This paper reviews the current knowledge of the climatological, structural, and organizational aspects of stratocumulus clouds and the physical processes controlling them. More of Earth’s surface is covered by stratocumulus clouds than by any other cloud type making them extremely important for Earth’s energy balance, primarily through their reflection of solar radiation. They are generally thin clouds, typically occupying the upper few hundred meters of the planetary boundary layer (PBL), and they preferably occur in shallow PBLs that are readily coupled by turbulent mixing to the surface moisture supply. Thus, stratocumuli favor conditions of strong lower-tropospheric stability, large-scale subsidence, and a ready supply of surface moisture; therefore, they are common over the cooler regions of subtropical and midlatitude oceans where their coverage can exceed 50% in the annual mean. Convective instability in stratocumulus clouds is driven primarily by the emission of thermal infrared radiation from near the cloud tops and the resulting turbulence circulations are enhanced by latent heating in updrafts and cooling in downdrafts. Turbulent eddies and evaporative cooling drives entrainment at the top of the stratocumulus-topped boundary layer (STBL), which is stronger than it would be in the absence of cloud, and this tends to result in a deepening of the STBL over time. Many stratocumulus clouds produce some drizzle through the collision–coalescence process, but thicker clouds drizzle more readily, which can lead to changes in the dynamics of the STBL that favor increased mesoscale variability, stratification of the STBL, and in some cases cloud breakup. Feedbacks between radiative cooling, precipitation formation, turbulence, and entrainment help to regulate stratocumulus. Although stratocumulus is arguably the most well-understood cloud type, it continues to challenge understanding. Indeed, recent field studies demonstrate that marine stratocumulus precipitate more strongly, and entrain less, than was previously thought, and display an organizational complexity much larger than previously imagined. Stratocumulus clouds break up as the STBL deepens and it becomes more difficult to maintain buoyant production of turbulence through the entire depth of the STBL. Stratocumulus cloud properties are sensitive to the concentration of aerosol particles and therefore anthropogenic pollution. For a given cloud thickness, polluted clouds tend to produce more numerous and smaller cloud droplets, greater cloud albedo, and drizzle suppression. In addition, cloud droplet size also affects the time scale for evaporation–entrainment interactions and sedimentation rate, which together with precipitation changes can affect turbulence and entrainment. Aerosols are themselves strongly modified by physical processes in stratocumuli, and these two-way interactions may be a key driver of aerosol concentrations over the remote oceans. Aerosol–stratocumulus interactions are therefore one of the most challenging frontiers in cloud–climate research. Low-cloud feedbacks are also a leading cause of uncertainty in future climate prediction because even small changes in cloud coverage and thickness have a major impact on the radiation budget. Stratocumuli remain challenging to represent in climate models since their controlling processes occur on such small scales. A better understanding of stratocumulus dynamics, particularly entrainment processes and mesoscale variability, will be required to constrain these feedbacks. CONTENTS Introduction...2 Climatology of stratocumulus...4 Annual mean...4 Temporal variability...6 Spatial scales of organization1...0 The stratocumulus-topped boundary layer...11 Vertical structure of the STBL...11 Liquid water...14 Entrainment interfacial layer...15 Physical processes controlling stratocumulus...16 Radiative driving of stratocumulus...16 Turbulence...21 Surface fluxes...24 Entrainment...25 Precipitation...26 Microphysics...27 Cloud droplet concentration and controlling factors...27 Microphysics of precipitation formation...29 Interactions between physical processes...32 Maintenance and regulating feedbacks...32 Microphysical–macrophysical interactions...34 Interactions between the STBL and large-scale meteorology...35 Formation...36 Dissipation and transition to other cloud types...36 Summary...40

