The meso-scale variability in cloudiness of the marine trade-wind layer is explored with large-eddy simulations of regional extent and validated against observations of the EUREC4A field campaign. 41 ...days of realistically forced simulations present a representative, statistical view on shallow convection in the winter North Atlantic trades that includes a wide range of meso-scale variability including the four recently identified patterns of spatial organization: Sugar, Gravel, Flowers and Fish. The results show that cloud cover is on average captured well but with discrepancies in its vertical and spatial distribution. Cloudiness at the lifting condensation level depends on the model resolution with the finer one producing on average a more realistic cloud profile. Independent of the resolution, the variability in cloudiness below the trade inversion is not captured, leading to a lack of stratiform cloudiness with implications on the detectability of meso-scale patterns whose cloud patches are characterized by stratiform clouds. The simulations tend to precipitate more frequently than observed, with a narrower distribution of echo intensities. The observed co-variability between cloudiness and environmental conditions is well captured.
An activity designed to characterise patterns of mesoscale (20 to 2,000 km) organisation of shallow clouds in the downstream trades is described. Patterns of mesoscale organisation observed from ...space were subjectively defined and learned by 12 trained scientists. The ability of individuals to communicate, learn and replicate the classification was evaluated. Nine‐hundred satellite images spanning the area from 48°W to 58°W, 10°N to 20°N for the boreal winter months (December–February) over 10 years (2007/2008 to 2016/2017) were classified. Each scene was independently labelled by six scientists as being dominated by one of six patterns (one of which was “no‐pattern”). Four patterns of mesoscale organisation could be labelled in a reproducible manner, and were labelled Sugar, Gravel, Fish and Flowers. Sugar consists of small, low clouds of low reflectivity, Gravel clouds form along apparent gust fronts, Fish are skeletal networks (often fishbone‐like) of clouds, while Flowers are circular clumped features defined more by their stratiform cloud elements. Both Fish and Flowers are surrounded by large areas of clear air. These four named patterns were identified 40% of the time, with the most common pattern being Gravel. Sugar was identified the least and suggests that unorganised and very shallow convection is unlikely to dominate large areas of the downstream trade winds. Some of the patterns show signs of seasonal and interannual variability, and some degree of scale selectivity. Comparison of typical patterns with radar imagery suggests that even this subjective and qualitative visual inspection of imagery appears to capture several important physical differences between shallow cloud regimes, such as precipitation and radiative effects.
Sugar: MODIS‐Aqua scenes from Worldview. The images cover the area from 60°W to 48°W and 10°N to 20°N. For these images the scenes have been extended to the west to include Barbados, coloured in artificial green, on the far left. For a sense of scale, Barbados fits in a rectangle of east–west dimension of 25 km and north–south dimension of 30 km. Depending on the quality of the reproduction, some features distinguishing these from other patterns may be difficult to discern from printed (rather than electronic) renditions of this article. From left to right the images correspond to 31 December 2014, 5 December 2015 and 20 January 2016.
The relationship between mesoscale convective organization, quantified by the spatial arrangement of convection, and oceanic precipitation in the tropical belt is examined using the output of a ...global storm‐resolving simulation. The analysis uses a 2D watershed segmentation algorithm based on local precipitation maxima to isolate individual precipitation cells and derive their properties. 10° by 10° scenes are analyzed using a phase‐space representation made of the number of cells per scene and the mean area of the cells per scene to understand the controls on the spatial arrangement of convection and its precipitation. The presence of few and large cells in a scene indicates the presence of a more clustered distribution of cells, whereas many small cells in a scene tend to be randomly distributed. In general, the degree of clustering of a scene (Iorg) is positively correlated to the mean area of the cells and negatively correlated to the number of cells. Strikingly, the degree of clustering, whether the cells are randomly distributed or closely spaced, to a first order does not matter for the precipitation amounts produced. Scenes of similar precipitation amounts appear as hyperbolae in our phase‐space representation, hyperbolae that follow the contours of the precipitating area fraction. Finally, including the scene‐averaged water vapour path (WVP) in our phase‐space analysis reveals that scenes with larger WVP contain more cells than drier scenes, whereas the mean area of the cells only weakly varies with WVP. Dry scenes can contain both small and large cells, but they can contain only few cells of each category.
