Abstract

Different entrainment-mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment-mixing parameterization that uses the grid-mean relative humidity without requiring the relative humidity of the entrained air. Second, the parameterization is implemented in a microphysics scheme in a large eddy simulation model. Third, sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment-mixing parameterization. The results indicate that the new entrainment-mixing 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 and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment-mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment-mixing parameterization by decreasing the cloud droplet size and evaporation time scale. This study sheds new light on the improvement of entrainment-mixing parameterizations in models.

Highlights

  • The process of entrainment and subsequent mixing between clouds and their environment is one of the most uncertain processes in cloud physics, which is thought to be crucial to many outstanding issues, including warm-rain initiation and subsequent precipitation characteristics, cloud-climate feedback, and evaluating the indirect effects of aerosol (Paluch and Baumgardner, 1989; Yum, 1998; Ackerman et al, 2004; Kim et al, 2008; Huang et al, 2008; Del Genio and Wu, 2010; Lu et al, 2011; Lu et al, 2014; Kumar et al, 2013; Zheng and Rosenfeld, 2015; Fan et al, 2016; Gao et al, 2020; Gao et al, 2021; Zhu et al, 2021; Xu et al, 2021; Kumar et al, 2013; Yang et al, 2016; Yang et al, 2021)

  • This study first improves the entrainment-mixing parameterization proposed by Luo et al (2020), which connects the homogeneous mixing degree and transition scale number to estimate the homogeneity of the subgrid mixing process and its impact on the droplet number concentration

  • The improved parameterization uses grid-mean relative humidity and can be implemented directly into microphysics schemes; there is no need to know the relative humidity of the entrained air

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Summary

Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological

Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science &. 3. Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, US. 5. College of Aviation Meteorology, Civil Aviation Flight University of China, Guanghan, China

Introduction
The new entrainment-mixing parameterization
LES model, simulation cases, and modelling setup
Cumulus case
Stratocumulus case
Mechanisms of the effects of the new entrainment-mixing parameterization
The effects of dissipation rate and aerosol concentration on the entrainmentmixing process
Dissipation rate
Aerosol concentration
Concluding remarks
Full Text
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