As part of the 1-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition September 2019 to October 2020, an advanced multiwavelength polarization Raman lidar was operated on board the German icebreaker Polarstern , which served as the main MOSAiC platform for advanced remote sensing studies of the atmosphere. The ice breaker was trapped in the ice from October 2019 to May 2020 and drifted through the Arctic Ocean at latitudes mainly between 85 and 88.5∘ N for 7.5 months, continuously monitoring aerosol and cloud layers in the central Arctic up to 30 km height . MOSAiC was the largest Arctic field campaign ever conducted. The expedition was motivated by the rapid sea ice loss, the unusual Arctic warming, and our incomplete knowledge about the complex processes controlling the Arctic climate .

We expected to detect a residual stratospheric sulfate aerosol layer, originating from the Raikoke volcanic eruption, with an aerosol optical thickness (AOT) of the order of 0.005–0.01 at 500 nm wavelength over the High Arctic during the main MOSAiC winter months (December–February), as will be outlined in detail in Sect. . The volcano in the Kuril Islands (48.3∘ N, 153.3∘ E) erupted on 22 June 2019 and influenced the aerosol conditions in the lower stratosphere at all latitudes north of about 20∘ N during the summer and autumn of 2019 . However, instead of an optically thin volcanic aerosol layer well above the tropopause, we observed a 10 km thick aerosol layer in the upper troposphere and lower stratosphere (UTLS), with an order of magnitude higher AOT of around 0.1, when we started our observation end of September 2019. Wildfire smoke was the dominating aerosol type in the main part of the prominent layer, with the backscatter centre just above the local tropopause. This smoke-containing layer was present over the North Pole range throughout the winter half-year until the polar vortex, the strongest of the last 40 years , and began to collapse in late April 2020. The occurrence of a persistent aerosol layer with clear wildfire smoke signatures over the entire winter half-year (2019–2020) is one of the outstanding events observed during the MOSAiC expedition . The following question arose: what was the source for this strong UTLS perturbation?

We hypothesize that extreme and long-lasting wildfires in central and eastern Siberia in the summer of 2019 were responsible for the UTLS smoke layer. The main burning phase lasted from 19 July to 14 August 2019 . Rather intense fires between 55 and 70∘ N injected enormous amounts of wildfire smoke into the free troposphere, in close proximity to the Arctic region. At the end of July 2019, stagnant air conditions favoured the accumulation of smoke over the fire areas north of Lake Baikal and led to a strong increase in the AOT of above 2 over several days. In the absence of any pyrocumulonimbus (pyroCb) convection and, thus, of a very efficient process to transport smoke into the lower stratosphere, we hypothesize that the smoke was lifted into the UTLS height range by the so-called self-lifting process . Details are given in Sect. . In this exceptional wildfire year 2019 , there were numerous other fires within the Arctic Circle (e.g. in Alaska, Greenland, and northern Canada). However, it seems, so far, that none of them was strong enough to contribute to a noticeable enhancement of the AOT in the UTLS height range .

Once in the UTLS height range, smoke particles become quickly distributed over the entire northern part of the Northern Hemisphere within a few weeks, as observed and documented for the first time in 2001 and recently confirmed after the record-breaking Canadian fires in the summer of 2017 . The decay of the stratospheric perturbation by the Canadian smoke took more than a half-year after injection in August 2017 .

Importantly, in addition to the strong perturbation of the UTLS aerosol conditions, a record-breaking ozone depletion was observed over the Arctic in the spring of 2020 . To our best knowledge, a potential impact of stratospheric aerosol on the complex chemical and meteorological processes leading to this strong ozone reduction was, however, not discussed in any of the published studies. As the main reason for the extraordinarily large ozone depletion, the long-lasting 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 and sulfate layers influenced ozone depletion in the spring of 2020 remains an open question that needs 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.

In this article, we present the main results of the MOSAiC smoke observations. In Sect. , a brief description of the Polarstern lidar and the data analysis methods are given. Next, in Sect. , we illuminate and discuss the possibility that Siberian wildfire smoke was able to reach the UTLS height range. MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) lidar measurements provide the observational basis in our discussion. In this context, we were also forced to explain why the CALIPSO aerosol-typing scheme misclassified the wildfire smoke as volcanic sulfate aerosol . This is discussed in Sect.  as well. In Sect. , we present our MOSAiC smoke observations. We begin with October and November 2019 case studies and continue with an overview of all lidar observations from October 2019 to May 2020. Finally, in Sect. , we provide insight into the ozone, smoke, and polar–stratospheric–cloud conditions during the winter and spring months (2019–2020) to stimulate research on a potential impact of wildfire smoke on the record-breaking ozone depletion. A summary and concluding remarks are given in Sect. . An introduction to our entire MOSAiC measurement programme and our research goals is provided by .

