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    Airborne observations of newly formed boundary layer aerosol particles under cloudy conditions
    (Katlenburg-Lindau : EGU, 2018) Altstädter, Barbara; Platis, Andreas; Jähn, Michael; Baars, Holger; Lückerath, Janine; Held, Andreas; Lampert, Astrid; Bange, Jens; Hermann, Markus; Wehner, Birgit
    This study describes the appearance of ultrafine boundary layer aerosol particles under classical “non-favourable” conditions at the research site of TROPOS (Leibniz Institute for Tropospheric Research). Airborne measurements of meteorological and aerosol properties of the atmospheric boundary layer (ABL) were repeatedly performed with the unmanned aerial system ALADINA (Application of Light-weight Aircraft for Detecting IN-situ Aerosol) during three seasons between October 2013 and July 2015. More than 100 measurement flights were conducted on 23 different days with a total flight duration of 53 h. In 26 % of the cases, maxima of ultrafine particles were observed close to the inversion layer at altitudes between 400 and 600 m and the particles were rapidly mixed vertically and mainly transported downwards during short time intervals of cloud gaps. This study focuses on two measurement days affected by low-level stratocumulus clouds, but different wind directions (NE, SW) and minimal concentrations (< 4.6 µg m−3) of SO2, as a common indicator for precursor gases at ground. Taken from vertical profiles, the onset of clouds led to a non-linearity of humidity that resulted in an increased turbulence at the local-scale and caused fast nucleation (e.g. Bigg, 1997; Wehner et al., 2010), but in relation to rapid dilution of surrounding air, seen in sporadic clusters of ground data, so that ultrafine particles disappeared in the verticality. The typical “banana shape” (Heintzenberg et al., 2007) of new particle formation (NPF) and growth was not seen at ground and thus these days might not have been classified as NPF event days by pure surface studies.
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    Long-term study on coarse mode aerosols in the Amazon rain forest with the frequent intrusion of Saharan dust plumes
    (Katlenburg-Lindau : EGU, 2018) Moran-Zuloaga, Daniel; Ditas, Florian; Walter, David; Saturno, Jorge; Brito, Joel; Carbone, Samara; Chi, Xuguang; Hrabě de Angelis, Isabella; Baars, Holger; Godoi, Ricardo H. M.; Heese, Birgit; Holanda, Bruna A.; Lavrič, Jošt V.; Martin, Scot T.; Ming, Jing; Pöhlker, Mira L.; Ruckteschler, Nina; Su, Hang; Wang, Yaqiang; Wang, Qiaoqiao; Wang, Zhibin; Weber, Bettina; Wolff, Stefan; Artaxo, Paulo; Pöschl, Ulrich; Andreae, Meinrat O.; Pöhlker, Christopher
    In the Amazonian atmosphere, the aerosol coarse mode comprises a complex, diverse, and variable mixture of bioaerosols emitted from the rain forest ecosystem, long-range transported Saharan dust (we use Sahara as shorthand for the dust source regions in Africa north of the Equator), marine aerosols from the Atlantic Ocean, and coarse smoke particles from deforestation fires. For the rain forest, the coarse mode particles are of significance with respect to biogeochemical and hydrological cycling, as well as ecology and biogeography. However, knowledge on the physicochemical and biological properties as well as the ecological role of the Amazonian coarse mode is still sparse. This study presents results from multi-year coarse mode measurements at the remote Amazon Tall Tower Observatory (ATTO) site. It combines online aerosol observations, selected remote sensing and modeling results, as well as dedicated coarse mode sampling and analysis. The focal points of this study are a systematic characterization of aerosol coarse mode abundance and properties in the Amazonian atmosphere as well as a detailed analysis of the frequent, pulse-wise intrusion of African long-range transport (LRT) aerosols (comprising Saharan dust and African biomass burning smoke) into the Amazon Basin.We find that, on a multi-year time scale, the Amazonian coarse mode maintains remarkably constant concentration levels (with 0.4 cmĝ'3 and 4.0 μg mĝ'3 in the wet vs. 1.2 cmĝ'3 and 6.5 μg mĝ'3 in the dry season) with rather weak seasonality (in terms of abundance and size spectrum), which is in stark contrast to the pronounced biomass burning-driven seasonality of the submicron aerosol population and related parameters. For most of the time, bioaerosol particles from the forest biome account for a major fraction of the coarse mode background population. However, from December to April there are episodic intrusions of African LRT aerosols, comprising Saharan dust, sea salt particles from the transatlantic passage, and African biomass burning smoke. Remarkably, during the core period of this LRT season (i.e., February-March), the presence of LRT influence, occurring as a sequence of pulse-like plumes, appears to be the norm rather than an exception. The LRT pulses increase the coarse mode concentrations drastically (up to 100 μg mĝ'3) and alter the coarse mode composition as well as its size spectrum. Efficient transport of the LRT plumes into the Amazon Basin takes place in response to specific mesoscale circulation patterns in combination with the episodic absence of rain-related aerosol scavenging en route. Based on a modeling study, we estimated a dust deposition flux of 5-10 kg haĝ'1 aĝ'1 in the region of the ATTO site. Furthermore, a chemical analysis quantified the substantial increase of crustal and sea salt elements under LRT conditions in comparison to the background coarse mode composition. With these results, we estimated the deposition fluxes of various elements that are considered as nutrients for the rain forest ecosystem. These estimates range from few g haĝ'1 aĝ'1 up to several hundreds of g haĝ'1 aĝ'1 in the ATTO region.The long-term data presented here provide a statistically solid basis for future studies of the manifold aspects of the dynamic coarse mode aerosol cycling in the Amazon. Thus, it may help to understand its biogeochemical relevance in this ecosystem as well as to evaluate to what extent anthropogenic influences have altered the coarse mode cycling already.
