Analysis of the Aerosol indirect Effects on the timing of Organization of Stratocumulus Clouds

Description

The nature and strength of the interactions between cloud microphysics and macrophysics are dependent on the meteorological environment. For example, for precipitation to exert an influence on the dynamics of low clouds, the large-scale meteorological environment must be conducive to precipitation formation. Similarly, aerosol-cloud interactions depend upon the aerosol loading, with clean marine air masses particularly sensitive to aerosol perturbations. Here, Large-eddy simulations are used to explore the aerosol indirect effects on the occurrence and duration of the Stratocumulus (Sc) organization. Initial conditions are based on measurements made as part of the Second Dynamics and Chemistry of the Marine Stratocumulus field study (DYCOMS-II). We altered the cloud droplet number concentration (CDNC) as a proxy for the aerosol impact on clouds, and found a threshold effect on cloud fraction. The averaged albedo over the domain, however, has no threshold due to Sc thickening in the low CDNC cases. Such thickening creates large positive LWP skewness that relates closely to the cloud organization. The evolution of the cloud is not sensitive to large CDNC, while it shows a sharp transition from closed to open cell convection once the CDNC drops below 15 cm-3, and the cloud cover maintains at for more than 24 hours in the low CDNC cases. A detailed microphysical look has been focused on the comparison between the particle-residence time scale and bulk auto-conversion time scale by tracking the massless particles in the LES domain. The fraction of particles with residence time scale larger than auto-conversion time scale shows negative relation with precipitation rate and organizational time scale. Meanwhile, Sc cloud cover dropped dramatically for all the CDNC cases when the fraction is larger than 2%. We also found that for sufficiently long simulation time (larger than 2 days), the large-scale thermodynamics determines the long-term cloud evolution. The presented modeling work will be evaluated using observervations from the ENA ARM site.