Most global climate models (GCMs) suffer from prediction biases in their dynamic and thermodynamic structures in and around the boundary layer (BL). It remains unclear which of these biases within the large-scale conditions are crucial to the accurate reproduction of BL clouds. To develop a better understanding of the effects of variations in the simulated large-scale conditions, this paper uses large-eddy simulations to evaluate the effects of the fluctuation based on the latest GCM ensemble data on the prediction of a Californian stratocumulus under perturbed environments. The result indicates the relative importance of each component, and the most important factors controlling cloud behavior are the amplitudes of jumps in vapor and temperature across a BL top. The given variations in wind velocity and its vertical shear, largescale subsidence, and surface heat fluxes have a lesser effect. This suggests that to reduce model biases predicted in GCMs, greater attention should be paid to the stratification structure across the BL top.
ASJC Scopus subject areas
- Atmospheric Science