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    Helicopter-borne observations of the continental background aerosol in combination with remote sensing and ground-based measurements
    (Katlenburg-Lindau : EGU, 2018) Düsing, Sebastian; Wehner, Birgit; Seifert, Patric; Ansmann, Albert; Baars, Holger; Ditas, Florian; Henning, Silvia; Ma, Nan; Poulain, Laurent; Siebert, Holger; Wiedensohler, Alfred; Macke, Andreas
    This paper examines the representativeness of ground-based in situ measurements for the planetary boundary layer (PBL) and conducts a closure study between airborne in situ and ground-based lidar measurements up to an altitude of 2300 m. The related measurements were carried out in a field campaign within the framework of the High-Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in September 2013 in a rural background area of central Europe. The helicopter-borne probe ACTOS (Airborne Cloud and Turbulence Observation System) provided measurements of the aerosol particle number size distribution (PNSD), the aerosol particle number concentration (PNC), the number concentration of cloud condensation nuclei (CCN-NC), and meteorological atmospheric parameters (e.g., temperature and relative humidity). These measurements were supported by the ground-based 3+2 wavelength polarization lidar system PollyXT, which provided profiles of the particle backscatter coefficient (σbsc) for three wavelengths (355, 532, and 1064 nm). Particle extinction coefficient (σext) profiles were obtained by using a fixed backscatter-to-extinction ratio (also lidar ratio, LR). A new approach was used to determine profiles of CCN-NC for continental aerosol. The results of this new approach were consistent with the airborne in situ measurements within the uncertainties. In terms of representativeness, the PNSD measurements on the ground showed a good agreement with the measurements provided with ACTOS for lower altitudes. The ground-based measurements of PNC and CCN-NC are representative of the PBL when the PBL is well mixed. Locally isolated new particle formation events on the ground or at the top of the PBL led to vertical variability in the cases presented here and ground-based measurements are not entirely representative of the PBL. Based on Mie theory (Mie, 1908), optical aerosol properties under ambient conditions for different altitudes were determined using the airborne in situ measurements and were compared with the lidar measurements. The investigation of the optical properties shows that on average the airborne-based particle light backscatter coefficient is 50.1 % smaller for 1064 nm, 27.4 % smaller for 532 nm, and 29.5 % smaller for 355 nm than the measurements of the lidar system. These results are quite promising, since in situ measurement-based Mie calculations of the particle light backscattering are scarce and the modeling is quite challenging. In contrast, for the particle light extinction coefficient we found a good agreement. The airborne-based particle light extinction coefficient was just 8.2 % larger for 532 nm and 3 % smaller for 355 nm, for an assumed LR of 55 sr. The particle light extinction coefficient for 1064 nm was derived with a LR of 30 sr. For this wavelength, the airborne-based particle light extinction coefficient is 5.2 % smaller than the lidar measurements. For the first time, the lidar ratio of 30 sr for 1064 nm was determined on the basis of in situ measurements and the LR of 55 sr for 355 and 532 nm wavelength was reproduced for European continental aerosol on the basis of this comparison. Lidar observations and the in situ based aerosol optical properties agree within the uncertainties. However, our observations indicate that a determination of the PNSD for a large size range is important for a reliable modeling of aerosol particle backscattering.
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    Extreme levels of Canadian wildfire smoke in the stratosphere over central Europe on 21-22 August 2017
    (Katlenburg-Lindau : EGU, 2018) Ansmann, Albert; Baars, Holger; Chudnovsky, Alexandra; Mattis, Ina; Veselovskii, Igor; Haarig, Moritz; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
    Light extinction coefficients of 500 Mm1, about 20 times higher than after the Pinatubo volcanic eruptions in 1991, were observed by European Aerosol Research Lidar Network (EARLINET) lidars in the stratosphere over central Europe on 21-22 August 2017. Pronounced smoke layers with a 1-2 km vertical extent were found 2-5 km above the local tropopause. Optically dense layers of Canadian wildfire smoke reached central Europe 10 days after their injection into the upper troposphere and lower stratosphere which was caused by rather strong pyrocumulonimbus activity over western Canada. The smoke-related aerosol optical thickness (AOT) identified by lidar was close to 1.0 at 532 nm over Leipzig during the noon hours on 22 August 2017. Smoke particles were found throughout the free troposphere (AOT of 0.3) and in the pronounced 2 km thick stratospheric smoke layer at an altitude of 14-16 km (AOT of 0.6). The lidar observations indicated peak mass concentrations of 70-100 μgm-3 in the stratosphere. In addition to the lidar profiles, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power (FRP) over Canada, and the distribution of MODIS AOT and Ozone Monitoring Instrument (OMI) aerosol index across the North Atlantic. These instruments showed a similar pattern and a clear link between the western Canadian fires and the aerosol load over Europe. In this paper, we also present Aerosol Robotic Network (AERONET) sun photometer observations, compare photometer and lidar-derived AOT, and discuss an obvious bias (the smoke AOT is too low) in the photometer observations. Finally, we compare the strength of this recordbreaking smoke event (in terms of the particle extinction coefficient and AOT) with major and moderate volcanic events observed over the northern midlatitudes.
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    An automatic observation-based aerosol typing method for EARLINET
    (Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, Matthias
    We present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.