Immersion freezing in particle-based aerosol-cloud microphysics: a probabilistic perspective on singular and time-dependent models
Sylwester Arabas, Jeffrey H. Curtis, Israel Silber, Ann M. Fridlind, Daniel A. Knopf, Matthew West, Nicole Riemer

TL;DR
This paper compares singular and time-dependent models of immersion freezing in aerosol-cloud microphysics, highlighting their applicability, limitations, and implications for probabilistic particle-based cloud simulations.
Contribution
It provides a detailed analysis of both models' responses to cooling rates and their integration challenges in flow-relevant cloud simulations.
Findings
Singular models are limited to specific cooling rate ranges.
Time-dependent models are better suited for detailed aerosol composition integration.
Flow-coupled simulations reveal benefits and challenges of super-particle methods.
Abstract
Cloud droplets containing ice-nucleating particles (INPs) may freeze at temperatures above the homogeneous freezing threshold temperature. This process, referred to as immersion freezing, is one of the modulators of aerosol-cloud interactions in the Earth's atmosphere. In modeling studies, immersion freezing is often described using either so-called "singular" or "time-dependent" parameterizations. Here, we juxtapose both approaches and discuss them in the context of probabilistic particle-based cloud microphysics modeling. First, using a box model, we contrast how both parameterizations respond to different idealized ambient cooling rate profiles and quantify the impact of the polydispersity of the immersed surface spectrum on the frozen fraction evolution. Second, using a prescribed-flow two-dimensional cloud model, we illustrate the implications of applying the singular model in…
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