Importance of Cloud Particle and Precipitation Complexity in Squall Line Simulations
As climate model resolution increases toward resolving convection, the representation of cloud microphysics-the way models represent parameters such as cloud drops, ice crystals, rain, and snow formation-requires increased precision. With greater complexity also comes an increased computational burden, so it is important to understand what level of complexity is appropriate for the computationally expensive high-resolution climate simulations. U.S. Department of Energy scientists at Brookhaven National Laboratory and their collaborators, through sensitivity studies of an idealized squall line with the Weather Research and Forecasting model (WRF), showed that there is a benefit of using two variables to describe the size distribution evolution of all hydrometeors, liquid as well as ice. It was also shown that two equally complex schemes (Milbrandt and Yau, 2005 [MY] and Morrison et al. 2009 [MTT]) still behave very differently in terms of surface precipitation and moist processes aloft. These differences could be entirely related to their different treatments of how raindrops break up and grow as they fall. Over the past years, the focus in microphysics modeling often has been on the role of droplet size distribution assumptions in state-of-the-art schemes, but this study has identified that an equally large variability is associated with processes such as ice initiation, growth processes, and raindrop breakup.
Van Weverberg, K., A. Vogelmann, H. Morrison, and J. Milbrandt. 2012. “Sensitivity of Idealized Squall Line Simulations to the Level of Complexity Used in Two-Moment Bulk Microphysics Schemes,” Monthly Weather Review 140, 1883-1907. DOI: 10.1175/MWR-D-11-00120.1