During the 1-year MOSAiC expedition the multiwavelength polarization Raman lidar Polly POrtabLe Lidar sYstem; was continuously operated on board the 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 2019 to the beginning of April 2020, the research vessel was north of 85∘ N and reached the maximum northern latitude of 88.6∘ N on 20 February 2020. A photograph of the Polarstern in the ice and snow-covered Arctic Ocean, together with a photograph of the main ship-based MOSAiC atmospheric measurement platforms on board the Polarstern, is shown in Fig. 2 in . A total of 6 containers for in situ aerosol monitoring and for active remote sensing of aerosols and clouds with lidars and radars were deployed on the front deck of the research vessel, including the ARM (Atmospheric Radiation Measurement) mobile facility AMF-1 .

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 on board Polarstern between Bremerhaven, Germany, and Cape Town, South Africa, and Punta Arenas, Chile , and was operated for the first time in the Arctic during a 2-month campaign in June and July 2017 . The OCEANET Polly instrument belongs to the lidar network PollyNET , which is part of the European Aerosol Research Lidar Network (EARLINET) organized within the Aerosols, Clouds and Trace gases Research InfraStructure (ACTRIS) project .

The set-up and basic technical details of the Polly instrument are given in . Linearly polarized laser pulses at 355, 532, and 1064 nm are transmitted into the atmosphere at an elevation angle of 85∘. The Polly instrument has 13 measurement channels (polarization-sensitive channels, elastic backscatter, and water vapour and nitrogen Raman channels for near-range and far-range profiling). Height profiles of the particle backscatter coefficient at the laser wavelengths, the particle extinction coefficient at 355 and 532 nm, the respective extinction-to-backscatter ratio (lidar ratio) at 355 and 532 nm, the particle linear depolarization ratio (PLDR) at 355 and 532 nm , and the mixing ratio of water vapour to dry air by using the Raman lidar return signals of water vapour and nitrogen can be determined.

The Raman lidar method was exclusively used to determine particle backscatter and extinction profiles up to 20 km height. The particle backscatter coefficient is obtained from the measured ratio of the elastic backscatter signal (355 and 532 nm) to the respective Raman signal (387 and 607 nm). The 1064 nm backscatter coefficient is calculated from the ratio of the 1064 nm elastic backscatter signal to the 607 nm nitrogen Raman signal. In the retrieval of the extinction coefficient, a least squares linear regression is applied to the respective Raman signal profiles. At heights above 20 km, the backscatter and extinction properties of the stratospheric background aerosol are determined from the elastic backscatter signal profiles (alone) by assuming a particle extinction-to-backscatter ratio (lidar ratio) of 50 sr . Calibration heights were generally set into the clean stratosphere (above 20 km height) and in the retrieval of background aerosol at about 35 km height. The backscatter signal intensities were always sufficiently above the detection limits for heights of 25–35 km. This means that the aerosol layers could always be fully resolved from base to top in terms of backscatter profiles.

The particle linear depolarization ratio (PLDR) is obtained from the cross-to-co-polarized signal ratio after the correction of Rayleigh contributions to light depolarization. The terms “co” and “cross” denote the planes of polarization parallel and orthogonal to the plane of linear polarization of the transmitted laser pulses, respectively. The depolarization ratio is observed at 355 and 532 nm and can be used to discriminate spherical particles (producing depolarization ratios close to zero) from nonspherical particles such as dust particles causing depolarization ratios around 0.3 at 532 nm;. In the case of Polly, the cross-polarized and total (cross-polarized + co-polarized) backscatter signals are measured. The specific approach to obtain the volume depolarization ratio (VDR) from the Polly observations is described by .

Different expressions for the Ångström exponent, a well-established parameter to characterize the spectral dependence of aerosol optical properties, are computed. The Ångström exponent Åx,λi,λj=ln⁡(xi/xj)/ln⁡(λj/λi) describes the wavelength dependence of an optical parameter x (backscatter β or extinction σ) in the spectral range from wavelength λi to λj.

