The Scaling and Structure of the Estuarine Bottom Boundary Layer

2005 ◽  
Vol 35 (1) ◽  
pp. 55-71 ◽  
Author(s):  
Mark T. Stacey ◽  
David K. Ralston
Keyword(s):  
Boundary Layer ◽  
Reynolds Stress ◽  
Friction Velocity ◽  
Turbulent Energy ◽  
Buoyancy Flux ◽  
Bottom Boundary Layer ◽  
Stress Profile ◽  
Layer Height ◽  
Bottom Boundary ◽  
Boundary Layer Height

Abstract A two-week dataset from a partially and periodically stratified estuary quantifies variability in the turbulence across the tidal and spring–neap time scales. These observations have been fit with a two-parameter model of the Reynolds stress profile, which produces estimates of the time variation of the bottom boundary layer height and the friction velocity. Conditions at the top of the bottom boundary layer indicate that the dynamics governing the development of the estuarine bottom boundary layer are different on ebb tides than on flood tides. The asymmetry in the flow is explained by consideration of the strain-induced buoyancy flux, which is stabilizing on ebb tides and destabilizing on flood tides. Based on these observations, a scaling approach to estimating estuarine bottom boundary layer parameters (height and friction velocity) is presented, which includes a modified Monin–Obukhov length scale to account for the horizontal buoyancy flux created by the sheared advection. Comparison with the observations of boundary layer height and friction velocity suggests that this approach may be successful in predicting bottom boundary layer parameters in estuaries and coastal regions with significant horizontal buoyancy fluxes. Comparison between the strain-induced buoyancy flux and shear production indicates that the straining of the density field is an important contributor to the turbulent kinetic energy budget and creates an asymmetry in turbulent energy between ebb and flood tides. It appears that the structure of the turbulence, specifically the ratio of the Reynolds stress to the turbulent energy, is also modified by tidal straining, further accentuating the ebb–flood asymmetries.

scholarly journals Estuarine Boundary Layer Mixing Processes: Insights from Dye Experiments*

2007 ◽  
Vol 37 (7) ◽  
pp. 1859-1877 ◽  
Author(s):  
Robert J. Chant ◽  
Wayne R. Geyer ◽  
Robert Houghton ◽  
Elias Hunter ◽  
James Lerczak
Keyword(s):  
Boundary Layer ◽  
Richardson Number ◽  
Flood Tide ◽  
Buoyancy Flux ◽  
Bottom Boundary Layer ◽  
Buoyancy Frequency ◽  
Entrainment Rate ◽  
Diapycnal Mixing ◽  
Bottom Boundary ◽  
Shear Production

Abstract A series of dye releases in the Hudson River estuary elucidated diapycnal mixing rates and temporal variability over tidal and fortnightly time scales. Dye was injected in the bottom boundary layer for each of four releases during different phases of the tide and of the spring–neap cycle. Diapycnal mixing occurs primarily through entrainment that is driven by shear production in the bottom boundary layer. On flood the dye extended vertically through the bottom mixed layer, and its concentration decreased abruptly near the base of the pycnocline, usually at a height corresponding to a velocity maximum. Boundary layer growth is consistent with a one-dimensional, stress-driven entrainment model. A model was developed for the vertical structure of the vertical eddy viscosity in the flood tide boundary layer that is proportional to u2*/N∞, where u* and N∞ are the bottom friction velocity and buoyancy frequency above the boundary layer. The model also predicts that the buoyancy flux averaged over the bottom boundary layer is equal to 0.06N∞u2* or, based on the structure of the boundary layer equal to 0.1NBLu2*, where NBL is the buoyancy frequency across the flood-tide boundary layer. Estimates of shear production and buoyancy flux indicate that the flux Richardson number in the flood-tide boundary layer is 0.1–0.18, consistent with the model indicating that the flux Richardson number is between 0.1 and 0.14. During ebb, the boundary layer was more stratified, and its vertical extent was not as sharply delineated as in the flood. During neap tide the rate of mixing during ebb was significantly weaker than on flood, owing to reduced bottom stress and stabilization by stratification. As tidal amplitude increased ebb mixing increased and more closely resembled the boundary layer entrainment process observed during the flood. Tidal straining modestly increased the entrainment rate during the flood, and it restratified the boundary layer and inhibited mixing during the ebb.

