Abstract
Abstract. The large-eddy model UCLALES–SALSA, with an exceptionally detailed aerosol description for both aerosol number and chemical composition, has been extended for ice and mixed-phase clouds. Comparison to a previous mixed-phase cloud model intercomparison study confirmed the accuracy of newly implemented ice microphysics. A further simulation with a heterogeneous ice nucleation scheme, in which ice-nucleating particles (INPs) are also a prognostic variable, captured the typical layered structure of Arctic mid-altitude mixed-phase cloud: a liquid layer near cloud top and ice within and below the liquid layer. In addition, the simulation showed a realistic freezing rate of droplets within the vertical cloud structure. The represented detailed sectional ice microphysics with prognostic aerosols is crucially important in reproducing mixed-phase clouds.
Highlights
Clouds are known to have a prominent influence on the hydrological cycle and the atmospheric radiation balance
We focus on how ice crystals and ice-nucleating particles (INPs) interact with clouds while tracking sectional aerosol size distribution
We implemented in UCLALES–SALSA model runs with the same semi-idealised simulation setup given in Ovchinnikov et al (2014) that attempted to minimise intermodel differences by applying identical descriptions for the following processes: surface properties and fluxes, large-scale forcings, radiation, cloud droplet freezing and ice growth processes and sedimentation, and the nudging of horizontal winds, potential temperature and water content above the altitude of 1200 m
Summary
Clouds are known to have a prominent influence on the hydrological cycle and the atmospheric radiation balance. While significant advances have been made in characterisation of liquid-phase clouds, the microphysical processes, especially heterogeneous ice nucleation, dynamics and radiative effects of mixed-phase and ice clouds remain more poorly constrained This is mainly because of challenges in obtaining representative observations and a lack of a detailed enough representation of microphysics in climate and numerical weather prediction models. The loss of INPs along with precipitating ice crystals limits cloud glaciation and dissipation (Rauber and Tokay, 1991; Harrington et al, 1999; Avramov and Harrington, 2010) Describing this process is not possible without a detailed description of aerosols, as is demonstrated in a 1-D cloud model study by Morrison et al (2005). We demonstrate the benefits of this approach to handle heterogeneous freezing over more simplified aerosol–ice–cloud treatments
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