Abstract. We present particle optical properties of stratospheric smoke layers observed with multiwavelength polarization Raman lidar over Punta Arenas (53.2∘ S, 70.9∘ W), Chile, at the southernmost tip of South America in January 2020. The smoke originated from the record-breaking bushfires in Australia. The stratospheric aerosol optical thickness reached values up to 0.85 at 532 nm in mid-January 2020. The main goal of this rapid communication letter is to provide first stratospheric measurements of smoke extinction-to-backscatter ratios (lidar ratios) and particle linear depolarization ratios at 355 and 532 nm wavelengths. These aerosol parameters are important input parameters in the analysis of spaceborne CALIPSO and Aeolus lidar observations of the Australian smoke spreading over large parts of the Southern Hemisphere in January and February 2020 up to heights of around 30 km. Lidar and depolarization ratios, simultaneously measured at 355 and 532 nm, are of key importance regarding the homogenization of the overall Aeolus (355 nm wavelength) and CALIPSO (532 nm wavelength) lidar data sets documenting the spread of the smoke and the decay of the stratospheric perturbation, which will be observable over the entire year of 2020. We found typical values and spectral dependencies of the lidar ratio and linear depolarization ratio for aged stratospheric smoke. At 355 nm, the lidar ratio and depolarization ratio ranged from 53 to 97 sr (mean 71 sr) and 0.2 to 0.26 (mean 0.23), respectively. At 532 nm, the lidar ratios were higher (75–112 sr, mean 97 sr) and the depolarization ratios were lower with values of 0.14–0.22 (mean 0.18). The determined depolarization ratios for aged Australian smoke are in very good agreement with respective ones for aged Canadian smoke, observed with lidar in stratospheric smoke layers over central Europe in the summer of 2017. The much higher 532 nm lidar ratios, however, indicate stronger absorption by the Australian smoke particles.

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Abstract. We present particle optical properties of stratospheric smoke layers observed over Punta Arenas (53.2° S, 70.9° W), Chile, at the southernmost tip of South America in January 2020. The smoke originated from the record-breaking bushfires in Australia. The stratospheric aerosol optical thickness reached values up to 0.7 at 532 nm in mid January 2020. The measured smoke extinction-to-backscatter ratios (lidar ratios) and linear depolarization ratios at 355 and 532 nm wavelength indicate shape, size, and light-absorption properties and are important input parameters in the analysis of spaceborne lidar observations of the CALIPSO and Aeolus missions. They are also of key importance regarding the homogenization of the overall Aeolus (355 nm wavelength) and CALIPSO (532 nm wavelength) smoke data sets and interpretation of the observations with respect to the spread of the smoke particles across the southern hemisphere and decay of the stratospheric perturbation. We found typical values and spectral dependencies of the lidar ratio and linear depolarization ratio for aged stratospheric smoke. At 355 nm, the lidar ratio and depolarization ratio ranged from 53–97 sr and 0.2–0.26, respectively. At 532 nm, the lidar ratios were higher (76–104 sr) and the depolarization ratios were lower with values around 0.15. The found lidar ratio and depolarization ratio values for Australian smoke are in good agreement with respective ones obtained from observations of stratospheric smoke layers over central Europe originating from the record-breaking Canadian wildfires in the summer of 2017. The higher 532 nm lidar ratios, however, indicate stronger absorption by the Australian smoke particles.

In September 2020, extremely strong wildfires in the western United States of America (i.e., mainly in California) produced large amounts of smoke, which was lifted into the free troposphere. These biomass-burning-aerosol (BBA) layers were transported from the US west coast towards central Europe within 3-4 days turning the sky milky and receiving high media attention. The present study characterises this pronounced smoke plume above Leipzig, Germany, using a ground-based multiwavelength-Raman-polarization lidar and the aerosol/cloud product of ESA's wind lidar mission Aeolus. An exceptional high smoke-AOT > 0.4 was measured, yielding to a mean mass concentration of 8 µg m −3 .The 355 nm lidar ratio was moderate at around 40-50 sr. The Aeolus-derived backscatter, extinction and lidar ratio profiles agree well with the observations of the ground-based lidar PollyXT considering the fact that Aeolus aerosol and cloud products are still preliminary and subject to ongoing algorithm improvements.

Abstract. Height-resolved air mass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations, especially when using lidar (light detection and ranging) to investigate different aerosol types throughout the atmosphere. Lidar networks, such as EARLINET (European Aerosol Research Lidar Network) in the frame of ACTRIS (Aerosol, Clouds and Trace Gases), observe profiles of optical aerosol properties almost continuously, but usually, additional information is needed to support the characterization of the observed particles. This work presents an approach explaining how backward trajectories or particle positions from a dispersion model can be combined with geographical information (a land cover classification and manually defined areas) to obtain a continuous and vertically resolved estimate of an air mass source above a certain location. Ideally, such an estimate depends on as few as possible a priori information and auxiliary data. An automated framework for the computation of such an air mass source is presented, and two applications are described. First, the air mass source information is used for the interpretation of air mass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Second, air mass source statistics are calculated for two multi-week campaigns to assess potential observation biases of lidar-based aerosol statistics. Such an automated approach is a valuable tool for the analysis of short-term campaigns but also for long-term data sets, for example, acquired by EARLINET.