Observation and Large‐Eddy Simulation of an Offshore Atmospheric Undular Bore During Sea‐Breeze Initiation

Numerical investigation of the interphase forces and turbulence closure in 3D square bubble columns

The effects of littoral zone vegetation on turbulent mixing in lakes

The present paper reports a numerical study of fully developed turbulent flow over a flat plate with a step change from a smooth to a rough surface. The Reynolds number based on momentum thickness for the smooth flow was Reθ=5950. The focus of the study was to investigate the capability of the Reynolds-averaged Navier–Stokes (RANS) equations to predict the internal boundary layer (IBL) created by the flow configuration. The numerical solution used a two-layer k−ε model to implement the effects of surface roughness on the turbulence and mean flow fields via the use of a hydrodynamic roughness length y0. The prediction for the mean velocity field revealed a development zone immediately downstream of the step in which the mean velocity profile included a lower region affected by the surface roughness below and an upper region with the characteristics of the smooth-wall boundary layer above. In this zone, both the turbulence kinetic energy and Reynolds shear stress profiles were characterized by a significant reduction in magnitude in the outer region of the flow that is unaffected by the rough surface. The turbulence kinetic energy profile was used to estimate the thickness of the IBL, and the resulting growth rate closely matched the experimental results. As such, the IBL is a promising test case for assessing the ability of RANS models to predict the discrete roughness configurations often encountered in industrial and environmental applications.

Abstract. In mesoscale climate models, urban canopy flow is typically parameterized in terms of the horizontally averaged (1-D) flow and scalar transport, and these parameterizations can be informed by computational fluid dynamics (CFD) simulations of the urban climate at the microscale. Reynolds averaged Navier–Stokes simulation (RANS) models have previously been employed to derive vertical profiles of turbulent length scale and drag coefficient for such parameterization. However, there is substantial evidence that RANS models fall short in accurately representing turbulent flow fields in the urban roughness sublayer. When compared with more accurate flow modeling such as large-eddy simulations (LES), we observed that vertical profiles of turbulent kinetic energy and associated turbulent length scales obtained from RANS models are substantially smaller specifically in the urban canopy. Accordingly, using LES results, we revisited the urban canopy parameterizations employed in the one-dimensional model of turbulent flow through urban areas and updated the parameterization of turbulent length scale and drag coefficient. Additionally, we included the parameterization of the dispersive stress, previously neglected in the 1-D column model. For this objective, the PArallelized Large-Eddy Simulation Model (PALM) is used and a series of simulations in an idealized urban configuration with aligned and staggered arrays are considered. The plan area density (λp) is varied from 0.0625 to 0.44 to span a wide range of urban density (from sparsely developed to compact midrise neighborhoods, respectively). In order to ensure the accuracy of the simulation results, we rigorously evaluated the PALM results by comparing the vertical profiles of turbulent kinetic energy and Reynolds stresses with wind tunnel measurements, as well as other available LES and direct numerical simulation (DNS) studies. After implementing the updated drag coefficients and turbulent length scales in the 1-D model of urban canopy flow, we evaluated the results by (a) testing the 1-D model against the original LES results and demonstrating the differences in predictions between new (derived from LES) and old (derived from RANS) versions of the 1-D model, and (b) testing the 1-D model against LES results for a test case with realistic geometries. Results suggest a more accurate prediction of vertical turbulent exchange in urban canopies, which can consequently lead to an improved prediction of urban heat and pollutant dispersion at the mesoscale.

Improving the Turbulence Coupling between High Resolution Numerical Weather Prediction Models and Lagrangian Particle Dispersion Models

The interaction of an urban heat island with a sea breeze front during moist convection over <scp>Tianjin, China</scp>

&amp;lt;p&amp;gt;Turbulence kinetic energy (TKE) is an important process variable to characterize the atmospheric boundary layer. State-of-the-art numerical weather prediction (NWP) models solve a prognostic TKE equation, this generates the interest in measurement data of this variable for verification of the NWP model output. Operational TKE measurements are typically performed using 3D ultrasonic anemometers; this limits their availability to near-surface levels (up to about 200 m above ground at a few tower sites). Alternatively, TKE may be derived from measurements with ground-based remote sensing instruments, such as Doppler lidars.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;At the Meteorological Observatory Lindenberg &amp;amp;#8211; Richard-A&amp;amp;#223;mann-Observatory (MOL-RAO) of the German Meteorological Service (DWD) we have implemented an algorithm suggested by Smalikho und Banakh (2017, Atmos. Meas. Tech. 10, 4191&amp;amp;#8211;4208) to derive TKE profiles from Doppler lidar measurements. In addition, this algorithm allows to derive profiles of momentum flux, eddy dissipation rate and the integral length scale of turbulence. Thus, a consistent data set to characterize turbulent processes in the atmospheric boundary layer can be obtained. The method includes a correction for an underestimation of TKE due to pulse volume averaging effects. It is based on a special Doppler lidar scan regime - a continuous scan mode (CSM) with very high azimuthal resolution (&amp;lt; 2 deg). This implies using a small number of lidar pulses per ray such that classical data filtering approaches cannot be applied.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We briefly introduce the scan configuration and the methodology for TKE derivation and discuss an alternative data filtering approach which has been realized and tested at MOL-RAO. The methodology has been applied to a data set covering one year of quasi-operational measurements with a Halo Photonics Streamline Doppler lidar at MOL-RAOs boundary-layer field site (GM) Falkenberg. Here, the intercomparison of the derived TKE values versus sonic measurements at a height of 90m at the GM Falkenberg tower shows good agreement. Case studies illustrate the potential to characterize enhanced turbulence associated with cold pools affiliated to thunderstorms or in the shear zone below the axis of a nocturnal low-level jet. Finally, the Doppler lidar TKE values have been compared to the output of DWD&amp;amp;#8217;s NWP models.&amp;lt;/p&amp;gt;

