Eddy Turnover Time Research Articles

Understanding density fluctuations in supersonic, isothermal turbulence.

Supersonic turbulence occurs in many environments, particularly in astrophysics. In the crucial case of isothermal turbulence, the probability density function (PDF) of the logarithmic density, s, is well measured, but a theoretical understanding of the processes leading to this distribution remains elusive. We investigate these processes using Lagrangian tracer particles to track s and [Formula: see text] in direct numerical simulations, and we show that their evolution can be modeled as a stochastic differential process with time-correlated noise. The temporal correlation functions of s and [Formula: see text] decay exponentially, as predicted by the model, and the decay timescale is ≈1/6 the eddy turnover time. The behaviors of the conditional averages of [Formula: see text] and [Formula: see text] are also well explained by the model, which shows that the density PDF arises from a balance between stochastic compressions/expansions, which tend to broaden the PDF, and the acceleration/deceleration of shocks by density gradients, which tends to narrow it.

Modified stochastic diffusion particle-tracking model (MSDPTM) incorporating energy cascade theory and eddy intermittency for suspended sediment transport in open channel flow.

This study presents a modified stochastic diffusion particle tracking model (MSDPTM) that incorporates energy cascade theory to more accurately simulate suspended sediment transport. The impact of turbulent eddies on sediment particles is an intermittent process, which is also considered in this study. The study examines the time correlation between eddies using eddy turnover time and finds that closer-scale eddies exhibit higher correlations than those farther apart. The statistical properties of particle movement, such as the ensemble mean and variance of particle trajectories, have been calculated and compared with the stochastic diffusion particle tracking model (SDPTM) results. Notably, MSDPTM with intermittency demonstrates a significantly larger ensemble mean of particle trajectories in the streamwise direction than other particle tracking models. The proposed model is validated through comparison with available data, showing its enhanced performance. The results of the simulation indicate that MSDPTM outperforms SDPTM, especially when the intermittency effect of eddies is considered.

Threshold transient growth as a criterion for turbulent mean profiles

Lozano-Duran et al. (J. Fluid Mech., vol. 914, 2021, p. A8) have recently identified the ability of streamwise-averaged turbulent streak fields ${\mathcal {U}}(y,z,t)\hat {\boldsymbol {x}}$ in minimal channels to produce short-term transient growth as the key linear mechanism needed to sustain turbulence at $Re_{\tau }=180$ . Here, in an attempt to extend this result to larger domains and higher $Re_{\tau }$ , we model this streak transient growth as a two-stage linear process by first selecting the dominant streak structure expected to emerge over the eddy turnover time on the turbulent mean profile $U(y)\hat {\boldsymbol {x}}$ , and then examining the secondary growth on this (frozen) streak field ${\mathcal {U}}(y,z)\hat {\boldsymbol {x}}$ . Choosing the mean streak amplitude and eddy turnover time consistent with simulations captures the growth thresholds found by Lozano-Duran et al. (2021) for sustained turbulence. In a larger domain at $Re_{\tau }=180$ , the most energetic near-wall streaks observed in simulations are close to the predicted optimal streaks. This most energetic streak spacing, approaches the optimal streak at $Re_{\tau }=550$ where the secondary growth possible on each also comes together. A key prediction from the model is that the threshold transient growth required to sustain turbulence decreases with increasing $Re_{\tau }$ . More fundamentally, the work of Lozano-Duran et al. (2021) and our results suggest a subtle but significant revision of Malkus's (J. Fluid Mech., vol. 1, 1956, pp. 521–539) classic hypothesis concerning realisable turbulent mean profiles. The key property for a realisable turbulent mean profile could be the ability to generate sufficient short-term transient growth rather than dependence on its (long-term) linear stability characteristics, which was Malkus's original idea.

