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A two-dimensional mathematical model of moist air convection in the sub-cloud and cloud layers is proposed. A theoretical analysis of the influence of near ground atmospheric parameters on the development of sub-cloud and cloud convection is provided, and the criteria of convection development are considered. As a rule, this relationship is parameterized in general circulation, regional or mesoscale models of the atmosphere. Therefore, achieving a more complete and correct understanding of this relationship can lead to an improvement in the accuracy of weather forecasts. The mathematical model describes the system of the equations of motion, heat conductivity and the continuity equations for a two-dimensional vertical plane. The approximate analytical solution of the system of equations is obtained. Expressions for the estimation of the convection height and height of maximum velocity are derived for vertical and horizontal components of updraft wind and for vertical distribution of temperature. From the expressions obtained, the criterion of sub-cloud convection development is derived. The expressions for the convection parameters at a condensation level have also been formulated, from which the criterion of cloud development through convection is derived. It is established that the development of cloud convection depends on absolute values of the dew point deficit in a near-surface layer and, in a greater degree, on vertical gradients of water vapor mass fraction. It is shown that at certain critical values of a vertical gradient of water vapor mass fraction “explosive convective growth” is observed. The application of the obtained results to artificial stimulation of convection by means of air heating in the near-ground atmosphere has shown that the success of such an application and the required air heating-up depend on: (i) the vertical temperature gradient; (ii) the vertical dew-point gradient; and (iii) the value of the dew point deficit in the near-ground layer. The analysis performed has shown the possibility of successful stimulation of artificial convection under specific favorable atmospheric conditions.

The Community Atmosphere Model, version 4 (CAM4), was released as part of the Community Climate System Model, version 4 (CCSM4). The finite volume (FV) dynamical core is now the default because of its superior transport and conservation properties. Deep convection parameterization changes include a dilute plume calculation of convective available potential energy (CAPE) and the introduction of convective momentum transport (CMT). An additional cloud fraction calculation is now performed following macrophysical state updates to provide improved thermodynamic consistency. A freeze-drying modification is further made to the cloud fraction calculation in very dry environments (e.g., the Arctic), where cloud fraction and cloud water values were often inconsistent in CAM3. In CAM4 the FV dynamical core further degrades the excessive trade-wind simulation, but reduces zonal stress errors at higher latitudes. Plume dilution alleviates much of the midtropospheric tropical dry biases and reduces the persistent monsoon precipitation biases over the Arabian Peninsula and the southern Indian Ocean. CMT reduces much of the excessive trade-wind biases in eastern ocean basins. CAM4 shows a global reduction in cloud fraction compared to CAM3, primarily as a result of the freeze-drying and improved cloud fraction equilibrium modifications. Regional climate feature improvements include the propagation of stationary waves from the Pacific into midlatitudes and the seasonal frequency of Northern Hemisphere blocking events. A 1° versus 2° horizontal resolution of the FV dynamical core exhibits superior improvements in regional climate features of precipitation and surface stress. Improvements in the fully coupled mean climate between CAM3 and CAM4 are also more substantial than in forced sea surface temperature (SST) simulations.

A better representation of the coupling between atmospheric water and circulation is necessary to reduce imprecision in climate model projections. Fifty years ago, Joseph Smagorinsky published a landmark paper ( 1 ) describing numerical experiments using the primitive equations (a set of fluid equations that describe global atmospheric flows). In so doing, he introduced what later became known as a General Circulation Model (GCM). GCMs have come to provide a compelling framework for coupling the atmospheric circulation to a great variety of processes. Although early GCMs could only consider a small subset of these processes, it was widely appreciated that a more comprehensive treatment was necessary to adequately represent the drivers of the circulation. But how comprehensive this treatment must be was unclear and, as Smagorinsky realized ( 2 ), could only be determined through numerical experimentation. These types of experiments have since shown that an adequate description of basic processes like cloud formation, moist convection, and mixing is what climate models miss most.

An international field campaign aiming at atmospheric and oceanic processes associated with the Madden–Julian oscillation (MJO) was conducted in and around the tropical Indian Ocean during October 2011–March 2012. The objective of the field campaign was to collect observations urgently needed to expedite the progress of understanding the key processes of the MJO, focusing on its convective initiation but also including propagation and maturation, and ultimately to improve skills of numerical simulation and prediction of the MJO. Primary targets of the field campaign included interaction of atmospheric deep convection with its environmental moisture, evolution of cloud populations, and air-sea interaction. Several MJO events were captured by ground-based, airborne, and oceanic instruments with advanced observing technology. Numerical simulations and real-time forecasts were integrated components of the field campaign in its design and operation. Observations collected during the campaign provide unprecedented opportunities to reveal detailed processes of the MJO and to assist evaluation, improvement, and development of weather and climate models. The data policy of the campaign encourages the broad research community to use the field observations to advance the MJO study.

Among all cloud-aerosol interactions, the invigoration effect is the most elusive. Most of the studies that do suggest this effect link it to deep convective clouds with a warm base and cold top. Here, we provide evidence from observations and numerical modeling of a dramatic aerosol effect on warm clouds. We propose that convective-cloud invigoration by aerosols can be viewed as an extension of the concept of aerosol-limited clouds, where cloud development is limited by the availability of cloud-condensation nuclei. A transition from pristine to slightly polluted atmosphere yields estimated negative forcing of ∼15 watts per square meter (cooling), suggesting that a substantial part of this anthropogenic forcing over the oceans occurred at the beginning of the industrial era, when the marine atmosphere experienced such transformation.

