Siberian ﬁre smoke in the High-Arctic winter stratosphere observed during MOSAiC 2019-2020

, Abstract. During the one-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition the German icebreaker Polarstern drifted through the Arctic Ocean ice from October 2019 to May 2020, mainly at latitudes between 85 ◦ N and 88.5 ◦ N. A multiwavelength polarization Raman lidar was operated aboard the research vessel and continuously monitored aerosol and cloud layers up to 30 km height. The highlight of the lidar measurements was the detection of a persistent, 10 km 5 deep wildﬁre smoke layer in the upper troposphere and lower stratosphere (UTLS) from about 7-8 km to 17-18 km height. The smoke layer was present throughout the winter half year until the polar vortex, the strongest of the last 40 years, collapsed in late April 2020. The smoke originated from major ﬁre events, especially from extraordinarily intense and long-lasting Siberian ﬁres in July and August 2019. In this article, we summarize the main ﬁndings of our seven-month smoke observations and char-acterize the aerosol properties and decay of the stratospheric perturbation in terms of geometrical, optical, and microphysical 10 properties. The UTLS aerosol optical thickness (AOT) at 532 nm ranged from 0.05-0.12 in October-November 2019 and was of the order of 0.03-0.06 during the central winter months (December-February). As an unambiguous sign of the dominance of smoke, the particle extinction-to-backscatter ratio (lidar ratio) at 355 nm was found to be much lower than the respective 532 nm lidar ratio. Mean values were 55 sr (355 nm) and 85 sr (532 nm). We further present a review of previous height-resolved Arctic aerosol observations (remote sensing) in our study. For the ﬁrst time, a coherent and representative view on 15 the aerosol layering features in the Central Arctic from the surface up to 27 km height during the winter half year is presented. Finally, a potential impact of the wildﬁre smoke aerosol on the record-breaking ozone depletion over the Arctic in the spring of 2020 is discussed based on smoke, ozone, and polar stratospheric cloud observations. ARM, Jürgen (Egon) Graeser, and all volunteers for their enormous efforts of producing the exemplary and uninterrupted MOSAiC dataset.

Importantly, in addition to the strong stratospheric aerosol perturbation, a record-breaking ozone depletion was observed over the Arctic in the spring of 2020 (DeLand et al., 2020;Manney et al., 2020;Wohltmann et al., 2020;Inness et al., 2020;Wilka et al., 2021;Dameris et al., 2021;Smyshlyaev et al., 2021). A potential impact of stratospheric aerosol on the complex chemical processes leading to this strong ozone reduction was however not mentioned in any of these articles. As the main 20 reason for the extraordinary large ozone depletion, the long-lasting, rather cold polar vortex was identified. The vortex triggered the development of polar stratospheric clouds over a comparably long time period from January to April 2020, strong chlorine activation, and ozone destruction. However, to what extent the polar smoke layers influenced ozone depletion in the spring of 2020 remain an open question that need to be clarified in the course of the MOSAiC data analysis and future studies on the interplay between smoke, polar stratospheric clouds (PSCs), and ozone depletion. 25 The article is organized as follows. A brief description of the Polarstern lidar and the data analysis is given in Sect. 2. Then, we present our MOSAiC smoke observations in Sect. 3. We begin with October and November 2019 case studies in Sect. 3.1, and continue with an overview of all lidar observations from October 2019 to May 2020 in Sect. 3.2. In this context, we will also discuss the potential contribution of Raikoke volcanic aerosol particles to the observed aerosol optical and microphyscial properties. In Sect. 3.3, we compare our results with foregoing field studies and long-term observations of optical properties to 30 highlight again the strong perturbation found in the MOSAiC winter half year of  to what extent the spread of wildfire smoke particles as well as the occurrence of PSCs, as observed with the CALIPSO and MOSAiC lidars, may have contributed to the stratospheric ozone depletion over the high Arctic. A summary and concluding remarks are given in Sect. 5.