Predicting the skin friction’s evolution in a forced turbulent channel flow

The present paper reports on the ability of neural networks (NN) and linear stochastic estimation (LSE) tools to predict the evolution of skin friction in a minimal turbulent channel (Reτ=165) after applying an actuation near the wall that is localized in space and time. Two different NN architectures are compared, namely multilayer perceptrons (MLP) and convolutional neural networks (CNN). The paper describes the effect that the predictive horizon and the type/size/number of wall-based sensors have on the performance of each estimator. The performance of MLPs and LSEs is very similar, and becomes independent of the sensor’s size when they are smaller than 60 wall units. For sufficiently small sensors, the CNN outperforms MLPs and LSEs, suggesting that CNNs are able incorporate some of the non-linearities of the near-wall cycle in their prediction of the skin friction evolution after the actuation. Indeed, the CNN is the only architecture able to achieve reasonable predictive capabilities using pressure sensors only. The predictive horizon has a strong effect on the predictive capacity of both NN and LSE, with a Pearson correlation coefficient that varies from 0.95 for short times (i.e., of the order of the actuation time) to less than 0.4 for times of the order of an eddy turn-over time. The analysis of the weights and filters in the LSE and NNs show that all estimators are targeting wall-signatures consistent with streaks, which is interpreted as the streak being the most causal feature in the near-wall cycle for the present forcing.

Spontaneous Stochasticity Amplifies Even Thermal Noise to the Largest Scales of Turbulence in a Few Eddy Turnover Times.

How predictable are turbulent flows? Here, we use theoretical estimates and shell model simulations to argue that Eulerian spontaneous stochasticity, a manifestation of the nonuniqueness of the solutions to the Euler equation that is conjectured to occur in Navier-Stokes turbulence at high Reynolds numbers, leads to universal statistics at finite times, not just at infinite time as for standard chaos. These universal statistics are predictable, even though individual flow realizations are not. Any small-scale noise vanishing slowly enough with increasing Reynolds number can trigger spontaneous stochasticity, and here we show that thermal noise alone, in the absence of any larger disturbances, would suffice. If confirmed for Navier-Stokes turbulence, our findings would imply that intrinsic stochasticity of turbulent fluid motions at all scales can be triggered even by unavoidable molecular noise, with implications for modeling in engineering, climate, astrophysics, and cosmology.

Stratification and temporal evolution of mixing regimes in diurnally heated river flows

Direct numerical simulations of stratified open channel flows subject to a varying surface heat flux are performed. The influence of the diurnal heating time on the spatial and temporal variation of mixing in the flow and the characteristics of the mean flow state are examined. The control parameters are the bulk stability parameter lambda_{B}, defined through the ratio of the channel height delta and a bulk Obukhov length scale mathscr{L}_{B}, and the diurnal time scale hat{t}, defined as the ratio of the heating time to an eddy turnover time. The Prandtl number Pr and Reynolds number Re_{tau} have values of 1 and 400. Simulations are performed over hat{t} = 1 to 24 and lambda_{B} = 0.6 to 26. Two key flow features are used to classify the flow regimes observed, namely the laminar layer depth (LLD) and stratified layer depth (SLD) where the LLD is defined as the depth from the free surface when the buoyancy Reynolds number Re_{B} approx 7 and the SLD is the depth from the free surface when the turbulent Froude number Fr approx 1. This study attempts to characterise how these length scales vary across the diel cycle. The LLD is a viscous length scale and a regime map of a viscous parameter, the bulk Obhukov Reynolds number Re_mathscr{L}, and hat{t} is presented to classify the LLD behaviour. A regime map of lambda _{B} and hat{t} is presented to classify the behaviour of the SLD. Three classifications for each layer depth behaviour within a diel cycle form the basis of the regime maps for this paper: a neutral flow where the LLD or SLD does not exist (denoted by NL and NS), a stratified flow where the LLD or SLD are diurnally varying (denoted as DL and DS) and a persistent layer of the LLD or SLD (denoted as PL and PS). The transition between the NL to DL is hat{t} propto Re_{mathscr{L}}^{4.5}, DL to PL is hat{t} propto Re_{mathscr{L}}^{- 0.5}, NS to DS is hat{t} propto lambda _{B}^{0} and DS to PS is hat{t} propto lambda _{B}^{1}. The regime maps may be used as a predictive tool to determine when suppressed mixing regimes occur in rivers. At each flow depth, the flow sweeps though a range of mixing states across the diel cycle. The local mixing efficiency are briefly assessed and found to scale well with the instantaneous Fr number according to the regimes proposed by Garanaik and Venayagamoorthy (J. Fluid Mech., vol. 867, 2019, pp. 323-333).

