Water-Channel Estimation of Eulerian and Lagrangian Time Scales of the Turbulence in Idealized Two-Dimensional Urban Canopies

Lagrangian and Eulerian statistics are obtained from a water-channel experiment of an idealized two-dimensional urban canopy flow in neutral conditions. The objective is to quantify the Eulerian \((T^{\mathrm{E}})\) and Lagrangian \((T^{\mathrm{L}})\) time scales of the turbulence above the canopy layer as well as to investigate their dependence on the aspect ratio of the canopy, AR, as the latter is the ratio of the width (W) to the height (H) of the canyon. Experiments are also conducted for the case of flat terrain, which can be thought of as equivalent to a classical one-directional shear flow. The values found for the Eulerian time scales on flat terrain are in agreement with previous numerical results found in the literature. It is found that both the streamwise and vertical components of the Lagrangian time scale, \(T_\mathrm{u}^\mathrm{L} \) and \(T_\mathrm{w}^\mathrm{L} \), follow Raupach’s linear law within the constant-flux layer. The same holds true for \(T_\mathrm{w}^\mathrm{L} \) in both the canopies analyzed \((AR= 1\) and \(AR= 2\)) and also for \(T_\mathrm{u}^\mathrm{L} \) when \(AR = 1\). In contrast, for \(AR = 2\), \(T_\mathrm{u}^\mathrm{L} \) follows Raupach’s law only above \(z=2H\). Below that level, \(T_\mathrm{u}^\mathrm{L} \) is nearly constant with height, showing at \(z=H\) a value approximately one order of magnitude greater than that found for \(AR = 1\). It is shown that the assumption usually adopted for flat terrain, that \(\beta =T^{\mathrm{L}}/T^{\mathrm{E}}\) is proportional to the inverse of the turbulence intensity, also holds true even for the canopy flow in the constant-flux layer. In particular, \(\gamma /i_\mathrm{u} \) fits well \(\beta _\mathrm{u} =T_\mathrm{u}^\mathrm{L} /T_\mathrm{u}^\mathrm{E} \) in both the configurations by choosing \(\gamma \) to be 0.35 (here, \(i_\mathrm{u} =\sigma _\mathrm{u} / \bar{u} \), where \(\bar{u} \) and \(\sigma _\mathrm{u} \) are the mean and the root-mean-square of the streamwise velocity component, respectively). On the other hand, \(\beta _\mathrm{w} =T_\mathrm{w}^\mathrm{L} /T_\mathrm{w}^\mathrm{E} \) follows approximately \(\gamma /i_\mathrm{w} =0.65/\left( {\sigma _\mathrm{w} /\bar{u} } \right) \) for \(z > 2H\), irrespective of the AR value. The second main objective is to estimate other parameters of interest in dispersion studies, such as the eddy diffusivity of momentum \((K_\mathrm{{T}})\) and the Kolmogorov constant \((C_0)\). It is found that \(C_0\) depends appreciably on the velocity component both for the flat terrain and canopy flow, even though for the latter case it is insensitive to AR values. In all the three experimental configurations analyzed here, \(K_\mathrm{{T}}\) shows an overall linear growth with height in agreement with the linear trend predicted by Prandtl’s theory.     

Understanding Diurnality and Inter-Seasonality of a Sub-tropical Urban Heat Island

