Observational quantification of the separation of simple and complex atmospheric ice particles

The impact of ice clouds on weather and climate is a function of ice particle shape through light scattering properties and cloud lifetime through ice particle sedimentation rates. Many weather forecast and climate models use two categories to represent ice cloud particles: cloud ice and snow, though the distinction between particle categories is generally without observational justification. Improved characterization of cloud ice and snow as well as the transition between them will make models more realistic. An analysis of particle imagery data from high-resolution aircraft particle imaging probes indicates that atmospheric ice particles can easily be separated by particle complexity. In this work, a technique is described which enables the clear separation of vapor grown particles from aggregates of particles. When applied to two example data sets, the technique shows that the separation between these categories occurs at 150 and 250 microns, for two example data sets. Key Points Cloud ice and snow are separated based on observations