Search Results

You are looking at 1 - 9 of 9 items for

  • Author or Editor: Harmen J. J. Jonker x
  • All content x
Clear All Modify Search
Vincent E. Perrin and Harmen J. J. Jonker

Abstract

This study investigates the droplet dynamics at the lateral cloud–environment interface in shallow cumulus clouds. A mixing layer is used to study a small part of the cloud edge using direct numerical simulation combined with a Lagrangian particle tracking and collision algorithm. The effect of evaporation, gravity, coalescence, and the initial droplet size distribution on the intensity of the mixing layer and the evolution of the droplet size distribution is studied. Mixing of the droplets with environmental air induces evaporative cooling, which results in a very characteristic subsiding shell. As a consequence, stronger horizontal velocity gradients are found in the mixing layer, which induces more mixing and evaporation. A broadening of the droplet size distribution is observed as a result of evaporation and coalescence. Gravity acting on the droplets allows droplets in cloudy filaments detrained from the cloud to sediment and remain longer in the unsaturated environment. While this effect of gravity did not have a significant impact in this case on the mean evolution of the mixing layer, it does contribute to the broadening of the droplet size distribution and thereby significantly increases the collision rate. Although more but smaller droplets result in more evaporative cooling, more droplets also increase small-scale fluctuations and the production of turbulent dissipation. For the smallest droplets considered with a radius of 10 μm, the authors found that, although a more pronounced buoyancy dip was present, the increase in dissipation rate actually led to a decrease in the turbulent intensity of the mixing layer. Extrapolation of the results to realistic clouds is discussed.

Full access
Siddhartha Mukherjee, Jerôme Schalkwijk, and Harmen J. J. Jonker

Abstract

The predictability horizon of convective boundary layers is investigated in this study. Large-eddy simulation (LES) and direct numerical simulation (DNS) techniques are employed to probe the evolution of perturbations in identical twin simulations of a growing dry convective boundary layer. Error growth typical of chaotic systems is observed, marked by two phases. The first comprises an exponential error growth as , with δ0 as the initial error, δ(t) as the error at time t, and Λ as the Lyapunov exponent. This phase is independent of the perturbation wavenumber, and the perturbation energy grows following a self-similar spectral shape dominated by higher wavenumbers. The nondimensional error growth rate in this phase shows a strong dependence on the Reynolds number (Re). The second phase involves saturation of the error. Here, the error growth follows Lorenz dynamics with a slower saturation of successively larger scales. An analysis of the spectral decorrelation times reveals two regimes: an Re-independent regime for scales larger than the boundary layer height and an Re-dependent regime for scales smaller than , which are found to decorrelate substantially faster for increasing Reynolds numbers.

Full access
Jerôme Schalkwijk, Harmen J. J. Jonker, and A. Pier Siebesma

Abstract

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.

Full access
Jesse Dorrestijn, Daan T. Crommelin, A. Pier Siebesma, Harmen J. J. Jonker, and Christian Jakob

Abstract

Observational 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 general circulation models.

Full access
Jesse Dorrestijn, Daan T. Crommelin, A. Pier Siebesma, Harmen J. J. Jonker, and Frank Selten

Abstract

Conditional Markov chain (CMC) models have proven to be promising building blocks for stochastic convection parameterizations. In this paper, it is demonstrated how two different CMC models can be used as mass flux closures in convection parameterizations. More specifically, the CMC models provide a stochastic estimate of the convective area fraction that is directly proportional to the cloud-base mass flux. Since, in one of the models, the number of CMCs decreases with increasing resolution, this approach makes convection parameterizations scale aware and introduces stochastic fluctuations that increase with resolution in a realistic way. Both CMC models are implemented in a GCM of intermediate complexity. It is shown that with the CMC models, trained with observational data, it is possible to improve both the subgrid-scale variability and the autocorrelation function of the cloud-base mass flux as well as the distribution of the daily accumulated precipitation in the tropics. Hovmöller diagrams and wavenumber–frequency diagrams of the equatorial precipitation indicate that, in this specific GCM, convectively coupled equatorial waves are more sensitive to the mean cloud-base mass flux than to stochastic fluctuations. A smaller mean mass flux tends to increase the power of the simulated MJO and to diminish equatorial Kelvin waves.