Although PollyNET delivers automatically calculated profiles, the lidar observations were manually analysed for the smoke and aerosol layers. In order to accurately determine the optical properties with a high signal-to-noise ratio, temporal averaging over comparably long time periods of 2–6 h were usually necessary to obtain extinction profiles up to 17–20 km height. The basic elastic backscatter and Raman signal profiles were vertically smoothed with a window length of 457.5 m (61 height bins; 7.5 m vertical resolution) in the case of the backscatter and depolarization ratio computations. Particle extinction and extinction-to-backscatter ratio (lidar ratio) profiling is based on a least squares regression analysis . Here, we used regression window lengths of 2002.5 m (267 height bins) in the computations. Next, 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.

Polar stratospheric clouds (PSCs), which frequently developed during the winter months (December to February), disturbed the determination of the aerosol backscatter and extinction profiles. Fortunately, most PSCs formed at heights above 17 km, and the main part of the aerosol layer was below 17 km height, so that the removal of the PSC-affected aerosol profile segments had no large influence on the smoke and aerosol products. We used the 1064 nm signal profile to identify the PSC-affected parts (by visual inspection) and cut out the respective backscatter and extinction contributions from the lidar data set. We estimate that a residual PSC-related uncertainty is ≤  5 % in terms of the 532 nm AOT. Backscatter and extinction contributions from optically thin PSCs occurring within the aerosol layers were not removed. We will discuss the impact of PSC occurrence on our smoke observations in Sect. .

To obtain estimates of microphysical properties of the smoke particles such as mass, volume, and surface area concentration, a conversion method is available . The 532 nm particle backscatter coefficients are input in the retrieval process. In the case of the MOSAiC data analysis, the smoke backscatter coefficients are converted to smoke extinction profiles, the first step, by assuming a smoke lidar ratio of 85 sr at 532 nm (mean value of all observations from October 2019 to March 2020). In the second step, the extinction coefficients are converted to microphysical properties by respective smoke conversion factors. To obtain smoke mass concentrations, we assume a smoke particle density of 1.15 g cm-3 . investigated different smoke aerosols in the laboratory and found smoke particle densities of 1.1–1.4 g cm-3, with values of about 1.05 ± 0.15 g cm-3 for organic carbon and 1.8 g cm-3 for elemental carbon. reviewed many smoke studies and concluded that the smoke particle density is 1.0–1.9 g cm-3. Thus, in cases with 2 %–10 % of black carbon (BC), the overall smoke particle density should be in the range of 1.0–1.3 g cm-3.

As an alternative approach, the retrieval of microphysical properties from backscatter and extinction lidar data by inversion with regularization is available . In the MOSAiC data analysis, we used the method of . The determination of the particle volume size distribution, volume and surface area concentrations, and the complex refractive index (assumed to be wavelength independent in the retrieval) from a small number of measured backscatter (at 355, 532, and 1064 nm) and extinction coefficients (at 355 and 532 nm) is a nonlinear, inverse, ill-posed problem, i.e. solutions are nonunique and highly oscillating without the introduction of appropriate mathematical tools such as regularization. The single scattering albedo (SSA), defined as the ratio of scattering-to-extinction coefficient, is finally calculated from the retrieved particle size distribution and complex refractive index characteristics with an uncertainty of ± 0.05.

Table  provides an overview of the main lidar products, the selected vertical smoothing and regression window lengths, signal averaging time intervals, and uncertainties in the directly measured and derived microphysical aerosol properties. The uncertainties in the lidar products are obtained from simulation studies, error propagation analysis, and comparison with ground-based Sun photometer and in situ measurements or airborne in situ measurements e.g.. The volume size distribution, not listed in Table  as product, can be derived with high accuracy, especially in cases of pronounced accumulation modes. In situ observations clearly show that size distributions of aged smoke particles are monomodal .

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 h throughout the entire MOSAiC period .

Additionally, we compare the Polly observations with Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) data and also with measurements with the Spitsbergen lidar KARL Koldewey Aerosol Raman Lidar;. 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 MOSAiC ozone profiles measured with ozonesondes launched on Polarstern, following a regular schedule from October 2019 to May 2020 .

For our studies of the smoke in the UTLS height range, a good knowledge of the tropopause height is important. The tropopause was computed from the MOSAiC radiosonde temperature and pressure profiles by using the approach of the Global Modelling and Assimilation Office (GMAO), Goddard Space Flight Centre, Greenbelt, Maryland, USA . In this approach, the tropopause height zTP is found from the height profile of the difference αT(z)-log⁡10p(z) with α=0.03, temperature T (in Kelvin), pressure p (hectopascals; hereafter hPa), and height z (metres). The tropopause pressure p(zTP) 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 zTP was not assigned. The obtained tropopause heights agree well with the ones we obtain by applying the definition of the World Meteorological Organization to the radiosonde temperature profiles and considering refinements in the determination described by . In most cases, the GMAO approach delivers 20–80 m lower tropopause levels and produces fewer outliers.

