Abstract
Stratocumulus clouds constitute one of the largest negative climate forcings in the global radiation budget. This forcing is determined, inter alia, by the cloud liquid water path (LWP), ...which we analyze using a combination of Gaussian process emulation and mixed-layer theory. For nocturnal, nonprecipitating stratocumuli, we show that LWP steady states constitute an equilibrium primarily between radiative cooling and entrainment warming and drying. These steady states are approached from lower LWPs due to reduced entrainment, while higher LWPs are depleted by stronger entrainment. An analytical solution for the LWP steady state reveals not only the environmental conditions in which a stratocumulus cloud can be maintained, but also distinct analytical properties of the entrainment velocity that are required for a stable LWP steady state that opposes perturbations. In particular, the results highlight the importance of an entrainment velocity that increases strictly monotonically with the LWP if stratocumuli are to attain a stable LWP steady state. This is demonstrated through analysis of two commonly used mixed-layer entrainment parameterizations.
Small shallow cumulus clouds (<1 km) over the tropical oceans appear to possess the ability to self‐organize into mesoscale (10–100 km) patterns. To better understand the processes leading to such ...self‐organized convection, we present Cloud Botany, an ensemble of 103 large‐eddy simulations on domains of 150 km, produced by the Dutch Atmospheric Large Eddy Simulation model on supercomputer Fugaku. Each simulation is run in an idealized, fixed, larger‐scale environment, controlled by six free parameters. We vary these over characteristic ranges for the winter trades, including parameter combinations observed during the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) field campaign. In contrast to simulation setups striving for maximum realism, Cloud Botany provides a platform for studying idealized, and therefore more clearly interpretable causal relationships between conditions in the larger‐scale environment and patterns in mesoscale, self‐organized shallow convection. We find that any simulation that supports cumulus clouds eventually develops mesoscale patterns in their cloud fields. We also find a rich variety in these patterns as our control parameters change, including cold pools lined by cloudy arcs, bands of cross‐wind clouds and aggregated patches, sometimes topped by thin anvils. Many of these features are similar to cloud patterns found in nature. The published data set consists of raw simulation output on full 3D grids and 2D cross‐sections, as well as post‐processed quantities aggregated over the vertical (2D), horizontal (1D) and all spatial dimensions (time‐series). The data set is directly accessible from Python through the use of the EUREC4A intake catalog.
Plain Language Summary
The organization of shallow cumulus clouds over the tropical ocean has recently received a lot of attention. This type of organization is potentially important for how the clouds are affected by a changing climate and also for how they modulate further warming. We present a collection of 103 detailed simulations of shallow cumulus clouds in idealized atmospheric environments. These environments are described by six parameters, and our collection is formed by systematically simulating different parameter combinations. This way an ensemble is created that spans up a multidimensional phase space of environmental conditions typical for the wintertime subtropical Atlantic Ocean. This approach allows us to form a picture of how the environmental conditions relate to the cloud organization that develops in the simulations. At a glance, most simulations evolve similarly: They quickly form small cumulus clouds, which then grow in size and organize into patterns. Often this leads to rainfall, which then causes further heterogeneity and pattern formation. The data is openly available online, and will serve future studies of cumulus clouds, their organization, and how they interact with the climate.
Key Points
We present Cloud Botany, an ensemble of idealized large‐eddy simulations of the winter trade wind regions, controlled by six varied parameters
The parameter ranges are chosen to match the climatology of the trade wind region
The simulations show a variety of cloud organization patterns: small cumulus, stripes, cold pools, cloud arcs, and anvils
Numerical simulations of the tropical mesoscales often exhibit a self‐reinforcing feedback between cumulus convection and shallow circulations, which leads to the self‐aggregation of clouds into ...large clusters. We investigate whether this basic feedback can be adequately captured by large‐eddy simulations (LESs). To do so, we simulate the non‐precipitating, cumulus‐topped boundary layer of the canonical “BOMEX” case over a range of numerical settings in two models. Since the energetic convective scales underpinning the self‐aggregation are only slightly larger than typical LES grid spacings, aggregation timescales do not converge even at rather high resolutions (<100 m). Therefore, high resolutions or improved sub‐filter scale models may be required to faithfully represent certain forms of trade‐wind mesoscale cloud patterns and self‐aggregating deep convection in large‐eddy and cloud‐resolving models, and to understand their significance relative to other processes that organize the tropical mesoscales.
Plain Language Summary
The most detailed models of our atmosphere frequently have their clouds spontaneously organize into large clusters. Small clouds (less than a kilometer in size) seem to play an important role in such “self‐aggregation.” However, even in detailed models small clouds are hard to adequately capture: Typically, they must resolve the motions in these clouds using only a few pixels, thus requiring additional, lower‐accuracy models for cloudy motions smaller than the pixel size. Here, we show that merely varying the resolution of several state‐of‐the‐art atmospheric models has an effect on how quickly they predict the self‐aggregation of clouds to occur, even when many complex, uncertain processes are removed from the problem. We show that this results from inconsistencies in how the smallest, resolved motions are represented at various model resolutions, and hypothesize that these inconsistencies arise because our models for the unresolved motions control the vigor of the cloudy motions in different ways when the resolution changes. To help work out how important self‐aggregation is in the real world, models of the phenomenon may therefore require finer resolutions than previously thought, or better models for the unresolved motions.