Interactions between high hydrogen content syngas–air premixed flames and homogeneous isotropic turbulence: Flame thickening

This paper reports the findings from a three-dimensional direct numerical simulation conducted to investigate the turbulent flame behaviors of premixed high-hydrogen content syngas (with 50% hydrogen on a per mole basis) and air mixtures. To accomplish this, a laminar flame front is placed in a homogeneous isotropic decaying turbulence field composed of a syngas–air mixture at an equivalence ratio of 0.7 and allowed to evolve for 1.4 eddy turnover times. Homogeneous isotropic turbulence is generated using a helical forcing function in a cubic domain with a grid size of 256 × 256 × 256. The Reynolds number based on the Taylor microscale, Reλ, is 57 for the generated turbulence field. The laminar flame front is placed at the center of the domain. The premixture enters the domain at a velocity of 8 m/s and at an initial temperature of 800 K. The pressure remains constant at 1 atm. In addition to quantifying the spatial and temporal evolution of turbulent characteristics and flame structure, the study also focuses on identifying turbulence/flame interactions, specifically, the impact of these interactions on flame thickness. Energy transfer from small to large scales, i.e., a reverse cascade is observed as a result of energy release due to chemical reactions at the small scales that is transferred to larger scales. The increase in turbulent intensities due to chemical reactions correlates with flame thickening.

The Departure from Mixed-Layer Similarity During the Afternoon Decay of Turbulence in the Free-Convective Boundary Layer: Results from Large-Eddy Simulations

This study analyses the departure of the velocity-variances profiles from their quasi-steady state described by the mixed-layer similarity, using large-eddy simulations with different prescribed shapes and time scales of the surface kinematic heat flux decay. Within the descriptive frames where the time is tracked solely by the forcing time scale (either constant or time-dependent) describing the surface heat flux decay, we find that the normalized velocity-variances profiles from different runs do not collapse while they depart from mixed-layer similarity. As the mixed-layer similarity relies on the assumption that the free-convective boundary layer is in a quasi-equilibrium, we consider the ratios of the forcing time scales to the convective eddy-turnover time scale. We find that the normalized velocity-variances profiles collapse in the only case where the ratio (widetilde{r}) of the time-dependent forcing time scale to the convective eddy-turnover time scale is used for tracking the time, supporting the independence of the departure from the characteristics of the surface heat flux decay. As a consequence of this result, the knowledge of widetilde{r} is sufficient to predict the departure of the velocity variances from their quasi-steady state, irrespective of the shape of the surface heat flux decay. This study highlights the importance of considering both the time-dependent forcing time scale and the convective eddy-turnover time scale for evaluating the response of the free-convective boundary layer to the surface heat flux decay.

