PNNL

Abstract

Simulations of mixed-phase clouds in short-range forecasts with the National Center for Atmospheric Research Community Atmosphere Model version 3 (CAM3) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed under the DOE CCPP-ARM Parameterization Testbed (CAPT), which initializes the climate models with analysis data produced from numerical weather prediction (NWP) centers. It is shown that CAM3 significantly underestimates the observed boundary layer mixed-phase clouds and cannot realistically simulate the variations with temperature and cloud height of liquid water fraction in the total cloud condensate based an oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer clouds while its clouds contain much less cloud condensate than CAM3 and the observations. Both models underestimate the observed cloud top and base for the boundary layer clouds. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used. The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes in CAM3. It is shown that the Bergeron-Findeisen process, i.e., the ice crystal growth by vapor deposition at the expense of coexisting liquid water, is important for the models to correctly simulate the characteristics of the observed microphysical properties in mixed-phase clouds. Sensitivity tests show that these results are not sensitive to the analysis data used for model initializations. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. Ice crystal number density has large impact on the model simulated mixed-phase clouds and their microphysical properties and needs to be accurately represented in climate models.