Modeling immersion freezing with aerosol-dependent prognostic ice nuclei in Arctic mixed-phase clouds

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Abstract

While recent laboratory experiments have thoroughly quantified the ice nucleation efficiency of different aerosol species, the resulting ice nucleation parameterizations have not yet been extensively evaluated in models on different scales. Here the implementation of an immersion freezing parameterization based on laboratory measurements of the ice nucleation active surface site density of mineral dust and ice nucleation active bacteria, accounting for nucleation scavenging of ice nuclei, into a cloud-resolving model with two-moment cloud microphysics is presented. We simulated an Arctic mixed-phase stratocumulus cloud observed during Flight 31 of the Indirect and Semi-Direct Aerosol Campaign near Barrow, Alaska. Through different feedback cycles, the persistence of the cloud strongly depends on the ice number concentration. It is attempted to bring the observed cloud properties, assumptions on aerosol concentration, and composition and ice formation parameterized as a function of these aerosol properties into agreement. Depending on the aerosol concentration and on the ice crystal properties, the simulated clouds are classified as growing, dissipating, and quasi-stable. In comparison to the default ice nucleation scheme, the new scheme requires higher aerosol concentrations to maintain a quasi-stable cloud. The simulations suggest that in the temperature range of this specific case, mineral dust can only contribute to a minor part of the ice formation. The importance of ice nucleation active bacteria and possibly other ice formation modes than immersion freezing remains poorly constrained in the considered case, since knowledge on local variations in the emissions of ice nucleation active organic aerosols in the Arctic is scarce.

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CITATION STYLE

APA

Paukert, M., & Hoose, C. (2014). Modeling immersion freezing with aerosol-dependent prognostic ice nuclei in Arctic mixed-phase clouds. Journal of Geophysical Research, 119(14), 9073–9092. https://doi.org/10.1002/2014JD021917

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