Generalisation of Levine's prediction for the distribution of freezing temperatures of droplets: A general singular model for ice nucleation
Richard P. Sear

TL;DR
This paper generalizes Levine's singular model for droplet freezing temperatures using extreme-value statistics, showing that the distribution follows a generalized extreme-value distribution and linking droplet size to median nucleation temperature.
Contribution
It introduces the most general singular model for ice nucleation based on extreme-value theory, extending Levine's original model and enabling predictions of freezing temperature scaling.
Findings
Distribution of freezing temperatures follows a generalized extreme-value distribution.
Model allows prediction of median nucleation temperature based on droplet size.
Provides a unified framework for analyzing droplet freezing temperature data.
Abstract
Models without an explicit time dependence, called singular models, are widely used for fitting the distribution of temperatures at which water droplets freeze. In 1950 Levine developed the original singular model. His key assumption was that each droplet contained many nucleation sites, and that freezing occurred due to the nucleation site with the highest freezing temperature. The fact that freezing occurs due to the maximum value out of large number of nucleation temperatures, means that we can apply the results of what is called extreme-value statistics. This is the statistics of the extreme, i.e., maximum or minimum, value of a large number of random variables. Here we use the results of extreme-value statistics to show that we can generalise Levine's model to produce the most general singular model possible. We show that when a singular model is a good approximation, the…
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Taxonomy
TopicsAtmospheric chemistry and aerosols · Atmospheric aerosols and clouds · Arctic and Antarctic ice dynamics
