Preprints
https://doi.org/10.5194/acp-2020-786
https://doi.org/10.5194/acp-2020-786

  02 Oct 2020

02 Oct 2020

Review status: a revised version of this preprint is currently under review for the journal ACP.

Ice multiplication from ice-ice collisions in the high Arctic: sensitivity to ice habit, rimed fraction and the spectral representation of the colliding particles

Georgia Sotiropoulou1,2, Luisa Ickes3, Athanasios Nenes2,4, and Annica M. L. Ekman1 Georgia Sotiropoulou et al.
  • 1Department of Meteorology, Stockholm University & Bolin Center for Climate Research, Stockholm, Sweden
  • 2Laboratory of Atmospheric Processes and their Impacts, School of Architecture, Civil & Environmental Engineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • 3Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden
  • 4Institue for Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, Greece

Abstract. Atmospheric models often fail to correctly reproduce the microphysical structure of Arctic mixed-phase clouds and underpredict ice water content, even when simulations are constrained by the observed levels of ice nucleating particles. In this study we investigate whether ice multiplication from ice-ice collisions, a process missing in most models, can account for the observed cloud ice in a stratocumulus cloud observed during the Arctic Summer Cloud Study campaign. Our results indicate that including ice-ice collisions can improve the modeled cloud water properties, but the degree of influence depends on other poorly constrained microphysical aspects that include ice habit, rimed fraction and cloud ice-to-snow autoconversion rate. Simulations with dendrites are less sensitive to variations in the assumed rimed fraction of the particle that undergoes break-up, compared to those with planar ice. Activating cloud ice-to-snow autoconversion decreases the sensitivity of the break-up process to both the assumed ice habit and rimed fraction. Finally, adapting a relatively small value for the threshold diameter at which cloud ice is converted to snow enhances break-up efficiency and improves the macrophysical representation of the cloud.

Georgia Sotiropoulou et al.

 
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Georgia Sotiropoulou et al.

Georgia Sotiropoulou et al.

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Latest update: 11 Apr 2021
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Short summary
Mixed-phase clouds are a large source of uncertainty in projections of the Arctic climate. This is partly due to the poor representation of the cloud-ice formation processes. Implementing a parameterization for ice multiplication due to mechanical break-up upon collision of two ice particles in a high resolution model improves cloud-ice phase representation. However, the results are sensitive to poorly constrained microphysical parameters (e.g. ice habit, rimed fraction, autoconversion rate).
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