead of G and therefore Γ^* instead of Γ is better suited for chemically active tracers because the tail of the transit time distribution is less weighted, especially for substances with shorter stratospheric lifetimes (Engel et al., 2018a; Ostermöller et al., 2017). To transfer the correlations from the balloon observations in 2009 and 2011 to the measurements during SouthTRAC in 2019, the observed mixing ratios are first divided by the respective estimated entry values to derive the normalized mixing ratios. The entry values are calculated by the modified age spectrum and tropospheric time trends from the AGAGE Network for the time of the balloon measurements. Multiplying the normalized mixing ratios by the entry mixing ratio for the time during SouthTRAC then allows a comparison to the directly determined correlations during SouthTRAC. Here, we compare the directly observed correlation from SouthTRAC to the indirectly determined correlations based on previous balloon observations transferred to 2019. Note that the indirectly determined values are based on observations that were not only performed about 10 years earlier but that were also from the Northern Hemisphere instead of the Southern Hemisphere. Figure 6 displays scaled correlations from the balloon observations (red) and correlations from the SouthTRAC data (black) of three long-lived substances against CFC-12. The balloon-based correlations correspond well to the correlations measured during the SouthTRAC campaign. Thus, the balloon-based correlations can be used to determine CCl_y from CFC-12 alone. As already mentioned earlier, Cl_total is also needed for the calculation of Cl_y (see Eq. 1). The mean age values derived for the balloon measurements are used for this purpose, and Cl_total is calculated for the conditions during SouthTRAC. Cl_y is then derived as the difference between Cl_total and CCl_y.

Figure 6Correlation between CFC-12 and CFC-11, between CFC-12 and CH₃Cl, and between CFC-12 and HCFC-142b. The raw measurements by GhOST-MS are shown in black, and the balloon observations scaled to the time of the SouthTRAC campaign using mean arrival time are shown in red.

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With the good agreement between observed correlations and scaled correlations from the balloon measurements and the previously described determination of Cl_y, we explore whether Cl_y can be successfully estimated from CFC-12 alone. Therefore, a correlation function for the conditions during Antarctic late winter 2019 has then been derived for the indirect calculation of Cl_y as a function of CFC-12 mixing ratios (Eq. 2). The coefficients for the correlation function with CFC-12 as the reference substance based on the balloon measurements can be taken from Table 2. In addition, the fit coefficients are given if one wants to use N₂O as the reference. N₂O shows a compact correlation with long-lived chlorinated substances and has been used in many publications for the determination of Cl_y (e.g., Schauffler et al., 2003; Strahan et al., 2014; Strahan and Douglass, 2018). Using CFC-12 from the GhOST-ECD channel and N₂O from the UMAQS instrument, we obtain comparable values for Cl_y (see Fig. S7 in the supporting information). In the following, CFC-12 from the GhOST-ECD channel is used as the reference in Eq. (2) for the indirect determination of inorganic chlorine.

Figure 7 shows semi-directly and indirectly determined inorganic chlorine as a function of mean age. Cl_y values were binned in intervals of 0.2 years, and the mean values are displayed. For both methods, inorganic chlorine increases with mean age of air as more molecules of the organic source gases are converted to the inorganic form. The difference between the two methods is rather small, with less than around 30 ppt difference between 1 and 4 years of mean age and a maximum difference of about 65 ppt at 5 years of mean age. Recent research suggests that SF₆-based mean age is biased because its suggested lifetime has been overestimated (e.g., Ray et al., 2017). As a guideline, Fig. 7 additionally shows a corrected mean age of air using one of the linear fit functions from Leedham Elvidge et al. (2018), based on a comparison of SF₆-based mean age with a combined mean age based on five alternative age tracers. The fundamental picture does not change, however, and thus we use the uncorrected mean age of air. The small deviation over the entire range of mean age indicates that adapted correlations from previous measurement campaigns and also from the Northern Hemisphere lead to comparable values in inorganic chlorine determined for the Southern Hemisphere. Hence the metric can be used for the calculations of Cl_y in the case where only measurements of CFC-12 are available. Since it was possible during SouthTRAC to measure the organic source gases, the Cl_y determined semi-directly from the measurements was used for further evaluation. However, the good comparability of the two methods offers the possibility to compare Cl_y from different measurement campaigns, which differ regarding the number of measured chlorinated substances (see Sect. 4.4). With the semi-directly determined Cl_y during SouthTRAC, correlation functions can be determined. Table 2 contains the coefficients for the correlation functions based on CFC-12 and N₂O as references. The correlation functions are limited to the minimum mixing ratio of the respective reference substance taken during the SouthTRAC campaign.

