Boundary-Layer Meteorology最新文献

Large-eddy simulations are used to evaluate mean profile similarity in the convective boundary layer (CBL). Particular care is taken regarding the grid sensitivity of the profiles and the mitigation of inertial oscillations in the simulation spin-up. The nondimensional gradients (phi ) for wind speed and air temperature generally align with Monin–Obukhov similarity across cases but have a steeper slope than predicted within each profile. The same trend has been noted in several other recent studies. The Businger-Dyer relations are modified here with an exponential cutoff term to account for the decay in (phi ) to first-order approximation, yielding improved similarity from approximately 0.05(z_i) to above 0.3(z_i), where (z_i) is the CBL depth. The necessity for the exponential correction is attributed to an extended transition from surface scaling to zero gradient in the mixed layer, where the departure from Monin–Obukhov similarity may be negligible at the surface but becomes substantial well below the conventional surface layer height of 0.1(z_i).

The backdrop for this study is a knowledge gap about how turbulence anisotropy relates to the dissimilar transport of momentum and scalars. We use single-level measurements of turbulence over an alpine glacier for exploring the dissimilar transport of momentum, heat, and moisture in stably stratified katabatic flows. Our study is motivated by the need of addressing their flux dissimilarity from a fresh perspective of anisotropic motions of turbulence. Its objective is to promote new understanding of boundary-layer turbulence anisotropy as one possible factor in dissimilar behaviours between momentum and scalar transport over a sloping terrain. Specifically, the momentum–heat flux correlation (({R}_{{F}_{uT}})) and the heat–moisture flux correlation (({R}_{{F}_{Tq}})) coefficients vary across three different bulk states of kinetic anisotropy. Those states, identified using the barycentric Lumley map, suggest the predominance of two-component turbulence (being axisymmetric or not) and miscellaneous turbulence (whose topological shape is less salient). Miscellaneous turbulence typically bears a higher degree of the flux similarity between momentum and heat (i.e., ({R}_{{F}_{uT}}) > 0.6) but a lower degree of that between heat and moisture (i.e., (left|{R}_{{F}_{Tq}}right|) < 0.7). The multi-resolution decomposition technique is then applied to identify larger-scale eddies of two-component topology, intermediate-scale eddies of oblate topology, and smaller-scale eddies of isotropic topology. Further analysis shows that an explicit change in eddy scale-wise topology is correlated not only with variations in ({R}_{{F}_{uT}}) and (left|{R}_{{F}_{Tq}}right|) but with the dissimilar transport of momentum and scalars, so explaining a deviation from the Reynolds and the Lewis analogies in fluid mechanics.

Studies on the shortwave spectrum, namely short-gravity, gravity-capillary, and parasitic-capillary waves, reveal that spectrum representation may modify the estimate of momentum transport at the air-sea interface. However, in numerical simulations, the shortwave spectra are usually approximated by simplified formulations. The effect of three shortwave spectrum formulations on the momentum balance at the air-sea interface was quantitatively evaluated for light to high wind speeds and fully developed seas. In the simulations, the spectra considered were: (i) obtained by an extrapolated function, (ii) dependent on the wave age derived from the observations, and (iii) from the solution of the energy balance equation. Considering computational time, the second was the fastest. while the first and third the computational time increased, respectively, by approximately 2–7% and 15–30%, depending on the wind speed. Concerning the observations, the mean square slope, the coupling parameter, and the drag coefficient, the second and third formulations showed better agreement, while the first one showed a large discrepancy. The results highlighted the importance of shortwave formulations in the analysis of the interaction between wind and wave.

