Harmen J.J. Jonker

Subsiding Shells Around Shallow Cumulus Clouds

Abstract In this study large-eddy simulations (LES) are used to gain more knowledge on the shell of subsiding air that is frequently observed around cumulus clouds. First, a detailed comparison between observational and numerical results is presented to better validate LES as a tool for studies of microscale phenomena. It is found that horizontal cloud profiles of vertical velocity, humidity, and temperature are in good agreement with observations. They show features similar to the observations, including the presence of the shell of descending air around the cloud. Second, the availability of the complete 3D dataset in LES has been exploited to examine the role of lateral mixing in the exchange of cloud and environmental air. The origin of the subsiding shell is examined by analyzing the individual terms of the vertical momentum equation. Buoyancy is found to be the driving force for this shell, and it is counteracted by the pressure-gradient force. This shows that evaporative cooling at the cloud edge, ...

Influence of the subcloud layer on the development of a deep convective ensemble

The rapid transition from shallow to deep convection is investigated using large-eddy simulations. The role of cold pools, which occur due to the evaporation of rainfall, is explored using a series of experiments in which their formation is suppressed.A positive feedback occurs: the presence of cold pools promotes deeper, wider, and more buoyant clouds with higher precipitation rates, which in turn lead to stronger cold pools. To assess the influence of the subcloud layer on the development of deep convection, the coupling between the cloud layer and the subcloud layer is explored using Lagrangian particle trajectories. As shown in previous studies, particles that enter clouds have properties that deviate significantly from the mean state. However, the differences between particles that enter shallow and deep clouds are remarkably small in the subcloud layer, and become larger in the cloud layer, indicating different entrainment rates. The particles that enter the deepest clouds also correspond to the widest cloud bases, which points to the importance of convective organization within the subcloud layer.

Mixing in Shallow Cumulus Clouds Studied by Lagrangian Particle Tracking

Mixing between shallow cumulus clouds and their environment is studied using large-eddy simulations. The origin of in-cloud air is studied by two distinct methods: 1) by analyzing conserved variable mixing diagrams (Paluch diagrams) and 2) by tracing back cloud-air parcels represented by massless Lagrangian particles that follow the flow. The obtained Paluch diagrams are found to be similar to many results in the literature, but the source of entrained air found by particle tracking deviates from the source inferred from the Paluch analysis. Whereas the classical Paluch analysis seems to provide some evidence for cloud-top mixing, particle tracking shows that virtually all mixing occurs laterally. Particle trajectories averaged over the entire cloud ensemble also clearly indicate the absence of significant cloud-top mixing in shallow cumulus clouds.

A refined view of vertical mass transport by cumulus convection

The purpose of this letter is to show that the traditional view of transport by shallow cumulus clouds needs important refinement. On the basis of a straightforward geometrical analysis of Large Eddy Simulation results of shallow cumulus clouds, we conclude (1) that the upward mass transport by clouds is strongly dominated by regions close to the edge of clouds rather than by the core region of clouds and (2) that the downward mass transport is dominated by processes just outside the cloud. The latter finding contradicts the accepted view of a uniformly descending dry environment. We therefore advocate a refined view which distinguishes between the near-cloud environment and the distant environment. The near-cloud environment is characterized by coherent descending motions, whereas the distant environment is rather quiescent and plays no significant role in vertical transport.

A statistical approach to the life cycle analysis of cumulus clouds selected in a virtual reality environment

In this study, a new method is developed to investigate the entire life cycle of shallow cumuli in large eddy simulations. Although trained observers have no problem in distinguishing the different life stages of a cloud, this process proves difficult to automate, because cloud-splitting and cloud-merging events complicate the distinction between a single system divided in several cloudy parts and two independent systems that collided. Because the human perception is well equipped to capture and to make sense of these time-dependent three-dimensional features, a combination of automated constraints and human inspection in a three-dimensional virtual reality environment is used to select clouds that are exemplary in their behavior throughout their entire life span. Three specific cases (ARM, BOMEX, and BOMEX without large-scale forcings) are analyzed in this way, and the considerable number of selected clouds warrants reliable statistics of cloud properties conditioned on the phase in their life cycle. The most dominant feature in this statistical life cycle analysis is the pulsating growth that is present throughout the entire lifetime of the cloud, independent of the case and of the large-scale forcings. The pulses are a self-sustained phenomenon, driven by a balance between buoyancy and horizontal convergence of dry air. The convective inhibition just above the cloud base plays a crucial role as a barrier for the cloud to overcome in its infancy stage, and as a buffer region later on, ensuring a steady supply of buoyancy into the cloud.