Figure 7Indirectly (green) determined Cl_y based on balloon observations in 2009 and 2011 and semi-directly (black) determined Cl_y as a function of age of air (bottom axis) and corrected age of air (top) using a linear fit $y=\mathrm{0.85}x-\mathrm{0.02}$ from Leedham Elvidge et al. (2018). The absolute difference between these methods is shown in red.

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Table 2Coefficients of the correlation function to indirectly derive Cl_y with the respective reference substance for the time of the SouthTRAC campaign (2019.75). Calculation of Cl_y with CFC-12 or N₂O and coefficients based on the balloon observations in 2009 and 2011 (Balloon) and coefficients based on the SouthTRAC measurements (SouthTRAC).

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4.3 Chlorine partitioning in the Antarctic winter 2019 lower stratosphere

Since inorganic chlorine plays a major role in ozone depletion, it is worth investigating its distribution in the Antarctic stratosphere. For the analysis only measurements polewards of 40^∘ equivalent latitude are used. As a vertical coordinate Θ was chosen. All measurements have been binned into 5 K potential temperature bins between 270 and 420 K (see Fig. 8). Bins that contain fewer than five data points are not included in the analysis. The uncertainties represented by the error bars are the 1σ standard deviations of the means. Up to the potential temperature at which air mass classification begins, the Cl_y is estimated based on all measurements. From the potential temperature at which air mass classification begins, Cl_y is estimated separately in each region. Measurements within the overlap area in the classification (see Fig. 2) are counted both as vortex and midlatitude measurements.

Figure 8Vertical profiles of Cl_y, Cl_y by region from 20 K above the local tropopause, CCl_y, and Cl_total averaged over 40–90^∘ S equivalent latitude for all flights during SouthTRAC. The data are displayed as a function of potential temperature. Vertical and horizontal error bars denote 1σ variability. The dashed line shows the averaged PV-based dynamical tropopause with the 1σ variability as a shaded area.

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In Fig. 8, the inferred Cl_y throughout the troposphere is close to zero and increases in the tropopause region. The tropospheric measurements during SouthTRAC are thus consistent with Cl_total derived from ground-based AGAGE measurements. The vertical profiles of vortex, vortex boundary, and midlatitude declared measurements show different gradients. In the midlatitudes, the inorganic chlorine hardly increases between 330 and 380 K, with values between 171±78 and 260±117 ppt, whereas the increase is stronger between 380 and 400 K, reaching a value of 446±124 ppt. The profile of the vortex boundary region increases in the range from 502±110 up to 1090±377 ppt in the Θ interval of 360 to 395 K. The variability of the vortex boundary profile increases with height. This is partly due to the air mass classification, since the range of values in the vortex boundary region increases with increasing potential temperature (see Fig. 2). Inorganic chlorine within the vortex could be obtained from Θ between 330 to 385 K. Cl_y inside the vortex increases significantly up to a value of 1687±19 ppt. Thus, in late winter and early spring at the highest measured potential temperatures, about half of the recorded chlorine is found in inorganic form. Despite this amount of inorganic chlorine in the lower stratosphere, the total polar ozone column was higher than usual in September 2019. As a result of the minor SSW event, chlorine deactivation began earlier in 2019, and the ozone hole was about 10×10⁶ km² in size and thus only 20 % of that in mid-September 2018 (Wargan et al., 2020).