Accurately representing boundary layer turbulent processes in numerical models is critical to improve tropical cyclone forecasts. A new turbulence kinetic energy (TKE)-based moist eddy-diffusivity mass-flux (EDMF-TKE) planetary boundary layer scheme has been implemented in NOAA’s Hurricane Analysis and Forecast System (HAFS). This study evaluates EDMF-TKE in hurricane conditions based on a recently developed framework using large-eddy simulation (LES). Single-column modeling tests indicate that EDMF-TKE produces much greater TKE values below 500-m height than LES benchmark runs in different high-wind conditions. To improve these results, two parameters in the TKE scheme were modified to ensure a match between the PBL and surface-layer parameterizations. Additional improvements were made by reducing the maximum allowable mixing length to 40 m based on LES and observations, by adopting a different definition of boundary layer height, and by reducing nonlocal mass fluxes in high-wind conditions. With these modifications, the profiles of TKE, eddy viscosity, and winds compare much better with LES results. Three-dimensional idealized simulations and an ensemble of HAFS forecasts of Hurricane Michael (2018) consistently show that the modified EDMF-TKE tends to produce a stronger vortex with a smaller radius of maximum wind than the original EDMF-TKE, while the radius of gale-force wind is unaffected. The modified EDMF-TKE code produces smaller eddy viscosity within the boundary layer compared to the original code, which contributes to stronger inflow, especially within the annulus of 1–3 times the radius of maximum wind. The modified EDMF-TKE shows promise to improve forecast skill of rapid intensification in sheared environments.

Velocity and forces on individual plants were measured within an emergent canopy with real plant morphology and used to develop predictions for the vertical profiles of velocity and turbulent kinetic energy (TKE). Two common plant species, Typha latifolia and Rotala indica, with distinctive morphology, were considered. Typha has leaves bundled at the base, and Rotala has leaves distributed over the length of the central stem. Compared to conditions with a bare bed and the same velocity, the TKE within both canopies was enhanced. For the Typha canopy, for which the frontal area increased with distance from the bed, the velocity, integral length‐scale, and TKE all decreased with distance from the bed. For the Rotala, which had a vertically uniform distribution of biomass, the velocity, integral length‐scale, and TKE were also vertically uniform. A turbulence model previously developed for random arrays of rigid cylinders was modified to predict both the vertical distribution and the channel‐average of TKE by defining the relationship between the integral length‐scale and plant morphology. The velocity profile can also be predicted from the plant morphology. Combining with the new turbulence model, the TKE profile was predicted from the channel‐average velocity and plant frontal area.

Experimental Characterization of the Marine Atmospheric Boundary Layer in the Havsul Area, Norway

Calculations of the effects of high free stream turbulence (FST) on heat transfer and skin friction in a flat plate turbulent boundary layer using different k-ε models (Launder-Sharma, K-Y Chien, Lam-Bremhorsi and Jones-Launder) are presented. This study was carried out in order to investigate the prediction capabilities of these models under high FST conditions. In doing so, TEXSTAN, a partial differential equation solver which is based on the ideas of Patankar and Spalding and solves steady-flow boundary layer equations, was used. Firstly, these models were compared as to how they predicted very low FST (≤ 1% turbulence intensity) cases. These baseline cases were tested by comparing predictions with both experimental data and empirical correlations. Then, these models were used in order to determine the effect of high FST (&gt;5% turbulence intensity) on heat transfer and skin friction and compared with experimental data. Predictions for heat transfer and skin friction coefficient for all the turbulence intensities tested by all the models agreed well (within 1–8%) with experimental data. However, all these models predicted poorly the dissipation of turbulent kinetic energy (TKE) in the free stream and TKE profiles. Physical reasoning as to why the aforementioned models differ in their predictions and the probable cause of poor prediction of free-stream TKE and TKE profiles are given.

Abstract. A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined, and transversal temporal autocovariance functions (ACFs) are determined for deriving the dissipation and molecular destruction rates. These are fundamental loss terms in the TKE as well as the potential temperature and mixing ratio variance equations. These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless of whether 1 or 10 s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations in vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ϵm≃7×10-4 g2 kg−2 s−1 for mixing ratio and ϵθ≃1.6×10-3 K2 s−1 for potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts to ≃10-2 m2 s−3. We also demonstrate that the vertical wind ACF coefficient kw∝w′2‾ and the TKE dissipation ϵ∝w′2‾3/2. For the molecular destruction rates, we show that ϵm∝m′2‾w′2‾1/2 and ϵθ∝θ′2‾w′2‾1/2. These equations can be used for parameterizations of ϵ, ϵm, and ϵθ. All noise error bars are derived by error propagation and are small enough to compare the results with previous observations and large-eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large-eddy simulations.

