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    Leipzig Ice Nucleation chamber Comparison (LINC): Intercomparison of four online ice nucleation counters
    (Katlenburg-Lindau : EGU, 2017) Burkert-Kohn, Monika; Wex, Heike; Welti, André; Hartmann, Susan; Grawe, Sarah; Hellner, Lisa; Herenz, Paul; Atkinson, James D.; Stratmann, Frank; Kanji, Zamin A.
    Ice crystal formation in atmospheric clouds has a strong effect on precipitation, cloud lifetime, cloud radiative properties, and thus the global energy budget. Primary ice formation above 235 K is initiated by nucleation on seed aerosol particles called ice-nucleating particles (INPs). Instruments that measure the ice-nucleating potential of aerosol particles in the atmosphere need to be able to accurately quantify ambient INP concentrations. In the last decade several instruments have been developed to investigate the ice-nucleating properties of aerosol particles and to measure ambient INP concentrations. Therefore, there is a need for intercomparisons to ensure instrument differences are not interpreted as scientific findings. In this study, we intercompare the results from parallel measurements using four online ice nucleation chambers. Seven different aerosol types are tested including untreated and acid-treated mineral dusts (microcline, which is a K-feldspar, and kaolinite), as well as birch pollen washing waters. Experiments exploring heterogeneous ice nucleation above and below water saturation are performed to cover the whole range of atmospherically relevant thermodynamic conditions that can be investigated with the intercompared chambers. The Leipzig Aerosol Cloud Interaction Simulator (LACIS) and the Portable Immersion Mode Cooling chAmber coupled to the Portable Ice Nucleation Chamber (PIMCA-PINC) performed measurements in the immersion freezing mode. Additionally, two continuous-flow diffusion chambers (CFDCs) PINC and the Spectrometer for Ice Nuclei (SPIN) are used to perform measurements below and just above water saturation, nominally presenting deposition nucleation and condensation freezing. The results of LACIS and PIMCA-PINC agree well over the whole range of measured frozen fractions (FFs) and temperature. In general PINC and SPIN compare well and the observed differences are explained by the ice crystal growth and different residence times in the chamber. To study the mechanisms responsible for the ice nucleation in the four instruments, the FF (from LACIS and PIMCA-PINC) and the activated fraction, AF (from PINC and SPIN), are compared. Measured FFs are on the order of a factor of 3 higher than AFs, but are not consistent for all aerosol types and temperatures investigated. It is shown that measurements from CFDCs cannot be assumed to produce the same results as those instruments exclusively measuring immersion freezing. Instead, the need to apply a scaling factor to CFDCs operating above water saturation has to be considered to allow comparison with immersion freezing devices. Our results provide further awareness of factors such as the importance of dispersion methods and the quality of particle size selection for intercomparing online INP counters.
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    Significant continental source of ice-nucleating particles at the tip of Chile's southernmost Patagonia region
    (Katlenburg-Lindau : EGU, 2022) Gong, Xianda; Radenz, Martin; Wex, Heike; Seifert, Patric; Ataei, Farnoush; Henning, Silvia; Baars, Holger; Barja, Boris; Ansmann, Albert; Stratmann, Frank
    The sources and abundance of ice-nucleating particles (INPs) that initiate cloud ice formation remain understudied, especially in the Southern Hemisphere. In this study, we present INP measurements taken close to Punta Arenas, Chile, at the southernmost tip of South America from May 2019 to March 2020, during the Dynamics, Aerosol, Cloud, And Precipitation Observations in the Pristine Environment of the Southern Ocean (DACAPO-PESO) campaign. The highest ice nucleation temperature was observed at −3◦C, and from this temperature down to ∼ −10◦C, a sharp increase of INP number concentration (NINP) was observed. Heating of the samples revealed that roughly 90 % and 80 % of INPs are proteinaceous-based biogenic particles at > −10 and −15◦C, respectively. The NINP at Punta Arenas is much higher than that in the Southern Ocean, but it is comparable with an agricultural area in Argentina and forestry environment in the US. Ice active surface site density (ns) is much higher than that for marine aerosol in the Southern Ocean, but comparable to English fertile soil dust. Parameterization based on particle number concentration in the size range larger than 500 nm (N>500 nm) from the global average (DeMott et al., 2010) overestimates the measured INP, but the parameterization representing biological particles from a forestry environment (Tobo et al., 2013) yields NINP comparable to this study. No clear seasonal variation of NINP was observed. High precipitation is one of the most important meteorological parameters to enhance the NINP in both cold and warm seasons. A comparison of data from in situ and lidar measurements showed good agreement for concentrations of large aerosol particles (> 500 nm) when assuming continental conditions for retrieval of the lidar data, suggesting that these particles were well mixed within the planetary boundary layer (PBL). This corroborates the continental origin of these particles, consistent with the results from our INP source analysis. Overall, we suggest that a high NINP of biogenic INPs originated from terrestrial sources and were added to the marine air masses during the overflow of a maximum of roughly 150 km of land before arriving at the measurement station.
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    Phase transition observations and discrimination of small cloud particles by light polarization in expansion chamber experiments
    (München : European Geopyhsical Union, 2016) Nichman, Leonid; Fuchs, Claudia; Järvinen, Emma; Ignatius, Karoliina; Höppel, Niko Florian; Dias, Antonio; Heinritzi, Martin; Simon, Mario; Tröstl, Jasmin; Wagner, Andrea Christine; Wagner, Robert; Williamson, Christina; Yan, Chao; Connolly, Paul James; Dorsey, James Robert; Duplissy, Jonathan; Ehrhart, Sebastian; Frege, Carla; Gordon, Hamish; Hoyle, Christopher Robert; Kristensen, Thomas Bjerring; Steiner, Gerhard; McPherson Donahue, Neil; Flagan, Richard; Gallagher, Martin William; Kirkby, Jasper; Möhler, Ottmar; Saathoff, Harald; Schnaiter, Martin; Stratmann, Frank; Tomé, António
    Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather, and general circulation models. The detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud particle-size range below 50 μm, remains challenging in mixed phase, often unstable environments. The Cloud Aerosol Spectrometer with Polarization (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure the variability in polarization state of their backscattered light. Here we operate the versatile Cosmics Leaving OUtdoor Droplets (CLOUD) chamber facility at the European Organization for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water, and ice particles. In this paper, optical property measurements of mixed-phase clouds and viscous secondary organic aerosol (SOA) are presented. We report observations of significant liquid–viscous SOA particle polarization transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarization ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulfate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentrations and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to tropical troposphere layer analysis.