In the last decades the energy-balance-closure problem has been thoroughly investigated from different angles, resulting in approaches to reduce but not completely close the surface energy balance gap. Energy transport through secondary circulations has been identified as a major cause of the remaining energy imbalance, as it is not captured by eddy covariance measurements and can only be measured additionally with great effort. Several models have already been developed to close the energy balance gap that account for factors affecting the magnitude of the energy transport by secondary circulations. However, to our knowledge, there is currently no model that accounts for thermal surface heterogeneity and that can predict the transport of both sensible and latent energy. Using a machine-learning approach, we developed a new model of energy transport by secondary circulations based on a large data set of idealized large-eddy simulations covering a wide range of unstable atmospheric conditions and surface-heterogeneity scales. In this paper, we present the development of the model and show first results of the application on more realistic LES data and field measurements from the CHEESEHEAD19 project to get an impression of the performance of the model and how the application can be implemented on field measurements. A strength of the model is that it can be applied without additional measurements and, thus, can retroactively be applied to other eddy covariance measurements to model energy transport through secondary circulations. Our work provides a promising mechanistic energy balance closure approach to 30-min flux measurements.

The present paper shows that local similarity theories, proposed for the strongly-stratified boundary layers, can be derived as invariant solutions defined under the Lie-group theory. A system truncated to the mean momentum and buoyancy equations is considered for this purpose. The study further suggests how similarity functions for the mean profiles are determined from the vertical fluxes, with a potential dependence on a measure of the anisotropy of the system. A time scale that is likely to characterize the transiency of a system is also identified as a non-dimensionalization factor.

Taylor’s Frozen Turbulence Hypothesis (TH) is a critical assumption in turbulent theory and practice which allows time series of point measurements of turbulent variables to be translated to the spatial domain via the mean wind. Using a 3D array of fibre-optic distributed temperature sensing in the atmospheric surface layer over an idealized desert site we present a systematic investigation of the applicability of Taylor’s Hypothesis to atmospheric surface layer flows over a variety of conditions: unstable, near-neutral, and stable atmospheric stabilities; and multiple measurement heights between the surface and 3 m above ground level. Both spatially integrated and spatially scale-dependent eddy velocities are investigated by means of time-lagged streamwise two-point correlations and compared to the mean Eulerian wind. We find that eddies travel slower than predicted by TH at small spatial separations, as predicted by TH at separations typically between 5 and 16 m, and faster than predicted by TH at larger spatial separations. In unstable atmospheric conditions the spatial separation at which eddy velocity is larger than Eulerian velocity decreases with height.

Wildland fire–atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in the measured temperature and the turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath a forest canopy. We use temperature and velocity measurements from tower-mounted sonic anemometers at multiple heights. Patterns in the wavelet-based energy density of the measured temperature plotted on a time–frequency plane indicate the presence of fire-modulated ramp–cliff structures in the low-to-mid-frequency band (0.01–0.33 Hz), with mean ramp durations approximately 20% shorter and ramp slopes that are an order of magnitude higher compared to no-fire conditions. We then investigate heat- and momentum-flux events near the canopy top through a cross-wavelet coherence analysis. Briefly before the fire-front arrives at the tower base, momentum-flux events are relatively suppressed and turbulent fluxes are chiefly thermally-driven near the canopy top, owing to the tilting of the flame in the direction of the wind. Fire-induced heat-flux events comprising warm updrafts and cool downdrafts are coherent down to periods of a second, whereas ambient heat-flux events operate mainly at higher periods (above 17 s). Later, when the strongest temperature fluctuations are recorded near the surface, fire-induced heat-flux events occur intermittently at shorter scales and cool sweeps start being seen for periods ranging from 8 to 35 s near the canopy top, suggesting a diminishing influence of the flame and increasing background atmospheric variability thereat. The improved understanding of the characteristic time scales associated with fire-induced turbulence features, as the fire-front evolves, will help develop more reliable fire behaviour and scalar transport models.

