The Power of Water: Examining Ice Crystal Nucleation’s Impact on Cloud Thermodynamic Properties

Cloud systems demonstrate great influence on Earth’s climate with both radiative and precipitation processes. However, detailed convection can be poorly represented in global climate models. By resolving fine-scale features, like cloud ice crystal nucleation, an improved understanding of the microphysics involved with deep convection will aid to more accurate incorporations of cloud systems into climate models. The purpose of this study is to analyze the differences in certain cloud thermodynamic properties, including mixing ratios and latent heat budgets, as a result of various ice nucleation cases. The Clark-Hall Cloud-Resolving Model (CRM) was initialized with observations from the 1997 Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) field campaign. Three model runs were completed, one for each of the following ice crystal nucleation types: primary, secondary, and artificial. The compositions of the cloud systems expressed interesting variations; artificial nucleation created the most Type A ice, small ice crystals that grow through deposition, while secondary nucleation had the most Type B ice, larger hydrometeors formed via collisions between Type A ice and water droplets. The artificial nucleation case experienced the greatest latent heating and cooling due to deposition and sublimation. Primary and secondary nucleation differed most greatly during latent heating phase changes at levels higher in the cloud system. In addition, the size of each cloud system, in part determined by its composition and latent heating characteristics, affected its radiative properties, thus creating precipitation differences between the three cases. These results provide greater insight into how various ice nucleation types ultimately modify atmospheric stability and precipitation trends in their environment. With this understanding, large-scale precipitation and radiative processes in future climate scenarios can be better addressed in climate modeling