Dimensions and Aspect Ratios of Natural Ice Crystals
Understanding the physical processes that lead to the formation, growth, and precipitation of clouds is vital to improving climate models. Previous studies have shown that accurate knowledge of relationships among the dimensions of length (L), width (W), and maximum dimension (D) of ice crystals is important because they are used to construct shape models for calculating the single-scattering and for determining the microphysical (e.g., cross-sectional area and fall velocity) properties of ice crystals. Additionally, new modeling approaches that explicitly predict particle properties, rather than using predefined ice categories as in traditional schemes, require statistical databases of L, W, and D of ice crystals. Existing databases of such properties are expanded to include cirrus clouds with different origins such as those originating from synoptic fronts, orographic (surface) influence, or in-cloud anvil growth from thunderstorms. The dimensions and aspect ratios (AR, which describes the dimension of the major axis divided by the dimension of the minor axis of crystals) were determined as functions of temperature and geophysical location.
The Cloud Particle Imager (CPI) records images of cloud particles with high resolution (2.3 µm) on a 1 million pixel charge coupled device. High-resolution images of ice crystals were recorded at temperatures between -87°C and 0°C during the following U.S. Department of Energy field campaigns: the 2006 Tropical Warm Pool International Cloud Experiment (TWP-ICE), 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC) in the Arctic, and 2010 Small PARTicles In CirrUS (SPARTICUS) campaign at the Southern Great Plains in Oklahoma. In situ ice crystal data from hexagonal plates, columns, and the components of bullet rosettes, which are the fundamental building blocks of ice crystal forms, were cataloged. These large databases are essential in representing the enormous spread of microphysical and radiative properties of ice crystals for retrieval algorithms and numerical modeling studies, and they will ultimately further enhance the predictive capabilities of climate models.
Um, J., G. M. McFarquhar, Y. P. Hong, S.-S. Lee, C. H. Jung, R. P. Lawson, and Q. Mo. 2015. “Dimensions and Aspect Ratios of Natural Ice Crystals,” Atmospheric Chemistry and Physics 15, 3933-56. DOI: 10.5194/acp-15-3933-2015.