Abstract

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

1. Introduction...2

2. Climatology of stratocumulus...4

   1. Annual mean...4

   2. Temporal variability...6

   3. Spatial scales of organization1...0

3. The stratocumulus-topped boundary layer...11

   1. Vertical structure of the STBL...11

   2. Liquid water...14

   3. Entrainment interfacial layer...15

4. Physical processes controlling stratocumulus...16

   1. Radiative driving of stratocumulus...16

   2. Turbulence...21

   3. Surface fluxes...24

   4. Entrainment...25

   5. Precipitation...26

5. Microphysics...27

   1. Cloud droplet concentration and controlling factors...27

   2. Microphysics of precipitation formation...29

6. Interactions between physical processes...32

   1. Maintenance and regulating feedbacks...32

   2. Microphysical–macrophysical interactions...34

   3. Interactions between the STBL and large-scale meteorology...35

   4. Formation...36

   5. Dissipation and transition to other cloud types...36

7. Summary...40

Abstract

Applying perturbation theory within a mixed layer framework, the response of the marine boundary layer (MBL) cloud thickness h to imposed increases of the cloud droplet concentration N_d as a surrogate for increases in cloud condensation nuclei (CCN) concentrations is examined. An analytical formulation is used to quantify the response and demonstrate theoretically that for the range of environmental conditions found over the subtropical eastern oceans, on time scales of less than a day, the cloud thickness feedback response is largely determined by a balance between the moistening/cooling of the MBL resulting from the suppression of surface precipitation, and the drying/warming resulting from enhanced entrainment resulting from increased turbulent kinetic energy. Quantifying the transient cloud response as a ratio of the second to the first indirect effects demonstrates that the nature of the feedback is critically dependent upon the nature of the unperturbed state, with the cloud-base height z _cb being the single most important determinant. For z _cb < 400 m, increasing N_d leads to cloud thickening in accordance with the Albrecht hypothesis. However, for z _cb > 400 m, cloud thinning occurs, which results in a feedback effect that increasingly cancels the Twomey effect as z _cb increases. The environmental conditions favoring an elevated cloud base are relatively weak lower-tropospheric stability and a dry free troposphere, although the former is probably more important over the subtropical eastern oceans. On longer time scales an invariable thickening response is found, and thus accurate quantification of the aerosol indirect effects will require a good understanding of the processes that control the time scale over which aerosol perturbations are modified.

Abstract

The evolution of subtropical stratocumulus clouds and the boundary layer is studied on daily time scales from the Lagrangian perspective, following the flow. Measures of humidity above the boundary layer and of inversion strength are obtained from reanalysis data, and their effects on the Lagrangian evolution of cloud cover and the boundary layer are compared. An analysis that disentangles these variables and tests their effects independently is developed. Increased inversion strength and increased humidity above the boundary layer lead to anomalously persistent cloud cover and slower Lagrangian deepening of the boundary layer. These parameters affect the stratocumulus boundary layer in different ways: inversion strength controls the buoyancy difference across the inversion, while humidity differences affect both the radiation balance and rate of cloud drop evaporation at cloud top. The relative strengths of the two effects of humidity are compared using two products: the entraining humidity in the layer directly above the inversion and the radiating humidity, which is the mean humidity in the column above the entraining humidity. Results show that the variability in the radiating humidity is the primary driver of Lagrangian boundary layer depth changes, but entraining humidity variation is mostly responsible for altering cloud lifetime.

Abstract

A Lagrangian technique is developed to sample satellite data to quantify and understand factors controlling temporal changes in low-cloud properties (cloud cover, areal-mean liquid water path, and droplet concentration). Over 62 000 low-cloud scenes over the eastern subtropical/tropical oceans are sampled using the A-Train satellites. Horizontal wind fields at 925 hPa from the ERA-Interim are used to compute 24-h, two-dimensional, forward, boundary layer trajectories with trajectory locations starting on the CloudSat/CALIPSO track. Cloud properties from MODIS and AMSR-E are sampled at the trajectory start and end points, allowing for direct measurement of the temporal cloud evolution. The importance of various controls (here, boundary layer depth, lower-tropospheric stability, and precipitation) on cloud evolution is evaluated by comparing cloud evolution for different initial values of these controls. Viewing angle biases are removed and cloud anomalies (diurnal and seasonal cycles removed) are used throughout to quantify cloud evolution relative to the climatological-mean evolution. Cloud property anomalies show temporal changes similar to those expected for a stochastic red noise process, with linear relationships between initial anomalies and their mean 24-h changes. This creates a potential bias when comparing the evolutions of sets of trajectories with different initial anomalies; three methods are introduced and evaluated to account for this. Results provide statistically robust observational support for theoretical/modeling studies by showing that low clouds in deep boundary layers and under weak inversions are prone to break up. Precipitation shows a more complex and less statistically significant relationship with cloud breakup. Cloud cover in shallow precipitating boundary layers is more persistent than in deep precipitating boundary layers. Liquid water path and cloud droplet concentration decrease more rapidly for precipitating clouds and in deep boundary layers.