Stochastic Parameterization of Convective Area Fractions with a Multicloud Model Inferred from Observational Data

AbstractObservational data of rainfall from a rain radar in Darwin, Australia, are combined with data defining the large-scale dynamic and thermodynamic state of the atmosphere around Darwin to develop a multicloud model based on a stochastic method using conditional Markov chains. The authors assign the radar data to clear sky, moderate congestus, strong congestus, deep convective, or stratiform clouds and estimate transition probabilities used by Markov chains that switch between the cloud types and yield cloud-type area fractions. Cross-correlation analysis shows that the mean vertical velocity is an important indicator of deep convection. Further, it is shown that, if conditioned on the mean vertical velocity, the Markov chains produce fractions comparable to the observations. The stochastic nature of the approach turns out to be essential for the correct production of area fractions. The stochastic multicloud model can easily be coupled to existing moist convection parameterization schemes used in ge...

On the Deceiving Aspects of Mixing Diagrams of Deep Cumulus Convection

Mixing processes in deep precipitating cumulus clouds are investigated by tracking Lagrangian particles in a large-eddy simulation. The trajectories of particles are reconstructed and the thermodynamic properties of cloud air are studied using mixing diagrams. The trajectory analysis shows that the in-cloud mixing is entirely dominated by lateral entrainment and that there is no significant vertical mixing by downdrafts originating from cloud top. Yet the thermodynamic properties of the particles are located close to a line in the mixing diagrams, which appears to be consistent with two-point vertical mixing. An attempt is made to resolve this paradox using the buoyancy-sorting model of Taylor and Baker, but it is found that this model does not provide a full explanation for the location of particles in the mixing diagram. However, it is shown that the mixing-line behavior can be well understood from a simple analytically solvable model that uses a range of different lateral entrainment rates. Two further factors that determine the location of particles in the mixing diagram are identified: the removal of noncloudy air and precipitation effects. Finally, a thermodynamic argument is given that explains the absence of coherent downdrafts descending from cloud top.

Turbulent Winds and Temperature Fronts in Large-Eddy Simulations of the Stable Atmospheric Boundary Layer

AbstractThe nighttime high-latitude stably stratified atmospheric boundary layer (SBL) is computationally simulated using high–Reynolds number large-eddy simulation on meshes varying from 2003 to 10243 over 9 physical hours for surface cooling rates Cr = [0.25, 1] K h−1. Continuous weakly stratified turbulence is maintained for this range of cooling, and the SBL splits into two regions depending on the location of the low-level jet (LLJ) and . Above the LLJ, turbulence is very weak and the gradient Richardson number is nearly constant: . Below the LLJ, small scales are dynamically important as the shear and buoyancy frequencies vary with mesh resolution. The heights of the SBL and Ri noticeably decrease as the mesh is varied from 2003 to 10243. Vertical profiles of the Ozmidov scale show its rapid decrease with increasing , with over a large fraction of the SBL for high cooling. Flow visualization identifies ubiquitous warm–cool temperature fronts populating the SBL. The fronts span a large vertical exten...

Detrainment in deep convection

This study explores the mechanisms that determine detrainment in deep cumulus convection. A set of 90 high-resolution Large Eddy Simulations is used to systematically explore the sensitivity of continental deep convection to the relative humidity and stability of the free troposphere. It appears that variations in the mass-flux profiles are determined by detrainment, rather than entrainment. The detrainment shows a strong dependence on the critical mixing ratio, a dimensionless parameter which describes which mixtures of cloud core and environmental air are positively buoyant. A conceptual approach to the parameterization of detrainment is proposed on the basis of these results.

Simple solutions to steady-state cumulus regimes in the convective boundary layer

A modeling framework is developed that extends the mixed-layer model to steady-state cumulus convection. The aim is to consider the simplest model that retains the essential behavior of cumulus-capped layers. The presented framework allows for the evaluation of stationary states dependent on external parameters. These states are completely independent of the initial conditions, and therefore represent an asymptote that might help deepen understanding of the dependence of the cloudy boundary layer on external forcings. Formulating separate equations for the lifting condensation level and the mixed-layer height, the dry and wet energetics can be distinguished. Regimes that can support steady-state cumulus clouds and regimes that cannot are identified by comparison of the dry and wet buoyancy effects. The dominant mechanisms that govern the creation and eventual depth of the cloud layer are identified. Model predictions are tested by comparison with a large number of independent large-eddy simulations for varying surface and large-scale conditions and are found to be in good agreement.