The turbulent flow field in an agitated system with baffles was solved numerically using the standard k-e model, an algebraic Reynolds stress model (ASM) and a differential Reynolds stress model (RSM). The commercial software FLOW3D (CFDS, Harwell Laboratories, 1991) was used for this purpose. The aim of the study was to investigate the influence of the impeller boundary conditions and turbulence models to the agreement with experimentally obtained laser-Doppler anemometry data. The boundary conditions for the impeller discharge used in the numerical calculations were obtained as whole-cycle-ensemble averages from experimental LDA-measurements (Fort et al., 1992). Since measurements of the rate of dissipation of turbulent kinetic energy ( ϵ) was not available the dissipation rate per unit mass in the impeller discharge was estimated from the expression: where k is the turbulent kinetic energy per unit mass and L the macroscale of turbulence in the pitched blade impeller discharge. The macroscale of turbulence (L) in the impeller boundary condition for e was varied in order to optimize the fit of theoretically obtained profiles of turbulent kinetic energy with experimental data. The constant A was fixed to 0.85 according to Wu and Patterson (1989). The optimal values of L for the different turbulence models were compared with the projected height of the impeller blade (h). All three components of the mean velocity were compared with experimental data for the optimal ratio of L/h for six radial cross-sections in the tank. The mean velocity field obtained from simulations showed good agreement with experimental data for all models, with somewhat better agreement for the k — e model. An optimal value of the ratio L/h was found to be equal to 2.0 for the k — ϵ model and 1.3 for the ASM. However, no such optimal value for the RSM could be determined in this study.

A model for the diffusion of turbulent kinetic energy (TKE) for high free stream turbulence (FST) boundary layers is implemented in commercially available FLUENT CFD code to predict the effects of high free stream turbulence on heat and momentum transport in a flat plate boundary layer using Launder and Spalding’s standard k-ε model. The computational results are compared with experimental data sets. When experimental and/or standard initial profiles and standard k-ε model were used for calculations of Stanton number and skin friction coefficient under high FST intensities the results were close to the experimental data (within 2%). However. TKE profiles had large deviations (within approximately 40 %) compared to the data for both moderately high FST (Tui = 6.53%) and very high FST (Tui = 25.7%) intensities. Since TKE values are used in calculations of skin friction coefficients and Stanton numbers through calculation of turbulent viscosity from k and ε, getting a correct result for these quantities from the wrong calculations of TKE seems contradictory. In an earlier study it was concluded that the TKE calculations were low compared to the data because k-ε models do not model the diffusion of high FST correctly. To correct this discrepancy, a new model for TKE diffusion was developed and used it in TEXSTAN code. The objective of the current study is to generalize this model and use it in more complicated geometries by applying to FLUENT code. Therefore at this first phase of this study, this diffusion model was implemented in the Launder and Spalding k-ε model contained in FLUENT code using User Defined Functions (UDF) by modifying the turbulent kinetic energy transport equation. The constant Cμ which exists in the turbulent viscosity equation was also modified using experimental data. This model considerably increased the TKE values for both moderately high and very high FST intensities showing that it functions as it was intended. While TKE perfectly matched with the experimental data sets (within 1–2%) for moderately high initial FST intensity, it still did not yield very good results for very high initial FST intensity. Under very high FST intensity TKE does not match data very well near the wall. The Stanton number and skin friction coefficient increased (about 30%) as expected since the new diffusion model increases TKE levels ner the wall. At this point it should be mentioned that standard k-ε model is a high Reynold number turbulence model which use wall functions near the wall. In earlier studies the new diffusion model was applied to a low Reynold number model in TEXSTAN code. In the continuing studies high Reynolds number k-ε model in FLUENT will be modified to create a low Reynolds number model via UDFs in order to get better predictions of the Stanton number and skin friction coefficients by use of damping function fμ and adjusting the value of turbulent Prandtl number. This study reports on progress in overall goal of implementing a new TKE diffusion model in FLUENT code.

Model turbulent kinetic energy profiles expected during drag reduction are synthesized from similarity arguments. At low drag reduction, it is postulated that the radial transport of turbulent kinetic energy and of axial momentum are analogous. Thus, in nondimensional terms, the maximum kinetic energy during drag reduction must exceed the Newtonian maximum kinetic energy by an amount proportional to the ’’effective slip,’’ which latter is the amount whereby the mean velocity during drag reduction exceeds that during Newtonian turbulent flow. At maximum drag reduction, the turbulent kinetic energy profile is related to the Newtonian profile by means of the respective mixing length constants, Xm and Xn; in the former case, the maximum turbulent kinetic energy is predicted to be Xn/Xm = 4.7 times the Newtonian. The model profiles are in accord with the (few) available experimental measurements of turbulence during drag reduction.