Langmuir turbulence in shallow water. Part 2. Large-eddy simulation

2007 ◽  
Vol 576 ◽  
pp. 63-108 ◽  
Author(s):  
A. E. TEJADA-MARTÍNEZ ◽  
C. E. GROSCH
Keyword(s):  
Boundary Layer ◽  
Shallow Water ◽  
Reynolds Stress ◽  
Bottom Boundary Layer ◽  
Reynolds Stresses ◽  
Component Structure ◽  
Bottom Boundary ◽  
Eddy Simulation ◽  
Shear Current ◽  
Anisotropy Tensor

Results of large-eddy simulation (LES) of Langmuir circulations (LC) in a wind-driven shear current in shallow water are reported. The LC are generated via the well-known Craik–Leibovich vortex force modelling the interaction between the Stokes drift, induced by surface gravity waves, and the shear current. LC in shallow water is defined as a flow in sufficiently shallow water that the interaction between the LC and the bottom boundary layer cannot be ignored, thus requiring resolution of the bottom boundary layer. After the introduction and a description of the governing equations, major differences in the statistical equilibrium dynamics of wind-driven shear flow and the same flow with LC (both with a bottom boundary layer) are highlighted. Three flows with LC will be discussed. In the first flow, the LC were generated by intermediate-depth waves (relative to the wavelength of the waves and the water depth). The amplitude and wavelength of these waves are representative of the conditions reported in the observations of A. E. Gargett & J. R. Wells in Part 1 (J. Fluid Mech. vol .000, 2007, p. 00). In the second flow, the LC were generated by shorter waves. In the third flow, the LC were generated by intermediate waves of greater amplitude than those in the first flow. The comparison between the different flows relies on visualizations and diagnostics including (i) profiles of mean velocity, (ii) profiles of resolved Reynolds stress components, (iii) autocorrelations, (iv) invariants of the resolved Reynolds stress anisotropy tensor and (v) balances of the transport equations for mean resolved turbulent kinetic energy and resolved Reynolds stresses. Additionally, dependencies of LES results on Reynolds number, subgrid-scale closure, size of the domain and grid resolution are addressed.In the shear flow without LC, downwind (streamwise) velocity fluctuations are characterized by streaks highly elongated in the downwind direction and alternating in sign in the crosswind (spanwise) direction. Forcing this flow with the Craik–Leibovich force generating LC leads to streaks with larger characteristic crosswind length scales consistent with those recorded by observations. In the flows with LC, in the mean, positive streaks exhibit strong intensification near the bottom and near the surface leading to intensified downwind velocity ‘jets’ in these regions. In the flow without LC, such intensification is noticeably absent. A revealing diagnostic of the structure of the turbulence is the depth trajectory of the invariants of the resolved Reynolds stress anisotropy tensor, which for a realizable flow must lie within the Lumley triangle. The trajectory for the flow without LC reveals the typical structure of shear-dominated turbulence in which the downwind component of the resolved normal Reynolds stresses is greater than the crosswind and vertical components. In the near bottom and surface regions, the trajectory for the flow with LC driven by wave and wind forcing conditions representative of the field observations reveals a two-component structure in which the downwind and crosswind components are of the same order and both are much greater than the vertical component. The two-component structure of the Langmuir turbulence predicted by LES is consistent with the observations in the bottom third of the water column above the bottom boundary layer.

scholarly journals Turbulent and Boundary Layer Characteristics during VOCALS-REx

2020 ◽  
Author(s):  
Dillon S. Dodson ◽  
Jennifer D. Small Griswold
Keyword(s):  
Boundary Layer ◽  
Mixed Boundary ◽  
Turbulent Energy ◽  
Cloud Layer ◽  
Cloud Base ◽  
Small Scale ◽  
Synoptic Scale ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Turbulent Characteristics

Abstract. Stratocumulus clouds have a significant impact on climate due to their large spatial extent, with areas of enhanced coverage termed stratocumulus decks. How turbulence evolves with time and influences the stratocumulus deck properties however, in particular throughout the vertical profile of the boundary layer, is still lacking through model parameterizations of the small-scale flow. Collecting in situ data to better understand the turbulence and physical processes occuring within the stratocumu- lus deck therefore key to better model parameterizations. Boundary layer and turbulent characteristics, along with synoptic scale changes in these properties over time, are examined using data collected from 14 research flights made with the CIR- PAS Twin Otter Aircraft. Data was collected during the VOMOS Ocean-Cloud-Atmosphere-Land Study-Regional Experiment (VOCALS-REx) at Point Alpha in October and November of 2008 off the cost of South America (20°S, 72°W). Findings show that the influence of a synoptic system on Nov 1st and 2nd brings in a moist layer above the boundary layer, leading to a deepening cloud layer and precipitation during passage, and a large increase in boundary layer height and cloud thinning after passage. The maximum value in turbulent kinetic energy (TKE) was measured on Nov. 1st due to precipitation destabilizing the sub-cloud layer while a minimum occurred on Nov. 2nd after precipitation had ceased due to turbulent mixing overturning the boundary layer and depleting the initial turbulent energy produced from the evaporation of precipitation below cloud base. Turbulent properties averaged over all 14 flights reach a maximum near cloud middle (between normalized in- cloud values of 0.25–0.75), with well mixed boundary layers experiencing two peaks in TKE, one near cloud base due to latent heat release and another near cloud top due to evaporational cooling. Overall, it appears that turbulence measured at Point Alpha is weaker than that measured over the open ocean to the west of Point Alpha, and that measured during other scientific campaigns. Synoptic scale analysis suggests that as the geopotential height decreases, the boundary layer height and entrainment zone thickness increases, accompanied by a decrease of in-cloud and below-cloud turbulence, and vice versa.

Evaluating Formulations of Stable Boundary Layer Height

2004 ◽  
Vol 43 (11) ◽  
pp. 1736-1749 ◽  
Author(s):  
D. Vickers ◽  
L. Mahrt
Keyword(s):  
Boundary Layer ◽  
Stable Boundary Layer ◽  
Richardson Number ◽  
Critical Value ◽  
Buoyancy Flux ◽  
Turbulence Energy ◽  
Bulk Richardson Number ◽  
Layer Height ◽  
Stable Boundary ◽  
Boundary Layer Height

Abstract Stable boundary layer height h is determined from eddy correlation measurements of the vertical profiles of the buoyancy flux and turbulence energy from a tower over grassland in autumn, a tower over rangeland with variable snow cover during winter, and aircraft data in the stable marine boundary layer generated by warm air advection over a cool ocean surface in summer. A well-defined h within the tower layer at the grass site (lowest 50 m) and the snow site (lowest 30 m) was definable only about 20% of the time. In the remaining stable periods, the buoyancy flux and turbulence energy either (a) remained constant with height, indicating a deep boundary layer, (b) increased with height, or (c) varied erratically with height. Approximately one-half of the tower profiles did not fit the traditional concepts of a boundary layer. The well-defined cases of h are compared with various formulations for the equilibrium depth of the stably stratified boundary layer based on the Richardson number or surface fluxes. The diagnostic models for h have limited success in explaining both the variance and mean magnitude of h at all three sites. The surface bulk Richardson number and gradient Richardson number approaches perform best for the combined data. For the surface bulk Richardson number method, the required critical value varies systematically between sites. The surface bulk Richardson number approach is modified to include a critical value that depends on the surface Rossby number, which incorporates the influence of surface roughness and wind speed on boundary layer depth.

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