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Abstract: In this study we introduce a novel extension of an existing Lagrangian particle dispersion model for application over urban areas by explicitly taking into account the urban canopy layer. As commonly done, the original model uses the zero-plane displacement as a lower boundary condition, while the extension reaches to the ground. To achieve this, spatially-averaged parametrizations of flow and turbulence characteristics are created by fitting functions to observational and numerical data. The extended model is verified with respect to basic model assumptions (well-mixed condition) and its behaviour is investigated for unstable/neutral/stable atmospheric stabilities. A sensitivity study shows that the newly introduced model parameters characterizing the canopy turbulence impact the model output less than previously existing model parameters. Comparing concentration predictions to the Basel Urban Boundary Layer Experiment—where concentrations were measured near roof level—shows that the modified model performs slightly better than the original model. More importantly, the extended model can also be used to explicitly treat surface sources (traffic) and assess concentrations within the urban canopy and near the surface (pedestrian level). The small improvement with respect to roof level concentrations suggests that the parametrized canopy profiles for flow and turbulence characteristics realistically represent the dispersion environment on average. PubDate: 2022-10-01

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Abstract: Large-eddy simulations (LES) are conducted to study the transport of momentum and passive scalar within and over a real urban canopy in the City of Boston, USA. This urban canopy is characterized by complex building layouts, densities and orientations with high-rise buildings. Special attention is given to the magnitude, variability and structure of dispersive momentum and scalar fluxes and their relative importance to turbulent momentum and scalar fluxes. We first evaluate the LES model by comparing the simulated flow statistics over an urban-like canopy to data reported in previous studies. In simulations over the considered real urban canopy, we observe that the dispersive momentum and scalar fluxes can be important beyond 2–5 times the mean building height, which is a commonly used definition for the urban roughness sublayer height. Above the mean building height where the dispersive fluxes become weakly dependent on the grid spacing, the dispersive momentum flux contributes about 10–15% to the sum of turbulent and dispersive momentum fluxes and does not decrease monotonically with increasing height. The dispersive momentum and scalar fluxes are sensitive to the time and spatial averaging. We further find that the constituents of dispersive fluxes are spatially heterogeneous and enhanced by the presence of high-rise buildings. This work suggests the need to parameterize both turbulent and dispersive fluxes over real urban canopies in mesoscale and large-scale models. PubDate: 2022-10-01

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Abstract: Lagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations used in these models were developed for coarse resolution grids, hence, when moving to the kilometre-scale the validity of these descriptions should be questioned. Here, we analyze the influence of the turbulence parameterization employed in the LPDM FLEXPART-COSMO model. Comparisons of the turbulence kinetic energy between the turbulence schemes of FLEXPART-COSMO and the underlying Eulerian model COSMO suggest that the dispersion in FLEXPART-COSMO suffers from a double-counting of turbulent elements when run at a high resolution of \(1 \times 1 \,\hbox {km}^2\) . Such turbulent elements are represented in both COSMO, by the resolved grid-scale winds, and FLEXPART, by its stochastic parameterizations. Therefore, we developed a new parametrization for the variations of the winds and the Lagrangian time scales in FLEXPART in order to harmonize the amount of turbulence present in both models. In a case study for a power plant plume, the new scheme results in improved plume representation when compared with in situ flight observations and with a tracer transported in COSMO. Further in-depth validation of the LPDM against methane observations at a tall tower site in Switzerland shows that the model’s ability to predict the observed tracer variability and concentration at different heights above ground is considerably enhanced using the updated turbulence description. The high-resolution simulations result in a more realistic and pronounced diurnal cycle of the tracer concentration peaks and overall improved correlation with observations when compared to previously used coarser resolution simulations (at 7 km \(\times \) 7 km). Our results indicate that the stochastic turbulence schemes of LPDMs, developed in the past for coarse resolution models, should be revisited to include a resolution dependency and resolve only the part of the turbulence spectrum that is a subgrid process at each different mesh size. Although our new scheme is specific to COSMO simulations at \(1 \times 1 \,\hbox {km}^2\) resolution, the methodology for deriving the scheme can easily be applied to different resolutions and other regional models. PubDate: 2022-10-01