4.4 Comparison of Cl_y in the Antarctic (SouthTRAC) and Arctic (PGS) polar winter

To compare Cl_y in the Antarctic polar vortex and in the Arctic polar vortex, measurements performed on the HALO aircraft during the PGS campaign were used. PGS consisted of the three partial missions POLSTRACC (Polar Stratosphere in a Changing Climate), GW-LCYCLE (Investigation of the Life cycle of gravity waves), and SALSA (Seasonality of Air mass transport and origin in the Lowermost Stratosphere) to probe stratospheric air during the Arctic winter in 2015/2016 (Oelhaf et al., 2019). Flights of the PGS campaign were conducted from 17 December 2015 until 18 March 2016 and can be separated into two main phases. For this study, only the flights from the second main phase from 26 February to 18 March are investigated, since they took place in a comparable period (later winter). The separation into vortex, vortex boundary, and midlatitude measurements is based on the above-mentioned method using N₂O measurements performed by the TRIHOP instrument on board HALO during PGS (Krause et al., 2018) (see Fig. S6 in the Supplement). In Sect. 4.2, the indirect method for the determination of Cl_y, where a direct measurement of all relevant chlorinated substances is not possible, was shown to provide values comparable to those obtained by the semi-direct method. During PGS, CFC-12 was measured with the ECD channel, but the MS channel was in NCI mode and could not measure all chlorinated substances. Cl_y was therefore calculated using the indirect method and CFC-12 measurements from the GhOST-ECD channel during PGS. As for SouthTRAC, the scaled correlations from observations of the cryogenic whole-air sampling on two balloon flights inside the Arctic polar vortex in 2009 and 2011 were used (correlation function for the Arctic winter 2015/2016 can be taken from the Supplement).

Figure 9 displays the mean vertical profiles of Cl_y inside the vortex and Cl_total of the respective hemisphere. Measurements from the individual campaigns have been binned into 5 K potential temperature (a) and potential temperature difference to the local tropopause (b). The PV-based dynamical tropopause was used for PGS, as was done for the SouthTRAC analysis. The mean PV-based tropopause was at 306 K during PGS, only slightly lower than that during SouthTRAC at 308 K. Independent of the vertical coordinate, total chlorine (Cl_total) in the lower stratosphere decreased from the time of PGS (2015/2016) to the time of SouthTRAC (2019). The difference between Cl_total from controlled substances during PGS and that during SouthTRAC is about 60±9.6 ppt. This difference can be explained by a combination of temporal trends of controlled substances and interhemispheric gradients. Using the rate of decline from Engel et al. (2018b) of $-\mathrm{12.7}\pm \mathrm{0.9}$ ppt yr⁻¹ for the controlled substances, a difference of about 45 ppt is expected due to the time difference between the two campaigns. The remaining difference of about 15 ppt can be explained by the higher Cl_total in the Northern Hemisphere.

Figure 9(a) Comparison of the vertical profiles of Cl_y inside the respective vortex where classification was possible and total chlorine from PGS (black) and SouthTRAC (green). Data are averaged over 40 to 90^∘ equivalent latitude of the respective hemisphere and are displayed as a function of potential temperature. Vertical and horizontal error bars denote 1σ variability. PV tropopause for PGS (black) and SouthTRAC (green) are displayed as dashed horizontal lines with the 1σ variability as shaded areas. Panel (b) is the same data as (a) but as a function of potential temperature relative to the local tropopause (PV) displayed with a dashed grey line.

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Using Θ as the vertical coordinate (Fig. 9a), vertical profiles of vortex classified Cl_y of PGS and SouthTRAC show different results. Although the Cl_y vortex profiles are similar until around 350 K, the SouthTRAC profile increased more steeply, reaching values more than 444 ppt larger than those during PGS at the same potential temperatures. Differences are slightly larger when using ΔΘ as the vertical coordinate (Fig. 9b). Although the two Cl_y profiles lie close together between 20 and 50 K ΔΘ, the differences between them increase to 540 ppt at 65 K ΔΘ. The fraction of total chlorine in the form of Cl_y during PGS at the same distance from the local tropopause as the maximum SouthTRAC Cl_y fraction is about 20 % in the midlatitudes (not shown) and about 40 % inside the vortex (Fig. 9b).

Figure 10Difference of the latitude–altitude cross section of Cl_y from PGS and SouthTRAC. Data are binned using equivalent latitude^* and ΔΘ.