From the first day of the MOSAiC observations in late September 2019, we observed a prominent and well-aged stratospheric aerosol layer with a broad maximum (in terms of backscattering) around 10 km height, just above the local tropopause. The layer showed smooth internal structures and clear wildfire smoke signatures up to about 12–13 km height, according to our Raman lidar observations. Further lidar observations at Leipzig (51.3∘ N, 12.4∘ E), Germany , and Ny-Ålesund, Svalbard (78.9∘ N, 11.9∘ E), Norway, indicated a strong increase in the UTLS AOT in August 2019, which cannot be explained by the conversion of SO2 plumes originating from the Raikoke volcanic eruption into sulfate aerosol. The emitted volcanic SO2 plumes were converted to sulfuric-acid-containing water droplets (about 75 % H2SO4 and 25 % H2O) within a few weeks after the eruption in June 2019. The maximum stratospheric sulfate aerosol load occurred in the first half of August 2019, followed by a decrease in the aerosol pollution from September to December 2019 by about a factor of 2 .

Based on a detailed study of the stratospheric perturbation after the eruption of the Sarychev Peak volcano (48.1∘ N, 153.2∘ E; a neighbour volcano of Raikoke) in June 2009 by , and the fact that the Raikoke SO2 emission was 20 % higher than the SO2 amount reaching the stratosphere after the Sarychev eruption, we expected a sulfate AOT at 550 nm of about 0.01 over the High Arctic in November 2019 and around 0.005 during the main winter months. The maximum Sarychev-related 550 nm AOT was 0.02, and the e-folding decay time of the stratospheric perturbation was about 80 ± 10 d. Observations of the maximum Raikoke sulfate AOT of 0.025 (mean value for the latitudinal belt from 40–55∘ N in August 2019 at a minimum influence of smoke contributions) and modelling studies of the decrease in the Raikoke sulfate AOT by a factor of 2 from August to October 2019 presented by corroborated our assumption and are in good agreement with respective decay studies of the Sarychev-related stratospheric perturbation presented by .

Most of the volcanic sulfate aerosol formed at heights above 13–15 km, according to ground-based lidar observations over Leipzig and the UK and the spaceborne CALIPSO lidar observations over the Northern Hemisphere. On the other hand, the main smoke layer was found between 6 and 12 km height over the Polarstern, with maximum backscatter values around 10 km height. It is, thus, likely that the aerosol traces above 13–15 km height, visible in the backscatter profiles up to 17–19 km height during the MOSAiC campaign, were caused by volcanic aerosol.

The strong changes in the UTLS aerosol load, as observed over Leipzig and Ny-Ålesund in August 2019, pointed to the extraordinarily strong and long-lasting forest fires in central and eastern Siberian in July and August 2019 . Figure  visualizes the tremendous environmental disaster over the central and eastern parts of Siberia at the end of July 2019. Several large fire centres are visible north, northwest, and northeast of Lake Baikal (53.5∘ N, 108∘ E), within an area of roughly 1000 km × 2000 km (95–125∘ E). The time series of monthly mean AOT (550 nm) in Fig. , measured with MODIS on board Aqua and Terra over the last 20 years, indicates that the fire season in 2019 belongs to the strongest during the last 2 decades.

An overview of the smoke situation in terms of mean AOT (for the time period from 20 July to 20 August 2019) is given in Fig. . We performed a very careful MODIS data analysis, taking all sensitive error sources (especially cloud interference) into consideration . The heaviest fires occurred in the region indicated by box 1 (about 650 km × 750 km), located directly north of Lake Baikal (53.5∘ N, 108∘ E). Many of the mean AOT values (average of the 27 d long main fire period) exceeded 1.5 and, over some regions, even 2.0. The daily time series of the area mean 550 nm AOT for the main fire centres in Fig.  shows that the AOT (in box 1) ranged from 1 to 2.5 over a 7 d period (in July 2019) and was continuously > 1 for more than 8 d in August 2019. HYSPLIT 10 d backward trajectories (not shown) indicated stagnant atmospheric conditions (low wind speeds throughout the troposphere) within box 1, especially from 24 to 27 July 2019 . As indicated in Fig. , the smoke obviously accumulated during these low wind conditions in box 1, so that the daily mean 550 nm AOT steadily increased from 0.4 (21 July) to 2.7 (27 July 2019).