During the one-year MOSAiC expedition the multiwavelength polarization Raman lidar Polly (POrtabLe Lidar sYstem) (Engelmann et al., 2016) was continuously operated aboard Polarstern. An overview of the Polarstern lidar instrument and all retrievable aerosol products is given by . Continuous, automated measurements of aerosol and cloud profiles up to stratospheric heights were collected from 26 September 2019 to 2 October 2020. From the beginning of October The Polly instrument is mounted inside the OCEANET-Atmosphere container of the Leibniz Institute for Tropospheric Research (TROPOS). This container is designed for routine operation aboard Polarstern between Bremerhaven, Germany, and Cape Town, South Africa and Punta Arenas, Chile (Kanitz et al., 2011(Kanitz et al., , 2013, and was operated for the first time in the Arctic during a two-month campaign in June and July 2017 (Griesche et al., 2020). The OCEANET Polly instrument belongs to the 15 lidar network PollyNET (Baars et al., 2016) which is part of the European Aerosol Research Lidar Network (EARLINET) (Pappalardo et al., 2014) organized within the Aerosols, Clouds and Trace gases Research InfraStructure (ACTRIS) project (ACTRIS, last access: 5 January, 2021).
The setup and basic technical details of the Polly instrument are given in Engelmann et al. (2016). The Polly instrument has 13 measurement channels (polarization sensitive channels, elastic-backscatter, water vapor and nitrogen Raman channels, for 20 near-range and far-range profiling). Laser pulses are emitted at the wavelengths of 355, 532, and 1064 nm. Height profiles of the particle backscatter coefficient at the laser wavelengths, of the particle extinction coefficient at 355 and 532 nm, respective extinction-to-backscatter ratio (lidar ratio) at 355 nm and 532 nm, the particle linear depolarization ratio at 355 nm and 532 nm (Baars et al., 2016(Baars et al., , 2019Hofer et al., 2017;Haarig et al., 2018;Ohneiser et al., 2020), and the mixing ratio of water vapor to dry air by using the Raman lidar return signals of water vapor and nitrogen (Dai et al., 2018) can be determined. 25 Although PollyNET delivers automatically calculated profiles, the lidar observations were manually analyzed for the smoke layers. In order to accurately determine the optical properties of the smoke layers with high signal-to-noise ratio, temporal averaging over comparably long time periods of 3-18 hours were usually necessary. The basic elastic-backscatter and Raman signal profiles were vertically smoothed with a window length of 457.5 m (61 bins, 7.5 m vertical resolution) in the case of the backscatter and depolarization ratio profiles. Particle extinction and extinction-to-backscatter ratio (lidar ratio) profiling 30 is based on a least-squares regression analysis (Baars et al., 2016). Here, we used regression window lengths of 2002.5 m (267 bins) in the computations. Afterwards, we further smoothed the profiles of the lidar products (backscatter, extinction, depolarization, and lidar ratios) linearly with window lengths increasing from 8 bins (at smoke layer base) to 11 bins (at layer top) in the case of the particle backscatter and depolarization ratio profiles, and increasing from 15 bins (base) to 20 bins (top) and from 45 bins (base) to 53 bins (top) in the case of the particle extinction and lidar ratio profiles, respectively.
Auxiliary data are required in the lidar data analysis in form of temperature and pressure profiles in order to calculate and correct for Rayleigh backscatter and extinction influences on the measured lidar return signal profiles. As an important contribution to MOSAiC, radiosondes were routinely launched every 6 hours throughout the entire MOSAiC period. In our 5 lidar data analysis and discussion of the results, we use the preliminary radiosonde products that were directly available during the expedition.
We also checked our observations for PSC occurrence and removed the profile parts that showed PSCs from the smoke data base. These stratospheric clouds can usually be easily identified. However, weak PSC structures developed in the smoke as well, predominately in January and February 2020, and these not well-defined layers were not removed. The impact of these 10 weak PSC layers is discussed in the next section.