This study investigates flow variability at different scales and its effects on the dispersion of a passive scalar in a regular street network by means of direct numerical simulations (DNS), and compared to wind tunnel (WT) measurements. Specific scientific questions addressed include: (i) sources of variability in the flow at street-network scale, (ii) the effects of such variability on both puff and continuous localised releases, (iii) additional sources of uncertainty related to experimental setups and their consequences. The street network modelled here consists of an array of rectangular buildings arranged uniformly and with periodic horizontal boundary conditions. The flow is driven by a body force at an angle of 45 degrees relative to the streets in the network. Sources of passive scalars were located near ground level at three different types of locations: a short street, an intersection between streets and a long street. Flow variability is documented at different scales: small-scale intra-street variations linked with local flow topology; inter-street flow structure differences; street-network scale variability; and larger-scale spatial variations associated with above-canopy structures. Flow statistics and the dispersion behaviour of both continuous and short-duration (puff) releases of a passive scalar in the street network are analysed and compared with the results of wind-tunnel measurements. Results agree well with the experimental data for a source location in an intersection, especially for flow statistics and mean concentration profiles for continuous releases. Larger differences arise in the comparisons of puff releases. These differences are quantified by computing several puff parameters including time of arrival, travel time, rise and decay times. Reasons for the differences are discussed in relation to the underlying flow variability identified, differences between the DNS and WT setup and uncertainties in the experimental setup. Implications for the propagation of short-duration releases in real urban areas are discussed in the light of our findings. In particular, it is highlighted that in modelling singular events such as accidental releases, characterising uncertainties is more meaningful and useful than computing ensemble averages.

A single-column turbulence model for stratified atmospheric boundary layer (ABL), which solves the transport equations of turbulence probability density function (PDF) using a Lagrangian stochastic modeling (LSM) approach, is proposed in this study. This study adopts previously developed stochastic differential equations (SDEs) for particle velocity and temperature and extends the LSM to simulate inhomogeneous turbulence. The proposed LSM is tested for its ability to fully simulate statistics of inhomogeneous stratified turbulence. In the model, particles evolve by SDEs, and turbulence statistics are calculated by averaging the properties of particles. The model provides a full representation of turbulence PDF and simulates turbulent transport without any modeling assumption. The model performance is evaluated against large-eddy simulation (LES) results in the simulations of convective and stable ABL cases. For the convective ABL, LSM realistically simulates the entrainment process with the temperature and heat flux profiles that closely match with LES. The joint PDF simulated by LSM reproduces a curved and highly skewed shape, and some distinct features, like the asymmetric distribution of vertical velocity and the separation of the PDF in the entrainment zone, are simulated. LSM also reproduces the entrainment enhancement by wind shear in the simulation of sheared convective ABL. The LSM simulation of stable ABL predicts realistic turbulence intensity and mean field profiles, where Gaussian-like PDFs are simulated both in LSM and LES.

Abstract

Recent studies have highlighted the importance of accurate meteorological conditions for urban transport and dispersion calculations. In this work, we present a novel scheme to compute the meteorological input in the Quick Urban & Industrial Complex (QUIC) diagnostic urban wind solver to improve the characterization of upstream wind veer and shear in the Atmospheric Boundary Layer (ABL). The new formulation is based on a coupled set of Ordinary Differential Equations (ODEs) derived from the Reynolds Averaged Navier–Stokes (RANS) equations, and is fast to compute. Building upon recent progress in modeling the idealized ABL, we include effects from surface roughness, turbulent stress, Coriolis force, buoyancy and baroclinicity. We verify the performance of the new scheme with canonical Large Eddy Simulation (LES) tests with the GPU-accelerated FastEddy solver in neutral, stable, unstable and baroclinic conditions with different surface roughness. Furthermore, we evaluate QUIC calculations with and without the new inflow scheme with real data from the Urban Threat Dispersion (UTD) field experiment, which includes Lidar-based wind measurements as well as concentration observations from multiple outdoor releases of a non-reactive tracer in downtown New York City. Compared to previous inflow capabilities that were limited to a constant wind direction with height, we show that the new scheme can model wind veer in the ABL and enhance the prediction of the surface cross-isobaric angle, improving evaluation statistics of simulated concentrations paired in time and space with UTD measurements.