Particle habit classification has been done on Cloud Particle Imager (CPI) data and applied to Ice Water Content (IWC) calculations. Particle properties such as length, width, area, perimeter, roundness and radial harmonics (similar to a fourier transform of the perimeter points) have been used to separate CPI observed particles by particle type. For clouds containing relatively simple particles agreement with visual classifications is typically greater than 90% while in clouds with more complicated particles agreement can decrease to 75%.

Ice Water Content calculated on a particle by particle basis can be done with particle habit information. Mass-dimensional relationships for individual particle types may provide better estimates of individual particle masses. Initial studies show that the use of mass-dimensional relationships for individual particles versus a generalized mass-dimensional relationship for all particles results in a decrease in calculated IWC by 10 to 30%.