A Case Study of Three-dimensional Cloud Resolving Model Simulations Using a Double-moment Cloud Microphysics Parameterization

Zheng Liu University of Washington
Thomas Ackerman University of Washington
Hugh Morrison NCAR

Category: Modeling

Working Group: Cloud-Aerosol-Precipitation Interaction

The Morrison double-moment microphysics parameterization used in this study predicts both the number concentration and mixing ratio for five hydrometeor species: cloud water, cloud ice, rain, snow, and graupel, along with the mass mixing ratio of water vapor. With the explicitly predicted hydrometeor number concentration, we expect the double-moment microphysics scheme to improve the simulation of microphysical processes and cloud properties. In this study, this microphysics scheme is utilized in a cloud resolving model, called the System for Atmospheric Modeling (SAM), to simulate cloud evolution during the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) 1997 summer Intensive Observation Period. We perform sensitivity studies of parameters for immersion freezing of droplets, which are critical for the properties of detrained ice from deep convection. We also investigate the snow auto-conversion threshold. Simulated precipitation and cloud properties are compared against the observations from the ARM instruments during this period. To understand the extent of the model-inherent uncertainty and its impact on the microphysics sensitivity studies, we also perform an ensemble of simulations by using the same model configurations and large-scale forcing and only varying initial soundings. Because of the computational cost of the three-dimensional simulations, we only apply these ensemble runs to a short period of time (four days) to examine the model bifurcation after precipitation, which is frequently seen in two-dimensional simulations.

This poster will be displayed at ASR Science Team Meeting.