Smoke microphysical properties such as volume, mass, and surface area concentration were retrieved by applying the POLIPHON (Polarization Lidar Photometer Networking) approach . A smoke particle density of 1.15 g cm −3 was assumed in the mass concentration retrieval. Alternatively to the POLIPHON method, we used the multiwavelength lidar inversion technique (Veselovskii et al., 2002) to derive microphysical properties of the smoke layers including 15 the particle size distribution.
Additionally, we compare the Polly observations with CALIOP data (CALIOP, last access: 5 January, 2021) and also with measurements with the Spitsbergen lidar KARL (Koldewey Aerosol Raman Lidar) (KARL, last access: 5 January, 2021; Hoffmann et al., 2009;Ritter et al., 2016). The lidar is located in Ny-Ålesund (Svalbard, Norway, 78.9 • N, 11.9 • E). In the discussion of a potential impact of the wildfire smoke on the record-breaking ozone depletion in the spring of 2020, we use the 20 MOSAiC ozone profiles measured with ozone sondes launched at Polarstern on a regular schedule from October 2019 to May 2020 (von der Gathen and Maturilli, 2020;Wohltmann et al., 2020).
For our studies of the smoke in the upper troposphere and lower stratosphere and quantification of the tropospheric and stratospheric smoke fractions, a good knowledge of the tropopause height is required. The tropopause was computed from the radiosonde temperature and pressure profiles by using the approach of the Global Modeling and Assimilation Office (GMAO), 25 Goddard Space Flight Center, Greenbelt, Maryland, USA (GMAO, 2008). In this approach, the tropopause height z TP is found from the height profile of the difference αT (z) − log 10 p(z) with α = 0.03, temperature T in Kelvin, pressure p in hPa, and height z in meter. The tropopause pressure p(z TP ) is defined as the pressure where the defined difference reaches its first minimum above the surface. If no clear minimum was found up to z = 13000 m over Polarstern, a tropopause height z TP was not assigned. The obtained tropopause heights agree well with the ones we obtain by applying the definition of the 30 World Meteorological Organization (WMO, 1992) to the radiosonde temperature profiles and considering refinements in the determination described by Klehr (last access: 5 January, 2021).  is not covered by any other lidar measurement. The spaceborne CALIPSO lidar is blind for the region >81.8 • N. A first brief overview of our UTLS smoke observations from October 2019 to May 2020 was given in . In this section, we present the full set of observed optical and microphysical properties and summarize the main results. We begin with several case studies in Sect. 3.1. A detailed October-to-May overview is then given in Sect. 3.2. In the last subsection    Fig. 7. Here, the Polarstern observations at 85.9 • N on 7 November are compared with the AWI multiwavelength Raman lidar observations at Spitsbergen at 78.9 • N of 4 November. Very similar smoke conditions were found over and 700 km south of the Polarstern. Long signal averaging times and large vertical smoothing length were 25 necessary to reduce the impact of signal noise at these comparably clean polar conditions. Because of the necessary signal and product smoothing procedures, the true (effective) height resolution is about 500 m (backscatter, depolarization ratio), 2000 m (extinction), and 2400 m (lidar ratio). The KARL observations were generally smoothed with window length of 2400 m.
As can be seen in Fig. 6 and 7, the maximum backscatter and extinction values were found around 9-10 km height, and thus just above the tropopause so that the possibility of removal of the aerosol particles by cirrus clouds (via particle scavenging November 2019. The wavelength dependence of the extinction coefficient σ λ , expressed in terms of the Ångström exponent A σ,355,532 =ln(σ 355 /σ 532 )/ ln(532/355) with wavelengths λ of 355 and 532 nm, was low with values around 0.7. Such a low Ångström exponent is typical for wildfire smoke.
