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In most previous direct numerical simulation (DNS) studies on droplet growth in turbulence, condensational growth and collisional growth were treated separately. Studies in recent decades have postulated that small-scale turbulence may accelerate droplet collisions when droplets are still small when condensational growth is effective. This implies that both processes should be considered simultaneously to unveil the full history of droplet growth and rain formation. This paper introduces the first direct numerical simulation approach to explicitly study the continuous droplet growth by condensation and collisions inside an adiabatic ascending cloud parcel. Results from the condensation-only, collision-only, and condensation–collision experiments are compared to examine the contribution to the broadening of droplet size distribution (DSD) by the individual process and by the combined processes. Simulations of different turbulent intensities are conducted to investigate the impact of turbulence on each process and on the condensation-induced collisions. The results show that the condensational process promotes the collisions in a turbulent environment and reduces the collisions when in still air, indicating a positive impact of condensation on turbulent collisions. This work suggests the necessity of including both processes simultaneously when studying droplet–turbulence interaction to quantify the turbulence effect on the evolution of cloud droplet spectrum and rain formation.

Although predictability represents one of the fundamental problems in atmospheric science, gaps in our knowledge remain. Theoretical understanding of the inverse error cascade is limited mostly to homogeneous. isotropic turbulence, whereas numerical simulations have focused on highly complex numerical weather prediction models. These results cannot be easily reconciled. This paper describes selected aspects of the predictability behavior of rotating stratified turbulence. The objective is to determine how the predictability varies with scale when the dynamics are more realistic than the idealized models that underlie the classical picture of predictability and yet are free of the parameterizations that complicate interpretation of NWP models. Using a numerical model of the nonhydrostatic Boussinesq equations, it is shown that the predictability decay, as diagnosed by the relative error, is slower for subsynoptic flow. The dependence on the deformation radius, differences between balanced and unbalanced modes, and implications for NWP models are discussed.

The authors present simulations of cloud-free and cloudy, nonprecipitating, convective turbulence at spatial resolutions down to [DELTA]x = 2.6 m for a domain size of [(1 km).sup.3]. The runs are analyzed with attention focused on the dynamical differences between resolutions and the presence or absence of moisture, as well as on the small-scale variability of the liquid water spectra in the cloudy cases. Because of evaporation and condensation, liquid water content does not act like a passive scalar. Much of the evaporation occurs in highly turbulent cloud-top mixing where differences in variances and kurtoses of real-space vorticity probability density functions between cloudy and cloud-free runs are also found. The cloudy cases have higher variance and lower kurtosis values than their cloud-free counterparts. The lower kurtosis values mean fewer high-intensity vortices for the cloudy cases, which is most likely due to the loss of buoyancy as evaporation occurs during entrainment events. This effect is associated with a change in the liquid water content spectra found in regions of cloud decay. Conditional sampling of these regions shows increased small-scale variability, above the background increase due to the bottleneck effect, of liquid water content spectra; this is not found in other cloudy regions. This may help explain recent measurements of enhanced small-scale liquid water content variability in aircraft measurements of stratocumulus clouds.

Although it is now accepted that imbalance in the atmosphere and ocean is generic, the feedback of the unbalanced motion on the balanced flow has not received much attention. In this work the parameterization problem is examined in the context of rotating stratified turbulence, that is, with a nonhydrostatic Boussinesq model. Using the normal modes as a first approximation to the balanced and unbalanced flow, the growth of ageostrophic perturbations to the quasigeostrophic flow and the associated feedback are studied. For weak stratification, there are analogies with the three-dimensionalization of decaying 2D turbulence: the growth rate of the ageostrophic perturbation follows a linear estimate, geostrophic energy is extracted from the base flow, and the associated damping on the geostrophic base flow (the 'eddy viscosity') is peaked at large horizontal scales. For strong stratification, the transfer spectra and eddy viscosities maintain this structure if there is synoptic-scale motion and the buoyancy scale is adequately resolved. This has been confirmed for global Rossby and Froude numbers of O(0.1). Implications for atmospheric and oceanic modeling are discussed.

