On the parameterization of ice crystal growth in numerical cloud models

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Description

The growth of ice crystals from vapor constitutes an important physical process within ice-containing, or cold, clouds. Ice crystals can grow rapidly to precipitation sizes through vapor growth alone; their growth constitutes an important sink of vapor which has potentially important impacts for the vapor budget of the upper troposphere. In addition, vapor growth produces complex crystal shapes that depend on temperature and supersaturation. While much is understood about crystal growth from vapor, cloud models generally contain simplified parameterizations that are formulated based on equivalent density spheres or specified mass-dimensional relationships based on aircraft data. We present a possible method to improve the prediction of primary crystal habit (a and c axis length) in bulk microphysical models. As an advantage, the new method is able to track the history of the particle’s growth, allowing for the prediction of bulk a and c axis lengths. This method thus allows the axis ratios and primary habits to evolve in time and space. Tests of the new method in comparison with a detailed, Lagrangian ice crystal growth model will be shown. This new method is based on the capacitance model for ice crystal growth, which fails at low ice supersaturations when surface kinetics dominate the growth process. However, we show that it is possible to re-derive the capacitance model so that surface kinetic effects for non-spherical particles are included in a consistent fashion. Tests in comparison with detailed ice crystal growth models show that this method of including surface kinetic effects is accurate, and thus provides a simplified way to improve ice crystal growth in cloud models at both low and high ice supersaturations.