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.
Abstract. The Hybrid End-To-End Aerosol Classification (HETEAC) model for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is introduced. The model serves as the common baseline for development, evaluation, and implementation of EarthCARE algorithms. It guarantees the consistency of different aerosol products from the multi-instrument platform and facilitates the conform specification of broad-band optical properties needed for EarthCARE radiative closure assessments. While the hybrid approach ensures that the theoretical description of aerosol microphysical properties is consistent with the optical properties of the measured aerosol types, the end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical, and radiative properties. Four basic aerosol components with prescribed microphysical properties are used to compose various natural and anthropogenic aerosols of the troposphere. The components contain weakly and strongly absorbing fine-mode as well as spherical and non-spherical coarse-mode particles and thus are representative for pollution, smoke, sea salt, and dust, respectively. Their microphysical properties are selected such that a good coverage of the observational phase space of intensive, i.e., concentration-independent, optical aerosol properties derived from EarthCARE measurements is obtained. Mixing rules to calculate optical and radiative properties of any aerosol blend composed of the four basic components are provided. Applications of HETEAC in the generation of test scenes, the development of retrieval algorithms for stand-alone and synergistic aerosol products from EarthCARE's Atmospheric Lidar (ATLID) and Multi-Spectral Imager (MSI), as well as for radiative closure assessments are discussed. In the end, conclusions for future development work are drawn.
Abstract. The Hybrid End-To-End Aerosol Classification (HETEAC) model for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is introduced. The model serves as the common baseline for the development, evaluation, and implementation of EarthCARE algorithms. It guarantees the consistency of different aerosol products from the multi-instrument platform and facilitates the conformity of broad-band optical properties needed for EarthCARE radiative-closure assessments. While the hybrid approach ensures that the theoretical description of aerosol microphysical properties is consistent with the optical properties of the measured aerosol types, the end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical, and radiative properties. Four basic aerosol components with prescribed microphysical properties are used to compose various natural and anthropogenic aerosols of the troposphere. The components contain weakly and strongly absorbing fine-mode and spherical and non-spherical coarse-mode particles and thus are representative for pollution, smoke, sea salt, and dust, respectively. Their microphysical properties are selected such that good coverage of the observational phase space of intensive, i.e., concentration-independent, optical aerosol properties derived from EarthCARE measurements is obtained. Mixing rules to calculate optical and radiative properties of any aerosol blend composed of the four basic components are provided. Applications of HETEAC in the generation of test scenes, the development of retrieval algorithms for stand-alone and synergistic aerosol products from EarthCARE's atmospheric lidar (ATLID) and multi-spectral imager (MSI), and for radiative-closure assessments are introduced. Finally, the implications of simplifying model assumptions and possible improvements are discussed, and conclusions for future validation and development work are drawn.
In this paper, we present long-term observations of the multiwavelength Raman lidar PollyXT conducted in the framework of the DACAPO-PESO campaign. Regardless of the relatively clean atmosphere in the southern mid-latitude oceans region, we regularly observed events of long-range transported smoke, originating either from regional sources in South America or from Australia. Two case studies will be discussed, both identified as smoke events that occurred on 5 February 2019 and 11 March 2019. For the first case considered, the lofted smoke layer was located at an altitude between 1.0 and 4.2 km, and apart from the predominance of smoke particles, particle linear depolarization values indicated the presence of dust particles. Mean lidar ratio values at 355 and 532 nm were 49 ± 12 and 24 ± 18 sr respectively, while the mean particle linear depolarization was 7.6 ± 3.6% at 532 nm. The advection of smoke and dust particles above Punta Arenas affected significantly the available cloud condensation nuclei (CCN) and ice nucleating particles (INP) in the lower troposphere, and effectively triggered the ice crystal formation processes. Regarding the second case, the thin smoke layers were observed at altitudes 5.5–7.0, 9.0 and 11.0 km. The particle linear depolarization ratio at 532 nm increased rapidly with height, starting from 2% for the lowest two layers and increasing up to 9.5% for the highest layer, indicating the possible presence of non-spherical coated soot aggregates. INP activation was effectively facilitated. The long-term analysis of the one year of observations showed that tropospheric smoke advection over Punta Arenas occurred 16 times (lasting from 1 to 17 h), regularly distributed over the period and with high potential to influence cloud formation in the otherwise pristine environment of the region.
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