There is a growing interest in understanding the role that moisture plays in atmospheric dynamics, particularly in its effect on predictability. Current research indicates that when moisture effects are added to an atmospheric model, the error growth produced by the new moist dynamics reduces the predictability times, especially at the scales of moist convection. The issue of moist convection's effect on predictability is addressed herein. By performing high-resolution large-ensemble runs, it is shown that although nonprecipitating moist convection is less predictable than dry convection resulting from the same forcing, this effect can be explained by the energy injected into the system through the latent heating and cooling arising from the convective motion. This extra energy is spread evenly over most scales of the convective dynamics. When the predictability times are scaled to account for the extra kinetic energy, and the resulting earlier growth of error energy, wet and dry convection have very similar error growth characteristics. Sensitivity tests are performed to ensure that the results from the large ensembles have converged and that they are consistent with either changing resolution, diffusion levels, initial error energy length scales, or forcing amplitude.

The goal of this work is to answer the question of whether nonuniformity in the spatial distribution of sizes and positions of cloud droplets and/or variable vertical velocity in a turbulent medium can contribute to the broadening of the droplet size distribution. A numerical approach to simulate the growth and trajectory of several tens of thousands of cloud droplets in a turbulent environment whose properties vary from droplet to droplet is used. The finite inertia of particles in a turbulent fluid causes particles to diverge from regions of high vorticity and to converge preferentially in regions of low vorticity, thus creating strong deviations in particle concentration. As a first step, the inertia effect was examined in the context of nongrowing, sedimenting, or nonsedimenting droplets. It was found that statistically significant preferential concentration is possible in conditions typical of cloud droplets in cumulus clouds. In the absence of sedimentation, preferential concentration increases as a function of the Stokes number [S.sub.t]. Allowing the droplets to sediment decreases preferential concentration to a degree that increases with the velocity ratio [S.sub.v]. A series of experiments including condensational growth of droplets was then performed. It was found that while the increasing preferential concentration of droplets, as a result of increasing eddy dissipation rate, does result in increases in the instantaneous dispersion of the supersaturation perturbation distribution, the width of the size distribution of droplets, which is a function of the dispersion in the time integral of the supersaturation perturbations, decreases. This result is a consequence of the decrease in decorrelation time of the supersaturation perturbations as the turbulence intensity increases. Comparison of the results herein with the observations made in quasi-adiabatic cloud cores leads one to the conclusion that the microscopic approach, even under the most favorable condition of no turbulence, produces too little broadening to explain the observations.

Chronic stress can lead to emotional burnout. Social service professionals can be particularly vulnerable to burnout due to compassion fatigue and vicarious trauma. Using Social Cognitive Theory (SCT), an intervention was developed to prevent and reduce the risk of emotional burnout among social service workers. Facilitators presented a stress management technique called VBR for vent, breathe, reset. Thirty-two participants completed a post-test. Participants reported moderate to high rankings on confidence in performing and likelihood to use the VBR technique. [ABSTRACT FROM AUTHOR]

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Date Presented 3/31/2017 The purpose of this study is to determine, based on individualized measures such as goal attainment scaling, the effectiveness of a group intervention combining sensory integration techniques with social skills training on the social behaviors of children with autism spectrum disorder. Primary Author and Speaker: Lori Charney Additional Authors and Speakers: Felicia Bartello, Erin Soulsby, Desirae Waltman, Ellen McLaughlin, Amanda Salak Contributing Authors: Jonathan Jorda [ABSTRACT FROM AUTHOR]

This paper studies an infinitely fast bimolecular chemical reaction in a two-dimensional biperiodic Navier-Stokes flow. The reactants in stoichiometric quantities are initially segregated by infinite gradients. The focus is placed on the initial stage of the reaction characterized by a well-defined one-dimensional material contact line between the reactants. Particular attention is given to the effect of the diffusion κ of the reactants. This study is an idealized framework for isentropic mixing in the lower stratosphere and is motivated by the need to better understand the effect of resolution on stratospheric chemistry in climate-chemistry models. Adopting a Lagrangian straining theory approach, we relate theoretically the ensemble mean of the length of the contact line, of the gradients along it, and of the modulus of the time derivative of the space-average reactant concentrations (here called the chemical speed) to the joint probability density function of the finite-time Lyapunov exponent λ with two times τ and τ[over ̃]. The time 1/λ measures the stretching time scale of a Lagrangian parcel on a chaotic orbit up to a finite time t, while τ measures it in the recent past before t, and τ[over ̃] in the early part of the trajectory. We show that the chemical speed scales like κ(1/2) and that its time evolution is determined by rare large events in the finite-time Lyapunov exponent distribution. The case of smooth initial gradients is also discussed. The theoretical results are tested with an ensemble of direct numerical simulations (DNSs) using a pseudospectral model.