Abstract

Cloud horizontal size distributions from near-global satellite data, from aircraft, and from a global high-resolution numerical weather prediction model, are presented for the scale range 0.1–8000 km and are shown to be well-represented using a single power-law relationship with an exponent of β = 1.66 ±0.04 from 0.1 to 1500 km or more. At scales longer than 1500 km, there is a statistically significant scale break with fewer very large clouds than expected from the power law. The size distribution is integrated to determine the contribution to cloud cover and visible reflectance from clouds larger than a given size. Globally, clouds with a horizontal dimension of 200 km or more constitute approximately 50% of the cloud cover and 60% of the reflectance, and this result is not sensitive to the minimum size threshold assumed in the integral assuming that the power law can be extrapolated below 100-m scale. The result is also not sensitive to whether the size distribution is determined using cloud segment length or cloud area. This emphasizes the great role played by large cloud sheets in determining the earth’s albedo. On the other hand, some 15% of global cloud cover comes from clouds smaller than 10 km, thus emphasizing the broad range of cloud sizes that contribute significantly to the earth’s radiation budget. Both of these results stem from the fact that β is slightly less than 2. The data are further divided and geographical and seasonal variations in the cloud size L ₅₀ for which clouds larger than L ₅₀ constitute 50% of the cloud cover are determined. The largest clouds (L ₅₀ > 300 km) are found over the midlatitude oceans, particularly in summer, and over the tropical convective regions of the west Pacific and Indian Oceans and the monsoon-influenced landmasses. The smallest clouds (L ₅₀ < 100 km) are found over the trade wind regions of the tropics/subtropics and over arid land areas. Small variations in the exponent β contribute significantly to the variations in L50. Finally, it is shown that a bounded cascade model can faithfully simulate the observed cloud size distributions and use this to examine the effects of limiting sensor resolution (pixel size) and domain size (number of pixels across image). Sensor resolution is not found to strongly impact the cloud size distribution provided the ratio of the domain to pixel size remains greater than ~1000. Thus, previous studies with small domain–pixel size ratios may provide biased information about the true cloud size distribution, and should be interpreted with caution.

Abstract

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.

Abstract

Composite mean fields and probability distribution functions (PDFs) of rain rate, cloud type and cover, cloud-top temperature, surface wind velocity, and water vapor path (WVP) are constructed using satellite observations of midlatitude cyclones from four oceanic regions (i.e., the North Pacific, South Pacific, North Atlantic, and South Atlantic). Reanalysis surface pressure fields are used to ascertain the locations of the cyclone centers, onto which the satellite fields are interpolated to give a database of ∼1500 cyclones from a two-year period (2003–04). Cyclones are categorized by their strength, defined here using surface wind speed, and by their WVP, and it is found that these two measures can explain a considerable amount of the intercyclone variability of other key variables. Composite cyclones from each of the four ocean basins exhibit similar spatial structure for a given strength and WVP. A set of nine composites is constructed from the database using three strength and three WVP ranges and is used to demonstrate that the mean column relative humidity of these systems varies only slightly (0.58–0.62) for a doubling in WVP (or equivalently a 7-K rise in sea surface temperature) and a 50% increase in cyclone strength. However, cyclone-mean rain rate increases markedly with both cyclone strength and WVP, behavior that is explained with a simple warm conveyor belt model. Systemwide high cloud fraction (tops above 440 hPa) increases from 0.23 to 0.31 as cyclone strength increases by 50%, but does not vary systematically with WVP. It is suggested that the composite fields constitute useful diagnostics for evaluating the behavior of large-scale numerical models, and may provide insight into how precipitation and clouds in midlatitude cyclones respond under a changed climate.

Abstract

Relationships among total water, condensed water, and cloud fraction in boundary layer and cold tropospheric stratiform clouds are investigated using a large observational dataset collected by the U.K. Met. Office C-130 aircraft. Values of the above parameters are estimated using horizontal aircraft runs ranging from 40 to 80 km in length. Boundary layer (warm cloud) data were taken from the Atlantic Stratocumulus Transition Experiment (ASTEX) and First International Satellite Cloud Climatology Project (ISCCP) Research Experiment (FIRE). Free tropospheric (cold cloud) data were taken from the European Cloud and Radiation Experiment (EUCREX). In both warm and cold cloud a single reasonably well-defined relationship exists between the cloud fraction and the total water content (vapor + condensate) when normalized with the saturation specific humidity. A relationship exists between the condensed water content and the cloud fraction when appropriately scaled with the saturation specific humidity. Functional forms fitted to the data are used as comparators to test three existing diagnostic cloud fraction parameterization schemes.