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Abstract: Within the roughness sublayer (RSL) of dense urban canopies composed of uniformly distributed cuboids, the time and planar-averaged mean velocity profile exhibits an approximate exponential shape characterized by a depth-independent attenuation coefficient a. A formulation that links a to the zero-plane displacement d and aerodynamic roughness length \(z_{\mathrm{om}}\) is proposed using a one-dimensional momentum balance between the background mean horizontal pressure gradient, vertical gradients of total stresses, and the drag force. Dispersive effects on a within the urban RSL are then explored using large-eddy simulations (LESs) that vary independently the planar ( \(\lambda _{\mathrm{p}}\) ) and frontal ( \(\lambda _{\mathrm{f}}\) ) densities of the cuboids. The LES results are used to compute d and \(z_{\mathrm{om}}\) by fitting a log-profile to the mean velocity above the canopy. Within the canopy, the LES results are also used to estimate (i) a by fitting an exponential profile to the computed time and planar-averaged velocity, (ii) profiles of drag coefficients, and (iii) turbulent as well as dispersive stresses. The LES results demonstrate that dispersive stresses can be commensurate with turbulent stresses in magnitude and act in the same direction. Moreover, dispersive transport, determined from vertical gradients of dispersive stresses, is some 25–75% of turbulent stress gradients. These dispersive effects impact a (and thus d and \(z_{\mathrm{om}}\) ) via two mechanisms: (i) reducing the effective adjustment length scale that leads to an increase in a and (ii) increasing the effective mixing length that leads to a reduction in a across a wide range of \(\lambda _{\mathrm{f}}\) and \(\lambda _{\mathrm{p}}\) . These two effects are shown to be partly compensatory giving rise to an apparent constant a with respect to height inside the canopy. The effects of mean recirculation and the usage of the drag force centroid method to estimate d are discussed. The analysis also evaluates the consequences of a finite roughness sublayer thickness extending above the canopy on the derived expressions. PubDate: 2022-10-01

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Abstract: The surface roughness lengths for momentum, \(z_{0u}\) , and heat, \(z_{0T}\) , are key parameters for modeling the momentum, mass and energy exchange between underlying surface and the atmosphere. Established approach predicts the dependency of the ratio \(C=\ln \left( z_{0u}/z_{0T}\right) \) on the roughness Reynolds number \({Re}_s\) , confirmed earlier for a number of surface types. This paper for the first time evaluates such a relationship based on the eddy covariance data collected on a boreal fen dominated by moss and sedge vegetation. It is shown that the best parameterization is provided by two dependencies: \(C=0.359~{Re}_s^{1/4}+0.711\) and \(C=0.032~{Re}_s^{1/2}+1.706\) . The significant sensitivity of these dependencies to longwave emissivity was revealed. We generalized this issue to linear analysis of parameter uncertainties in the MOST formulas. This analysis suggested, that the surface temperature errors contribute more to C evaluation compared to heat flux uncertainties, the former being affected also by mismatch between footprints of radiation and eddy covariance measurements. The practical solutions to minimize the issue are proposed. Comparison of our measurement data and obtained dependencies for C with known functions \(C(Re_s)\) for other types of surface from literature demonstrated that grassland and cropland surface types are the closest to fen in terms of \(z_{0u}/z_{0T}\) . PubDate: 2022-09-21

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Abstract: Observations of turbulent heat fluxes over inland water bodies are scarce despite being critical to adequate lake parametrization for numerical weather forecast and climate models. Scintillometry has allowed for the regional (~ km2) estimation of turbulent heat fluxes, but few studies have assessed its performance over water. We compare scintillometry-derived turbulent heat fluxes over an 85-km2 dimictic boreal hydropower reservoir in eastern Canada (50.69° N, 63.24° W) with data from a raft-based eddy-covariance system. To the best of our knowledge, this is one of the first studies to quantify evaporation over an inland water body using a set of optical and microwave scintillometers. The scintillometer beam path extended 1.7 km over a section of the reservoir with depths of up to 100 m, from 14 August to 9 October 2019. Forty-nine days of data were retained. This study quantifies the impact of atmospheric stability on the derived fluxes and explores the use of temperature differences at the water–air interface from a point close to the centre of the scintillometer beam to properly estimate the direction of the sensible heat flux. The scintillometry approaches were well correlated with the eddy-covariance estimations for sensible heat fluxes (R2 up to 0.86, 32% bias), while the agreement decreased for latent heat fluxes (R2 up to 0.59, 69% bias). The scintillometer measured much larger latent heat fluxes than the eddy-covariance set-up. These results may be due to the larger footprint of the scintillometers capturing greater heterogeneity in the fluxes. PubDate: 2022-09-15