The striking feature for the dominance of smoke particles is, however, the observed pronounced inverse spectral dependence of the extinction-to-backscatter or lidar ratio together with the comparably large 532 nm lidar ratios of 70-90 sr (Fig. 6c). This 5 is typically found in cases of aged smoke after long-range transport (Müller et al., 2005;Haarig et al., 2018;Ohneiser et al., 2020). Arctic haze, which may also contain aged biomass burning particles, is also able to produce an inverse spectral behavior of the lidar ratio (Ritter et al., 2016;.  Wandinger et al. (1995) and Jäger and Deshler (2003). By assuming the same lidar ratio of 40 sr at 355 and 532 nm for volcanic particles and a typical difference between the 532 and 355 nm lidar ratio of 25-30 sr for aged wildfire smoke (see recent review in Haarig et al. (2018)) the clear lidar ratio difference of 20-25 sr as given in Fig. 6 and 7 is only consistent with a volcanic aerosol fraction of ≤20%. It is worthwhile to emphasize in 15 this context that such an unambiguous aerosol typing is only possible with dual-wavelength lidars permitting the independent retrieval of backscatter, extinction, lidar ratio and depolarization ratio, and, most important, of the spectral dependencies of these optical properties.
The particle and volume linear depolarization ratio in Fig. 6b and 7b were very low at both laser wavelengths of 355 and 532 nm and indicated the presence of spherical particles. Differences between the KARL and Polly observations in Fig. 7b are 20 insignificant. Both, the volcanic as well as the smoke particles were spherical according to the lidar observations. The main phase of smoke particle aging obviously occurred already in the troposphere during the first days after emission. Assuming a core-shell structure of the smoke particles (Dahlkötter et al., 2014;Yu et al., 2019;Gialitaki et al., 2020), slight deviations from the spherical shape (e.g., caused by an irregular black-carbon-containing core structure) can lead to depolarization ratios of up to 0.25 at 355 nm and 0.2 at 532 nm (Haarig et al., 2018;Gialitaki et al., 2020;Ohneiser et al., 2020). This core structure gets 25 compact (or collapses) during the aging process so that the particles become spherical and the depolarization ratios are close to zero.  roughly between 30-60 sr on 23 July. The layer extended from the tropopause at 11 km to 12.5 km height (10 July) and from 14-16.5 km (23 July). The AOT at 532 nm was about 0.01-0.015 (10 July) and 0.02-0.03 (23 July). The depolarization ratio was rather low and indicated spherical sulfuric-acid droplets. Figure 8 and Table 1 provide information on the underlying microphysical properties of the Arctic smoke and summarize the main optical and microphysical particle characteristics discussed above for the two days (25 October and 7 November 2019) 5 and for another observation taken on 13 October 2019. The volume size distributions shown in Fig. 8 were obtained from the Polly observation by applying the lidar inversion method to the layer-mean three backscatter and two extinction coefficients (Veselovskii et al., 2012). All size distributions are normalized so that the integral over each shown size distribution is one.
The 532 nm extinction profiles in Fig. 6c were used to estimate mass and surface-area concentration profiles by applying the conversion factors for the polar smoke in Ansmann et al. (2020). Surface area values of 0.2-0.4 cm 2 m −3 in the center of the 10 smoke layer in Fig. 8 correspond to 20-40 µm 2 cm −3 . This latter unit is typically used in PSC studies (Jumelet et al., 2008(Jumelet et al., , 2009). These surface area values are in the same range as found for PSC particle layers.
The findings agree well with many in-situ observations of long-transported aged smoke (Fiebig et al., 2003;Petzold et al., 2007;Dahlkötter et al., 2014). As typical for smoke layers, a well-defined accumulation mode was found. A distinct coarse mode was absent. The sharp edge of the size distribution towards larger particles may indicate an efficient removal of the 15 large smoke and volcanic particles during the several-month long-term travel. The effective radii of the smoke particles were relatively small with values from 0.2-0.25 µm. As shown by Müller et al. (2007) for smoke layers in the middle troposphere, the particles can grow to large sizes (with effective radii close to 0.35 µm) as a result of particle aging during long-range travel.
