Bulletin of the American Physical Society
70th Annual Meeting of the APS Division of Fluid Dynamics
Volume 62, Number 14
Sunday–Tuesday, November 19–21, 2017; Denver, Colorado
Session M15: Focus Sessions: Fluid Dynamics of Atmospheric Clouds IIIGeophysical
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Chair: Rudie Kunnen,, Eindhoven University of Technology Room: 601 |
Tuesday, November 21, 2017 8:00AM - 8:13AM |
M15.00001: Spectra of turbulent flow in cumulus cloud Toshiyuki Gotoh, Izumi Saito, Takeshi Watanabe We have seamlessly simulated evolution of droplets and turbulence for about ten minutes in a small box which is ascending inside the maritime cumulus cloud. Under the prescribed vertical structure of the mean temperature and water vapor mixing ratio and the periodic boundary condition, the turbulence is computed by the DNS and the particles evolve obeying the condensation-evaporation, collision-coalescence with the hydrodynamic interaction, the Reynolds number dependent drag, and the gravitational sedimentation. It is found that the kinetic energy spectrum obeys nearly Kolmogorov spectrum $k^{-5/3}$ while the spectra of the temperature and water vapor mixing ratio are much shallower than $k^{-5/3}$. An explanation of modification of the spectra is explored by examining the droplet number density spectrum $E_n(k,t)$ and the condensation rate spectrum $E_{C_{\rm d}}(k,t)$. Two spectra are very similar to each other, nearly $k^{1}$ at low wavenumber range and $k^{-\alpha}, 1<\alpha <2$ at high wavenumber range. It is argued that the coupling between droplets and temperature and water vapor mixing ratio through the condensation-evaporation yields the shallow spectra. Comparison with the data observed at mountain top is also made. [Preview Abstract] |
Tuesday, November 21, 2017 8:13AM - 8:26AM |
M15.00002: Growth of cloud droplets from aerosol in turbulence Izumi Saito, Toshiyuki Gotoh, Takeshi Watanabe The purpose of this study is to show that a DNS model can reproduce a statistical relationship associated with aerosol indirect effects. The relationship, which predicts that the spectral width of the cloud-droplet size-distribution decreases with the increase of the cloud-droplet number concentration, was derived based on a simple Langevin model and confirmed by laboratory experiments in a previous study (Chandrakar et al, 2017, {\it Proc. Natl. Acad. Sci. USA} {\bf 113} 14243--14248). We used the ``cloud microphysics simulator," which was developed by the present authors in a previous study and is a DNS model resolving droplet dynamics, turbulence, and microscale thermodynamical effects. From the DNS results, it is shown that the statistical relationship holds very well, confirming the validity of the DNS for cloud turbulence study. [Preview Abstract] |
Tuesday, November 21, 2017 8:26AM - 8:39AM |
M15.00003: Statistical theory on the analytical form of cloud particle size distributions Wei Wu, Greg McFarquhar Several analytical forms of cloud particle size distributions (PSDs) have been used in numerical modeling and remote sensing retrieval studies of clouds and precipitation, including exponential, gamma, lognormal, and Weibull distributions. However, there is no satisfying physical explanation as to why certain distribution forms preferentially occur instead of others. Theoretically, the analytical form of a PSD can be derived by directly solving the general dynamic equation, but no analytical solutions have been found yet. Instead of using a process level approach, the use of the principle of maximum entropy (MaxEnt) for determining the analytical form of PSDs from the perspective of system is examined here. Here, the issue of variability under coordinate transformations that arises using the Gibbs/Shannon definition of entropy is identified, and the use of the concept of relative entropy to avoid these problems is discussed. Focusing on cloud physics, the four-parameter generalized gamma distribution is proposed as the analytical form of a PSD using the principle of maximum (relative) entropy with assumptions on power law relations between state variables, scale invariance and a further constraint on the expectation of one state variable (e.g. bulk water mass). [Preview Abstract] |
Tuesday, November 21, 2017 8:39AM - 8:52AM |