We theorize that self-lifting of the smoke was initiated at these favourable stagnant conditions, and this led to the ascent of optically dense aerosol layers. Strong absorption of solar radiation by the black-carbon-containing smoke heated the surrounding air in lofted smoke plumes, which were injected into heights of 3–5 km before. The created buoyancy then forced the plumes to further ascend up to the upper troposphere (up to the tropopause at around 10 km). This is the only plausible explanation for an efficient vertical transport over several kilometres in the absence of pyroCb convection. It is well accepted that pyroCb convection can lift large amounts of wildfire smoke into the lower stratosphere . However, from mid-July to mid-August 2019, vigorous thunderstorms over the burning areas in Siberia did not develop.

argue that prolific pyroCb activity caused the lifting of Siberian smoke into the stratosphere in July and August 2019. We cannot confirm this statement. We checked the available satellite observations over central and eastern Siberia and found no evidence for any noticeable impact of strong cumulus convection and thunderstorm activity over the Siberian fire places on vertical smoke transport. For this reason, we introduced the self-lifting process as the missing link between the Siberian fires in the summer 2019 and the observed stratospheric wildfire smoke layer in late summer, autumn, and winter.

The CALIPSO lidar observations in Fig.  corroborate our hypothesis. Smoke layers were observed with the spaceborne lidar in the direct neighbourhood of the intense fire areas (box 2 in Fig. ) up to the tropopause at 10 km on 26 July 2019 at 21:00 UTC. All layers above the tropopause very likely indicate Raikoke-related volcanic aerosol. The backward trajectories in Fig.  provide an impression of the stagnant smoke conditions below the CALIPSO flight track. Trajectories arriving at 3 and 7 km height show a direct smoke transport from box 2 to the flight track of the CALIPSO lidar. The trajectory for the arrival height of 9 km (and all trajectories arriving higher up) was not in direct contact with the smoke sources, i.e. a direct smoke uptake during the travel over the fire region was not possible. Thus, the smoke detected by the CALIPSO lidar around 9–10 km height must have been lifted by several kilometres before.

Self-lifting processes were reported several times after major wildfire events ; however, these were for stratospheric smoke layers only. To our best knowledge, there is no report in the literature on observed self-lifting processes in the troposphere up to the tropopause. The unique stagnant weather conditions, i.e. the absence of strong winds and wind shear, may be one of the key prerequisites for starting well-organized self-lifting processes within the troposphere. When these lifted smoke plumes are advected away from the source regions afterwards, meteorological processes around the jet stream will result in mixing of the smoke into the lowermost stratosphere.

This new aspect of tropospheric self-lifting will be illuminated in detail in a follow-up article based on extensive simulation studies. Here, we present a first result (Fig. ) to provide an impression of how much time it takes to lift wildfire smoke at cloud-free or cloudy conditions from the smoke injection heights (e.g. 3–5 km) to UTLS heights of 9–10 km (tropopause level at 10 km in the simulation). We used the radiative transfer model ecRAD to compute the heating rates, and subsequently, we computed ascent rates as a function of these heating rates for given potential temperature gradients . In Fig. , a smoke layer (with a Gaussian shape in terms of light extinction profile), initially centred at 4 km height, was simulated. The daily course of the Sun for summertime conditions at 65∘ N was considered. According to Fig. , the 500 nm AOT increased from 0.5 to 2.5 from 22 to 26 July 2021 in box 1. This may indicate a day-by-day production of smoke layers, with a mean AOT of the order of 0.5 at stagnant conditions. The smoke started to ascend and did not leave the tropospheric column for several days, so that the AOT increased steadily over days. The lifting of such smoke layers with 500 nm AOT of 0.5, and of layers with AOT of 1.0, is simulated in Fig. . The BC fraction was set to 15 %, 7.5 %, and 5 % during the first 12 h, the next 12 h, and for the rest of the simulation period, respectively, to roughly consider particle ageing during the first 24–36 h after injection. For simplicity, we used the layer mean heating rate, together with the potential temperature gradient (radiosonde; Olenek, Siberia; July–August mean temperature profile), to compute the lifting rates . However, it should be mentioned that the vertical profile of the heating rate at cloud-free conditions shows an inhomogeneous behaviour (not presented here), with stronger heating at the top and lowest heating at the base of the smoke layer so that a coherent ascent of a given smoke layer over several kilometres is not possible in reality. Instead, diffuse aerosol structures are more likely to develop and ascend with different speed.