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Abstract: We characterize the turbulent flow, using direct numerical simulations (DNS), within a closed channel between two parallel walls with a canopy of constant areal density profile on the lower wall. The canopy is modelled using different formulations of the Forchheimer drag, and the characteristic properties of the turbulent flows are compared. In particular, we examine the influence of the added drag on the mean profiles of the flow and the balance equations of the turbulent kinetic energy. We find that the different formulations of the drag strongly affect the mean and the turbulent profiles close to the canopy. We also observe the changes in the local anisotropy of the turbulent flow in the presence of the canopy. We find that there is an equal transfer of energy from the streamwise component to both the transverse components outside the canopy by the pressure and velocity-gradient correlation; inside the canopy, this correlation removes energy from both the streamwise and the wall-normal fluctuations and injects into the spanwise component. As a result, the energy content of the spanwise fluctuations is comparable to that of the streamwise components inside the canopy. Inside the canopy, we observe that the turbulent transport of Reynolds stresses acts as an important source of turbulent kinetic energy. The pressure-fluctuation transport plays a significant role inside the canopy close to the wall and is comparable to turbulent transport. PubDate: 2022-09-14

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Abstract: Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), \(z/L\) . However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes. PubDate: 2022-09-13

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Abstract: Tornados are a major hazard in many regions around the world and as such it is necessary to analyze them. However, such analyses require accurately tracking them first. Currently, there are gaps in the available vortex detection methods when processing a wind-field dataset to locate a series of points that are identifiable as the tornado centreline. This study proposes a novel solution that corrects for deficiencies in previous attempts to identify vortex centres when applied to tornado wind-fields, which would have otherwise led to identifying merely the region of the vortex, several potential centres requiring post-processing, or erroneously approximating the tornado centre. Additionally, this method combines the efficiency required to process large datasets of temporal and spatial wind velocity vector distributions with the accuracy needed to reliably calculate a specific line as a tornado centre. This method is compared to five other approaches commonly used for vortex identification in order to assess: (a) how accurately they identify the centre region, (b) how they handle extraneous vortices that are not of interest, and (c) their computational efficiency in processing a wind-field dataset. With the proposed method, it would be possible to plot a tornado path from formation to dissipation and perform analyses to understand the vortex characteristics with respect to this path without requiring extensive user-intervention. PubDate: 2022-09-09

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Abstract: Optimal disturbances of a turbulent stably stratified plane Couette flow in a wide range of Reynolds and Richardson numbers are studied. These disturbances are computed based on a simplified system of equations in which turbulent Reynolds stresses and heat fluxes are approximated by isotropic viscosity and diffusivity with the coefficients obtained from results of direct numerical simulation. Three types of disturbances are considered: large-scale streamwise-elongated rolls converting into streamwise streaks; large-scale vortical structures, inclined in the vertical plane, changing the inclination to the opposite in process of their evolution; near-wall rolls converting into streaks. Large-scale rolls and streaks predominate at neutral or weakly stable stratification while the inclined structures begin to dominate at moderately stable stratification. Near-wall rolls and streaks appear at any stratification and their spanwise size in wall length units does not depend on the values of Reynolds and Richardson numbers. It is shown that the development of inclined optimal disturbances is due to the coupled action of the lift-up effect and the inviscid Orr mechanism. The energetics of the optimal disturbances is discussed. It is shown that inclined optimal disturbances dissipate rapidly after reaching maximum energy amplification. PubDate: 2022-09-08

