Comment on amt-2022-153

Abstract

Ice nucleation in the atmosphere is the precursor to important processes that determine cloud properties and lifetime. Computational models that are used to predict weather and project future climate changes require parameterizations of both homogeneous nucleation (i.e., in pure water) and heterogeneous nucleation (i.e., catalysed by ice-nucleating particles, INPs). Microfluidic systems have gained momentum as a tool for obtaining such parameterizations and gaining insight into the stochastic and deterministic contributions to ice nucleation. In this regard, polydimethylsiloxane (PDMS) devices are typically used to generate droplets in microchannels that are then cooled and monitored “on-chip”. However, using PDMS has two drawbacks. First, it has a low thermal conductivity that generates temperature gradients within a PDMS chip upon cooling from below, which can lead to increased temperature uncertainty at the droplets’ location. Second, it readily absorbs water and is gas permeable, which compromises the stability of droplets over extended timescales. To overcome these shortcomings, we have developed a new instrument: the Microfluidic Ice Nuclei Counter Zürich (MINCZ). In MINCZ, droplets are generated using a PDMS chip, but are then stored in fluoropolymer tubing that is relatively impermeable to water and solvents. Droplets within the tubing are cooled in an ethanol bath that ensures efficient heat transfer and reduces uncertainty in droplet temperature. Herein, we describe the design of MINCZ, which fulfils the following requirements: (i) high accuracy and precision in measuring droplet temperatures within 0.2 K; (ii) ability to reach the homogeneous freezing point of pure water, with a median freezing temperature of 237.3±0.1 K for droplets with a diameter of 75 μm; and (iii) the ability to simultaneously perform several freeze–thaw cycles on hundreds of droplets. These characteristics allow to narrow the reported spread in nucleation rates as a function of temperature in past work, to detect mediocre and poor ice-nucleating particles at any temperature above that of homogeneous freezing, and to investigate the stochastic behaviour of nucleation. We validate MINCZ by measuring homogeneous freezing temperatures of water droplets and heterogeneous freezing temperatures of aqueous suspensions containing microcline, a common and effective INP in the atmosphere. In the future, MINCZ will be used to investigate the stochastic and deterministic behaviour of INPs, motivated by a need for better-constrained parameterizations of ice nucleation in weather and climate models, where the presence or absence of ice influences cloud optical properties and precipitation formation.