However, as discussed by Das et al. (2020), the relatively low effective radii may be the result of the missing impact of pyroCb activity in the case of the Siberian fires in July and August 2019. The larger effective particle size for pyroCb-sourced smoke 20 (Haarig et al., 2018;Ohneiser et al., 2020) is possibly due to the rapid coagulation of the individual aerosol particles in dense smoke plumes emitted from extreme pyroCb events combined with the removal of the larger smoke and volcanic particles. The found smoke particle surface area concentrations in Table 1 are similar to typical PSC particle surface area concentrations and thus may have provided relevant sites for ozone-depleting heterogeneous chemical processes.
The values for the refractive index (real part n real , imaginary part n imag ) and the single scattering albedo SSA in Table 1  during long-range transport in the troposphere or in the stratosphere. When discussing polar smoke properties one needs to keep in mind that these observations are hard to compare with smoke properties at other places around the globe. The smoke (observed from October to May) circulated around the North Pole in total darkness at very low temperatures for months, and it is simply unknown in which way the smoke chemical and physcial properties change with time and how they influence the optical properties of the aged smoke and contributed to the strong ozone reductions in winter and spring of 2020. This will be 5 further discussed in the next subsection.  Figure 9a shows the temporal evolution of the geometrical properties of the smoke layer as observed close to the North Pole during the winter half year. The UTLS aerosol layer extended, on average, from 7-8 km to 17-18 km height. The smoke layer base was always close to the tropopause. Figure 10 provides details of the smoke layer depths. As can be seen, the vertical extent of the smoke layer was most frequently between 7 and 11 km (in 80% out of all cases). By comparing the 2019 with 20 the 2020 observations, it can also be seen that the layer thickness increased with time. The layer top reached greater heights in 2020. This was probably caused by advection of smoke (and enhanced ozone) containing air masses from lower latitudes, as will be discussed further in Sect. 4. Fig. 9a are colored to distinguish different levels of particle backscattering and extinction. The backscatter coefficients at 532 nm were multiplied by a lidar ratio of 85 sr to obtain the respective value of the extinction coefficient. 25 The maximum light-extinction values were found around or just above the tropopause. A trend of downward motion of the smoke layer in terms of the optical properties is not visible. The extinction coefficients around the tropopause slowly decreased with time from values >10 Mm −1 in October and November to <5 Mm −1 in April 2020 (Fig. 9a).

The vertical bars in
The vertically non-symmetric distribution of the aerosol concentration (here expressed in terms of light extinction) with the maximum close to the base of the smoke layer may indicate an efficient removal of the particles in the troposphere by cirrus 30 formation and ice crystal sedimentation processes. Once the aerosol particles reached the heights below the tropopause due to gravitational settling or downward mixing, they became obviously efficiently deposited by scavenging and precipitation processes. A part of the smoke particles may have served as ice-nucleating particles . Figure 9a also contains information about the occurrence of PSCs. Most of the PSCs over Polarstern were detected in January 2020. A measurement from 15 January 2020 is presented in Fig. 11. According to the PSC classification scheme (Achtert and Tesche, 2014), we observed a type Ib PSC. This type is made up of supercooled liquid ternary solutions that consist of H 2 SO 4 , HNO 3 , and H 2 O. PSCs were most frequently found in the upper part of or above the smoke layer. All in all, we observed a much lower number of PSCs over the North Pole region (86 • to 88.6 • N) during the winter and spring seasons of 2020 than the CALIPSO lidar within the latitudinal range from 60 • to 81.8 • N where most of the ozone depletion occurred as 5 discussed in Sect. 4. We corrected our stratospheric smoke observations in Fig. 9 for clearly identified PSC effects. But weak PSC effects remained in the optical data for January and February as was mentioned in Sect. 2 and is visible in Fig. 12a and c by slightly enhanced depolarization ratios and decreased Ångström exponents as discussed below. The remaining PSC impact on the AOTvalues was estimated to be of the order of <5%. are in same range as the ones for typical PSCs (Jumelet et al., 2008(Jumelet et al., , 2009) as mentioned. 