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Development of the DRoplet Ice Nuclei Counter Zurich (DRINCZ): validation and application to field-collected snow samples
Type of publication
Peer-reviewed
Publikationsform
Original article (peer-reviewed)
Author
David Robert O., Cascajo-Castresana Maria, Brennan Killian P., Rösch Michael, Els Nora, Werz Julia, Weichlinger Vera, Boynton Lin S., Bogler Sophie, Borduas-Dedekind Nadine, Marcolli Claudia, Kanji Zamin A.,
Project
Elucidating Ice Nucleation Mechanisms Relevant to the Atmosphere: Is deposition nucleation really immersion freezing in pores?
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Original article (peer-reviewed)
Journal
Atmospheric Measurement Techniques
Volume (Issue)
12(12)
Page(s)
6865 - 6888
Title of proceedings
Atmospheric Measurement Techniques
DOI
10.5194/amt-12-6865-2019
Open Access
URL
http://doi.org/10.5194/amt-12-6865-2019
Type of Open Access
Publisher (Gold Open Access)
Abstract
Abstract. Ice formation in the atmosphere is important for regulating cloud lifetime, Earth's radiative balance and initiating precipitation. Due to the difference in the saturation vapor pressure over ice and water, in mixed-phase clouds (MPCs), ice will grow at the expense of supercooled cloud droplets. As such, MPCs, which contain both supercooled liquid and ice, are particularly susceptible to ice formation. However, measuring and quantifying the concentration of ice-nucleating particles (INPs) responsible for ice formation at temperatures associated with MPCs is challenging due to their very low concentrations in the atmosphere (∼1 in 105 at −30 ∘C). Atmospheric INP concentrations vary over several orders of magnitude at a single temperature and strongly increase as temperature approaches the homogeneous freezing threshold of water. To further quantify the INP concentration in nature and perform systematic laboratory studies to increase the understanding of the properties responsible for ice nucleation, a new drop-freezing instrument, the DRoplet Ice Nuclei Counter Zurich), is developed. The instrument is based on the design of previous drop-freezing assays and uses a USB camera to automatically detect freezing in a 96-well tray cooled in an ethanol chilled bath with a user-friendly and fully automated analysis procedure. Based on an in-depth characterization of DRINCZ, we develop a new method for quantifying and correcting temperature biases across drop-freezing assays. DRINCZ is further validated performing NX-illite experiments, which compare well with the literature. The temperature uncertainty in DRINCZ was determined to be ±0.9 ∘C. Furthermore, we demonstrate the applicability of DRINCZ by measuring and analyzing field-collected snow samples during an evolving synoptic situation in the Austrian Alps. The field samples fall within previously observed ranges for cumulative INP concentrations and show a dependence on air mass origin and upstream precipitation amount.
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