Lagrangian conditional statistics and flow topology in edge plasma turbulence

Lagrangian statistics and particle transport in edge plasma turbulence are investigated using the Hasegawa–Wakatani model and its modified version. The latter shows the emergence of pronounced zonal flows. Different values of the adiabaticity parameter are considered. The main goal is to characterize the role of coherent structures, i.e., vortices and zonal flows, and their impact on the Lagrangian statistics of particles. Computationally intensive long time simulations following ensembles of test particles over hundreds of eddy turnover times are considered in statistically stationary turbulent flows. The flow topology is characterized using the Lagrangian Okubo–Weiss criterion in order to split the flow into topologically different domains. In elliptic and hyperbolic regions, the probability density functions (PDFs) of the residence time have self-similar algebraic decaying tails. However, in the intermediate regions, the PDFs exhibit exponentially decaying tails. Topologically conditioned PDFs of the Lagrangian velocity, and acceleration and density fluctuations are likewise computed. The differences between the classical Hasegawa–Wakatani system and its modified version are assessed, and the role of zonal flows is highlighted. The density flux spectrum, which characterizes the contributions of different length scales, is studied, and its inertial scaling is found to be in agreement with predictions based on dimensional arguments. Analyzing the angular change of particle tracers at different time scales, corresponding to coarse grained curvature, completes the study, and these multiscale geometric statistics quantify the directional properties of the particle motion in different flow regimes.

Evolution of Droplet Size Distributions During the Transition of an Ultraclean Stratocumulus Cloud System to Open Cell Structure: An LES Investigation Using Lagrangian Microphysics

AbstractA state‐of‐the‐art Lagrangian microphysics scheme is used in a large‐eddy simulation to investigate the stratocumulus transition from closed to open cell structure. Processes controlling precipitation development, which is a key to the transition, are analyzed by leveraging unique benefits of Lagrangian microphysics, particularly the ability to track computational drops in the flow. Sufficient time is needed for coalescence growth of cloud drops to drizzle within the updraft‐downdraft cycle of large eddies. This favors broad drop size distributions (DSDs) and drizzle growth in downdrafts, where drops are typically much older than in updrafts. During the closed cell stage, mean cloud drop radius is too small, and the DSDs are too narrow, so that the timescale for coalescence is much longer than the large eddy turnover time and drizzle growth is limited. The closed‐to‐open cell transition occurs when these timescales become comparable and the precipitation flux increases sharply.

Generation of gravitational waves from freely decaying turbulence

We study the stochastic gravitational wave background (SGWB) produced by freely decaying vortical turbulence in the early Universe. We thoroughly investigate the time correlation of the velocity field, and hence of the anisotropic stresses producing the gravitational waves. With hydrodynamical simulations, we show that the unequal time correlation function (UETC) of the Fourier components of the velocity field is Gaussian in the time difference, as predicted by the “sweeping” decorrelation model. We introduce a decorrelation model that can be extended to wavelengths around the integral scale of the flow. Supplemented with the evolution laws of the kinetic energy and of the integral scale, this provides a new model UETC of the turbulent velocity field consistent with the simulations. We discuss the UETC as a positive definite kernel, and propose to use the Gibbs kernel for the velocity UETC as a natural way to ensure positive definiteness of the SGWB. The SGWB is given by a 4-dimensional integration of the resulting anisotropic stress UETC with the gravitational wave Green's function. We perform this integration using a Monte Carlo algorithm based on importance sampling, and find that the result matches that of the simulations. Furthermore, the SGWB obtained from the numerical integration and from the simulations show close agreement with a model in which the source is constant in time and abruptly turns off after a few eddy turnover times. Based on this assumption, we provide an approximate analytical form for the SGWB spectrum and its scaling with the initial kinetic energy and integral scale. Finally, we use our model and numerical integration algorithm to show that including an initial growth phase for the turbulent flow heavily influences the spectral shape of the SGWB. This highlights the importance of a complete understanding of the turbulence generation mechanism.