35 We compared our UTLS AOT observations with respective satellite aerosol retrievals discussed by Kloss et al. (2021).   Table 2 contains the respective mean values of the intensive aerosol properties. Again, a clear smoke signature is visible in Fig. 12 and Table 2, expressed by the inverse wavelength dependence of the lidar ratio and the rather different Ångström exponents for 15 backscattering and extinction. Figure 13 shows monthly mean profiles of the 532 nm particle extinction coefficient. The same lidar data as in Fig. 9c are used here, i.e., the height profiles of the particle backscatter coefficient at 532 nm were multiplied by a lidar ratio of 85 sr and then separately averaged for each of the shown seven months. As can be seen, there is clear separation between the aerosol within the polar dome (Stohl, 2006;Bozem et al., 2019) and above this isolated polar air mass. The vertical depth of the polar 20 dome increased from October to Februay. The smoke layer maximum is close to but above the tropopause for the period from October to February. The smoke particle concentration decreased with time from October to April, however, the remarkable similarity of the the three profiles for the central winter months (December to February) indicates again the strong impact of the polar vortex on the polar aerosol conditions to provide steady state conditions for advection from more southern Arctic latitudes and removal of smoke when entering the troposphere from above. In spring (see March and April profiles), with the 25 returning sunlight, changing meteorological conditions including the impact of absorption of solar radiation by the smoke, the stable polar stratification of different air masses started to collapse. We finally estimated the smoke aerosol load over the Arctic by multiplying the area (considering latitudes >66.7 • N) by a mean smoke layer depth of 8 km, a mean smoke extinction coefficient of about 5 Mm −1 , a volume-to-extinction conversion factor of 0.124· 10 −12 Mm for wildfire smoke , and the smoke particle density of 1.15 g m −3 , and yield 0.2 Mt of smoke as a guess for the mean value of the smoke 30 aerosol load over the Arctic during the winter halfyear 2019-2020.

Comparison with foregoing Arctic aerosol studies
In Fig. 14 i.e., the height range in which also the unprecedented strong ozone reduction was found from January to April 2020 (see next section). To what extent were the wildfire particles directly involved in heterogeneous chemical processes by increasing the particle surface area available to convert nonreactive chlorine components into reactive forms?

PSCs, UTLS wildfire smoke and ozone depletion
The wildfire smoke particles in the stratosphere were probably glassy, showed a core-shell morphology, and were probably 10 largely composed of organic material (organic carbon, OC, in the shell) and, to a minor part, of black carbon (BC, concentrated in the core part). The volcanic aerosol particles (sulfuric-acid particles) and the smoke particles were most likely widely externally mixed, however, collisions and coagulation of smoke and volcanic aerosol particles leading to internally mixed particles cannot be excluded. Changes in the morphology (size, shape, and internal structure) of smoke particles and their internal mixing state were ongoing during the long-range transport. 15 The smoke-PSC-ozone research field is meanwhile (since 2017) as important as the studies on the impact of stratospheric volcanic aerosol on ozone depletion (Ansmann et al., 1996;Zhu et al., 2018) because major wildfire smoke events may occur frequently in future as a result of climate change as discussed in the introduction. It is interesting to note in the context that the stratospheric aerosol conditions in both hemispheres (2019 in the northern hemisphere, 2020 in the southern hemisphere) (Ohneiser et al., 2020;Khaykin et al., 2020;Kablick et al., 2020;Kloss et al., 2021) were significantly perturbed by 20 wildfire smoke, and in both hemispheres record-breaking ozone depletion was reported (https://public.wmo.int/en/media/news/ record-breaking-2020-ozone-hole-closes) and occurred in a smoke-polluted stratospheric environment.
The goal of this section is to provide a composite view on the Artic ozone situation 2019-2020 based on CALIPSO PSC observations, our MOSAiC smoke and PSC observations, and MOSAiC ozone profiles measured with sondes launched from Polarstern. The data may serve as a useful guide for an improved atmospheric modeling of this record-breaking ozone-depletion 25 event with the specific aim to clearify the role of smoke in the complex ozone depletion processes.