Observations in subtropical regions show that stratiform low cloud cover is well correlated with the lower-troposphere stability (LTS), defined as the difference in potential temperature θ between the 700-hPa level and the surface. The LTS can be regarded as a measure of the strength of the inversion that caps the planetary boundary layer (PBL). A stronger inversion is more effective at trapping moisture within the marine boundary layer (MBL), permitting greater cloud cover. This paper presents a new formulation, called the estimated inversion strength (EIS), to estimate the strength of the PBL inversion given the temperatures at 700 hPa and at the surface. The EIS accounts for the general observation that the free-tropospheric temperature profile is often close to a moist adiabat and its lapse rate is strongly temperature dependent. Therefore, for a given LTS, the EIS is greater at colder temperatures. It is demonstrated that while the seasonal cycles of LTS and low cloud cover fraction (CF) are strongly correlated in many regions, no single relationship between LTS and CF can be found that encompasses the wide range of temperatures occurring in the Tropics, subtropics, and midlatitudes. However, a single linear relationship between CF and EIS explains 83% of the regional/seasonal variance in stratus cloud amount, suggesting that EIS is a more regime-independent predictor of stratus cloud amount than is LTS under a wide range of climatological conditions. The result has some potentially important implications for how low clouds might behave in a changed climate. In contrast to Miller’s thermostat hypothesis that a reduction in the lapse rate (Clausius–Clapeyron) will lead to increased LTS and increased tropical low cloud cover in a warmer climate, the results here suggest that low clouds may be much less sensitive to changes in the temperature profile if the vertical profile of tropospheric warming follows a moist adiabat.

Liquid water path (LWP) mesoscale spatial variability in marine low cloud over the eastern subtropical oceans is examined using two months of daytime retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra satellite. Approximately 20 000 scenes of size 256 km × 256 km are used in the analysis. It is found that cloud fraction is strongly linked with the LWP variability in the cloudy fraction of the scene. It is shown here that in most cases LWP spatial variance is dominated by horizontal scales of 10–50 km, and increases as the variance-containing scale increases, indicating the importance of organized mesoscale cellular convection (MCC). A neural network technique is used to classify MODIS scenes by the spatial variability type (no MCC, closed MCC, open MCC, cellular but disorganized). It is shown how the different types tend to occupy distinct geographical regions and different physical regimes within the subtropics, although the results suggest considerable overlap of the large-scale meteorological conditions associated with each scene type. It is demonstrated that both the frequency of occurrence, and the variance-containing horizontal scale of the MCC increases as the marine boundary layer (MBL) depth increases. However, for the deepest MBLs, the MCC tends to be replaced by clouds containing cells but lacking organization. In regions where MCC is prevalent, a lack of sensitivity of the MCC type (open or closed) to the large-scale meteorology was found, suggesting a mechanism internal to the MBL may be important in determining MCC type. The results indicate that knowledge of the physics of MCC will be required to completely understand and predict low cloud coverage and variability in the subtropics.

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.climate | aerosol−cloud effects | general circulation models | radiative forcing | satellite observations Clouds play a key role in Earth's radiation budget, and aerosols serve as the seeds upon which cloud droplets form. Anthropogenic activity has led to an increase in aerosol particle concentrations globally and an increase in those particles that act as cloud condensation nuclei (CCN) and ice nucleating particles (INP). The effect of an increase in aerosols on cloud optical properties, and associated radiative forcing, is the most uncertain component of historical radiative forcing of Earth's climate caused by greenhouse gases (GHGs) and aerosols. The Intergovernmental Panel on Climate Change (IPCC) AR5 assessment of climate forcing factors (Fig. S1) ascribes "high" confidence to the estimate of direct aerosol radiative forcing (mean

SUMMARYShip-based radar measurements obtained during the East Pacific Investigation of Climate 2001 stratocumulus (Sc) cruise are used to derive characteristics of the rainfall from drizzling Sc. Reflectivity to rain rate (Z-R) relationships are determined from shipboard raindrop-size distribution measurements obtained from observations using filter-paper, and compared to Z-R relationships derived from aircraft probe data from below north-east Atlantic drizzling Sc and stratus. A model for the evaporation and sedimentation of drizzle is combined with reflectivity profiles from a millimetre-wavelength cloud radar to derive information on the mean raindrop radius and drizzle drop concentrations at cloud base, and to show how Z-R relationships change with height below the cloud base. The Z-R relationships are used in conjunction with shipborne C-band radar reflectivity data to estimate areal average precipitation with uncertainties at cloud base and at the surface. In the Sc drizzle Z-R relationship, Z = aR b (where a and b are constants), the estimated exponent b = 1.1 to 1.4 is lower than commonly observed in deep convective rain (b = 1.5). Analyses indicate that variations in Sc rain rates and reflectivities are influenced both by fluctuations in drizzle drop concentration and in mean radius, but that number concentration contributes more to the modulation of rain rate in Sc. Rain rates derived using the scanning C-band radar are found to be spatially variable, with much of the accumulation originating from a small fraction of the drizzling area. The observations also suggest that rain rate in marine Sc is strongly dependent on cloud liquidwater path, and inversely correlated with cloud droplet concentration.

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The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.

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