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Abstract Arctic single‐layer mixed‐phase clouds were studied using a one‐dimensional model that incorporated the adaptive habit growth model for ice microphysics. The base case was from the Indirect and Semidirect Aerosol Campaign, and it was perturbed over a range of cloud‐average temperatures, maximum (per model run) ice nuclei (IN) concentrations, and large‐scale subsidence velocities. For each parameter combination, the model was iterated out to 48 hr, and the time, called the glaciation time, to complete disappearance of liquid recorded if this occurred within the 48 hr. Dependence of glaciation times on cloud‐average temperatures from −30°C to −5°C, maximum IN concentrations from 0.10 to 30 L⁻¹, and strong–no subsidence, with both isometric and habit‐dependent ice crystal growth, were investigated. For isometric crystal growth, the relationship between the critical maximum IN concentration (IN_crit), the maximum (per model run) IN concentration above which a mixed‐phase cloud glaciated within a fixed model runtime, and cloud‐average temperature was monotonic. IN_critdecreased with decreasing cloud‐average temperature. Strengthening of subsidence led to a further decrease in IN_critfor every cloud‐average temperature. For habit‐dependent ice crystal growth, the relationship between IN_critand cloud‐average temperature was nonmonotonic. Ice crystals develop dendritic and columnar habits near −15°C and −7°C, respectively, and at these two temperatures, ice crystals grew and depleted supercooled liquid water faster than the case when ice crystals grew isometrically. This led to deep local minima in IN_critaround these two temperatures in the model runs. Habit‐dependent ice crystal growth, coupled with changes in cloud‐average temperature, IN_crit, and subsidence strength, led to significant changes in Arctic single‐layer mixed‐phase cloud lifetimes. 

Abstract Variability of ice microphysical properties like crystal size and density in cirrus clouds is important for climate through its impact on radiative forcing, but challenging to represent in models. For the first time, recent laboratory experiments of particle growth (tied to crystal morphology via deposition density) are combined with a state‐of‐the‐art Lagrangian particle‐based microphysics model in large‐eddy simulations to examine sources of microphysical variability in cirrus. Simulated particle size distributions compare well against balloon‐borne observations. Overall, microphysical variability is dominated by variability in the particles' thermodynamic histories. However, diversity in crystal morphology notably increases spatial variability of mean particle size and density, especially at mid‐levels in the cloud. Little correlation between instantaneous crystal properties and supersaturation occurs even though the modeled particle morphology is directly tied to supersaturation based on laboratory measurements. Thus, the individual thermodynamic paths of each particle, not the instantaneous conditions, control the evolution of particle properties.