The MOSAiC and CALIPSO measurements are shown in Fig. 15 and 16. 40 ozone sondes were launched during the sevenmonth period from October 2019 to may 2020 (von der Gathen and Maturilli, 2020;Wohltmann et al., 2020). 13 out of the 40 sondes were launched from the beginning of March to mid of April 2020 and thus during the period with lowest ozone concentration. 30 To obtain an idea about the impact of the PSCs on chlorine activation and subsequent ozone destruction, we analyzed the CALIPSO observations in the latitudinal belt from 60 • N to 80 • N on a daily basis. The pink lines in Fig. 15 indicate the height range in which PSCs were detected. The top of the PSC height range was always easy to identify in the CALIPSO observations.
The base height must be exercised with care because the lowermost PSCs may have produced too weak backscatter and were then not clearly detectable in the noisy CALIPSO data. According to the MOSAiC radiosondes launched four times a day The smoke layer, extending roughly from the tropopause to 15-18 km height did not overlap with the region with very low 10 ozone concentration in the spring of 2020, and also not with the PSC height range until mid of January 2020. Horizontal ozone transport above the smoke layer was probably responsible for the local ozone maximum between 15 and 20 km height until 10 December 2019. Later on, ozone-rich and smoke-rich air became advected from lower latitudes and as consequence the smoke layer height increased in December, and afterwards followed the enhanced ozone signature from mid December to mid March. Since mid of January 2020, the layer with enhanced ozone concentration was influenced by both, smoke and PSCs. 15 To obtain a more clear picture on ozone depletion during the winter and spring season 2019-2020, Fig. 16 presents ozone deviations from the long-term mean values as discussed by Inness et al. (2020) together with the PSC and smoke layer information. Also, the PSC observations with the Polarstern lidar are included. Inness et al. (2020) used a reanalysis dataset produced by the Copernicus Atmosphere Monitoring service (CAMS, reanalysis, 2003(CAMS, reanalysis, -2019 to describe the evolution of the 2020 Arctic ozone season and to compare it with years back to 2003. Inness et al. (2020) pointed out that the December anomaly may 20 be due to the observed and modeled reduced meridional mixing because of reduced wave activity. However, there is a clear signature of chemical ozone depletion leading to the extremely low ozone values over the North Pole in March and April 2020. In March 2020, ozone values in the ozone layer over the North Pole were partly reduced to more than 10 mPa below the climatological values. Again, we notice a clear link between PSC occurrence and anomalously large ozone reduction. But we see a large vertical overlap between the smoke layer and the height range with strong negative ozone deviations. As was 25 mentioned by Manney et al. (2020), the height range with strong ozone anomalies reached down to unusually low heights and thus to heights where smoke was permanently present. Surface area concentrations of the smoke particles were in the same range of typical values for Arctic PSCs (as shown in Fig. 9). All in all, Fig. 16 may motivate future studies on the interplay between smoke, PSCs, and ozone depletion based on advanced modelling in a way presented by Zhu et al. (2018) in the case of an additional impact of volcanic aerosol on ozone depletion.
We presented a detailed optical and microphysical characterization of an unexpected UTLS smoke layer over the North Pole region in the winter half year of 2019-2020. Never before, such a strong perturbation of the stratospheric aerosol conditions in the High Arctic was measured and reported. For the first time, the spread of smoke of a major forest fire event up to stratospheric heights could be explained by self-lifting effects, and thus without the need of pyroCb convection. The majority of the smoke originated from strong, long-lasting wildfires in Siberia in July and August 2019. A month earlier, the Raikoke volcano erupted and the resulting stratospheric sulfuric-acid aerosol layers also covered large parts of the northern hemisphere.
We emphasized the need for a dual wavelength lidar, such as the Polarstern Polly operated during the MOSAiC expedition, to 5 unambiguously identify the prevailing aerosol type based on the spectral dependence of the lidar ratio. We estimated the impact of volcanic aerosol contribution to the overall stratospheric aerosol mass concentration to <20%. The UTLS smoke AOT at 532 nm ranged from 0.05-0.12 in October-November 2019 and was of the order of 0.03-0.06 during the central winter months (December-February). The observed extinction-to-backscatter ratios (lidar ratios) were, on average, 55 sr at the wavelength of 355 nm and of 85 sr at 532 nm as typical for moderately light-absorbing smoke. The light-extinction-related 355-532 nm 10 Ångström exponent of around 0.65 also clearly indicated that smoke particles dominated.
