Preprints
https://doi.org/10.5194/egusphere-2026-2403
https://doi.org/10.5194/egusphere-2026-2403
20 May 2026
 | 20 May 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Cloud-phase sensitivities of a simulated Arctic stratocumulus to aerosol and microphysical parameters

Hannah C. Frostenberg, Jessie M. Creamean, Erik S. Thomson, Heather Guy, Roman Pohorsky, Camille Mavis, Ian M. Brooks, Nicolas Fauré, Lea Haberstock, Julia Kojoj, Sonja Murto, Julia Schmale, Michael Tjernström, Paul Zieger, and Luisa Ickes

Abstract. Low-level, mixed-phase clouds are a key component of the Arctic energy budget and can impact the extent and thickness of sea ice. These clouds are influenced by aerosols and microphysical processes that can determine the phase partitioning and thereby cloud lifetime and radiative impacts. Atmospheric models often struggle to represent phase partitioning in Arctic mixed-phase clouds correctly. Aerosol number concentration (ANC), aerosol type (Atype), ice crystal number concentration (ICNC), and ice crystal morphology (ice crystal habit; IChab) have previously been shown to impact phase partitioning in Arctic clouds. In this study, we quantified the relative importance of these parameters for simulated liquid water path (LWP), ice water path (IWP), and downward longwave radiation at the surface (DWLW) of a slightly supercooled Arctic mixed-phase cloud by applying factorial analysis. Using MIMICA, the MISU-MIT Cloud Aerosol large-eddy simulation code, we found that ANC was the most important parameter for LWP and DWLW, while ICNC controlled IWP. IChab ranked third for all simulated variables, yet it crucially determined the final phase state of the cloud. The impact of Atype was negligible compared to the other three parameters. Recognizing the limits of relying on a single case study and model, our results suggest that future Arctic field campaigns should prioritize observations of ANC, ICNC, and, crucially, ice habit for slightly supercooled mixed-phase clouds. Models must also represent different ice habits to accurately simulate cloud phase partitioning and its subsequent impact on the Arctic energy budget.

Competing interests: Four coauthors are editors for Atmospheric Chemistry and Physics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Hannah C. Frostenberg, Jessie M. Creamean, Erik S. Thomson, Heather Guy, Roman Pohorsky, Camille Mavis, Ian M. Brooks, Nicolas Fauré, Lea Haberstock, Julia Kojoj, Sonja Murto, Julia Schmale, Michael Tjernström, Paul Zieger, and Luisa Ickes

Status: open (until 02 Jul 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Hannah C. Frostenberg, Jessie M. Creamean, Erik S. Thomson, Heather Guy, Roman Pohorsky, Camille Mavis, Ian M. Brooks, Nicolas Fauré, Lea Haberstock, Julia Kojoj, Sonja Murto, Julia Schmale, Michael Tjernström, Paul Zieger, and Luisa Ickes

Data sets

MIMICA LES output to analyze cloud-phase sensitivities in an Arctic stratocumulus Hannah C. Frostenberg, Luisa Ickes https://doi.org/10.5281/zenodo.19761135

Model code and software

MIMICA v5 version for analyzing cloud-phase sensitivities of an Arctic stratocumulus Hannah C. Frostenberg, Luisa Ickes https://doi.org/10.5281/zenodo.19762208

Hannah C. Frostenberg, Jessie M. Creamean, Erik S. Thomson, Heather Guy, Roman Pohorsky, Camille Mavis, Ian M. Brooks, Nicolas Fauré, Lea Haberstock, Julia Kojoj, Sonja Murto, Julia Schmale, Michael Tjernström, Paul Zieger, and Luisa Ickes
Metrics will be available soon.
Latest update: 21 May 2026
Download
Short summary
Arctic low clouds containing both droplets and ice crystals strongly impact sea ice and therefore require accurate modeling. Using a high-resolution atmospheric model, we found that particle and ice concentrations, alongside ice crystal shape, strongly dictate the simulated cloud. Therefore, these specific properties should be prioritized during future Arctic observational campaigns. Furthermore, atmospheric models must be able to represent a variety of ice crystal shapes.
Share