Photo above: Microscope image of droplets, about 50 µm in diameter, that are cooled below the melting point of ice (0 °C). The diameter of a human hair is about 70 µm. Lighter shaded droplets are liquid. Darker shaded droplets formed ice and thus appear darker.
Professor Daniel Knopf at the Stony Brook University School of Marine and Atmospheric Sciences and collaborators at the Paul-Scherrer Institute in Switzerland and the Weizmann Institute in Israel are interested in understanding the origins of ice crystallization, considered one of the grand challenges of atmospheric science. The efforts of their research were recently published in npj Climate and Atmospheric Science.
The formation of ice crystals in the atmosphere is an important process impacting precipitation and climate. Despite this recognition, current climate models do no take into account the formation of ice crystals from ambient aerosol particles (i.e., particles spanning sizes from a few nanometer to 10s of micrometer). This is due to our insufficient understanding of the governing processes that initiate the freezing of a droplet.
In the laboratory, various types of aerosol particles are examined for their potential acting as atmospheric ice-nucleating particles (INPs). Laboratory studies have well documented that mineral dust species can serve as INPs leading to the formation of ice particles. However, laboratory experiments are usually not conducted at conditions typical of the atmosphere and, thus, the question is debated, how to translate the ice formation rates observed in the laboratory to the real world. This will ultimately define how accurate we can predict ice formation in cloud and climate models.
![How do you translate the formation of ice observed in the lab to the atmosphere? According to tests by Dr. Knopf and his colleagues, supercooled droplets in the lab contain ice-nucleating particles. They are trying to determine if these ice nucleating particles are special, if nucleation proceeds randomly, are their experiments accurate and do parameterizations reflect these issues.](https://you.stonybrook.edu/somas/files/2020/01/knopf-process-1024x804.png)
The description of the freezing of supercooled cloud droplets for accurate implementation and prediction in cloud and climate models.
The research team designed an experiment that allows observation of 1000s of micrometer-sized droplets that contain illite mineral dust acting as ice-nucleating particles. Their work unambiguously demonstrates that i) ice nucleation commences in a random manner, ii) it depends on time, and iii) that our current control of sample preparation is the likely cause for the large observed variability in ice nucleation data and differences in data interpretation. By observation of a large number of droplet freezing events, analyzed by a Monte Carlo simulation, Knopf and collaborators show that the typically observed data scatter is due to the random nature of nucleation and our limited ability to control particle surface area on the nanoscale.
The researchers suggest that these issues are directly responsible for the debated various model parameterizations of cloud droplet freezing by INPs. The findings of this study directly impact the measured ice nucleation rates and thus their application in cloud and climate models. It challenges commonly applied parameterizations that imply that nucleation is time-independent and ice formation is a singular and one site specific event.
![Microscope image of an ice crystal, about 100 µm in diameter, that formed from a submicron aerosol particle.](https://you.stonybrook.edu/somas/files/2020/01/knopf-icecrystal-300x244.png)
Microscope image of an ice crystal, about 100 µm in diameter, that formed from a submicron aerosol particle.
Title: Stochastic nucleation processes and substrate abundance explain time-dependent freezing in supercooled droplets
Authors: Daniel A. Knopf, Peter A. Alpert, Assaf Zipori, Naama Reicher and Yinon Rudich
Abstract: Atmospheric immersion freezing (IF), a heterogeneous ice nucleation process where an ice nucleating particle (INP) is immersed in supercooled water, is a dominant ice formation pathway impacting the hydrological cycle and climate. Implementation of IF derived from field and laboratory data in cloud and climate models is difficult due to the high variability in spatio-temporal scales, INP composition, and morphological complexity. We demonstrate that IF can be consistently described by a stochastic nucleation process accounting for uncertainties in the INP surface area. This approach accounts for time-dependent freezing, a wide range of surface areas and challenges phenomenological descriptions typically used to interpret IF. The results have an immediate impact on the current description, interpretation, and experiments of IF and its implementation in models. The findings are in accord with nucleation theory, and thus should hold for any supercooled liquid material that nucleates in contact with a substrate.