Gravitational wave signal from primordial magnetic fields in the Pulsar Timing Array frequency band

The NANOGrav, Parkes, European, and International Pulsar Timing Array (PTA) Collaborations have reported evidence for a common-spectrum process that can potentially correspond to a stochastic gravitational wave background (SGWB) in the 1--100 nHz frequency range. We consider the scenario in which this signal is produced by magnetohydrodynamic (MHD) turbulence in the early Universe, induced by a nonhelical primordial magnetic field at the energy scale corresponding to the quark confinement phase transition. We perform MHD simulations to study the dynamical evolution of the magnetic field and compute the resulting SGWB. We show that the SGWB output from the simulations can be very well approximated by assuming that the magnetic anisotropic stress is constant in time, over a time interval related to the eddy turnover time. The analytical spectrum that we derive under this assumption features a change of slope at a frequency corresponding to the GW source duration that we confirm with the numerical simulations. We compare the SGWB signal with the PTA data to constrain the temperature scale at which the SGWB is sourced, as well as the amplitude and characteristic scale of the initial magnetic field. We find that the generation temperature is constrained to be in the 1--200 MeV range, the magnetic field amplitude must be $>1$\% of the radiation energy density at that time, and the magnetic field characteristic scale is constrained to be $>10$\% of the horizon scale. We show that the turbulent decay of this magnetic field will lead to a field at recombination that can help to alleviate the Hubble tension and can be tested by measurements in the voids of the Large Scale Structure with gamma-ray telescopes like the Cherenkov Telescope Array.

On the validity of quasilinear theory applied to the electron bump-on-tail instability

The accuracy of quasilinear theory applied to the electron bump-on-tail instability, a classic model problem, is explored with conservative high-order discontinuous Galerkin methods applied to both the quasilinear equations and to a direct simulation of the Vlasov–Poisson equations. The initial condition is chosen in the regime of beam parameters for which quasilinear theory should be applicable. Quasilinear diffusion is initially in good agreement with the direct simulation but later underestimates the turbulent momentum flux. The greater turbulent flux of the direct simulation leads to a correction from quasilinear evolution by quenching the instability in a finite time. Flux enhancement above quasilinear levels occurs as the phase space eddy turnover time in the largest amplitude wavepackets becomes comparable to the transit time of resonant phase fluid through wavepacket potentials. In this regime, eddies effectively turn over during wavepacket transit so that phase fluid predominantly disperses by eddy phase mixing rather than by randomly phased waves. The enhanced turbulent flux of resonant phase fluid leads, in turn, through energy conservation to an increase in non-resonant turbulent flux and, thus, to an enhanced heating of the main thermal body above quasilinear predictions. These findings shed light on the kinetic turbulence fluctuation spectrum and support the theory that collisionless momentum diffusion beyond the quasilinear approximation can be understood through the dynamics of phase space eddies (or clumps and granulations).

Pitch-Angle Anisotropy Controls Particle Acceleration and Cooling in Radiative Relativistic Plasma Turbulence.

Nature's most powerful high-energy sources are capable of accelerating particles to high energy and radiating it away on extremely short timescales, even shorter than the light crossing time of the system. It is yet unclear what physical processes can produce such an efficient acceleration, despite the copious radiative losses. By means of radiative particle-in-cell simulations, we show that magnetically dominated turbulence in pair plasmas subject to strong synchrotron cooling generates a nonthermal particle spectrum with a hard power-law range (slope p∼1) within a few eddy turnover times. Low pitch-angle particles can significantly exceed the nominal radiation-reaction limit, before abruptly cooling down. The particle spectrum becomes even harder (p<1) over time owing to particle cooling with an energy-dependent pitch-angle anisotropy. The resulting synchrotron spectrum is hard (νF_{ν}∝ν^{s} with s∼1). Our findings have important implications for understanding the nonthermal emission from high-energy astrophysical sources, most notably the prompt phase of gamma-ray bursts and gamma-ray flares from the Crab nebula.

Spray dispersion regimes following atomization in a turbulent co-axial gas jet

A canonical co-axial round-jet two-fluid atomizer where atomization occurs over a wide range of momentum ratios: $M=1.9 - 376.4$ is studied. The near field of the spray, where the droplet formation process takes place, is characterized and linked to droplet dispersion in the far field of the jet. Counterintuitively, our results indicate that in the low-momentum regime, increasing the momentum in the gas phase leads to less droplet dispersion. A critical momentum ratio of the order of $M_c=50$ , that separates this regime from a high-momentum one with less dispersion, is found in both the near and far fields. A phenomenological model is proposed that determines the susceptibility of droplets to disperse beyond the nominal extent of the gas phase based on a critical Stokes number, $St=\tau _p/T_E=1.9$ , formulated based on the local Eulerian large scale eddy turnover time, $T_E$ , and the droplets’ response time, $\tau _p$ . A two-dimensional phase space summarizes the extent of these different regimes in the context of spray characteristics found in the literature.

