ALBERT

Description: 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.

Description: Ice-nucleating particles (INPs) produce ice from supercooled water droplets through heterogeneous freezing in the atmosphere. INPs have often been collected at the Jungfraujoch research station (at 3500 m a.s.l.) in central Switzerland; yet spatially diverse data on INP occurrence in the Swiss Alps are scarce and remain uncharacterized. We address this scarcity through our Swiss alpine snow sample study which took place during the winter of 2018. We collected a total of 88 fallen snow samples across the Alps at 17 different locations and investigated the impact of altitude, terrain, time since last snowfall and depth upon freezing temperatures. The INP concentrations were measured using the home-built DRoplet Ice Nuclei Counter Zurich (DRINCZ) and were then compared to spatial, temporal and physicochemical parameters. Boxplots of the freezing temperatures showed large variability in INP occurrence, even for samples collected 10 m apart on a plain and 1 m apart in depth. Furthermore, undiluted samples had cumulative INP concentrations ranging between 1 and 200 INP mL−1 of snowmelt over a temperature range of −5 to −19 ∘C. From this field-collected dataset, we parameterized the cumulative INP concentrations per cubic meter of air as a function of temperature with the following equation cair*(T)=e-0.7T-7.05, comparing well with previously reported precipitation data presented in Petters and Wright (2015). When assuming (1) a snow precipitation origin of the INPs, (2) a cloud water content of 0.4 g m−3 and (3) a critical INP concentration for glaciation of 10 m−3, the majority of the snow precipitated from clouds with glaciation temperatures between −5 and −20 ∘C. Based on the observed variability in INP concentrations, we conclude that studies conducted at the high-altitude research station Jungfraujoch are representative for INP measurements in the Swiss Alps. Furthermore, the INP concentration estimates in precipitation allow us to extrapolate the concentrations to a frozen cloud fraction. Indeed, this approach for estimating the liquid water-to-ice ratio in mixed-phase clouds compares well with aircraft measurements, ground-based lidar and satellite retrievals of frozen cloud fractions. In all, the generated parameterization for INP concentrations in snowmelt could help estimate cloud glaciation temperatures.

Description: Ice nucleating particles (INPs) produce ice from supercooled water droplets through heterogeneous freezing in the atmosphere. Since the concentration of ice crystals affects the radiative properties of clouds as well as precipitation, constraining the liquid water to ice ratio could help reduce aerosol-cloud interaction uncertainties. INPs have been collected at the Jungfraujoch research station (at 3500 m a.s.l.) in central Switzerland; yet spatially diverse data on INP occurrence in the Swiss Alps are scarce and remain uncharacterized. We address this scarcity through our Swiss Alpine snow sample study which took place during the winter of 2018. We collected a total of 88 fallen snow samples across the Alps at different locations, altitudes, terrains, times since last snowfall and depths. The INP concentrations were measured using the homebuilt DRoplet Ice Nuclei Counter Zurich (DRINCZ) and were then compared to spatial, meteorological and physiochemical parameters. We also extend an alternative way of displaying frozen fraction (FF) versus temperature data through visualizing freezing temperatures as a boxplot to field collected samples. This plotting method displays the freezing temperature in one dimension, instead of the former two dimensions of FF vs temperature, allowing a condensed display of freezing temperature measurements. In the collected snow samples, large variability in INP occurrence was found, even for samples collected 10 m apart on a plain and 1 m apart in depth. Furthermore, undiluted samples had INP concentrations ranging between 1 and 100 INP ml−1 of snow water over a temperature range of −5 to −19 °C. From this field-collected data set, we parameterize the INP concentrations per milliliter of meltwater as a function of temperature with the following equation c*air (T)=e(−0.7T–7.05), comparing well with previously reported precipitation data presented in Petters and Wright, 2015. When assuming a cloud water content of 0.4 g−3 and a critical INP concentration for glaciation of 10 m−3, the majority of the snow precipitated from clouds with glaciation temperatures between −5 and −20 °C. Based on the observed variability in INP concentrations, we conclude that studies conducted at the high-altitude research station Jungfraujoch are representative for INP measurements in the Swiss Alps. Furthermore, the INP concentration precipitation estimates allow us to extrapolate the concentrations to a cloud frozen fraction. Indeed, this approach for estimating the liquid water to ice ratio in mixed phase clouds compares well with aircraft measurements, ground-based lidar and satellite retrievals of cloud frozen fractions. In all, the generated parameterization for INP concentrations in meltwater could help estimate cloud glaciation temperatures.

Description: 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 (DRINCZ) 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 an 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.

Description: Aerosol–cloud interactions, including the ice nucleation of supercooled liquid water droplets caused by ice-nucleating particles (INPs) and macromolecules (INMs), are a source of uncertainty in predicting future climate. Because INPs and INMs have spatial and temporal heterogeneity in source, number, and composition, predicting their concentration and distribution is a challenge requiring apt analytical instrumentation. Here, we present the development of our drop Freezing Ice Nuclei Counter (FINC) for the estimation of INP and INM concentrations in the immersion freezing mode. FINC's design builds upon previous droplet freezing techniques (DFTs) and uses an ethanol bath to cool sample aliquots while detecting freezing using a camera. Specifically, FINC uses 288 sample wells of 5–60 µL volume, has a limit of detection of −25.4 ± 0.2 ∘C with 5 µL, and has an instrument temperature uncertainty of ± 0.5 ∘C. We further conducted freezing control experiments to quantify the nonhomogeneous behavior of our developed DFT, including the consideration of eight different sources of contamination. As part of the validation of FINC, an intercomparison campaign was conducted using an NX-illite suspension and an ambient aerosol sample from two other drop freezing instruments: ETH's DRoplet Ice Nuclei Counter Zurich (DRINCZ) and the University of Basel's LED-based Ice Nucleation Detection Apparatus (LINDA). We also tabulated an exhaustive list of peer-reviewed DFTs, to which we added our characterized and validated FINC. In addition, we propose herein the use of a water-soluble biopolymer, lignin, as a suitable ice-nucleating standard. An ideal INM standard should be inexpensive, accessible, reproducible, unaffected by sample preparation, and consistent across techniques. First, we compared lignin's freezing temperature across different drop freezing instruments, including on DRINCZ and LINDA, and then determined an empirical fit parameter for future drop freezing validations. Subsequently, we showed that commercial lignin has consistent ice-nucleating activity across product batches and demonstrated that the ice-nucleating ability of aqueous lignin solutions is stable over time. With these findings, we present lignin as a good immersion freezing standard for future DFT intercomparisons in the research field of atmospheric ice nucleation.