A21D-0168
A Cloud-Resolving Modeling Intercomparison Study on Properties of Cloud Microphysics, Convection, and Precipitation for a Squall Line Cas

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Jiwen Fan1, Bin Han1, Hugh Morrison2, Adam Varble3, Edward Mansell4, Jason Milbrandt5, Yuan Wang6, Yun Lin7, Xiquan Dong8, Scott E Giangrande9, Michael P Jensen9, Scott M Collis10, Kirk North11 and Pavlos Kollias11, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)National Center for Atmospheric Research, Boulder, CO, United States, (3)University of Utah, Salt Lake City, UT, United States, (4)National Severe Storms Lab, Norman, OK, United States, (5)Environment Canada Ottawa, Ottawa, ON, Canada, (6)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (7)Texas A & M University College Station, College Station, TX, United States, (8)University of North Dakota, Grand Forks, ND, United States, (9)Brookhaven National Laboratory, Upton, NY, United States, (10)Argonne National Laboratory, Argonne, IL, United States, (11)McGill University, Montreal, QC, Canada
Abstract:
The large spread in CRM model simulations of deep convection and aerosol effects on deep convective clouds (DCCs) makes it difficult (1) to further our understanding of deep convection and (2) to define “benchmarks” and recommendations for their use in parameterization developments. Past model intercomparison studies used different models with different complexities of dynamic-microphysics interactions, making it hard to isolate the causes of differences between simulations. In this intercomparison study, we employed a much more constrained approach – with the same model and same experiment setups for simulations with different cloud microphysics schemes (one-moment, two-moment, and bin models). Both the piggybacking and interactive approaches are employed to explore the major microphysical processes that control the model differences and the significance of their feedback to dynamics through latent heating/cooling and cold pool characteristics.

Real-case simulations are conducted for the squall line case 20 May 2011 from the MC3E field campaign. Results from the piggybacking approach show substantially different responses of the microphysics schemes to the same dynamical fields. Although the interactive microphysics-dynamics simulations buffer some differences compared with those from the piggyback runs, large differences still exist and are mainly contributed by ice microphysical processes parameterizations. The presentation will include in-depth analyses of the major microphysical processes for the squall line case, the significance of the feedback of the processes to dynamics, and how those results differ in different cloud microphysics schemes.