Influence of a turbulent entrainment–mixing parameterization on the simulation of clouds
Liu, Yangang — Brookhaven National Laboratory
Area of research:
While turbulent entrainment mixing significantly affects cloud properties, the range in the different types of mixing and their differing effects on clouds are not treated in atmospheric models. A new parameterization has been developed that represents this range of effects, and its impacts are demonstrated in simulations of cumulus and stratiform clouds.
The new parameterization enables representation of the full range of turbulent entrainment mixing processes that occur in the atmosphere. This study demonstrates the importance of treating these processes, reinforcing the need to represent the interaction of aerosols and turbulence to improve cloud microphysics in climate models.
Different turbulent entrainment–mixing processes can occur in clouds; however, homogeneous mixing is often implicitly assumed in cloud microphysics schemes used in models, ranging from large-eddy simulations (LES) to climate models. Here, a new entrainment–mixing parameterization is presented that treats the range of homogeneous and inhomogeneous mixing using the grid mean relative humidity, which avoids the need of using relative humidity of the entrained air, which is unavailable in models. The parameterization is implemented into the LES version of WRF-Solar and sensitivity experiments are conducted to examine the parameterization impacts on simulated clouds. The results show that parameterization has a larger impact on the number concentration, volume mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous mixing dominates in the stratocumulus case while homogeneous mixing dominates in the cumulus case because of its larger turbulence dissipation rate. A large aerosol concentration or small turbulence dissipation rate enhances the effects of this new entrainment–mixing parameterization by decreasing the evaporation timescale and increasing the turbulent mixing timescale. This study demonstrates the feasibility and importance of parameterizing entrainment–mixing processes in numerical models.