As can be seen in Fig. , smoke can be lifted in stagnant conditions within about 2–6 d up to UTLS heights in the case of moderate smoke layer AOTs. In the case of the simulation with a closed cloud deck below the ascending smoke layer, the solar radiation available for absorption by the smoke layer (with a relatively low AOT) is a factor of 1.5–1.9 higher compared to cloud-free conditions because of the strong reflection of solar radiation by liquid water cloud layers (with albedo close to 1.0). Note that MODIS indicated rather inhomogeneous smoke-related AOT fields over central and eastern Siberia and north of the burning areas. The AOT partly exceeded 3.0 over large areas. Figure  thus provides only insight into typical self-lifting timescales for moderately enhanced AOT conditions. As mentioned, an interesting aspect is also that the heating of smoke layers is vertically inhomogeneous so that a coherent ascent of layers over days, even in rather stagnant conditions (no change of wind direction and speed with height), seems to be almost impossible in the troposphere. The resulting incoherent aerosol structures are visible in the CALIPSO observation in Fig. .

The comparably slow ascent (compared to fast lifting within 30–90 min in the case of pyroCb convection) and thus comparably long residence times in the humid troposphere (with high levels of condensable gases) has consequences for the chemical, microphysical, and optical properties of the smoke particles. At tropospheric conditions, fast particle ageing takes place and can be completed within 3–4 d. At the end of the particle ageing process, most of the smoke particles have developed a perfect spherical core shell structure, as clearly indicated by the low particle depolarization ratio measured with lidar. This, in turn, has consequences for a lidar-based aerosol-typing strategy and the discrimination of smoke from sulfate particles, as will be discussed in Sect. . The context of smoke ageing, changing morphological properties of smoke particles, and resulting optical properties is presented in .

Below, we summarize our key findings and the critical points to be considered as follows:

The self-lifting hypothesis is of key importance in our attempt to relate the MOSAiC UTLS smoke observations from October 2019 to May 2020 to the strong fires in Siberia in July–August 2019.

Figure  shows the track of the RV (research vessel) Polarstern from October 2019 to May 2020. The icebreaker was slowly drifting through the ice at latitudes ≥ 85∘ N for more than 7 months. The highest northern latitude, at 88.6∘ N was reached around 20 February 2020. Favourable weather conditions for lidar measurements up to the middle stratosphere were given most of the time. Note that the spaceborne CALIPSO lidar is blind for the region > 81.8∘ N.

Figure  shows that a strong polar vortex built up during the central winter months and controlled the weather and aerosol conditions from mid-December to May. According to , the wintertime westerly winds in the polar stratosphere (from about 15–50 km) were extraordinarily strong during the Northern Hemisphere winter of 2019–2020. As a consequence, very stable weather and airflow patterns prevailed below the vortex, and as a result, there were almost constant aerosol conditions in the UTLS height range throughout the winter.

In Fig. a, the time series of the scaled potential vorticity sPV; along the route of the Polarstern drift is presented. sPV is a useful quantity for detecting the polar vortex edge . ERA5 (ECMWF reanalysis of the global climate, fifth generation; ECMWF – European Centre for Medium-Range Weather Forecasts) data of the potential vorticity and temperature on the pressure fields of 30, 50, 70, 100, and 125 hPa were used in the computation of sPV by applying Eq. (2) in . A sPV value of >160×10-6 s-1 indicates that the Polarstern was below the polar vortex from January until 20 April 2020 when the vortex began to collapse.

In Fig. b, the temperatures for six height levels are shown. The temperatures continuously decreased with time. Favourable conditions for PSC formation at heights above 17 km were given in January and February 2020, when the temperatures dropped below -78∘C. The low variability in the temperature time series for heights below 18 km from mid-December 2019 to mid-April 2020 corroborates that the weather patterns were rather stable, and meridional air mass exchange was widely suppressed.

The following two facts motivated us to briefly discuss a potential impact of the UTLS aerosol on ozone depletion. First, a record-breaking ozone depletion was observed in the spring of 2020 , and second, at the same time, a strong perturbation of the stratospheric aerosol conditions occurred. The fact that a potential relationship between the high UTLS pollution levels and strong ozone reduction is not considered in any of the studies on ozone depletion mentioned above can be regarded as the third motivating aspect.

It is well known that strong ozone reduction is linked to the development of a strong and long-lasting polar vortex, which favours increased PSC formation. In these clouds, active chlorine components are produced via heterogeneous chemical processes on the surface of the PSC particles. Finally, the chlorine species destroy ozone molecules in the spring season. It is also known that volcanic sulfate aerosol particles can serve as sites for heterogeneous chemical reaction and can lead to an increased release of active chlorine components and, thus, contribute to an enhanced ozone reduction . We observed the impact of the Pinatubo aerosol on ozone depletion at midlatitudes (Leipzig and Lindenberg, Germany) in the winters of 1991–1992 and 1992–1993 and quantified the reduction as a function of the surface area concentration of the volcanic sulfate particles . We found an ozone loss of up to 30 % at sulfate particle surface area concentrations of 25–35 µm2 cm-3 in the central part of the volcanic sulfate layer during the first winter after the major volcanic eruption.

