The effect of anthropogenic aerosols on clouds has the potential to be a key component for climate change predictions, yet is one of the least understood. It is possible that high aerosol loading can change the convection intensity and hence the electrical activity of thunderstorm clouds. Focusing on the Amazon dry season, where thousands of man‐made forest fires inject smoke into the atmosphere, we studied the aerosol effects on thunderclouds. We used the ground‐based World‐Wide Lightning Location Network (WWLLN) lightning measurements together with Aqua‐MODIS aerosol and cloud data to show evidence for the transition between two opposing effects of aerosols on clouds. The first is the microphysical effect which is manifested in an increase in convective intensity (and electrical activity), followed by the radiative effect that becomes dominant with the increase in aerosol loading leading to a decrease in convective intensity.

Warm rain production as the end result of all clouds' processes is highly affected by aerosol loading and properties. Here an axisymmetric bin microphysics cloud model is used to study the aerosol's effects on the competition and synergy between processes in a single convective cloud, to provide a baseline for studies of aerosol effects on cloud fields. A new measure that considers the timing of processes is suggested for evaluating the optimal conditions for maximum rain yield. These conditions are linked to an optimal aerosol concentration (N_{rain_op}), which drives similar time intervals to maximum collected mass and to maximum vertical development. N_{rain_op} is a function of cloud size and thermodynamic conditions. Giant cloud condensation nuclei (GCCN) impact was shown before to precede the initiation of collision‐coalescence and to increase the amount of rain from polluted clouds. Here we show that the GCCN effect is important only under aerosol conditions above N_{rain_op}.

A numerical cloud model is used to study the influence of aerosol on the microphysics and dynamics of moderate-sized, coastal, convective clouds that develop under the same meteorological conditions. The results show that polluted convective clouds start their precipitation later and precipitate less than clean clouds but produce larger rain drops. The evaporation process is more significant at the margins of the polluted clouds (compared to the clean cloud) due to a higher drop surface area to volume ratio and it is mostly from small drops. It was found that the formation of larger raindrops in the polluted cloud is due to a more efficient collection process.

Clouds play a key role in Earth's energy budget and water cycle. Their response to global warming contributes the largest uncertainty to climate prediction. Here, by performing an empirical orthogonal function analysis on 42 years of reanalysis data of global cloud coverage, we extract an unambiguous trend and El-Niño–Southern-Oscillation-associated modes. The trend mode translates spatially to decreasing trends in cloud coverage over most continents and increasing trends over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trends in cloud coverage over land. Our results suggest potential stress on the terrestrial water cycle and changes in the energy partition between land and ocean, all associated with global warming.

Physical insights into processes governing temporal organization and evolution of cloud fields are of great importance for climate research. Here using large eddy simulations with a bin microphysics scheme, we show that warm convective cloud fields exhibit oscillations with two distinct periods (~10 and ~90 min, for the case studied here). The shorter period dominates the nonprecipitating phase, and the longer period is related to the precipitating phase. We show that rain processes affect the domain's thermodynamics, hence forcing the field into a low‐frequency recharge‐discharge cycle of developing cloudiness followed by precipitation‐driven depletion. The end result of precipitation is stabilization of the lower atmosphere by warming of the cloudy layer (due to latent heat release) and cooling of the subcloud layer (by rain evaporation, creating cold pools). As the thermodynamic instability weakens, so does the cloudiness, and the rain ceases. During the nonprecipitating phase of the cycle, surface fluxes destabilize the boundary layer until the next precipitation cycle. Under conditions that do not allow development of precipitation (e.g., high aerosol loading), high‐frequency oscillations dominate the cloud field. Clouds penetrating the stable inversion layer trigger gravity waves with a typical period of ~10 min. In return, the gravity waves modulate the clouds in the field by modifying the vertical velocity, temperature, and humidity fields. Subsequently, as the polluted nonprecipitating simulations evolve, the thermodynamic instability increases and the cloudy layer deepens until precipitation forms, shifting the oscillations from high to low frequency. The organization of cold pools and the spatial scale related to these oscillations are explored.