Convection often appears organized in satellite imagery which raises the question as to the importance of organization for climate. Here we found that convection does not appear to use organization to rain more. We also investigated the relationship between precipitation, moisture and precipitating area fraction and found that convection rains more in a moister atmosphere, not because the area of its cells increases, but because it triggers more convective cells.
We review bulk representations of tropical and subtropical maritime atmospheric boundary layers. Three types of bulk representations are studied in detail: stratocumulus topped mixed layers, ...trade-wind layers, and sub-cloud mixed layers. Through the development of a consistent description of these disparate regimes, connections among their varied representations are emphasized, as well as their relation to regions of deeper convection. New results relating to the equilibrium mass flux and cloud fraction in the trade winds; the ability of bulk models to represent qualitatively major cloud regimes; and the relationship amongst different bulk representations of the surface layer are presented. Throughout we emphasize the identification of consistent and physically based mixing and cloud regime rules for use in intermediate complexity models of the tropical climate, which in turn can be used to study cloud and dynamical interactions on larger scales. PUBLICATION ABSTRACT
RCEMIP, an intercomparison of multiple types of models configured in radiative–convective equilibrium (RCE), is proposed. RCE is an idealization of the climate system in which there is a balance ...between radiative cooling of the atmosphere and heating by convection. The scientific objectives of RCEMIP are three-fold. First, clouds and climate sensitivity will be investigated in the RCE setting. This includes determining how cloud fraction changes with warming and the role of self-aggregation of convection in climate sensitivity. Second, RCEMIP will quantify the dependence of the degree of convective aggregation and tropical circulation regimes on temperature. Finally, by providing a common baseline, RCEMIP will allow the robustness of the RCE state across the spectrum of models to be assessed, which is essential for interpreting the results found regarding clouds, climate sensitivity, and aggregation, and more generally, determining which features of tropical climate a RCE framework is useful for. A novel aspect and major advantage of RCEMIP is the accessibility of the RCE framework to a variety of models, including cloud-resolving models, general circulation models, global cloud-resolving models, single-column models, and large-eddy simulation models.
This article explores how atmospheric radiative heating, due to the presence of clouds, influences the Madden‐Julian Oscillation (MJO) as simulated by four comprehensive atmosphere general ...circulation models. Simulations in which clouds are transparent to electromagnetic radiation (“clouds‐off”) are compared with control simulations in which clouds are allowed to interact with radiation (“clouds‐on”). Making clouds transparent to radiation leads to robust changes of the mean state: the westerly winds in the equatorial Indo‐Pacific area weaken and the precipitation reveals a shift from single to double Intertropical Convergence Zones. These changes are accompanied by weaker MJOs. Also, the moisture sensitivity of precipitation changes, however not consistently within our group of models. Further analyses show that within the active phase of intraseasonal variability, cloud‐radiative effects amplify the heating profiles compared to clouds‐off. Heating from nonradiative processes is dominated by the parameterized convection, but large‐scale heating associated with cloud microphysical processes acting on the grid‐scale modifies the shape of the heating profile, leading to a top‐heaviness when cloud‐radiative effects are accounted for. The radiative heating due to clouds slows down the phase speed of the MJO. Averaged over the entire MJO life cycle, the column‐integrated radiative heating due to clouds lags the vertically integrated moist static energy by 40°–60° of longitude (equivalently 7–10 days assuming a period of 60 days). All four models studied reveal more pronounced Kelvin waves when clouds are transparent to radiation, suggesting that cloud‐radiative effects on large‐scale heating profiles damp smaller scale, or faster, Kelvin waves and amplify MJO‐like disturbances.
Key Points:
Cloud‐radiative effects lead to a more realistic mean state and a better MJO
In the convective MJO phase, the heating profile is more top‐heavy
Stronger Kelvin waves are connected with weaker MJOs
Abstract
This study investigates the effects of aerosol on clouds, precipitation, and the organization of trade wind cumuli using large eddy simulations (LES). Results show that for this ...shallow-cumulus-under-stratocumulus case, cloud fraction increases with increasing aerosol as the aerosol number mixing ratio increases from 25 (domain-averaged surface precipitation rate ∼0.65 mm day−1) to 100 mg−1 (negligible surface precipitation). Further increases in aerosol result in a reduction in cloud fraction. It is suggested that opposing influences of aerosol-induced suppression of precipitation and aerosol-induced enhancement of evaporation are responsible for this nonmonotonic behavior.