The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for the atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol–cloud interactions, chemistry–climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical system component of earth system models and models for decadal prediction in the near-term future—for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model. Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud droplet activation by aerosols, subgrid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with ecosystem dynamics and hydrology. Its horizontal resolution is approximately 200 km, and its vertical resolution ranges approximately from 70 m near the earth’s surface to 1 to 1.5 km near the tropopause and 3 to 4 km in much of the stratosphere. Most basic circulation features in AM3 are simulated as realistically, or more so, as in AM2. In particular, dry biases have been reduced over South America. In coupledmode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks remains problematic, as in AM2. The most intense 0.2% of precipitation rates occur less frequently in AM3 than observed. The last two decades of the twentieth century warm in CM3 by 0.32°C relative to 1881–1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of 0.56° and 0.52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol–cloud interactions, and its warming by the late twentieth century is somewhat less realistic than in CM2.1, which warmed 0.66°C but did not include aerosol–cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud–aerosol interactions to limit greenhouse gas warming.

Aerosols serve as cloud condensation nuclei (CCN) and thus have a substantial effect on cloud properties and the initiation of precipitation. Large concentrations of human-made aerosols have been reported to both decrease and increase rainfall as a result of their radiative and CCN activities. At one extreme, pristine tropical clouds with low CCN concentrations rain out too quickly to mature into long-lived clouds. On the other hand, heavily polluted clouds evaporate much of their water before precipitation can occur, if they can form at all given the reduced surface heating resulting from the aerosol haze layer. We propose a conceptual model that explains this apparent dichotomy.

Tropical deep convection exhibits complex organization over a wide range of scales. This study investigates the relationships between the spatial organization of deep convection and the large-scale atmospheric state. By using several satellite datasets and reanalyses, and by defining a simple diagnostic of convective aggregation, relationships between the degree of convective aggregation and the amount of water vapor, turbulent surface fluxes, and radiation are highlighted above tropical oceans. When deep convection is more aggregated, the middle and upper troposphere are drier in the convection-free environment, turbulent surface fluxes are enhanced, and the low-level and midlevel cloudiness is reduced in the environment. Humidity and cloudiness changes lead to a large increase in outgoing longwave radiation. Cloud changes also result in reduced reflected shortwave radiation. Owing to these opposing effects, the sensitivity of the radiative budget at the top of the atmosphere to convective aggregation turns out to be weak, but the distribution of radiative heating throughout the troposphere is affected. These results suggest that feedbacks between convective aggregation and the large-scale atmospheric state might influence large-scale dynamics and the transports of water and energy and, thus, play a role in the climate variability and change. These observational findings are qualitatively consistent with previous cloud-resolving model results, except for the effects on cloudiness and reflected shortwave radiation. The proposed methodology may be useful for assessing the representation of convective aggregation and its interaction with the large-scale atmospheric state in various numerical models.

This paper describes climate simulations of the Community Atmosphere Model, version 5 (CAM5), coupled with a higher-order turbulence closure known as Cloud Layers Unified by Binormals (CLUBB). CLUBB is a unified parameterization of the planetary boundary layer (PBL) and shallow convection that is centered around a trivariate probability density function (PDF) and replaces the conventional PBL, shallow convection, and cloud macrophysics schemes in CAM5. CAM–CLUBB improves many aspects of the base state climate compared to CAM5. Chief among them is the transition of stratocumulus to trade wind cumulus regions in the subtropical oceans. In these regions, CAM–CLUBB provides a much more gradual transition that is in better agreement with observational analysis compared to CAM5, which is too abrupt. The improvement seen in CAM–CLUBB can be largely attributed to the gradual evolution of the simulated turbulence, which is in part a result of the unified nature of the parameterization, and to the general improved representation of shallow cumulus clouds compared to CAM5. In addition, there are large differences in the representation and structure of marine boundary layer clouds between CAM–CLUBB and CAM5. CAM–CLUBB is also shown to be more robust, in terms of boundary layer clouds, to changes in vertical resolution for global simulations in a preliminary test.

Diurnal and seasonal variation, intensity, and structure of deep convective systems (DCSs; with 20-dBZecho tops exceeding 14 km) over the Tibetan Plateau–South Asian monsoon region from the Tibetan Plateau (TP) to the ocean are investigated using 14 yr of Tropical Rainfall Measuring Mission (TRMM) data. Four unique regions characterized by different orography are selected for comparison, including the TP, the southern Himalayan front (SHF), the South Asian subcontinent (SAS), and the ocean. DCSs and intense DCSs (IDCSs; with 40-dBZecho tops exceeding 10 km) occur more frequently over the continent than over the ocean. About 23% of total DCSs develop into IDCSs in the SHF, followed by the TP (21%) and the SAS (15%), with the least over the ocean (2%). The average 20-dBZecho-top height of IDCSs exceeds 16km and 9% of them even exceed 18 km. DCSs and IDCSs are the most frequent over the SHF, especially in the westernmost SHF, where the intensity—in terms of strong radar echo-top (viz., 40 dBZ) height, ice-particle content, and lightning flash rate—is the strongest. DCSs over the TP are relatively weak in convective intensity and small in size but occur frequently. Oceanic DCSs possess the tallest cloud top (which mainly reflects small ice particles) and the largest size, but their convective intensity is markedly weaker. DCSs and IDCSs show a similar diurnal variation, mainly occurring in the afternoon with a peak at 1600 local time over land. Although most of both DCSs and IDCSs occur between April and October, DCSs have a peak in August, whereas IDCSs have a peak in May.