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Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb ). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb ), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. Those processes are manifest in a number of relationships that can be expressed as factors dlnX/dlnY driving aerosol effects on cloud radiative forcing. These factors include the relationships between cloud condensation nuclei (CCN) concentration and emissions, droplet number and CCN concentration, cloud fraction and droplet number, cloud optical depth and droplet number, and cloud radiative forcing and cloud optical depth. The relationship between cloud optical depth and droplet number can be further decomposed into the sum of two terms involving the relationship of droplet effective radius and cloud liquid water path with droplet number. These relationships can be constrained using observations of recent spatial and temporal variability of these quantities. However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. Our analysis of Aerosol Comparisons between Observations and Models (AeroCom) model simulations suggests that estimates of relationships from recent variability are poor constraints on relationships from anthropogenic change for some terms, with even the sign of some relationships differing in many regions. Proxies connecting recent spatial/temporal variability to anthropogenic change, or sustained measurements in regions where emissions have changed, are needed to constrain estimates of anthropogenic aerosol impacts on cloud radiative forcing.

Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state‐of‐the‐art global climate models (GCM), especially those in which embedded cloud‐resolving models replace conventional statistical parameterizations (i.e., multiscale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre‐industrial and present‐day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten‐year GCM simulations with nudging provide a more stable estimate of the global‐annual mean net aerosol indirect radiative forcing than do conventional free‐running simulations. The estimates have mean values and 95% confidence intervals of −1.19 ± 0.02 W/m2 and −1.37 ± 0.13 W/m2for nudged and free‐running simulations, respectively. Nudging also substantially increases the fraction of the world's area in which a statistically significant aerosol indirect effect can be detected (66% and 28% of the Earth's surface for nudged and free‐running simulations, respectively). One‐year MMF simulations with and without nudging provide global‐annual mean net aerosol indirect radiative forcing estimates of −0.81 W/m2 and −0.82 W/m2, respectively. These results compare well with previous estimates from three‐year free‐running MMF simulations (−0.83 W/m2), which showed the aerosol‐cloud relationship to be in better agreement with observations and high‐resolution models than in the results obtained with conventional cloud parameterizations. Key Points Nudged simulations provide more stable estimates of aerosol indirect effects Nudging increases the area a statistically significant signal can be detected Nudging enables computation‐expensive GCMs to estimate aerosol indirect effects

Postfrontal cloud regime transitions often result from strong aerosol‐cloud‐precipitation interaction. Using ACTIVATE measurements from 40 flights, we show a diurnal pattern of evolving aerosol particle size distributions (PSD) in the marine boundary layer upwind of clouds. A nucleation mode grows in size between 12 and 17 LT, likely from new particle formation (NPF), and an accumulation mode increases in concentration during daytime. Selecting the day of strongest size growth, we use quasi‐Lagrangian large‐eddy simulations to examine cloud impacts. With a morning PSD, moderate aerosol hygroscopicity aligns best with satellite and field campaign observational targets. Using a PSD near 17 LT, greater cloud droplet number concentrations delay the precipitation onset and keep albedo elevated for longer, primarily driven by increased accumulation mode concentrations, which facilitate an updraft‐limited regime and inhibit activation of smaller modes despite their growth after NPF. These results constitute a caveat for NPF‐related activation under polluted conditions.