Under clean conditions (25 mg−1), drizzle is shown to initiate and maintain mesoscale organization of cumulus convection. Precipitation induces downdrafts and cold pool outflow as the cumulus cell develops. At the surface, the center of the cell is characterized by a divergence field, while the edges of the cell are zones of convergence. Convergence drives the formation and development of new cloud cells, leading to a mesoscale open cellular structure. These zones of new cloud formation generate new precipitation zones that continue to reinforce the cellular structure. For simulations with an aerosol concentration of 100 mg−1 the cloud fields do not show any cellular organization. On average, no evidence is found for aerosol effects on the lifetime of these clouds, suggesting that cloud fraction response to changes in aerosol is tied to the frequency of convection and/or cloud size.
Radiative‐convective equilibrium simulations with the general circulation model ECHAM6 are used to explore to what extent the dependence of large‐scale convective self‐aggregation on sea‐surface ...temperature (SST) is driven by the convective parameterization. Within the convective parameterization, we concentrate on the entrainment parameter and show that large‐scale convective self‐aggregation is independent of SST when the entrainment rate for deep convection is set to zero or when the convective parameterization is removed from the model. In the former case, convection always aggregates very weakly, whereas in the latter case, convection always aggregates very strongly. With a nontrivial representation of convective entrainment, large‐scale convective self‐aggregation depends nonmonotonically on SST. For SSTs below 295 K, convection is more aggregated the smaller the SST because large‐scale moisture convergence is relatively small, constraining convective activity to regions with high wind‐induced surface moisture fluxes. For SSTs above 295 K, convection is more aggregated the higher the SST because entrainment is most efficient in decreasing updraft buoyancy at high SSTs, amplifying the moisture‐convection feedback. When halving the entrainment rate, convection is less efficient in reducing updraft buoyancy, and convection is less aggregated, in particular at high SSTs. Despite most early work on self‐aggregation highlighted the role of nonconvective processes, we conclude that convective self‐aggregation and the global climate state are sensitive to the convective parameterization.
Key Points
The dependence of convective self‐aggregation on SST is sensitive to the convective parameterization, in particular to the entrainment rate
Self‐aggregation dominates the statistics of the stationary state, partly masking the direct impact of the convective parameterization
The SST dependence of convective self‐aggregation is controlled by entrainment efficiency at high SSTs, and by a WISHE feedback at low SSTs
ECHAM6, the sixth generation of the atmospheric general circulation model ECHAM, is described. Major changes with respect to its predecessor affect the representation of shortwave radiative transfer, ...the height of the model top. Minor changes have been made to model tuning and convective triggering. Several model configurations, differing in horizontal and vertical resolution, are compared. As horizontal resolution is increased beyond T63, the simulated climate improves but changes are incremental; major biases appear to be limited by the parameterization of small‐scale physical processes, such as clouds and convection. Higher vertical resolution in the middle atmosphere leads to a systematic reduction in temperature biases in the upper troposphere, and a better representation of the middle atmosphere and its modes of variability. ECHAM6 represents the present climate as well as, or better than, its predecessor. The most marked improvements are evident in the circulation of the extratropics. ECHAM6 continues to have a good representation of tropical variability. A number of biases, however, remain. These include a poor representation of low‐level clouds, systematic shifts in major precipitation features, biases in the partitioning of precipitation between land and sea (particularly in the tropics), and midlatitude jets that appear to be insufficiently poleward. The response of ECHAM6 to increasing concentrations of greenhouse gases is similar to that of ECHAM5. The equilibrium climate sensitivity of the mixed‐resolution (T63L95) configuration is between 2.9 and 3.4 K and is somewhat larger for the 47 level model. Cloud feedbacks and adjustments contribute positively to warming from increasing greenhouse gases.
Key Points
To describe ECHAM6, as it was configured for participation in CMIP5
To describe the climate of ECHAM6
To describe the climate sensitivity of ECHAM6
PDF