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Abstract: Time integration of the unsteady Reynolds-averaged Navier–Stokes (URANS) equations is the principal approach used in numerical weather prediction. This approach represents a balanced compromise between accuracy and computational cost. The URANS equations require the flow to be decomposed into an ensemble mean and excursions that are presumed to be entirely related to turbulence, thereby enabling conventional closure schemes to be used to describe their statistics. Implicit in such a decomposition is the assumption of a spectral gap between the unsteadiness in the mean flow and the scales of turbulence. Modelling challenges arise when some of the unresolved fluctuations are related to non-turbulent, structured motions that can also blur the spectral gap and render conventional closure schemes ineffective. This work seeks to clarify modelling issues that occur when unresolved fluctuations include submesoscale motions and persistent secondary circulations related to surface heterogeneities. Because submeso motions and persistent secondary circulations are not random, new theoretical tactics are discussed to represent their effects on URANS transport. By reviewing the interpretation of fluctuating terms in the URANS equations, we suggest the use of large-eddy simulations, direct numerical simulations and field measurements to guide the development of closure schemes that explicitly include fluxes due to submeso motions and persistent secondary circulations. PubDate: 2022-09-05

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Abstract: The uncrewed airborne measurement platform MASC-3 (Multi-Purpose Airborne Sensor Carrier) is used to measure the influence of a forested escarpment with differing leaf area indices (LAI) onto the wind field. Data from flight legs between 30 and 200 m above ground with uphill (westerly) wind during summer (July–September) and winter (October–March) seasons between 2018 and 2021 are analyzed. Compared with a low value of LAI, it is found that the mean wind speed acceleration is stronger for a high values of LAI, and the turbulence is enhanced in the lee of the trees in the lowest 20–60 m above ground. During summer with a high LAI, the inclination angle is more clearly defined into an upward motion above the slope and downward motion above the plateau. The results of the airborne dataset fits well into the theoretical and analytical models established in the 1970s and 1980s. PubDate: 2022-09-01

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Abstract: Fields of Lagrangian ( \(T^{L}\) ) and Eulerian ( \(T^{E}\) ) time scales of the turbulence within a regular array of two-dimensional obstacles of unit aspect ratio have been determined by means of a water-channel experiment reproducing the atmospheric boundary layer in neutral conditions. It has been found that there is a strong spatial inhomogeneity both of the scales and of their ratio, \(\beta = T^{L} /T^{E}\) . The results can provide useful information on numerical modelling of tracer dispersion in urban areas. PubDate: 2022-09-01

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Abstract: The magnitude of the entrainment buoyancy flux, and hence the growth rate of the convective boundary layer, does not increase monotonically with wind shear. Explanations for this have previously been based on wind-shear effects on the turbulence kinetic energy. By distinguishing between turbulent and non-turbulent regions, we provide an alternative explanation based on two competing wind-shear effects: the initial decrease in the correlation between buoyancy and vertical velocity fluctuations, and the increase in the turbulent area fraction. The former is determined by the change in the dominant forcing; without wind shear, buoyancy fluctuations drive vertical velocity fluctuations and the two are thus highly correlated; with wind shear, vertical velocity fluctuations are partly determined by horizontal velocity fluctuations via the transfer of kinetic energy through the pressure–strain correlation, thus reducing their correlation with the buoyancy field. The increasing turbulent area fraction, on the other hand, is determined by the increasing shear production of turbulence kinetic energy inside the entrainment zone. We also show that the dependence of these conditional statistics on the boundary-layer depth and on the magnitude of the wind shear can be captured by a single non-dimensional variable, which can be interpreted as an entrainment-zone Froude number. PubDate: 2022-09-01

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Abstract: The theoretical foundations of the exponential and power-law analytical formulations for the size–frequency and intensity–frequency distributions of the convective vortices, including dust devils, are re-examined. Jaynes’ general statistical arguments based on Shannon’s entropy maximum principle leading to an exponential distribution are supplemented by Rényi’s maximum entropy principle which is shown to lead to a power-law distribution. In both cases, a key ingredient of the theory is the a priori knowledge of a first finite moment of the distribution. Applications to statistics of convective vortices, including dust devils, on Earth and Mars are discussed. The existence of a finite expectation value of the vortex diameter related to the absolute value of the Obukhov length scale in the atmospheric boundary layer allows a quantitative explanation of a burst of convective vortex activity observed at the InSight landing site in northern autumn on Mars. PubDate: 2022-09-01