We present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead‐lag phase difference between cloud‐proxy liquid water path (LWP) and aerosol‐proxy cloud droplet number concentration (Nd) in an Eulerian framework using satellite‐based observations and climate model outputs. This approach allows us to identify the causality and dominant adjustment timescales governing the correlation between LWP and Nd. Satellite observations indicate a more prevalent positive correlation between daytime LWP and Nd regardless of whether LWP leads or lags Nd. The positive cloud water response, associated with precipitation processes, typically occurs within 1 hr, while the negative response resulting from entrainment drying, usually takes 2–4 hr. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and Nd compared to observations. Plain Language Summary We employ a wavelet phase coherence analysis to understand how changes in cloud water and cloud droplet concentration are related to each other over time. By analyzing satellite data and climate model output, we study when one variable leads or lags the other and how quickly they adjust to one another. Our findings show that during the day cloud water and cloud droplet concentration often change in the same direction, indicating cloud development and precipitation processes. This effect usually happens within 1 hr. Sometimes cloud water and cloud droplet concentration can change in opposite directions. This is due to clouds being more prone to evaporation at their tops when there is an increase in smaller droplets. Typically this effect takes approximately 2–4 hr to occur. We also compared our observations with a climate model, which shows a too rapid and overly strong negative cloud water response to the change in cloud droplet concentration. Key Points Wavelet phase coherence method is introduced to understand the causal relationships and adjustment timescales of aerosol‐cloud interactions Satellite observations indicate prevalent and rapid positive responses of cloud water path to cloud droplet number concentration CAM6 shows overly rapid and strong negative but insufficient positive responses of cloud water path to cloud droplet number concentration

Numerical simulations described in previous studies showed that adding cloud condensation nuclei to marine stratocumulus can prevent their breakup from closed into open cells. Additional analyses of the same simulations show that the suppression of rain is well described in terms of cloud drop effective radius (re). Rain is initiated when re near cloud top is around 12–14 μm. Cloud water starts to get depleted when column‐maximum rain intensity (Rmax) exceeds 0.1 mm h−1. This happens when cloud‐top re reaches 14 μm. Rmax is mostly less than 0.1 mm h−1 at re < 14 μm, regardless of the cloud water path, but increases rapidly when re exceeds 14 μm. This is in agreement with recent aircraft observations and theoretical studies in convective clouds so that the mechanism is not limited to describing marine stratocumulus. These results support the hypothesis that the onset of significant precipitation is determined by the number of nucleated cloud drops and the depth (D) above cloud base within the cloud that is required for cloud drops to reach re of 14 μm. In turn, this can explain the conditions for initiation of significant drizzle and opening of closed cells providing the basis for a simple parameterization for GCMs that unifies the representation of both precipitating and non‐precipitating clouds as well as the transition between them. Furthermore, satellite global observations of cloud depth (from base to top), and cloud‐top re can be used to derive and validate this parameterization. Key Points Numerical simulations show how aerosols and cloud depth control rain initiation Rain is iniated when drops r‐eff reach 14 mum regardless of cloud water path This can explain the control of aerosols on change between closed and open cells

This study shows for the first time statistical evidence that when anthropogenic aerosols over the eastern United States during summertime are at their weekly mid‐week peak, tornado and hailstorm activity there is also near its weekly maximum. The weekly cycle in summertime storm activity for 1995–2009 was found to be statistically significant and unlikely to be due to natural variability. It correlates well with previously observed weekly cycles of other measures of storm activity. The pattern of variability supports the hypothesis that air pollution aerosols invigorate deep convective clouds in a moist, unstable atmosphere, to the extent of inducing production of large hailstones and tornados. This is caused by the effect of aerosols on cloud drop nucleation, making cloud drops smaller and hydrometeors larger. According to simulations, the larger ice hydrometeors contribute to more hail. The reduced evaporation from the larger hydrometeors produces weaker cold pools. Simulations have shown that too cold and fast‐expanding pools inhibit the formation of tornados. The statistical observations suggest that this might be the mechanism by which the weekly modulation in pollution aerosols is causing the weekly cycle in severe convective storms during summer over the eastern United States. Although we focus here on the role of aerosols, they are not a primary atmospheric driver of tornados and hailstorms but rather modulate them in certain conditions. Key Points Hailstorms and tornadic storms occur more frequently in more polluted moist air masses Pollution aerosols can cause convective storms to become severe