M15.00004: An economical model for simulating droplet spectrum evolution in turbulent cloud chambers and wind tunnels Steven Krueger, W. Cantrell, D. Niedermeier, R. Shaw, F. Stratmann Although airborne instruments provide detailed information about the microphysical structure of clouds, the measurements provide only a few snapshots of each cloud. Deducing the droplet spectrum evolution from such measurements is next to impossible. We are using two alternative approaches: laboratory studies and numerical simulations. The former relies on a new turbulent cloud chamber (the Pi Chamber) at Michigan Technical University, as well as the first humid turbulent wind tunnel (LACIS-T) at the Leibniz Institute for Tropospheric Research. Both produce conditions for droplet growth (i.e., supersaturation) by mixing saturated vapor at different temperatures. The Pi Chamber produces turbulence by inducing Rayleigh-B\'enard convection, while the wind tunnel generates turbulence with a grid. We are using the Explicit Mixing Parcel Model (EMPM) to numerically simulate droplet spectrum evolution in these flows. The EMPM explicitly links turbulent mixing and droplet spectrum evolution by representing a turbulent flow in a 1D domain with the linear eddy model. The EMPM can economically span scales from those of the smallest turbulent eddies to those of the largest. The EMPM grows or evaporates thousands of individual cloud droplets according to their local environments. [Preview Abstract] |
Tuesday, November 21, 2017 8:52AM - 9:05AM |
M15.00005: Passive moist transfer in Rayleigh-Benard convection Lu ZHANG, Keqing XIA We present the heat transfer measurement of moist Rayleigh-Benard convection in a rectangular cell at $Pr\sim0.7$, $Sc\sim0.6$. The overall heat transfer rate is much larger than that of single gas phase due to the presence of phase transition on both boundaries. In addition, the measured heat transfer rate may be expressed approximately as $(dM/dt) \times L$, where $dM/dt$ is the moist (mass) transfer rate and $L$ is latent heat of water. We found $(dM/dt)/\Delta_{ep}\sim Ra^{0.28}$, where $\Delta_{ep}$ is the saturated vapor pressure difference between the two plates. Since the body force is dominated by the temperature rather than the partial pressure of water vapor in the parameter range of the experiment, we can treat the vapor pressure as a passive scalar. Furthermore, we explore the $Sc$ number dependence of passive scalar transport in a 2D square domain at $Ra=10^{8}$. The nondimensionalized passive scalar transport rate, $Nu_{C}$, scales as $Sc^{0.47}$ for $0.2\leq Sc\leq 1.4$, and $Sc^{0.36}$ for $1.4\leq Sc\leq 60$. The transition of the $Sc$ scaling is found to be related to the cross-over of the viscous boundary layer and the passive scalar boundary layer. [Preview Abstract] |
Tuesday, November 21, 2017 9:05AM - 9:18AM |
M15.00006: The dynamics of droplets in moist Rayleigh-Benard turbulence Kamal Kant Chandrakar, Dennis van der Voort, Greg Kinney, Will Cantrell, Raymond Shaw Clouds are an intricate part of the climate, and strongly influence atmospheric dynamics and radiative balances. While properties such as cloud albedo and precipitation rate are large scale effects, these properties are determined by dynamics on the microscale, such droplet sizes, liquid water content, etc. The growth of droplets from condensation is dependent on a multitude of parameters, such as aerosol concentration (nucleation sites) and turbulence (scalar fluctuations and coalescence). However, the precise mechanism behind droplet growth and clustering in a cloud environment is still unclear. In this investigation we use a facility called the Pi Chamber to generate a (miniature) cloud in a laboratory setting with known boundary conditions, such as aerosol concentration, temperature, and humidity. Through the use of particle imaging velocimetry (PIV) on the droplets generated in the cloud, we can investigate the dynamics of these cloud droplets in the convective (Rayleigh-Benard) turbulence generated through an induced temperature gradient. We show the influence of the temperature gradient and Froude number (gravity forces) on the changing turbulence anisotropy, large scale circulation, and small-scale dissipation rates. [Preview Abstract] |
Tuesday, November 21, 2017 9:18AM - 9:31AM |
M15.00007: Particle-inertia and phase-change induced vortex-dipole collapse S. Ravichandran, Rama Govindarajan Non-buoyant vortices in a dipole move in straight lines perpendicular to the line joining them. Quite to the contrary, we showed that buoyant vortices can collide with and annihilate each other. We present results from analytical considerations and extensive numerical simulations to show how such a collapse can be caused by the combined effects of particle inertia and the thermodynamics of phase change. We use the thermodynamics of the water vapour--liquid water system, with water droplets forming the particle phase. Water droplets are thrown out of the vicinity of the vortices, thus making the vortices devoid of condensation nuclei. This leaves the vortices colder than their surroundings, making them buoyant, and possibly leading to a collapse. We show that collapse occurs only when the product of the particle- and phase-change- Stokes numbers is greater than a threshold. We discuss potential implications for the fluid dynamics of clouds. [Preview Abstract] |
Tuesday, November 21, 2017 9:31AM - 9:44AM |
M15.00008: The Route to Raindrop Formation in a Shallow Cumulus Cloud Simulated by a Lagrangian Cloud Model Yign Noh, Fabian Hoffmann, Siegfried Raasch The mechanism of raindrop formation in a shallow cumulus cloud is investigated using a Lagrangian cloud model (LCM). The analysis is focused on how and under which conditions a cloud droplet grows to a raindrop by tracking the history of individual Lagrangian droplets. It is found that the rapid collisional growth, leading to raindrop formation, is triggered when single droplets with a radius of 20 $\mu$m appear in the region near the cloud top, characterized by a large liquid water content, strong turbulence, large mean droplet size, a broad drop size distribution (DSD), and high supersaturations. Raindrop formation easily occurs when turbulence-induced collision enhancement(TICE) is considered, with or without any extra broadening of the DSD by another mechanism (such as entrainment and mixing). In contrast, when TICE is not considered, raindrop formation is severely delayed if no other broadening mechanism is active. The reason leading to the difference is clarified by the additional analysis of idealized box-simulations of the collisional growth process for different DSDs in varied turbulent environments. It is found that TICE does not accelerate the timing of the raindrop formation for individual droplets, but it enhances the collisional growth rate significantly afterward. [Preview Abstract] |
Tuesday, November 21, 2017 9:44AM - 9:57AM |
M15.00009: Turbulence-induced broadening of cloud droplet size distributions: implications for aerosol indirect effects Raymond Shaw, Will Cantrell, Kamal Kant Chandrakar, Greg Kinney, Mikhail Ovchinnikov, Subin Thomas, Fan Yang The optical properties and precipitation efficiency of warm clouds depend on the droplet size distribution and its moments, including the statistical relative-dispersion of the distribution. Cloud droplet growth in a turbulent environment is studied by creating turbulent moist Rayleigh-B{\'{e}}nard convection in a laboratory chamber (the Pi Chamber) and a parallel LES with (bin) cloud-microphysics. Cloud formation is achieved by injecting aerosols into the water-supersaturated environment created by the isobaric mixing of saturated air at different temperatures. A range of steady-state cloud droplet number concentrations is achieved by supplying aerosols at different rates. The results reveal a surprising role of turbulence in cloud droplet formation and growth that can be understood as occurring in two regimes: a polluted cloud regime ($Da \gg 1$) in which thermodynamic conditions are rather uniform and cloud droplet sizes are similar, and a clean cloud regime ($Da \ll 1$) in which thermodynamic conditions are highly variable and cloud droplet sizes are very diverse. The narrowing of the cloud droplet size distribution under polluted conditions introduces a new stabilizing factor by which increased aerosol concentration can suppress precipitation and enhance cloud brightness. [Preview Abstract] |
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