Thus, it seems to be reasonable to assume that the observed smoke and volcanic particles over the High Arctic also had an influence on the observed strong ozone reduction in the late winter and early spring months of 2019–2020. The difference, compared to sulfate particles, is that smoke particles in the stratosphere are most likely glassy, show a core shell morphology, and are largely composed of organic material (organic carbon – OC; in the shell) and, to a lesser extent, of black carbon (BC; concentrated in the core part). It is also possible that collisions and coagulation of smoke and volcanic aerosol particles partly led to internally mixed particles. All this complicates studies on the impact of the smoke-dominated Arctic aerosol in the stratosphere on ozone depletion occurring during the MOSAiC expedition.

As was pointed out by , there are two pathways to influence ozone depletion by aerosol pollution. The particles can influence the evolution of PSCs and specifically their microphysical properties number concentration and size distribution;, and on the other hand, the particles can be directly involved in heterogeneous chemical processes by increasing the particle surface area available to convert nonreactive chlorine components into reactive forms. A third (indirect) impact of smoke, when well distributed over large parts of the Northern or Southern hemispheres, is via the influence on large-scale atmospheric dynamics .

The goal of this section is just to compile all information we have regarding PSC occurrence, smoke and sulfate conditions, and ozone depletion during the MOSAiC campaign and to provide an extended view on the Arctic ozone conditions in the winter half-year of 2019–2020 based on CALIPSO PSC observations, our MOSAiC aerosol and PSC observations, and MOSAiC ozone profiles measured with sondes launched from Polarstern. These data may serve as a stimulating guide for modelling teams to clarify the role of smoke in the complex ozone depletion processes.

Figure a shows the polar vortex characteristics for the winter season (2019–2020). The strong, cold, and persistent polar vortex controlled the atmospheric conditions above 15 km height from January to April–May 2020. The MOSAiC and CALIPSO measurements are shown in Fig. . In total, 40 ozone sondes were launched during the 7-month period from October 2019 to May 2020 . Out of the 40 sondes, 13 were launched from the beginning of March to mid-April 2020 and, thus, during the main period with lowest ozone concentration.

We analysed the CALIPSO observations in the latitudinal belt from 60 to 80∘ N on a daily basis. The black lines in Fig. a 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 4 times a day on board the Polarstern, the lowest temperatures occurred between 15 and 27 km height in the central winter (December 2019 to March 2020). The PSC-relevant temperatures of <- 78 ∘C were found between 18 and 27 km height in December 2019 and continuously propagated downward to about 15–23 km height in early March 2020. This height range of low temperatures coincides well with the PSC height range in Fig. a and also with the respective PSC retrievals presented by .

In addition to the PSC height range, the time series of the UTLS aerosol layer base and top heights, as well as of the tropopause height, are shown in Fig. a. As can be seen in the composite figure, a layer with very low ozone partial pressure between 15 and 20 km height was observed above the Polarstern in March and April 2020 (until the polar vortex began to collapse around 20 April). This layer of low ozone concentration coincides with the PSC height range in which chlorine activation occurred in the months before. The UTLS aerosol layer, extending roughly from the tropopause to 15–18 km height, did not overlap with the region with very low ozone concentration in the spring of 2020, and also not with the PSC height range until mid-January 2020.

To obtain a more detailed picture on ozone depletion during the winter and spring season (2019–2020), Fig. b presents ozone deviations from the long-term mean values, as discussed by , together with PSC and smoke layer information. used a reanalysis data set produced by the Copernicus Atmosphere Monitoring service (CAMS; reanalysis; 2003–2019) to describe the evolution of the 2020 Arctic ozone season and to compare it with years dating back to 2003. 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. We notice a clear link between PSC occurrence and anomalously large ozone reduction. But we see also a large vertical overlap between the UTLS aerosol layer and the height range, with strong negative ozone deviations at heights as low as 9–10 km. This was also confirmed by . The height range with significant ozone anomalies reached down to unusually low heights and, thus, to heights where smoke and, to a lesser extent, volcanic sulfate particles were permanently present. Surface area concentrations of the smoke particles were of the order of 5–15 µm2 cm-3 at 10–12 km height from January to April 2020 and, thus, in the same range of values for Arctic PSCs (as shown in Fig. ). In April 2020 (not shown), PSCs were no longer observed; however, the UTLS aerosol layer was still present. All in all, Fig.  may motivate model-based studies on the interplay between smoke, sulfate particles, PSCs, and ozone depletion. A first fruitful approach was presented by , with a focus on the impact of volcanic sulfate aerosol.

