Aerosol indirect effects suffer from large uncertainty in climate models and among observations. This study focuses on two plausible factors: regime dependence of aerosol‐cloud interactions and the effect of cloud droplet spectral shape. We show, using a new parcel model, that combined consideration of droplet number concentration (N_c) and relative dispersion (ε, ratio of standard deviation to mean radius of the cloud droplet size distribution) better characterizes the regime dependence of aerosol‐cloud interactions than considering N_c alone. Given updraft velocity (w), ε increases with increasing aerosol number concentration (N_a) in the aerosol‐limited regime, peaks in the transitional regime, and decreases with further increasing N_a in the updraft‐limited regime. This new finding further reconciles contrasting observations in literature and reinforces the compensating role of dispersion effect. The nonmonotonic behavior of ε further quantifies the relationship between the transitional N_a and w that separates the aerosol‐ and updraft‐limited regimes.

Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm‐rain initiation, and aerosol‐cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume‐mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume‐mean radius changes from positive to negative as volume‐mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment‐mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume‐mean radius, including the results in polluted fog observations. The results could shed new light on the so‐called “twilight zone” between cloudy and cloud‐free air, which in turn affects evaluation of aerosol‐cloud interactions and retrieval of aerosol optical depth.

Land‐atmosphere interactions and boundary layer processes often control the formation of shallow clouds and subsequently deep convective precipitation over the U.S. Southern Great Plains. In this study, we examine the impacts of large‐scale advection on the cloud populations and land‐atmospheric coupling observed during the Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems field campaign in 2016. We performed two large eddy simulations using the Weather Research and Forecasting Model for a day in which the transition from clear‐sky to shallow precipitating clouds and isolated deep convection was observed. The control simulation reproduced the overall distribution of cloud populations by using realistic soil conditions with an interactive land model. In the sensitivity simulation where large‐scale advection is removed, a strong relationship between the land and boundary layer is found. To study the timing, location, and intensity of convective initiation and the relationship of clouds with land surface properties, a cluster analysis of equivalent potential temperature is performed for the simulation without large‐scale advection. That analysis shows that convective clouds first form over regions with higher surface sensible heat flux. Precipitation from those convective clouds likely triggers new updrafts nearby about 2 hr later through the lifting associated with cold pools. The cluster analysis also shows that in addition to the spatial pattern of soil moisture, land use and soil texture in western Oklahoma also influence the location of convective initiation.

Postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario.