On the periodicity of atmospheric von Kármán vortex streets

For over 100 years, laboratory-scale von Kármán vortex streets (VKVSs) have been one of the most studied phenomena within the field of fluid dynamics. During this period, countless publications have highlighted a number of interesting underpinnings of VKVSs; nevertheless, a universal equation for the vortex shedding frequency ( \(N\) ) has yet to be identified. In this study, we have investigated \(N\) for mesoscale atmospheric VKVSs and some of its dependencies through the use of realistic numerical simulations. We find that vortex shedding frequency associated with mountainous islands, generally demonstrates an inverse relationship to cross-stream obstacle length ( \(L\) ) at the thermal inversion height of the atmospheric boundary layer. As a secondary motive, we attempt to quantify the relationship between \(N\) and \(L\) for atmospheric VKVSs in the context of the popular Strouhal number ( \(Sr\) )–Reynolds number ( \(Re\) ) similarity theory developed through laboratory experimentation. By employing numerical simulation to document the \(Sr{-}Re\) relationship of mesoscale atmospheric VKVSs (i.e., in the extremely high \(Re\) regime) we present insight into an extended regime of the similarity theory which has been neglected in the past. In essence, we observe mesoscale VKVSs demonstrating a consistent \(Sr\) range of 0.15–0.22 while varying \(L\) (i.e, effectively varying \(Re\) ).     

On the effective hydraulic conductivity and macrodispersivity for density-dependent groundwater flow

In this paper, semi-analytical expressions of the effective hydraulic conductivity ( $K^{E})$ and macrodispersivity ( $\alpha ^{E})$ for 3D steady-state density-dependent groundwater flow are derived using a stationary spectral method. Based on the derived expressions, we present the dependence of $K^{E}$ and $\alpha ^{E}$ on the density of fluid under different dispersivity and spatial correlation scale of hydraulic conductivity. The results show that the horizontal $K^{E}$ and $\alpha ^{E}$ are not affected by density-induced flow. However, due to gravitational instability of the fluid induced by density contrasts, both vertical $K^{E}$ and $\alpha ^{E}$ are found to be reduced slightly when the density factor ( $\gamma $ ) is less than 0.01, whereas significant decreases occur when $\gamma $ exceeds 0.01. Of note, the variation of $K^{E}$ and $\alpha ^{E}$ is more significant when local dispersivity is small and the correlation scale of hydraulic conductivity is large.     

Data depth for the uniform distribution

Given a set $X$ of $k$ points and a point $z$ in the $n$ -dimensional euclidean space, the Tukey depth of $z$ with respect to $X$ , is defined as $m/k$ , where $m$ is the minimum integer such that $z$ is not in the convex hull of some set of $k-m$ points of $X$ . If $z$ belongs to the closed region $B$ delimited by an ellipsoid, define the continuous depth of $z$ with respect to $B$ as the quotient $V(z)/\text{ Vol }(B)$ , where $V(z)$ is the minimum volume of the intersection of $B$ with the halfspaces defined by any hyperplane passing through $z$ , and $\text{ Vol }(B)$ is the volume of $B$ . We consider $z$ a random variable and prove that, if $z$ is uniformly distributed in $B$ , the continuous depth of $z$ with respect to $B$ has expected value $1/2^{n+1}$ . This result implies that if $z$ and $X$ are uniformly distributed in $B$ , the expected value of Tukey depth of $z$ with respect to $X$ converges to $1/2^{n+1}$ as the number of points $k$ goes to infinity. These findings have applications in ecology, namely within the niche theory, where it is useful to explore and characterize the distribution of points inside species niche.     

Passive scalar roughness lengths for atmospheric boundary layer flow over complex, fractal topographies

When modeling atmospheric boundary layer flow over rough landscapes, surface fluxes of flow quantities (momentum, temperature, etc.) can be described with equilibrium logarithmic law expressions, all of which require specification of a roughness length that is, physically, the elevation at which the flow quantity equals its surface value. In high Reynolds number flows, such as the atmospheric boundary layer, inertial forces associated with turbulent eddy motions are responsible for surface momentum fluxes (form, or pressure drag). Surface scalar fluxes, on the other hand, occur exclusively via diffusion in the immediate vicinity of the topography—the interfacial region—before being advected by turbulent eddy motions into the bulk of the flow. Owing to this difference in surface transfer mechanism, the passive scalar roughness length, $z_{0S}$ , is known to be less than the momentum roughness length, $z_0$ . In this work, classical relations are used to specify $z_{0S}$ during large-eddy simulation of atmospheric boundary layer flow over aerodynamically rough, synthetic, fractal topographies which exhibit power-law height energy spectrum, $E_h (k) \sim k^{\beta _s}$ , where $\beta _s$ is a (predefined) spectral exponent. These topographies are convenient since they resemble natural landscapes and $\beta _s$ can be varied to change the topography’s aerodynamic roughness (the study considers a suite of topographies with $-2.4 \le \beta _s \le -1.2$ , where $-2.4$ and $-1.2$ are the “most smooth” and “most rough” cases, respectively, corresponding with roughness Reynolds number, $Re_0 \approx 10$ and $300$ ). It is often assumed that $z_{0S}/z_{0} \approx 10^{-1}$ for all $Re_0$ . But results from this work show that the roughness length ratio, $z_{0S}/z_{0}$ , depends strongly on $Re_0$ , ranging between $10^{-3}$ and $10^{-1}$ .     

Investigating the complex relationship between in situ Southern Ocean pCO_{2} and its ocean physics and biogeochemical drivers using a nonparametric regression approach

The objective in this paper is to investigate the use of a non-parametric approach to model the relationship between oceanic carbon dioxide \((pCO_2)\) and a range of ocean physics and biogeochemical in situ variables in the Southern Ocean, which influence its in situ variability. The need for this stems from the need to obtain reliable estimates of carbon dioxide concentrations in the Southern Ocean which plays an important role in the global carbon flux cycle. The main challenge involved in this objective is the spatial limitation and seasonal bias of the in situ data. Moreover, studies have also reported that the relationship between \(pCO_2\) and its drivers is complex. As such, in this paper, we use the non-parametric kernel regression approach since it is able to accurately capture the complex relationships between the response and predictor variables. In this analysis we use the in situ data obtained from the SANAE49 return leg journey between Antarctic to Cape Town. To the best of our knowledge, this is the first time this data set has been subjected to such analysis. The model variants were developed on a training data subset, and the ‘goodness’ of the models were assessed on an “unseen” test data subset. Results indicate that the nonparametric approach consistently captures the relationship more accurately in terms of mean square error, root mean square error and mean absolute error, over a standard parametric approach (multiple linear regression). These results provide a platform for using the developed nonparametric regression model based on in situ measurements to predict \(pCO_2\) for a larger spatial region in the Southern Ocean based on satellite biogeochemical measurements of predictor variables, given that satellites do not measure \(pCO_2\) .     

Gravity currents with double stratification: a numerical and analytical investigation

We consider high-Reynolds-number Boussinesq gravity current and intrusion systems in which both the ambient and the propagating “current” are linearly stratified. The main focus is on a current of fixed volume released from a rectangular lock; the height ratio of the fluids $H$ , the stratification parameter of the ambient $S$ , and the internal stratification parameter of the current, $\sigma $ , are quite general. We perform two-dimensional Navier–Stokes simulation and compare the results with those of a previously-published one-layer shallow-water model. The results provide insights into the behavior of the system and enhance the confidence in the approximate model while also revealing its limitations. The qualitative predictions of the model are confirmed, in particular: (1) there is an initial “slumping” stage of propagation with constant speed $u_N$ , after which $u_N$ decays with time; (2) for fixed $H$ and $S$ , the increase of $\sigma $ causes a slower propagation of the current; (3) for some combinations of the parameters $H,S, \sigma $ the fluid released from the lock lacks initially (or runs out quickly of) buoyancy “driving power” in the horizontal direction, and does not propagate like a gravity current. There is also a fair quantitative agreement between the predictions of the model and the simulations concerning the spread of the current.     

Initial mixing of inclined dense jet in perpendicular crossflow

A comprehensive experimental investigation for an inclined ( $60^{\circ }$ to vertical) dense jet in perpendicular crossflow—with a three-dimensional trajectory—is reported. The detailed tracer concentration field in the vertical cross-section of the bent-over jet is measured by the laser-induced fluorescence technique for a wide range of jet densimetric Froude number $Fr$ and ambient to jet velocity ratios $U_r$ . The jet trajectory and dilution determined from a large number of cross-sectional scalar fields are interpreted by the Lagrangian model over the entire range of jet-dominated to crossflow-dominated regimes. The mixing during the ascent phase of the dense jet resembles that of an advected jet or line puff and changes to a negatively buoyant thermal on descent. It is found that the mixing behavior is governed by a crossflow Froude number $\mathbf{F} = U_r Fr$ . For $\mathbf{F} < 0.8$ , the mixing is jet-dominated and governed by shear entrainment; significant detrainment occurs and the maximum height of rise $Z_{max}$ is under-predicted as in the case of a dense jet in stagnant fluid. While the jet trajectory in the horizontal momentum plane is well-predicted, the measurements indicate a greater rise and slower descent. For $\mathbf{F} \ge 0.8$ the dense jet becomes significantly bent-over during its ascent phase; the jet mixing is dominated by vortex entrainment. For $\mathbf{F} \ge 2$ , the detrainment ceases to have any effect on the jet behavior. The jet trajectory in both the horizontal momentum and buoyancy planes are well predicted by the model. Despite the under-prediction of terminal rise, the jet dilution at a large number of cross-sections covering the ascent and descent of the dense jet are well-predicted. Both the terminal rise and the initial dilution for the inclined jet in perpendicular crossflow are smaller than those of a corresponding vertical jet. Both the maximum terminal rise $Z_{max}$ and horizontal lateral penetration $Y_{max}$ follow a $\mathbf{F}^{-1/2}$ dependence in the crossflow-dominated regime. The initial dilution at terminal rise follows a $S \sim \mathbf{F}^{1/3}$ dependence.     

Three-way compositional analysis of water quality monitoring data

Water quality monitoring data typically consist of \(J\) parameters and constituents measured at \(I\) number of static locations at \(K\) sets of seasonal occurrences. The resulting \(I \times J \times K\) three-way array can be difficult to interpret. Additionally, the constituent portion of the dataset (e.g., major ion and trace element concentration, pH, etc.) is compositional in that it sums to a constant (e.g., 1 kg/L) and is mathematically confined to the simplex, the sample space for compositional data. Here we apply a Tucker3 model on centered log-ratio data to find low dimensional representation of latent variables as a means to simplify data processing and interpretation of three years of seasonal compositional groundwater chemistry data for 14 wells at a study site in Wyoming, USA. The study site has been amended with treated coalbed methane produced water, using a subsurface drip irrigation system, to allow for irrigation of forage crops. Results from three-way compositional data analysis indicate that primary controls on water quality at the study site include: solutes concentration by evapotranspiration, cation exchange, and dissolution of native salts. These findings agree well with results from more detailed investigations of the site. In addition, the model identified Ba uptake during gypsum precipitation in some portions of the site during the final 6–9 months of investigation, a process for which the timing and extent had not previously been identified. These results suggest that multi-way compositional analyses hold promise as a means to more easily interpret water quality monitoring data.     

A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of \(\text {NO}_{x}\) in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated \(R^2\) of approximately \(0.7\) at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.     

Gravity currents with tailwaters in Boussinesq and non-Boussinesq systems: two-layer shallow-water dam-break solutions and Navier–Stokes simulations

We consider the dam-break initial stage of propagation of a gravity current of density $\rho _{c}$ released from a lock (reservoir) of height $h_0$ in a channel of height $H$ . The channel contains two-layer stratified fluid. One layer, called the “tailwater,” is of the same density as the current and is of thickness $h_T (< h_0)$ , and the other layer, called the “ambient,” is of different density $\rho _{a}$ . Both Boussinesq ( $\rho _{c}/\rho _{a}\approx 1$ ) and non-Boussinesq systems are investigated. By assuming a large Reynolds number, we can model the flow with the two-layer shallow-water approximation. Due to the presence of the tailwater, the “jump conditions” at the front of the current are different from the classical Benjamin formula, and in some circumstances (clarified in the paper) the interface of the current matches smoothly with the horizontal interface of the tailwater. Using the method of characteristics, analytical solutions are derived for various combinations of the governing parameters. To corroborate the results, two-dimensional direct numerical Navier–Stokes simulations are used, and comparisons for about 80 combinations of parameters in the Boussinesq and non-Boussinesq domains are performed. The agreement of speed and height of the current is very close. We conclude that the model yields self-contained and fairly accurate analytical solutions for the dam-break problem under consideration. The results provide reliable insights into the influence of the tailwater on the propagation of the gravity current, for both heavy-into-light and light-into-heavy motions. This is a significant extension of the classical gravity-current theory from the particular $h_T=0$ point to the $h_T > 0$ domain.     

Quantifying a significance of sediment particle size to hyporheic sedimentary oxygen demand with a permeable stream bed

A mechanistic model of sedimentary oxygen demand (SOD) for hyporheic flow is presented. The permeable sediment bed, e.g. sand or fine gravel, is considered with hydraulic conductivity in the range $0.1 < K < 20$  cm/s. Hyporheic pore water flow is induced by pressure fluctuations at the sediment/water interface due to near-bed turbulent coherent motions. A 2-D advection–diffusion equation is linked to the pore water flow model to simulate the effect of advection–dispersion driven by interstitial flow on oxygen transfer through the permeable sediment. Microbial oxygen uptake in the sediment is expressed as a function of the microbial growth rate, and is related to the sediment properties, i.e. the grain diameter $(d_{s})$ and porosity $(\phi )$ . The model describes the significance of sediment particle size to oxygen transfer through the sediment and microbial oxygen uptake: With increasing grain diameter $(d_{s})$ , the hydraulic conductivity $(K)$ increases so does the oxygen transfer rate, while particle surface area per volume (the available surface area for colonization by biofilms) decreases reducing the microbial oxygen uptake rate. Simulation results show that SOD increases as the hydraulic conductivity $(K)$ increases before a threshold has been reached. After that, SOD diminishes with the increment of the hydraulic conductivity $(K)$ .     

Physical and biological controls of algal blooms in the Río de la Plata

Coupled three-dimensional hydrodynamic and ecological numerical simulations were used to investigate the role of transport, stagnation zones and dispersion on inter-annual blooms of the diatom Aulacoseira sp. in the vicinity of the drinking water intakes of the Buenos Aires city (Argentina) in the upper Río de la Plata. Three different summer events were analyzed. First, a mild biomass bloom year (2006–2007), second, a high biomass bloom year (2007–2008) and third, a “normal” no bloom year (2009–2010). Simulated water height, water temperature, suspended solids and chlorophyll \(a\) concentrations patterns compared well with field data. Results revealed that the advection of phytoplankton cells via inflows to the Río de la Plata triggered Aulacoseira sp. blooms in the domain. In addition, excessive growth observed near the drinking water intakes, along the Argentinean margin, were associated with long retention times (stagnant region) and weak horizontal dispersion. Increased concentrations of suspended solids in the water column, in response to re-suspension events, did not prevent the blooms, however, were found to also play a key role in controlling the rate of phytoplankton growth. Finally, a non-dimensional parameter, R, that considers phytoplankton patch size, e-folding growth and dispersion time scales is shown to determine the potential bloom occurrences, as well as bloom intensity; R values higher than 5.7 suggest intense phytoplankton growth. For the mild biomass bloom year, \(R = 7.5\) , for the high biomass bloom year, \(R = 11\) and for the “normal” no bloom year \(R= 0.4\) .     

Waves and turbulence in katabatic winds

The measurements taken during the Vertical Transport and Mixing Experiment (VTMX, October, 2000) on a northeastern slope of Salt Lake Valley, Utah, were used to calculate the statistics of velocity fluctuations in a katabatic gravity current in the absence of synoptic forcing. The data from ultrasonic anemometer-thermometers placed at elevations 4.5 and 13.9 m were used. The contributions of small-scale turbulence and waves were isolated by applying a high-pass digital (Elliptical) filter, whereupon the filtered quantities were identified as small-scale turbulence and the rest as internal gravity waves. Internal waves were found to play a role not only at canonical large gradient Richardson numbers $(\overline{\hbox {Ri}_\mathrm{g} } >1)$ , but sometimes at smaller values $(0.1 < \overline{\hbox {Ri}_\mathrm{g}}<1)$ , in contrast to typical observations in flat-terrain stable boundary layers. This may be attributed, at least partly, to (critical) internal waves on the slope, identified by Princevac et al. [1], which degenerate into turbulence and help maintain an active internal wave field. The applicability of both Monin-Obukhov (MO) similarity theory and local scaling to filtered and unfiltered data was tested by analyzing rms velocity fluctuations as a function of the stability parameter z/L, where L is the Obukhov length and z the height above the ground. For weaker stabilities, $\hbox {z/L}<1$ , the MO similarity and local scaling were valid for both filtered and unfiltered data. Conversely, when $\hbox {z/L}>1$ , the use of both scaling types is questionable, although filtered data showed a tendency to follow local scaling. A relationship between z/L and $\overline{\hbox {Ri}_\mathrm{g} }$ was identified. Eddy diffusivities of momentum $\hbox {K}_\mathrm{M}$ and heat $\hbox {K}_\mathrm{H}$ were dependent on wave activities, notably when $\overline{\hbox {Ri}_\mathrm{g} } > 1$ . The ratio $\hbox {K}_{\mathrm{H}}/\hbox {K}_{\mathrm{M}}$ dropped well below unity at high $\overline{\hbox {Ri}_\mathrm{g} }$ , in consonance with previous laboratory stratified shear layer measurements as well as other field observations.     

Functional ANOVA starting from discrete data: an application to air quality data

A nonparametric functional approach is proposed to compare the mean functions of $k$ k samples of curves. In practice, curves data are usually collected in a discrete form and hence they must be pre-processed to use purely functional techniques. However, in the context of $k$ k -sample tests, the pre-processing step can have effects in terms of power reduction. Hall and Van Keilegom (Stat Sin 17:1511–1531, 2007) proposed a methodology to minimizing these effects in the context of tests for the equality of two distribution functions. Their procedure is here extended to the case of $k$ k -sample hypothesis tests. The asymptotic validity of the procedure is established and its finite sample performance is analyzed through Monte Carlo experiments. As an illustration, the method is applied to air quality data collected from several monitoring stations placed at different geographical locations at the center of Spain.     

Large eddy simulation of dispersion around an isolated cubic building: evaluation of localized dynamic k_\mathrm{SGS}-equation sub-grid scale model

In the present study, the prediction accuracy of a dynamic one-equation sub-grid scale model for the large eddy simulation of dispersion around an isolated cubic building is investigated. For this purpose, the localized dynamic $k_\mathrm{SGS} $ -equation model (LDKM) is employed and the results are compared with the available experimental data and two other classic sub-grid scale models, namely, standard Smagorinsky–Lilly model (SSLM) and dynamic Smagorinsky–Lilly model (DSLM). It is shown that the three SGS models give results in good agreement with experiment. However, near the ground level of the leeward wall, dimensionless time-averaged concentration, $\langle K\rangle $ , profile is not quite similar to the experimental data. It is also demonstrated that the LDKM predicts the values of $\langle K\rangle $ on the roof, leeward and side walls more acceptably than the SSLM and DSLM. Whereas, the streamwise elongation of time-averaged structures of the plume shape is more over-estimated with the LDKM than with the other two SGS models. In terms of numerical difficulty, the LDKM is found to be stable and computationally reasonable. In addition, it does not suffer from a flow dependent constant such as the Smagorinsky coefficient employed in the SSLM model.     