A low-storage method consistent with second-order statistics for time-resolved databases of turbulent channel flow up to [formula omitted

Wall-bounded flows play an important role in numerous common applications, and have been intensively studied for over a century. However, the dynamics and structure of the logarithmic and outer regions remain controversial to this date, and understanding their dynamics is essential for the development of effective prediction and control strategies, and for the construction of a complete theory of wall-bounded flows. Recently, the use of time-resolved direct numerical simulations of turbulent flows at high Reynolds numbers has proved useful to study the physics of wall-bounded turbulence, but a proper analysis of the logarithmic and outer layers requires simulations at high Reynolds numbers in large domains, making the storage of complete time series challenging. In this paper a novel low-storage method for time-resolved databases is presented. This approach reduces the storage cost of time-resolved databases by storing filtered flow fields that target the large and intermediate scales, while retaining all the information needed to fully reconstruct the flow at the level of filtered flow fields and complete second-order statistics. This is done by storing also the filtered turbulent stresses, allowing to recover the exact effect of the small scales on the large and intermediate scales. A significant speed-up of the computations is achieved, first, by relaxing the numerical resolution, which is shown to affect only the dynamics close to the wall, but not the large scales stored in the database, and, second, by exploiting the computing power and efficiency of GPU co-processors using a new high-resolution hybrid CUDA-MPI code. This speed-up allows running for physically meaningful times to capture the dynamics of the large scales. The resulting temporally resolved large-scale database of a turbulent channel flow up to Reτ=5300, in large boxes for long times, is briefly introduced, showing significant indicators of large-scale dynamics with characteristic times of the order of up to eight eddy turnover times.

Eccentric millisecond pulsars by resonant convection

ABSTRACT Eccentric millisecond pulsars (eMSPs) with white dwarf companions exhibit orbital eccentricities orders of magnitude larger than predicted by turbulent convection in the white dwarfs’ red giant progenitors. The orbital periods of eMSPs cluster around P = 20–30 d, remarkably close to the red giant convective eddy turnover time teddy. We propose that the anomalously large eccentricities are resonantly driven by convective flows somehow made coherent when the turnover time matches the tidally locked red giant’s spin period, which is also the tidal forcing period. Numerical simulations of rotating red giants and magnetic field studies of stars show some evidence for especially ordered flow patterns when the convective Rossby number P/teddy is of order unity. We show that resonant convection boosts eccentricities by a factor of (tnuc/P)1/2 ≈ 3 × 103 over the random-walk values that characterize conventional MSPs, in good agreement with observations (tnuc is the giant’s nuclear burning time-scale). We also show how variations in the eddy turnover time arising from red giant metallicity variations can reproduce the observed effective width of the resonance, ΔP/P ≈ 0.4.

Mean field dynamo action in shearing flows – II. Fluctuating kinetic helicity with zero mean

ABSTRACT Here we explore the role of temporal fluctuations in kinetic helicity on the generation of large-scale magnetic fields in the presence of a background linear shear flow. Key techniques involved here are same as in our earlier work, where we have used the renovating flow based model with shearing waves. Both the velocity and the helicity fields are treated as stochastic variables with finite correlation times, τ and τh, respectively. Growing solutions are obtained when τh &amp;gt; τ, even when this time-scale separation, characterized by m = τh/τ, remains below the threshold for causing the turbulent diffusion to turn negative. In regimes when turbulent diffusion remains positive, and τ is of the order of eddy turnover time T, the axisymmetric modes display non-monotonic behaviour with shear rate S: both, the growth rate γ and the wavenumber k* corresponding to the fastest growing mode, first increase, reach a maximum and then decrease with |S|, with k* being always smaller than eddy-wavenumber, thus boosting growth of magnetic fields at large length-scales. The cycle period Pcyc of growing dynamo wave is inversely proportional to |S| at small shear, exactly similar to the fixed kinetic helicity case of our earlier work. This dependence becomes shallower at larger shear. Interestingly enough, various curves corresponding to different choices of m collapse on top of each other in a plot of mPcyc with |S|.