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Figure 10 shows the difference between PGS and SouthTRAC Cl_y in a latitude–altitude cross section. Equivalent latitude^* was used as a horizontal coordinate, i.e., the geographic latitude for all tropospheric observations and equivalent latitude for all stratospheric ones (Keber et al., 2020); ΔΘ was used as a vertical coordinate. Since the tropopause height of the two hemispheres is different and changes with the season, the tropopause relative coordinate ΔΘ accounts for tropopause variability and allows for better comparison of Cl_y. The data have been binned in 5^∘ latitude and 5 K of potential temperature relative to the local tropopause. Only bins which contain at least five data points were considered in this analysis. The difference was calculated by subtracting each Southern Hemispheric latitude–altitude bin from the equivalent Northern Hemispheric latitude–altitude bin. Values in the troposphere differ only slightly. In the lower stratosphere, a separation into two areas can be seen. In the lower stratosphere at higher latitudes, overall higher mixing ratios were derived during SouthTRAC in comparison to PGS. There are two bins with substantially higher values during SouthTRAC, with around 900 ppt more Cl_y between 80 and 90 K of ΔΘ and 65 to 70^∘ equivalent latitude. This difference is much larger than the difference when comparing vortex classified measurements (Fig. 9). Thus, it is very likely that vortex core and vortex edge values are compared due to the different Arctic and Antarctic vortex size, stability, and strength of the transport barrier. Therefore, performing the comparison in equivalent latitude and potential temperature coordinates removes only some of the sources of discrepancy. The stratosphere of the midlatitudes shows consistently higher Cl_y values during PGS. The highest values of Cl_y reached are 315 ppt higher during PGS between 65 and 70 K of ΔΘ and 40 to 45^∘ equivalent latitude. The already-mentioned difference of Cl_total between PGS and SouthTRAC amounts to 60±9.6 ppt. This maximum difference of 60±9.6 ppt will only propagate completely to Cl_y when all chlorine is converted to the inorganic form. Taking into account the difference in Cl_total between the two campaigns would reduce the observed differences in the midlatitudes, where mixing ratios of Cl_y were higher during PGS, but would increase the differences in the high latitudes, where higher Cl_y was derived for SouthTRAC. The observed differences in Cl_y are thus clearly larger than can be explained by the temporal difference in Cl_total. Possible reasons for the observed differences can be derived from the hemispheric difference of the Brewer–Dobson circulation using the age of air as a common metric for transport. Konopka et al. (2015) showed that the age of air is always younger north of 60^∘ N than south of 60^∘ S in the corresponding season. Older air will be higher in Cl_y as a larger fraction of total chlorine has already been converted to the inorganic form. Therefore, the observed differences in Cl_y, with higher Cl_y values in the southern high latitudes than in the northern high latitudes (see Figs. 9 and 10), are consistent with the differences in the age of air found by Konopka et al. (2015). In addition, Engel et al. (2018b) updated the long-term total column HCl and ClONO₂ (representing Cl_y) record reported by Mahieu et al. (2014) in the stratosphere at Jungfraujoch (46.5^∘ N) and at Lauder (45^∘ S) through the end of 2016. A negative trend of Cl_y is observed at both stations but with a non-significant trend for the Jungfraujoch data over the last decade and a slightly larger negative trend from the Lauder data. In addition, trends between 1997 and 2016 are given at both stations, with $-\mathrm{0.42}\pm \mathrm{0.23}$ % yr⁻¹ and $-\mathrm{0.51}\pm \mathrm{0.12}$ % yr⁻¹ for HCl and $-\mathrm{0.60}\pm \mathrm{0.39}$ % yr⁻¹ and $-\mathrm{0.74}\pm \mathrm{0.59}$ % yr⁻¹ for ClONO₂ at Jungfraujoch station and Lauder station, respectively. Furthermore, the Global Ozone Chemistry And Related trace gas Data records for the Stratosphere (GOZCARDS) shows short-term lower-stratospheric HCl trends that are negative at southern latitudes and slightly positive (marginal significance) at northern midlatitudes between 2005 and 2015/2018 (Froidevaux et al., 2015, 2019). Although the trends given are indicative of the interhemispheric differences in Cl_y decline, they do not explain the difference in Cl_y at midlatitudes of 200 ppt or more shown in Fig. 10. The lowest 20 K above the local tropopause show in general minor differences between the two hemispheres. There are two exceptions. A bin between 0 and 5 K of ΔΘ and 30 to 35^∘ equivalent latitude and a bin between 10 and 15 K of ΔΘ and 45 to 50^∘ equivalent latitude both have around 200 ppt more Cl_y during PGS. However, this Θ range is in general affected by cross- tropopause mixing in both hemispheres, leading to generally small differences in the extratropical tropopause layer.