Based on an extended review of the literature dealing with aerosol profile observations in the Arctic, we were able to develop a coherent picture on aerosol structures and layering features for the autumn and winter seasons up to 27 km height. In the next step, we will analyze the MOSAiC lidar observations of the summer halfyear to fully cover the annual cycle of Arctic aerosol conditions as a function of height. 15 We discussed, to our knowledge for the first time, a potential impact of the wildfire smoke aerosol on the record-breaking ozone depletion over the Arctic in the spring of 2020 based on vertically resolved information on PSC and smoke occurrence and strength of ozone depletion. This discussion may initiate in-depth modeling studies to clarify the role of wildfire smoke in stratospheric PSC formation and ozone reduction processes. If follow-on studies will indicate a link between huge fires (caused by unusually hot temperatures and droughts as a result of climate change), corresponding smoke occurrence in the 20 lower stratosphere, and severe ozone depletion in the Arctic and Antarctica, the climate change debate will be added by a new, and until now, not considered important aspect.
As one of another important follow-on tasks, we will explore the potential of wildfire smoke to influence cirrus formation during the winter half year. A first case study was discussed in Engelmann et al. (2020). Furthermore, we will contrast these results with ones of similar studies of aerosol-cirrus interaction during the summer half year when long-range transport of 25 anthropogenic haze mixed with mineral dust from Asia, Europe, and North America as well as episodic wildfire smoke events prevailed.

Data availability
Polly lidar observations (level 0 data, measured signals) are in the PollyNET data base (PollyNet, last access: 5 January, 2021) with quicklooks at http://polly.tropos.de. All the analysis products are available at TROPOS upon request (polly@tropos.de). SD and MM were responsible for radiosonde and ozonesonde measurements.

8 Competing interests
The authors declare that they have no conflict of interest.

Financial support
The data was produced as part of the international Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) with the tag MOSAiC20192020 and Project ID AWI_PS122_00. This project has also received funding from Di Pierro, M., Jaeglé, L., Eloranta, E. W., and Sharma, S.: Spatial and seasonal distribution of Arctic aerosols observed by the CALIOP 20 satellite instrument (2006-2012), Atmospheric Chemistry and Physics, 13, 7075-7095, https://doi.org/10.5194/acp-13-7075-2013, 2013 , 9, 1767-1784, https://doi.org/10.5194/amt-9-1767 Table 1. Optical and microphysical properties of the polar wildfire smoke layer in the autumn of 2019. Layer mean values of the particle backscatter coefficient β, extinction coefficient σ, lidar ratio S, and backscatter, extinction and lidar-ratio-related Ångström exponents A β , Aσ, and AS, respectively, are given in the upper part. Indices indicate wavelength in nm and wavelength spectrum. The lower block contains the retrieved particle number concentration (particles with radius >50 nm), mean and effective particle radius rmean and r eff , volume (V ), mass (m), and surface area (s) concentration, real (n real ) and imaginary part ( Table 2. Mean values and standard deviations of smoke optical properties computed from the time series in Fig. 12. 151 daily observations from the beginning of October 2019 to mid of March 2020 are considered. δp denotes the particle linear depolarization ratio (PLDR). In the case of the lidar ratio S, we checked all daily profiles and subjectively selected only cases with clear profile information, not corrupted by a too high noise level so that the profile was strongly fluctuating. 46 days (355 nm lidar ratio) and 36 days (532 nm lidar ratio) are considered.
The Ångström exponents for the lidar ratio and the extinction coefficient are calculated from the mean values of S355 and S532 in Fig. 12 and the mean values of σ355 and σ532 in Fig. 9c.