A climatology of thermodynamic phase of precipitating cloud is presented derived from global—land and ocean—, retrievals from Cloudsat, CALIPSO, and Moderate Resolution Imaging Spectroradiometer. Like precipitation rate, precipitation frequency is dominated by warm rain, defined as rain produced via the liquid phase only, over the tropical oceans outside the Intertropical Convergence Zone and by cold rain, produced via the ice phase, over the midlatitude oceans and continents. Warm rain is very infrequent over the continents, with significant warm rain found only in onshore flow in the tropics, and over India, China, and Indochina. Comparison of the properties of precipitating and nonprecipitating warm clouds shows that the scarcity of warm rain over land can be explained by smaller effective radii in continental clouds that delay the onset of precipitation. The results highlight the importance of ice‐phase processes for the global hydrological cycle and may lead to an improved parameterization of precipitation in general circulation models.

This article discusses some of the challenges that have limited progress in quantifying the radiative forcing associated with aerosol–cloud interactions (ACI) in warm (liquid-water) clouds. It reviews recent progress and suggests new ways of viewing the problem that might accelerate progress. It calls for much greater attention to the scale problem, both in terms of aerosol–cloud process representation in models and comparison with observations. It suggests careful consideration of the balance in detail with which processes are represented, and proposes a merging of detailed process understanding and system-wide behavior. In this spirit, it advocates tackling the problem with models of varying complexity that consider both the depth and breadth of the complex dynamical system. Finally, it considers shifting attention from untangling aerosol and meteorological effects on cloud systems towards understanding the co-variability of key aerosol and meteorological drivers of cloud systems.

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔN_d, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔN_d, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (N_d) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔN_d, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔN_d, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) N_d, (iii) the statistical approach for inferring the sensitivity of N_d to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of N_d, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the N_d-to-CCN sensitivity, key issues are the updraught distributions and the role of N_d sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.