We quantify the spatial and temporal aspects of the urban heat-island (UHI) effect for Kanpur, a major city in the humid sub-tropical monsoon climate of the Gangetic basin. Fixed station measurements are used to investigate the diurnality and inter-seasonality in the urban–rural differences in surface temperature (\({\Delta } T_\mathrm{s}\)) and air temperature (\({\Delta } T_\mathrm{c}\)) separately. The extent of the spatial variations of the nighttime \({\Delta } T_\mathrm{c}\) and \({\Delta } T_\mathrm{s}\) is investigated through mobile campaigns and satellite remote sensing respectively. Nighttime \({\Delta } T_\mathrm{c}\) values dominate during both the pre-monsoon (maximum of 3.6 \(^\circ \hbox {C}\)) and the monsoon (maximum of 2.0 \(^\circ \hbox {C}\)). However, the diurnality in \({\Delta } T_\mathrm{s}\) is different, with higher daytime values during the pre-monsoon, but very little diurnality during the monsoon. The nighttime \({\Delta } T_\mathrm{s}\) value is mainly associated with differences in the urban–rural incoming longwave radiative flux (\(r^{2}=0.33\) during the pre-monsoon; 0.65 during the monsoon), which, in turn, causes a difference in the outgoing longwave radiative flux. This difference may modulate the nighttime \({\Delta } T_\mathrm{c}\) value as suggested by significant correlations (\(r^{2}=0.68\) for the pre-monsoon; 0.50 for the monsoon). The magnitude of \({\Delta } T_\mathrm{c}\) may also be modulated by advection, as it is inversely related with the urban wind speed. A combination of in situ, remotely sensed, and model simulation data were used to show that the inter-seasonality in \({\Delta } T_\mathrm{s}\), and, to a lesser extent, in \({\Delta } T_\mathrm{c}\), may be related to the change in the land use of the rural site between the pre-monsoon and the monsoon periods. Results suggest that the degree of coupling of \({\Delta } T_\mathrm{s}\) and \({\Delta } T_\mathrm{c}\) may be a strong function of land use and land cover.     

Edge-to-Stem Variability in Wet-Canopy Evaporation From an Urban Tree Row

Evaporation from wet-canopy (\(E_\mathrm{C}\)) and stem (\(E_\mathrm{S}\)) surfaces during rainfall represents a significant portion of municipal-to-global scale hydrologic cycles. For urban ecosystems, \(E_\mathrm{C}\) and \(E_\mathrm{S}\) dynamics play valuable roles in stormwater management. Despite this, canopy-interception loss studies typically ignore crown-scale variability in \(E_\mathrm{C}\) and assume (with few indirect data) that \(E_\mathrm{S}\) is generally \({<}2\%\) of total wet-canopy evaporation. We test these common assumptions for the first time with a spatially-distributed network of in-canopy meteorological monitoring and 45 surface temperature sensors in an urban Pinus elliottii tree row to estimate \(E_\mathrm{C}\) and \(E_\mathrm{S}\) under the assumption that crown surfaces behave as “wet bulbs”. From December 2015 through July 2016, 33 saturated crown periods (195 h of 5-min observations) were isolated from storms for determination of 5-min evaporation rates ranging from negligible to 0.67 \(\hbox {mm h}^{-1}\). Mean \(E_\mathrm{S}\) (0.10 \(\hbox {mm h}^{-1}\)) was significantly lower (\(p < 0.01\)) than mean \(E_\mathrm{C}\) (0.16 \(\hbox {mm h}^{-1}\)). But, \(E_\mathrm{S}\) values often equalled \(E_\mathrm{C}\) and, when scaled to trunk area using terrestrial lidar, accounted for 8–13% (inter-quartile range) of total wet-crown evaporation (\(E_\mathrm{S}+E_\mathrm{C}\) scaled to surface area). \(E_\mathrm{S}\) contributions to total wet-crown evaporation maximized at 33%, showing a general underestimate (by 2–17 times) of this quantity in the literature. Moreover, results suggest wet-crown evaporation from urban tree rows can be adequately estimated by simply assuming saturated tree surfaces behave as wet bulbs, avoiding problematic assumptions associated with other physically-based methods.     

Katabatic Flow: A Closed-Form Solution with Spatially-Varying Eddy Diffusivities

The Nieuwstadt closed-form solution for the stationary Ekman layer is generalized for katabatic flows within the conceptual framework of the Prandtl model. The proposed solution is valid for spatially-varying eddy viscosity and diffusivity (O’Brien type) and constant Prandtl number (Pr). Variations in the velocity and buoyancy profiles are discussed as a function of the dimensionless model parameters \(z_0 \equiv \hat{z}_0 \hat{N}^2 Pr \sin {(\alpha )} |\hat{b}_\mathrm{s} |^{-1}\) and \(\lambda \equiv \hat{u}_{\mathrm{ref}}\hat{N} \sqrt{Pr} |\hat{b}_\mathrm{s} |^{-1}\), where \(\hat{z}_0\) is the hydrodynamic roughness length, \(\hat{N}\) is the Brunt-Väisälä frequency, \(\alpha \) is the surface sloping angle, \(\hat{b}_\mathrm{s}\) is the imposed surface buoyancy, and \(\hat{u}_{\mathrm{ref}}\) is a reference velocity scale used to define eddy diffusivities. Velocity and buoyancy profiles show significant variations in both phase and amplitude of extrema with respect to the classic constant \(\textit{K}\) model and with respect to a recent approximate analytic solution based on the Wentzel-Kramers-Brillouin theory. Near-wall regions are characterized by relatively stronger surface momentum and buoyancy gradients, whose magnitude is proportional to \(z_0\) and to \(\lambda \). In addition, slope-parallel momentum and buoyancy fluxes are reduced, the low-level jet is further displaced toward the wall, and its peak velocity depends on both \(z_0\) and \(\lambda \).     

On the Relevance of $$\ln (z_{0} /z_{0T})= kB^{-1}$$

The assumption that the roughness Reynolds number \(( Re_{*})\) can be used as a basis for quantifying the boundary-layer property \({ kB}^{-1} (= \ln (z_{0}/z_{0T}))\) as in some modern numerical models is questioned. While \({ Re}_{*}\) is a useful property in studies of pipe flow, it appears to have only marginal applicability in the case of treeless terrain, as studied in the two experimental situations presented here. For both the daytime and night-time cases there appears to be little correlation between \({ kB}^{-1}\) and \({ Re}_{*}\). For daytime, the present studies indicate that the assumption \({ kB}^{-1} \approx 2\) is acceptable, while for night-time, the scatter involved in relating \({ kB}^{-1}\) to \({ Re}_{*}\) suggests there is little reason to assume a direct relationship. However, while the scatter affecting all of the night-time results is large, there remains a significant correlation between the heat and momentum fluxes upon which an alternative methodology for describing bulk air–surface exchange at night could be constructed. The friction coefficient (\(C_{f}\)) and the turbulent Stanton number \(({ St}_{*})\) are discussed as possible alternatives for describing bulk properties of the air layer adjacent to the surface. While describing the surface roughness in terms of the friction coefficient provides an attractive simplification relative to the conventional methodologies based on roughness length and stability considerations, use of the Stanton number shares many of uncertainties that affect \({ kB}^{-1}\). The transitions at dawn and dusk remain demanding situations to address.     

Scale Properties of Anisotropic and Isotropic Turbulence in the Urban Surface Layer

The scale properties of anisotropic and isotropic turbulence in the urban surface layer are investigated. A dimensionless anisotropic tensor is introduced and the turbulent tensor anisotropic coefficient, defined as C, where \(C = 3d_{3}\,+\,1 (d_{3}\) is the minimum eigenvalue of the tensor) is used to characterize the turbulence anisotropy or isotropy. Turbulence is isotropic when \(C \approx 1\), and anisotropic when \(C \ll 1\). Three-dimensional velocity data collected using a sonic anemometer are analyzed to obtain the anisotropic characteristics of atmospheric turbulence in the urban surface layer, and the tensor anisotropic coefficient of turbulent eddies at different spatial scales calculated. The analysis shows that C is strongly dependent on atmospheric stability \(\xi = (z-z_{\mathrm{d}})/L_{{\textit{MO}}}\), where z is the measurement height, \(z_{\mathrm{d}}\) is the displacement height, and \(L_{{\textit{MO}}}\) is the Obukhov length. The turbulence at a specific scale in unstable conditions (i.e., \(\xi < 0\)) is closer to isotropic than that at the same scale under stable conditions. The maximum isotropic scale of turbulence is determined based on the characteristics of the power spectrum in three directions. Turbulence does not behave isotropically when the eddy scale is greater than the maximum isotropic scale, whereas it is horizontally isotropic at relatively large scales. The maximum isotropic scale of turbulence is compared to the outer scale of temperature, which is obtained by fitting the temperature fluctuation spectrum using the von Karman turbulent model. The results show that the outer scale of temperature is greater than the maximum isotropic scale of turbulence.     

Investigation of Turbulence Parametrization Schemes with Reference to the Atmospheric Boundary Layer Over the Aegean Sea During Etesian Winds

The spatial structure of the marine atmospheric boundary layer (MABL) over the Aegean Sea is investigated using the Weather Research and Forecasting (WRF) mesoscale model. Two ‘first-order’ non-local and five ‘1.5-order’ local planetary boundary-layer (PBL) parametrization schemes are used. The predictions from the WRF model are evaluated against airborne observations obtained by the UK Facility for Airborne Atmospheric Measurements BAe-14 research aircraft during the Aegean-GAME field campaign. Statistical analysis shows good agreement between measurements and simulations especially at low altitude. Despite the differences between the predicted and measured wind speeds, they reach an agreement index of 0.76. The simulated wind-speed fields close to the surface differ substantially among the schemes (maximum values range from 13 to \(18\hbox { m s}^{-1}\) at 150-m height), but the differences become marginal at higher levels. In contrast, all schemes show similar spatial variation patterns in potential temperature fields. A warmer (1–2 K) and drier (2–3\(\hbox { g kg}^{-1})\) layer than is observed, is predicted by almost all schemes under stable conditions (eastern Aegean Sea), whereas a cooler (up to 2 K) and moister (1–2\(\hbox { g kg}^{-1})\) layer is simulated under near-neutral to nearly unstable conditions (western Aegean Sea). Almost all schemes reproduce the vertical structure of the PBL and the shallow MABL (up to 300 m) well, including the low-level jet in the eastern Aegean Sea, with non-local schemes being closer to observations. The simulated PBL depths diverge (up to 500 m) due to the different criteria applied by the schemes for their calculation. Under stable conditions, the observed MABL depth corresponds to the height above the sea surface where the simulated eddy viscosity reaches a minimum; under neutral to slightly unstable conditions this is close to the top of the simulated entrainment layer. The observed sensible heat fluxes vary from ?40 to \(25\hbox { W m}^{-2}\), while the simulated fluxes range from ?40 to \(40\hbox { W m}^{-2}\); however, all of the schemes’ predictions are close to the observations under unstable conditions. Finally, all schemes overestimate the friction velocity, although the simulated range (from 0.2 to \(0.5\hbox { m s}^{-1})\) is narrower than that observed (from 0.1 to \(0.7\hbox { m s}^{-1})\).     

Turbulent Flow Over Large Roughness Elements: Effect of Frontal and Plan Solidity on Turbulence Statistics and Structure

Wind-tunnel experiments were carried out on fully-rough boundary layers with large roughness (\(\delta /h \approx 10\), where h is the height of the roughness elements and \(\delta \) is the boundary-layer thickness). Twelve different surface conditions were created by using LEGO? bricks of uniform height. Six cases are tested for a fixed plan solidity (\(\lambda _\mathrm{P}\)) with variations in frontal density (\(\lambda _\mathrm{F}\)), while the other six cases have varying \(\lambda _\mathrm{P}\) for fixed \(\lambda _\mathrm{F}\). Particle image velocimetry and floating-element drag-balance measurements were performed. The current results complement those contained in Placidi and Ganapathisubramani (J Fluid Mech 782:541–566, 2015), extending the previous analysis to the turbulence statistics and spatial structure. Results indicate that mean velocity profiles in defect form agree with Townsend’s similarity hypothesis with varying \(\lambda _\mathrm{F}\), however, the agreement is worse for cases with varying \(\lambda _\mathrm{P}\). The streamwise and wall-normal turbulent stresses, as well as the Reynolds shear stresses, show a lack of similarity across most examined cases. This suggests that the critical height of the roughness for which outer-layer similarity holds depends not only on the height of the roughness, but also on the local wall morphology. A new criterion based on shelter solidity, defined as the sheltered plan area per unit wall-parallel area, which is similar to the ‘effective shelter area’ in Raupach and Shaw (Boundary-Layer Meteorol 22:79–90, 1982), is found to capture the departure of the turbulence statistics from outer-layer similarity. Despite this lack of similarity reported in the turbulence statistics, proper orthogonal decomposition analysis, as well as two-point spatial correlations, show that some form of universal flow structure is present, as all cases exhibit virtually identical proper orthogonal decomposition mode shapes and correlation fields. Finally, reduced models based on proper orthogonal decomposition reveal that the small scales of the turbulence play a significant role in assessing outer-layer similarity.     

Quantifying the Influence of Random Errors in Turbulence Measurements on Scalar Similarity in the Atmospheric Surface Layer

The influence of random errors in turbulence measurements on scalar similarity for temperature, water vapour, \(\hbox {CO}_{2}\), and \(\hbox {NH}_{3}\) is investigated using two eddy-covariance datasets collected over a lake and a cattle feedlot. Three measures of scalar similarity, namely, the similarity constant in the flux–variance relationship, the correlation coefficient between two scalars and the relative transport efficiency, are examined. The uncertainty in the similarity constant \(C_{s}\) in the flux–variance relationship resulting from random errors in turbulence measurements is quantified based on error propagation analyses and a Monte-Carlo sampling method, which yields a distribution instead of a single value for \(C_{s}\). For different scalars, the distributions of \(C_{s}\) are found to significantly overlap, implying that scalars are transported similarly under strongly unstable conditions. The random errors in the correlation coefficients between scalars and the relative transport efficiencies are also quantified through error propagation analyses, and they increase as the atmosphere departs from neutral conditions. Furthermore, the correlation coefficients between three scalars (water vapour, \(\hbox {CO}_{2}\), and \(\hbox {NH}_{3}\)) are statistically different from unity while the relative transport efficiencies are not, which highlights the difference between these two measures of scalar similarity. The results suggest that uncertainties in these measures of scalar similarity need to be quantified when using them to diagnose the existence of dissimilarity among different scalars.     

Aerodynamic Properties of Rough Surfaces with High Aspect-Ratio Roughness Elements: Effect of Aspect Ratio and Arrangements

We examine the effect of varying roughness-element aspect ratio on the mean velocity distributions of turbulent flow over arrays of rectangular-prism-shaped elements. Large-eddy simulations (LES) in conjunction with a sharp-interface immersed boundary method are used to simulate spatially-growing turbulent boundary layers over these rough surfaces. Arrays of aligned and staggered rectangular roughness elements with aspect ratio >1 are considered. First the temporally- and spatially-averaged velocity profiles are used to illustrate the aspect-ratio effects. For aligned prisms, the roughness length (\(z_\mathrm{o}\)) and the friction velocity (\(u_*\)) increase initially with an increase in the roughness-element aspect ratio, until the values reach a plateau at a particular aspect ratio. The exact value of this aspect ratio depends on the coverage density. Further increase in the aspect ratio changes neither \(z_\mathrm{o}\), \(u_*\) nor the bulk flow above the roughness elements. For the staggered cases, \(z_\mathrm{o}\) and \(u_*\) continue to increase for the surface coverage density and the aspect ratios investigated. To model the flow response to variations in roughness aspect ratio, we turn to a previously developed phenomenological volumetric sheltering model (Yang et al., in J Fluid Mech 789:127–165, 2016), which was intended for low to moderate aspect-ratio roughness elements. Here, we extend this model to account for high aspect-ratio roughness elements. We find that for aligned cases, the model predicts strong mutual sheltering among the roughness elements, while the effect is much weaker for staggered cases. The model-predicted \(z_\mathrm{o}\) and \(u_*\) agree well with the LES results. Results show that the model, which takes explicit account of the mutual sheltering effects, provides a rapid and reliable prediction method of roughness effects in turbulent boundary-layer flows over arrays of rectangular-prism roughness elements.     

Seasonal Variations in Drag Coefficient over a Sastrugi-Covered Snowfield in Coastal East Antarctica

The surface of windy Antarctic snowfields is subject to drifting snow, which leads to the formation of sastrugi. In turn, sastrugi contribute to the drag exerted by the snow surface on the atmosphere and hence influence drifting snow. Although the surface drag over rough sastrugi fields has been estimated for individual locations in Antarctica, its variation over time and with respect to drifting snow has received little attention. Using year-round data from a meteorological mast, seasonal variations in the neutral drag coefficient at a height of 10 m \((C_{{ DN}10})\) in coastal Adelie Land are presented and discussed in light of the formation and behaviour of sastrugi based on observed aeolian erosion patterns. The measurements revealed high \(C_{{ DN}10} \) values \((\ge \) 2 \(\times \) 10\(^{-3})\) and limited drifting snow (35% of the time) in summer (December–February) versus lower \(C_{{ DN}10} \) values \((\approx \) 1.5 \(\times \) \(10^{-3})\) associated with more frequent drifting snow (70% of the time) in winter (March–November). Without the seasonal distinction, there was no clear dependence of \(C_{{ DN}10} \) on friction velocity or wind direction, but observations revealed a general increase in \(C_{{ DN}10} \) with rising air temperature. The main hypothesis defended here is that higher temperatures increase snow cohesion and the development of sastrugi just after snow deposition while inhibiting the sastrugi streamlining process by raising the erosion threshold. This increases the contribution of the sastrugi form drag to the total surface drag in summer when winds are lighter and more variable. The analysis also showed that, in the absence of erosion, single snowfall events can reduce \(C_{{ DN}10} \) to \(1\,\times \,10^{-3}\) due to the burying of pre-existing microrelief under newly deposited snow. The results suggest that polar atmospheric models should account for spatial and temporal variations in snow surface roughness through a dynamic representation of the sastrugi form drag.     

Observations of Atmospheric Methane and Carbon Dioxide Mixing Ratios: Tall-Tower or Mountain-Top Stations?

Mountain-top observations of greenhouse gas mixing ratios may be an alternative to tall-tower measurements for regional scale source and sink estimation. To investigate the equivalence or limitations of a mountain-top site as compared to a tall-tower site, we used the unique opportunity of comparing in situ measurements of methane (\(\hbox {CH}_{4}\)) and carbon dioxide (\(\hbox {CO}_{2}\)) mixing ratios at a mountain top (986 m above sea level, a.s.l.) with measurements from a nearby (distance 28.4 km) tall tower, sampled at almost the same elevation (1009 m a.s.l.). Special attention was given to, (i) how local wind statistics and greenhouse gas sources and sinks at the mountain top influence the observations, and (ii) whether mountain-top observations can be used as for those from a tall tower for constraining regional greenhouse gas emissions. Wind statistics at the mountain-top site are clearly more influenced by local flow systems than those at the tall-tower site. Differences in temporal patterns of the greenhouse gas mixing ratios observed at the two sites are mostly related to the influence of local sources and sinks at the mountain-top site. Major influences of local sources can be removed by applying a statistical filter (\(5{\mathrm{th}}\) percentile) or a filter that removes periods with unfavourable flow conditions. In the best case, the bias in mixing ratios between the mountain-top and the tall-tower sites after the application of the wind filter was \({-}0.0005\pm 0.0010\) ppm for methane (September, 0000–0400 UTC) and \(0.11\pm 0.18\) ppm for \(\hbox {CO}_{2}\) (February, 1200–1600 UTC). Temporal fluctuations of atmospheric \(\hbox {CH}_{4}\) and \(\hbox {CO}_{2}\) mixing ratios at both stations also showed good agreement (apart from \(\hbox {CO}_{2}\) during summertime) as determined by moving bi-weekly Pearson correlation coefficients (up to 0.96 for \(\hbox {CO}_{2}\) and 0.97 for \(\hbox {CH}_{4}\)). When only comparing mixing ratios minimally influenced by local sources (low bias and high correlation coefficients), our measurements indicate that mountain-top observations are comparable to tall-tower observations.     

The Effect of Breaking Waves on $$\hbox {CO}_2$$ Air–Sea Fluxes in the Coastal Zone

The influence of wave-associated parameters controlling turbulent \(\hbox {CO}_2\) fluxes through the air–sea interface is investigated in a coastal region. A full year of high-quality data of direct estimates of air–sea \(\hbox {CO}_2\) fluxes based on eddy-covariance measurements is presented. The study area located in Todos Santos Bay, Baja California, Mexico, is a net sink of \(\hbox {CO}_2\) with a mean flux of \(-1.3\, \upmu \hbox {mol m}^{-2}\hbox {s}^{-1}\) (\(-41.6\hbox { mol m}^{-2}\hbox {yr}^{-1}\)). The results of a quantile-regression analysis computed between the \(\hbox {CO}_2\) flux and, (1) wind speed, (2) significant wave height, (3) wave steepness, and (4) water temperature, suggest that the significant wave height is the most correlated parameter with the magnitude of the flux but the behaviour of the relation varies along the probability distribution function, with the slopes of the regression lines presenting both positive and negative values. These results imply that the presence of surface waves in coastal areas is the key factor that promotes the increase of the flux from and into the ocean. Further analysis suggests that the local characteristics of the aqueous and atmospheric layers might determine the direction of the flux.     

Observations of Lake-Breeze Events During the Toronto 2015 Pan-American Games

Enhanced meteorological observations were made during the 2015 Pan and Parapan American Games in Toronto in order to measure the vertical and horizontal structure of lake-breeze events. Two scanning Doppler lidars (one fixed and one mobile), a C-band radar, and a network including 53 surface meteorological stations (mesonet) provided pressure, temperature, humidity, and wind speed and direction measurements over Lake Ontario and urban areas. These observations captured the full evolution (prior, during, and after) of 27 lake-breeze events (73% of observation days) in order to characterize the convective and dynamic processes driving lake breezes at the local scale and mesoscale. The dominant signal of a passing lake-breeze front (LBF) was an increase in dew-point temperature of \(2.3 \pm 0.3 \,^{\circ }\hbox {C}\), coinciding with a \(180^{\circ }\) shift in wind direction and a decrease in air temperature of \(2.1 \pm 0.2 \,^{\circ }\hbox {C}\). Doppler lidar observations over the lake detected lake breezes 1 hour (on average) before detection by radar and mesonet. On days with the synoptic flow in the offshore direction, the lidars observed wedge-shaped LBFs with shallow depths, which inhibited the radar’s ability to detect the lake breeze. The LBF’s ground speed and inland penetration distance were found to be well-correlated (\(r = 0.78\)), with larger inland penetration distances occurring on days with non-opposing (non-offshore) synoptic flow. The observed enhanced vertical motion \(({>} 1\hbox { m s}^{-1})\) at the LBF, observed by the lidar on 54% of lake-breeze days, was greater (at times \({>} 2.5\hbox { m s}^{-1}\)) than that observed in previous studies and longer-lasting over the lake than over land. The weaker and less pronounced lake-breeze structure over land is illustrated in two case studies highlighting the lifetime of the lake-breeze circulation and the impact of propagation distance on lake-breeze intensity.     

Effect of Surface Heterogeneity on the Boundary-Layer Height: A Case Study at a Semi-Arid Forest

We investigate the effects of an isolated meso-\(\gamma \)-scale surface heterogeneity for roughness and albedo on the atmospheric boundary-layer (ABL) height, with a case study at a semi-arid forest surrounded by sparse shrubland (forest area: \(28~\text{ km }^2\), forest length in the main wind direction: 7 km). Doppler lidar and ceilometer measurements at this semi-arid forest show an increase in the ABL height over the forest compared with the shrubland on four out of eight days. The differences in the ABL height between shrubland and forest are explained for all days with a model that assumes a linear growth of the internal boundary layer of the forest through the convective ABL upwind of the forest followed by a square-root growth into the stable free atmosphere. For the environmental conditions that existed during our measurements, the increase in ABL height due to large sensible heat fluxes from the forest (\(600~\text {W~m}^{-2}\) in summer) is subdued by stable stratification in the free atmosphere above the ABL, or reduced by high wind speeds in the mixed layer.     

Estimating Sediment Mass Fluxes on Surfaces Sheltered by Live Vegetation

We present a simple model based on already existing and widely used equations for estimating particle mass fluxes on surfaces sheltered by live vegetation. Wind-tunnel measurements of vertical profiles of mass flux in three different dense live plant canopies, and as a function of the spatially averaged skin friction velocity \({u_{\tau }}'\), provide the baseline set of data. For the bare-sand surface, the total mass flux Q shows the typical \(b({u_\tau }' - {u_{\tau t}}')^{3 }\) increase with increasing skin friction velocity \({u_{\tau }}'\), where b is a constant and \({u_{\tau t}}'\) is the threshold at the onset of particle erosion. Similar relations, however, with different values for b and \({u_{\tau t}}'\) compared to the bare-sand surface were found for experiments with 5.25 and 24.5 plants \(\hbox {m}^{-2}\) and can be explained by the spatial variations of \(u_{\tau }\) for the canopy cases. Based on the resulting parameters b and \({u_{\tau t}}'\), which are found to be functions of the roughness density \(\lambda \), we present a final simple relation \(Q(\lambda ,\, {u_{\tau }}')\) used for estimating the total mass flux for surfaces sheltered by live vegetation.     

Spatially-Averaged Temperature Structure Parameter Over a Heterogeneous Surface Measured by an Unmanned Aerial Vehicle

The structure parameter of temperature, \({C_{T}^{2}}\) , in the lower convective boundary layer was measured using the unmanned mini aerial vehicle M²AV. The measurements were carried out on two hot summer days in July 2010 over a heterogeneous land surface around the boundary-layer field site of the Lindenberg Meteorological Observatory—Richard-Aßmann-Observatory of the German Meteorological Service. The spatial series of \({C_{T}^{2}}\) showed considerable variability along the flight path that was caused by both temporal variations and surface heterogeneity. Comparison of the aircraft data with \({C_{T}^{2}}\) values derived from tower-based in situ turbulence measurements showed good agreement with respect to the diurnal variability. The decrease of \({C_{T}^{2}}\) with height as predicted by free-convection scaling could be confirmed for the morning and afternoon flights while the flights around noon suggest a different behaviour.     

Partitioning Eddy-Covariance Methane Fluxes from a Shallow Lake into Diffusive and Ebullitive Fluxes

Methane (\(\mathrm {CH}_{4}\)) is known to be emitted from lakes to the atmosphere via processes such as diffusion and ebullition (i.e., bubble emission). We developed a practical method for partitioning eddy-covariance \(\mathrm {CH}_{4}\) fluxes from a shallow lake into diffusive and ebullitive fluxes using a wavelet analysis based on local scalar similarity between the \(\mathrm {CH}_{4}\) concentration and other reference scalars, such as the air temperature or water vapour concentration, in the wavelet time-scale domain, with the hypothesis that similar and dissimilar fluctuation components are related to diffusive and ebullitive \(\mathrm {CH}_{4}\) fluxes, respectively. Our method is applied to approximately two weeks of data obtained at a shallow mid-latitude lake. The partitioned diffusive flux has a physically sound relationship with wind speed, supporting the validity of the method. The ratio of the diffusive flux to the total flux is typically 0.11 with flow from an area of steady bubble emission, but otherwise 0.36. Further validation is required using a larger dataset and data from other lakes. The proposed method can be easily applied to historical data because it requires only 10-Hz data of \(\mathrm {CH}_{4}\) concentration and other reference scalars, along with an empirical parameter.     

The Effects of Heat Advection on UK Weather and Climate Observations in the Vicinity of Small Urbanized Areas

Weather and climate networks traditionally follow rigorous siting guidelines, with individual stations located away from frost hollows, trees or urban areas. However, the diverse nature of the UK landscape suggests that the feasibility of siting stations that are truly representative of regional climate and free from distorting local effects is increasingly difficult. Whilst the urban heat island is a well-studied phenomenon and usually accounted for, the effect of warm urban air advected downwind is rarely considered, particularly at rural stations adjacent to urban areas. Until recently, urban heat advection (UHA) was viewed as an urban boundary-layer process through the formation of an urban plume that rises above the surface as it is advected. However, these dynamic UHA effects are shown to also have an impact on surface observations. Results show a significant difference in temperatures anomalies (\(p\,< \,0.001\)) between observations taken downwind of urban and rural areas. For example, urban heat advection from small urbanized areas (\(\sim \)1\(\,\hbox {km}^{2}\)) under low cloud cover and wind speeds of 2–3\(\,\hbox {m}\,\hbox {s}^{-1}\) is found to increase mean nocturnal air temperatures by 0.6\(\,^{\circ }\hbox {C}\) at a horizontal distance of 0.5 km. Fundamentally, these UHA results highlight the importance of careful interpretation of long-term temperature data taken near small urban areas.     

Scaling of Wall-Normal Turbulence Intensity and Vertical Eddy Structures in the Atmospheric Surface Layer

Adequate high-quality data on three-dimensional velocities in the atmospheric surface layer (height \(\delta \)) were acquired in the field at the Qingtu Lake Observation Array. The measurement range occupies nearly the entire logarithmic layer from approximately \(0.006\delta \)–\(0.2\delta \). The turbulence intensity and eddy structures of the velocity fluctuations in the logarithmic region were primarily analyzed, and their variations in the z (wall-normal) direction were revealed. The primary finding was that the turbulent intensity of wall-normal velocity fluctuations exhibits a sharp upswing in the logarithmic region, which differs from classic scaling law and laboratory results. The upswing of the wall-normal turbulence intensity in the logarithmic region is deemed to be linear based on an ensemble of 20 sets of data. In addition, the wall-normal extent of the correlated structures and wall-normal spectra were compared to low Reynolds number results in the laboratory.