Key Points
In large‐eddy simulations, sub‐kilometer scale cumulus convection self‐organizes into mesoscale structures through shallow circulations
The aggregation time‐scale does not converge with model resolution for typical discretization choices
Numerical representations of the tropical mesoscales may require finer model resolutions than previously thought
Abstract
The sensitivity of warm- and mixed-phase orographic precipitation to the aerosol background with simultaneous changes in the abundance of cloud condensation nuclei and ice nucleating ...particles is explored in an idealized, two-dimensional modeling study. The concept of precipitation susceptibility dlnP/dlnN, where P is the precipitation mixing ratio and N the cloud droplet number, is adapted for orographic clouds. Precipitation susceptibility is found to be low because perturbations to different precipitation formation pathways compensate each other. For mixed-phase conditions, this in particular means a redistribution between warm and cold pathways. The compensating behavior is described as a consequence of a balance equation for the cloud water along parcel trajectories that constrains the total precipitation formation to match the drying from condensation and vapor deposition on ice-phase hydrometeors caused by the mountain flow. For an aerosol-independent condensation rate (saturation adjustment), this balance requirement limits aerosol impacts on orographic precipitation (i) to the evaporation of hydrometeors and (ii) to the glaciation state of the cloud, which controls the contribution of vapor deposition to drying. The redistribution of precipitation formation pathways is coupled to a redistribution of the total hydrometeor mass between hydrometeor categories. Aerosol effects on the glaciation state of the cloud enhance this redistribution effect such that liquid and ice adjustments do not compensate. For the externally constrained, fully adjusted steady-state situation studied, precipitation susceptibility quantifies the redistribution effect rather than changes in precipitation production as in previous studies.
Abstract
The strength of the effective anthropogenic climate forcing from aerosol–cloud interactions is related to the susceptibility of precipitation to aerosol effects. Precipitation susceptibility ...d lnP/d lnN has been proposed as a metric to quantify the effect of aerosol-induced changes in cloud droplet number N on warm precipitation rate P. Based on the microphysical rate equations of the Seifert and Beheng two-moment bulk microphysics scheme, susceptibilities of warm-, mixed-, and ice-phase precipitation and cirrus sedimentation to cloud droplet and ice crystal number are estimated. The estimation accounts for microphysical adjustments to the initial perturbation in N. For warm rain, d lnP/d lnN < −2aut/(aut + acc) is found, which depends on the rates of autoconversion (aut) and accretion (acc). Cirrus sedimentation susceptibility corresponds to the exponent of crystal sedimentation velocity with a value of −0.2. For mixed-phase clouds, several microphysical contributions that explain low precipitation susceptibilities are identified: (i) Because of the larger hydrometeor sizes involved, mixed-phase collection processes are less sensitive to changes in hydrometeor size than autoconversion. (ii) Only a subset of precipitation formation processes is sensitive to droplet or crystal number. (iii) Effects on collection processes and diffusional growth compensate. (iv) Adjustments in cloud liquid and ice amount compensate the effect of changes in ice crystal and cloud droplet number. (v) Aerosol perturbations that simultaneously affect ice crystal and droplet number have opposing effects.
Abstract
Stratocumulus occur in closed- or open-cell states, which tend to be associated with high or low cloud cover and the absence or presence of precipitation, respectively. Thus, the transition ...between these states has substantial implications for the role of this cloud type in Earth’s radiation budget. In this study, we analyze transitions between these states using an ensemble of 127 large-eddy simulations, covering a wide range of conditions. Our analysis is focused on the behavior of these clouds in a cloud fraction (
f
c
) scene albedo (
A
) phase space, which has been shown in previous studies to be a useful framework for interpreting system behavior. For the transition from closed to open cells, we find that precipitation creates narrower clouds and scavenges cloud droplets for all
f
c
. However, precipitation decreases the cloud depth for
f
c
> 0.8 only, causing a rapid decrease in
A
. For
f
c
< 0.8, the cloud depth actually increases due to mesoscale organization of the cloud field. As the cloud deepening balances the effects of cloud droplet scavenging in terms of influence on
A
, changes in
A
are determined by the decreasing
f
c
only, causing a linear decrease in
A
for
f
c
< 0.8. For the transition from open to closed cells, we find that longwave radiative cooling drives the cloud development, with cloud widening dominating for
f
c
< 0.5. For
f
c
> 0.5, clouds begin to deepen gradually due to the decreasing efficiency of lateral expansion. The smooth switch between cloud widening and deepening leads to a more gentle change in
A
compared to the transitions under precipitating conditions.
Significance Statement
By reflecting a substantial fraction of solar shortwave radiation back to space, shallow clouds constitute a major cooling agent in Earth’s radiation budget. To constrain this effect, a profound understanding of cloud cover and cloud albedo is necessary. In this study, we analyze the processes that drive the variability in these cloud properties in stratocumulus clouds, a very common cloud type covering approximately 20% of the globe. For these clouds, we show that changes from low to high or high to low cloud cover are different due to the underlying cloud micro- and macrophysics, elucidating this crucial aspect of aerosol–cloud–climate interactions.
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