M. Paukert

Intercomparison of large‐eddy simulations of Arctic mixed‐phase clouds: Importance of ice size distribution assumptions

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.

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

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.

Redistribution of ice nuclei between cloud and rain droplets: Parameterization and application to deep convective clouds

In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. In contrast, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. Here we introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.