Mesoscale nesting interface of the PALM model system 6.0

Abstract. In this paper, we present a newly developed mesoscale nesting interface for the PALM model system 6.0, which enables PALM to simulate the atmospheric boundary layer under spatially heterogeneous and non-stationary synoptic conditions. The implemented nesting interface, which is currently tailored to the mesoscale model COSMO, consists of two major parts: (i) the preprocessor INIFOR (initialization and forcing), which provides initial and time-dependent boundary conditions from mesoscale model output, and (ii) PALM's internal routines for reading the provided forcing data and superimposing synthetic turbulence to accelerate the transition to a fully developed turbulent atmospheric boundary layer. We describe in detail the conversion between the sets of prognostic variables, transformations between model coordinate systems, as well as data interpolation onto PALM's grid, which are carried out by INIFOR. Furthermore, we describe PALM's internal usage of the provided forcing data, which, besides the temporal interpolation of boundary conditions and removal of any residual divergence, includes the generation of stability-dependent synthetic turbulence at the inflow boundaries in order to accelerate the transition from the turbulence-free mesoscale solution to a resolved turbulent flow. We demonstrate and evaluate the nesting interface by means of a semi-idealized benchmark case. We carried out a large-eddy simulation (LES) of an evolving convective boundary layer on a clear-sky spring day. Besides verifying that changes in the inflow conditions enter into and successively propagate through the PALM domain, we focus our analysis on the effectiveness of the synthetic turbulence generation. By analysing various turbulence statistics, we show that the inflow in the present case is fully adjusted after having propagated for about two to three eddy-turnover times downstream, which corresponds well to other state-of-the-art methods for turbulence generation. Furthermore, we observe that numerical artefacts in the form of grid-scale convective structures in the mesoscale model enter the PALM domain, biasing the location of the turbulent up- and downdrafts in the LES. With these findings presented, we aim to verify the mesoscale nesting approach implemented in PALM, point out specific shortcomings, and build a baseline for future improvements and developments.

Implementing a New Formulation in WRF-LES for Buoyant Plume Simulations: bPlume-WRF-LES Model

AbstractA new formulation—bPlume-WRF-LES model—was implemented within the Weather Research and Forecasting (WRF) Model to simulate the two-way coupling between the atmospheric boundary layer (ABL) and gas plume (denser and lighter) released into the atmosphere. The existing WRF large-eddy simulation (WRF-LES) modeling system was modified by coupling an additional transport equation for the plume gas mixture and by accounting for the buoyant production term in the turbulence kinetic energy equation. The focus of the work was to understand the effect of atmospheric forcings on plume rise, plume mixing, and plume dynamics during the early stages of plume development. For this purpose, the bPlume-WRF-LES model was used to simulate the release of buoyant plumes from a large area source into different atmospheric conditions with varying stratification and mean wind forcing values. Plumes released in a convective ABL background rise according to the 2/3 power law with time before reaching the boundary layer top and spreading laterally. The convective ABL eddy turnover time scale () dictates the rate at which plume mixes with the ambient air inside the convective boundary layer (CBL) and the plume dilution rate scales as . Both the stratification and wind forcing enhance the plume mixing from the early plume development stage, and dilute the plume much faster. An increase in the mean winds within the CBL contributes to uniform mixing and greater bent-over plume behavior at a shorter downwind distance from the source.