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Abstract: This study expands the study conducted by Zhang et al. (Boundary-Layer Meteorol, 2022, Vol. 183, 97–123) to elucidate turbulent structures within an ideal two-dimensional street canyon, and determine their contribution to pollutant removal. In response to the limitations of the reference study wherein spanwise turbulent structures were not elucidated, an advanced technique called spectral proper orthogonal decomposition (SPOD) with two-dimensional Fourier transformation was applied in the current study. This approach combined proper orthogonal decomposition along the spatial streamwise and vertical directions and Fourier decomposition along the time and spatial spanwise direction. Using this technique, various fluctuation patterns were reasonably decomposed and visualised according to their scales. In addition, their intensities and contributions to pollutant removal were quantitatively analysed using the SPOD spectrum and cospectra. The time scales of most energetic modes were found to be proportional to their spanwise length scales, regardless of their scales and flow mechanisms. The ranges of the spanwise wavenumber and frequency, at which pollutant removal events occurred at the roof level, were specified. These ranges coincided with those of small-scale structures caused by Kelvin–Helmholtz instabilities. Further complex analysis of the correlation between large- and small-scale structures showed that large-scale structures have a high possibility of indirectly enhancing or weakening pollutant removal by amplifying or suppressing small-scale structures. This occurred stochastically along both time and spanwise directions. Quantitatively, the amplitude of small-scale structures was amplified or suppressed by 13–16% on average by high- or low-momentum fluids. PubDate: 2022-08-27

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Abstract: Although the fidelity of computational-fluid-dynamics (CFD) models for the study of flow in plant canopies has significantly increased over the past decades, the inability to exactly measure the canopy structure and its material and physiological properties introduces a degree of uncertainty in model results that is often difficult to quantify. The present work addresses this problem by proposing a Bayesian uncertainty quantification (UQ) framework for evaluating the impact of uncertain canopy geometry on selected microscale flow statistics (the quantities of interest, QoIs, of the problem). The framework links available in-situ measurements of flow statistics to the uncertainty stemming from foliage spatial distribution and orientation, as well as from the aerodynamic plant response. The uncertainty is first characterized via a Markov chain Monte Carlo procedure, and then propagated to the QoIs through the Monte Carlo sampling method, which returns mean profiles and two-standard-deviation-(2SD-)intervals for the QoIs. The UQ framework relies on a one-dimensional CFD solver to simulate the flow over the Duke Forest, located near Durham, North Carolina, USA. Model results are compared against a standard deterministic solution in terms of mean velocity, Reynolds stress and turbulence-kinetic-energy profiles, as well as canopy aerodynamic parameters. For the considered QoIs, it is found that the 2SD-intervals obtained with the UQ procedure cover \(80\%\) of the experimental intervals, whereas the deterministic solution overlaps with only \(47 \%\) of them. Overall, this study highlights the potential of UQ to advance CFD capabilities for predicting exchange processes between realistic plant canopies and the surrounding atmosphere. PubDate: 2022-07-29

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Abstract: Turbulent data from three sites are utilized to analyze the characteristic features of the Eulerian autocorrelation function (EAF) of horizontal (longitudinal and lateral) wind components and temperature under different regimes of wind speed and near-surface atmospheric stability. It is shown that classical formulations do not adequately describe the observed EAF behaviour and are unable to capture the peak of the significant negative observed lobe. These formulations are modified by introducing a phase angle \(\alpha\) to make them consistent with the observations. The modified formulations are shown to better characterize the behaviour of the EAF curve and its absolute value of significant negative lobe ( \(\left {R}_{Min}\right \) ) for both low and moderate wind conditions for all three datasets. Further, a new parametrization for the meandering parameter m is proposed in terms of the observed value of \(\left {R}_{Min}\right \) without using any formulations for the EAF. It is found that the majority of low and moderate wind data belong to the significant meandering range, although the extent of meandering is found to be relatively more pronounced at low wind speeds as compared to moderate wind speeds. The occurrence of meandering (low-frequency horizontal wind oscillations) is found to be independent of stability, topography, and geographical location. PubDate: 2022-07-01 DOI: 10.1007/s10546-022-00715-8