Identification of cloud ice particle shapes for climate and weather prediction simulations
Ice particle shapes in tropospheric clouds play an important role in precipitation formation and they have a great impact on the Earth’s radiation budget. In different applications, due to the hexagonal symmetry of the crystal lattice of the ordinary ice, cloud ice particles have commonly been assumed to have symmetrical hexagonal shapes (i.e. hexagonal plates, columns, dendrites). However, recent airborne observations have shown that the majority of ice cloud particles are polycrystalline and have irregular shapes. Identification of cloud ice particle shapes (and characterization of their statistics) has significant implications for both climate and weather prediction simulations.
This project investigates the effects of clouds on climate and improvement of weather prediction models, more specifically on the climatology of ice particle habits formed in tropospheric clouds and their role in precipitation formation and radiation transfer. A large data set of high-resolution images of cloud ice particles associated with a wide range of environmental conditions and of different cloud types has been collected. The topic of this work focuses on developing image recognition procedures/software for segregation of ice particle shapes into 15-20 basic ice habit categories. The main outcome of this research will be a statistics of ice particle habits for different temperature intervals and cloud types.
Collaborating institution: Environment Canada