The impact of air pollution control programs on the vertical structure of precipitation remains poorly understood. Using multiple data sources, we observed a yearly decrease in aerosol optical depth (AOD) in southern China from 2014 to 2019, probably due to these programs. In contrast, the precipitation top height related to rain onset (PTH0), increased annually after accounting for thermodynamic variations. Further analyses revealed that, within the mixed/lower atmospheric layers, the growth of precipitating particles (SlopeA/SlopeB) was significantly faster/slower in 2014 compared to subsequent years. The correlation coefficients (R) between AOD and SlopeA and PTH0 were 0.99 and −0.94, respectively. As this study is based on multi‐source observations, further research incorporating model simulations is necessary to elucidate the mechanisms underlying the impact of emission reductions on the vertical structure of precipitation. Plain Language Summary From 2014 to 2019, the concentration of atmospheric pollutants decreased annually as the Chinese government's pollution control measures were strengthened. Our findings indicate that the height of rain onset increased each year when differences in thermodynamic conditions were eliminated, while the growth of precipitating particles within the mixed atmospheric layer decreased annually. Additionally, high aerosol concentrations were found to suppress the growth of precipitating particles within the lower layer. While these results are based on observational data, further investigation using model simulations is required to elucidate the underlying mechanisms. These observations may provide helpful references for future research. Key Points Following the implementation of emission reduction measures, aerosol optical depth decreased annually, while the height of rain onset increased each year The growth of precipitating particles within the mixed layer (SlopeA) decreased annually When aerosol concentration is high, the growth of precipitating particles within the lower layer (SlopeB) is suppressed

Lagrangian Cloud Model (LCM) is a mixed Eulerian/Lagrangian approach to atmospheric large eddy simulation (LES), with two‐way coupling between Eulerian dynamics and thermodynamics and Lagrangian microphysics. Since Lagrangian representation of microphysics does not suffer from numerical diffusion in the radius space and solves full droplet growth equations, it may be considered an alternative for the bin approach. This paper documents the development of LCM to include collision/coalescence processes. The proposed algorithm maps Lagrangian parcels collision/coalescence events on the specified two‐dimensional grid, with the first dimension spanning aerosol radius and the second dimension spanning the cloud droplet radius. The proposed approach is capable of representation of aerosol activation, deactivation, transport inside the droplets, and processing by clouds and in the future may be used to investigate details of these processes. As an illustration, LCM with collision/coalescence is used to investigate effects of aerosols on cloud microphysics and dynamics for a marine stratocumulus cloud. Two extreme cases are considered that represent low and high aerosol concentrations. It is shown that the aerosol type significantly affects cloud microphysics as well as cloud dynamics. In agreement with previous studies, a larger entrainment rate is simulated for the high aerosol concentration. For the low aerosol concentration, intense collision/coalescence and drizzle modify the aerosol size distribution, reducing the concentration in the dry radius range of 0.02 to 0.2 μm and increasing the concentration for dry radii larger than 0.3 μm.

To investigate the impact of advanced microphysics schemes using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted using Weather Research and Forecasting (WRF) model for a severe mesoscale convective system (MCS) formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation linked with the convective system are improved in the WDM6 simulation. During the developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with the mixing ratio of hydrometeors (cloud, rain, graupel, snow, and ice), the number concentration of cloud and rainwater are also predictable in WDM6. To understand the differences in the vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with the Nr readily available in WDM6. Varied vertical distribution and large differences in rain number concentration and rain particle mass is evident between the schemes. Inclusion of the number concentration of rain and cloud, CCN, along with the mixing ratio of different hydrometers has improved the storm morphology in WDM6. Furthermore, the latent heating (LH) profiles of six major phase transformation processes (condensation, evaporation, freezing, melting, deposition, and sublimation) are also computed from microphysical production terms to deeply study the storm vertical structure. The main differences in condensation and evaporation terms are evident between the simulations due to the varied treatment of warm rain processes and the inclusion of CCN activation in WDM6. To investigate cloud–aerosol interactions, numerical simulation is conducted by increasing the CCN (aerosol) concentration in WDM6, which simulated comparatively improved pattern correlation for rainfall simulation along with intense hydrometer distribution. It can be inferred that the change in aerosol increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution, and subsequent rainfall. Relatively, the WDM6 simulated latent heating profile distribution is more consistent with the ERA5 computed moisture source and sink terms due to the improved formulation of warm rain processes.