In this two-part study, relationships between the cloud gamma size distribution shape parameter, microphysical processes, and cloud characteristics of nonprecipitating shallow cumulus clouds are investigated using large-eddy simulations. In Part I, the dependence of the shape parameter (which is closely related to the distribution width) on cloud properties and processes was investigated. However, the distribution width also impacts cloud process rates and in turn cloud properties, and it is this aspect of the relationship that is explored in Part II and is discussed in the context of aerosol-cloud interactions. In simulations with a bulk microphysics scheme, it is found that the evaporation rates are much more sensitive to the value of the shape parameter than to the condensation rates. This is due to changes in both the rate of removal of mass and the rate of removal of fully evaporated droplets. As a result, cloud properties such as droplet number concentration, mean droplet diameter, and cloud fraction are strongly impacted by the value of the shape parameter, particularly in the subsaturated regions of the clouds. These changes can be on the same order of magnitude as changes due to increasing or decreasing the aerosol concentration by a factor of 16. Particular attention is paid to the impact of the shape parameter on cloud albedo. The cloud albedo increases as the shape parameter is increased as a result of the changes in evaporation. The magnitude of the increase is about 4 times larger than previous estimates. However, this increase in cloud albedo is largely offset by a decrease in the cloud fraction, which results in only small increases to the domain-average albedo. Implications for the aerosol relative dispersion effect are discussed.

In this two-part study, the relationships between the width of the cloud droplet size distribution and the microphysical processes and cloud characteristics of nonprecipitating shallow cumulus clouds are investigated using large-eddy simulations. In Part I, simulations are run with a bin microphysics scheme and the relative widths (standard deviation divided by mean diameter) of the simulated cloud droplet size distributions are calculated. They reveal that the value of the relative width is higher and less variable in the subsaturated regions of the cloud than in the supersaturated regions owing to both the evaporation process itself and enhanced mixing and entrainment of environmental air. Unlike in some previous studies, the relative width is not found to depend strongly on the initial aerosol concentration or mean droplet concentration. Nonetheless, local values of the relative width are found to positively correlate with local values of the droplet concentrations, particularly in the supersaturated regions of clouds. In general, the distributions become narrower as the local droplet concentration increases, which is consistent with the difference in relative width between the supersaturated and subsaturated cloud regions and with physically based expectations. Traditional parameterizations for the relative width (or shape parameter, a related quantity) of cloud droplet size distributions in bulk microphysics schemes are based on cloud mean values, but the bin simulation results shown here demonstrate that more appropriate parameterizations should be based on the relationship between the local values of the relative width and the cloud droplet concentration.

The condensation and evaporation rates predicted by bin and bulk microphysics schemes in the same model framework are compared in a statistical way using simulations of non-precipitating shallow cumulus clouds. Despite other fundamental disparities between the bin and bulk condensation parameterizations, the differences in condensation rates are predominantly explained by accounting for the width of the cloud droplet size distributions simulated by the bin scheme. While the bin scheme does not always predict a cloud droplet size distribution that is well represented by a gamma distribution function (which is assumed by bulk schemes), this fact appears to be of secondary importance for explaining why the two schemes predict different condensation and evaporation rates. The width of the cloud droplet size is not well constrained by observations, and thus it is difficult to know how to appropriately specify it in bulk microphysics schemes. However, this study shows that enhancing our observations of this width and its behavior in clouds is important for accurately predicting condensation and evaporation rates.

The topic of combining observations from instruments of different frequencies and sensitivities on remote sensing platforms has been underutilized in undergraduate and graduate atmospheric science curricula, but is vital to obtaining holistic views of the Earth climate system. An online education applet on this topic has been developed for use in radar and remote sensing atmospheric science courses that meets the requirements outlined in Table 1. The developed applet attempts to reduce the curriculum gap by guiding students through atmospheric weather phenomena and allowing them to explore the performance of a variety of radar frequencies and characteristics. This applet leverages a high-resolution cloud-resolving model and satellite radar simulator to provide a synthetic learning laboratory environment. It contains one-to-one comparisons between the simulated environment and approximate observations of that environment through the use of hypothetical remote sensing instruments. A limited set of orbits and planar views are selected to highlight advantages and shortfalls of potential instrument configurations. Future formal assessments of the learning tool will allows its effectiveness to be quantified and guide further improvement of the tool beyond currently planned development activities.

Single-moment microphysics schemes have long enjoyed popularity for their simplicity and efficiency. However, in this article it is argued through theoretical considerations, idealized thunderstorm simulations, and radiative-convective equilibrium (RCE) simulations that the assumptions inherent in these parameterizations can induce large errors in the proper representation of clouds and their feedbacks to the atmosphere. For example, precipitation is shown to increase by 200% through changes to fixed parameters in a singlemoment scheme and low-cloud fraction in the RCE simulations drops from about 15% in double-moment simulations to about 2% in single-moment simulations. This study adds to the large body of work that has shown that double-moment schemes generally outperform single-moment schemes. Therefore, it is recommended that future studies, regardless of their focus and especially those employing cloud-resolving models to simulate a realistic atmosphere, strongly consider moving to the exclusive use of multimoment microphysics schemes.