Full access
Jerôme Schalkwijk, Harmen J. J. Jonker, A. Pier Siebesma, and Erik Van Meijgaard

Abstract

Since the advent of computers midway through the twentieth century, computational resources have increased exponentially. It is likely they will continue to do so, especially when accounting for recent trends in multicore processors. History has shown that such an increase tends to directly lead to weather and climate models that readily exploit the extra resources, improving model quality and resolution. We show that Large-Eddy Simulation (LES) models that utilize modern, accelerated (e.g., by GPU or coprocessor), parallel hardware systems can now provide turbulence-resolving numerical weather forecasts over a region the size of the Netherlands at 100-m resolution. This approach has the potential to speed the development of turbulence-resolving numerical weather prediction models.

Full access
Peter P. Sullivan, Jeffrey C. Weil, Edward G. Patton, Harmen J. J. Jonker, and Dmitrii V. Mironov

Abstract

The 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 C r = [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 extent, tilt forward more so as the surface cooling increases, and propagate coherently. In a height–time reference frame, an instantaneous vertical profile of temperature appears intermittent, exhibiting a staircase pattern with increasing distance from the surface. Observations from CASES-99 also display these features. Conditional sampling based on linear stochastic estimation is used to identify coherent structures. Vortical structures are found upstream and downstream of a temperature front, similar to those in neutrally stratified boundary layers, and their dynamics are central to the front formation.

Full access
Jerôme Schalkwijk, Harmen J. J. Jonker, A. Pier Siebesma, and Fred C. Bosveld

Abstract

Results are presented of two large-eddy simulation (LES) runs of the entire year 2012 centered at the Cabauw observational supersite in the Netherlands. The LES is coupled to a regional weather model that provides the large-scale information. The simulations provide three-dimensional continuous time series of LES-generated turbulence and clouds, which can be compared in detail to the extensive observational dataset of Cabauw. The LES dataset is available from the authors on request.

This type of LES setup has a number of advantages. First, it can provide a more statistical approach to the study of turbulent atmospheric flow than the more common case studies, since a diverse but representative set of conditions is covered, including numerous transitions. This has advantages in the design and evaluation of parameterizations. Second, the setup can provide valuable information on the quality of the LES model when applied to such a wide range of conditions. Last, it also provides the possibility to emulate observation techniques. This might help detect limitations and potential problems of a variety of measurement techniques.

The LES runs are validated through a comparison with observations from the observational supersite and with results from the “parent” large-scale model. The long time series that are generated, in combination with information on the spatial structure, provide a novel opportunity to study time scales ranging from seconds to seasons. This facilitates a study of the power spectrum of horizontal and vertical wind speed variance to identify the dominant variance-containing time scales.

Full access
Steven J. A. van der Linden, Bas J. H. van de Wiel, Igor Petenko, Chiel C. van Heerwaarden, Peter Baas, and Harmen J. J. Jonker

Abstract

High-resolution large-eddy simulations of the Antarctic very stable boundary layer reveal a mechanism for systematic and periodic intermittent bursting. A nonbursting state with a boundary layer height of just 3 m is alternated by a bursting state with a height of ≈5 m. The bursts result from unstable wave growth triggered by a shear-generated Kelvin–Helmholtz instability, as confirmed by linear stability analysis. The shear at the top of the boundary layer is built up by two processes. The upper, quasi-laminar layer accelerates due to the combined effect of the pressure force and rotation by the Coriolis force, while the lower layer decelerates by turbulent friction. During the burst, this shear is eroded and the initial cause of the instability is removed. Subsequently, the interfacial shear builds up again, causing the entire sequence to repeat itself with a time scale of ≈10 min. Despite the clear intermittent bursting, the overall change of the mean wind profile is remarkably small during the cycle. This enables such a fast erosion and recovery of the shear. This mechanism for cyclic bursting is remarkably similar to the mechanism hypothesized by Businger in 1973, with one key difference. Whereas Businger proposes that the flow acceleration in the upper layer results from downward turbulent transfer of high-momentum flow, the current results indicate no turbulent activity in the upper layer, hence requiring another source of momentum. Finally, it would be interesting to construct a climatology of shear-generated intermittency in relation to large-scale conditions to assess the generality of this Businger mechanism.

Open access