To provide some numbers regarding the potential aerosol impact on the observed ozone depletion via heterogeneous chemical processes on and in the particles, we compare our Pinatubo observations in central Europe in the winter of 1991–1992 with the MOSAiC ozone and aerosol measurements in March 2020 and our stratospheric smoke observations over Punta Arenas, southern Chile at 53∘ S in September 2020 when the record-breaking ozone hole over Antarctica developed. In the first winter after the major Pinatubo volcanic eruptions, the surface area concentration of the sulfate particles was as high as 20–35 µm2 cm-3 in the height range from 15–20 km height, and the ozone reduction (compared to the climatological mean) was of the order of 15 %–30 %. In March 2020, we measured smoke particle surface area concentrations of 5–10 µm2 cm-3 in 10–12 km height over the North Pole region. The ozone loss was 20 %–25 % in this height range, according to Fig. b taken from . Finally, after the strong Australian bushfires in December 2019 and January 2020 , we measured smoke surface area concentrations of the order of 1–5 µm2 cm-3 over Punta Arenas in the height range from 14–22 km, with large ozone depletion in September 2020 (9 months after injection), and according to preliminary simulations (assuming that sulfate and smoke particles show similar chlorine-activation efficiencies), the aerosol-induced ozone loss was about 5 % . These numbers indicate that additional aerosol in the usually clean stratosphere is able to lead to an additional ozone loss of the order of 5 %–10 % (and more) so that events of strong ozone reduction may become record-breaking events. In September 2021, again strong ozone depletion was observed over Antarctica at still significantly enhanced stratospheric smoke levels as our ongoing lidar observations indicate.

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. To the best of our knowledge, such a strong perturbation of the stratospheric aerosol conditions in the High Arctic has never been reported before. We hypothesized that the detected smoke originated from strong, long-lasting wildfires in Siberia in July and August 2019. Importantly, a month earlier, the Raikoke volcano erupted, and the resulting stratospheric sulfuric acid aerosol layers also covered large parts of the Northern Hemisphere. However, using lidar measurements during our field campaign and modelling efforts presented in the literature, we showed that the volcanic aerosol could not explain the observed strong perturbation of the stratospheric aerosol layer in the High Arctic with AOTs of the order of 0.1. The Raikoke-related AOT fraction at 532 nm was estimated to always be lower than 15 %. In particular, our analyses suggest that self-lifting effects (in the absence of pyroCb convection) caused the spread of smoke up to tropopause heights above Siberia.

We indirectly emphasized (without stating that explicitly) the need for a multiwavelength polarization Raman lidar, such as the Polarstern Polly operated during the MOSAiC expedition, to unambiguously identify the prevailing aerosol type based on the spectral dependence of the lidar ratio. 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 is typical for light-absorbing smoke. The extinction-related 355–532 nm Ångström exponent of around 0.65 also clearly indicated that smoke particles dominated. We were able to develop a coherent picture of aerosol structures and layering features for the autumn and winter seasons up to 30 km height. In the next step, we will analyse the MOSAiC lidar observations of the summer half-year to fully cover the annual cycle of Arctic aerosol conditions as a function of height.

In this article, we also discussed the potential impact of the wildfire smoke and sulfate aerosol on the record-breaking ozone depletion over the Arctic in the spring of 2020, based on vertically resolved information on PSC and smoke and sulfate aerosol occurrence and the strength of the ozone depletion. The preliminary discussions may stimulate in-depth modelling studies to clarify the role of the UTLS aerosol in stratospheric PSC formation and ozone reduction processes. In the case of the strong Australian bushfires, we observed a very clear coincidence of the Australian smoke layer and the layer with record-breaking ozone destruction over the southern parts of South America. If follow-on studies indicate a link between huge fires (caused by unusually hot temperatures and droughts as a result of climate change), corresponding smoke occurrence in the 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 yet considered important aspect.

As an outlook, we will explore the potential of wildfire smoke to influence cirrus formation during the winter half-year. A first case study was discussed in . 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 anthropogenic haze mixed with mineral dust from Asia, Europe, and North America, as well as episodic wildfire smoke events, prevailed.