Development of the DRoplet Ice Nuclei Counter Zurich (DRINCZ): validation and application to field-collected snow samples
Atmospheric Measurement Techniques Discussions(2019)
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 (similar to 1 in 10(5) at -30 degrees 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 degrees 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.
MoreTranslated text
Key words
snow,samples,field-collected
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined