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

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.

Immersion Freezing of Kaolinite: Scaling with Particle Surface Area

“…In both studies the same instrument, a combination of Immersion Mode Cooling Chamber-Zurich Ice Nucleation Chamber (IMCA-ZINC; Lüönd et al 2010), was applied for the measurements. To study the immersion freezing results of the three studies, we compare the ice nucleation surface site densities since it was used for this purpose in the literature (e.g., Murray et al 2012) and was applied as model input parameter for describing heterogeneous ice nucleation (e.g., Paukert and Hoose 2014). The comparison of n s values helps to study the comparability of different instruments and the impact of time on the immersion freezing ability.…”

Modelling micro- and macrophysical contributors to the dissipation of an Arctic mixed-phase cloud during the Arctic Summer Cloud Ocean Study (ASCOS)

“…The COSMO model was used in a semi-idealized LES setup with periodic boundary conditions similar to Paukert and Hoose (2014). The model domain included 64 grid points in each horizontal direction with a grid spacing of 100 m. In order to account for the radiative fluxes throughout the atmospheric column (after Ritter and Geleyn, 1992), the top of the model domain was extended up to 22 km, with a vertical grid spacing of 15 m below 1005 m altitude, and an exponentially decreasing grid spacing aloft.…”

Classical nucleation theory of immersion freezing: sensitivity of contact angle schemes to thermodynamic and kinetic parameters

“…A deterministic immersion freezing parameterization scheme based on Niemand et al (2012) is included in the evaluation for comparison (for more details on the deterministic parameterization scheme see Appendix D). The Niemand et al (2012) scheme is frequently used in literature for comparing laboratory measurements, e.g., Atkinson et al (2013), Hoffmann et al (2013), Kanji et al (2013), O'Sullivan et al (2014), Tobo et al (2014), and Umo et al (2015), but also as a parameterization scheme in model studies, e.g., Barahona et al (2014), Paukert and Hoose (2014), and Hande et al (2015).…”