Moisture effects on eolian particle entrainment

In wind tunnel experiments, we study the effects of soil moisture on the threshold condition to entrain fine grain sand/silt into eolian flow and the near-bed concentration of airborne particles. To study the effect of particle shape on moisture bonding, we use two types of particles nearly equal in size: spherical glass beads $(d_{50} = 134\,\upmu \mathrm{m})$ and sieved quartz sand $(d_{50} = 139 \,\upmu \mathrm{m})$ . Both are poorly graded soils. We conducted these experiments at low moisture contents $({<}1\,\%)$ . We found that the spherical particles were more sensitive to changes in moisture than the sand, attributable to the large differences in specific surface area of the two particles. The larger specific surface area for sand is due to the surface roughness of the angular sand particle. Consequently, sand “stores” more moisture via surface adsorption, requiring higher soil moisture content to form liquid bridges between sand particles. Based on these findings, we extend the concept of a threshold moisture content, $w^{\prime }$ —originally proposed for clayey soils—to soils that lack any measureable clay content. This allows application of existing models developed for clayey soils that quantify the moisture effect on the threshold friction velocity to sand and silty soils (i.e., clay content $=$ 0). Additionally, we develop a model that quantifies the moisture effects on near-surface airborne particulate concentration, using experimental observations to determine the functional dependence on fluid and particle properties, including soil specific area. These models can be applied to numerical simulation of particulate plume formation and dispersion.     

Aeolian erosion of storage piles yards: contribution of the surrounding areas

Dust emissions from stockpiles surfaces are often estimated applying mathematical models such as the widely used model proposed by the USEPA. It employs specific emission factors, which are based on the fluid flow patterns over the near surface. But, some of the emitted dust particles settle downstream the pile and can usually be re-emitted which creates a secondary source. The emission from the ground surface around a pile is actually not accounted for by the USEPA model but the method, based on the wind exposure and a reconstruction from different sources defined by the same wind exposure, is relevant. This work aims to quantify the contribution of dust re-emission from the areas surrounding the piles in the total emission of an open storage yard. Three angles of incidence of the incoming wind flow are investigated ( $30^{\circ }, 60^{\circ }$ and $90^{\circ }$ ). Results of friction velocity from numerical modelling of fluid dynamics were used in the USEPA model to determine dust emission. It was found that as the wind velocity increases, the contribution of particles re-emission from the ground area around the pile in the total emission also increases. The dust emission from the pile surface is higher for piles oriented $30^{\circ }$ to the wind direction. On the other hand, considering the ground area around the pile, the $60^{\circ }$ configuration is responsible for higher emission rates (up to 67 %). The global emissions assumed a minimum value for the piles oriented perpendicular to the wind direction for all wind velocity investigated.     

Horizontal transport,mixing and retention in a large,shallow estuary: Río de la Plata

We use field data and a high-resolution three-dimensional (3D) hydrodynamic numerical model to investigate the horizontal transport and dispersion characteristics in the upper reaches of the shallow Río de la Plata estuary, located between the Argentinean and Uruguayan coasts, with the objective of relating the mixing characteristics to the likelihood of algal bloom formation. The 3D hydrodynamic model was validated with an extensive field experiment including both, synoptic profiling and in situ data, and then used to quantify the geographic variability of the local residence time and rate of dispersion. We show that during a high inflow regime, the aquatic environment near the Uruguayan coast, stretching almost to the middle of the estuary, had short residence time and horizontal dispersion coefficient of around 77 \(\mathrm {m}^{2}\,\mathrm {s}^{-1}\) , compared to the conditions along the Argentinean coastal regime where the residence time was much longer and the dispersion coefficient (40 \(\mathrm {m}^{2}\,\mathrm {s}^{-1}\) ) much smaller, making the Argentinian coastal margin more susceptible for algae blooms.