Inferring Ice/Ocean Surface Roughness from Horizontal Current Measurements

1989 ◽  
Vol 111 (2) ◽  
pp. 155-159 ◽  
Author(s):  
M. G. McPhee
Keyword(s):  
Boundary Layer ◽  
Surface Roughness ◽  
Local Stress ◽  
Horizontal Stress ◽  
Current Speed ◽  
Small Scale ◽  
Horizontal Current ◽  
Similarity Model ◽  
Scale Roughness ◽  
Shear Production

Turbulence measurements in the underice boundary layer from two Arctic drift stations are used to develop a method for estimating the small-scale roughness, zo, of the ice underside from horizontal current and current variance, sampled at one level. Horizontal variance is shown to be well correlated with turbulent kinetic energy (TKE). Measurements also indicate that at depths where turbulence is fully developed to the surface roughness, shear production of TKE is approximately in balance with viscous dissipation, so that the magnitude of local horizontal stress is proportional to flow variance. A similarity model is used to extrapolate local stress to the interface, and zo is estimated from the logarithmic profile for current speed. The method has application for using remote data buoys, equipped with “smart” current meters, for mapping the underice roughness.

scholarly journals A MODIFIED TWO-SCALE MICROWAVE SCATTERING MODEL FOR A GAUSSIAN-DISTRIBUTED CONDUCTING ROUGH SURFACE

2018 ◽  
Vol XLII-3 ◽  
pp. 2141-2146
Author(s):  
F. Yu ◽  
H. Wang ◽  
Z. Y. Chen
Keyword(s):  
Surface Roughness ◽  
Rough Surface ◽  
Large Scale ◽  
Incident Angle ◽  
Wavelet Packet ◽  
Small Scale ◽  
Backscattering Coefficient ◽  
Microwave Scattering ◽  
Scattering Model ◽  
Scale Roughness

A modified two-scale microwave scattering model (MTSM) was presented to describe the scattering coefficient of natural rough surface in this paper. In the model, the surface roughness was assumed to be Gaussian so that the surface height <i>z(x, y)</i> can be split into large-scale and small-scale components relative to the electromagnetic wavelength by the wavelet packet transform. Then, the Kirchhoff Model (KM) and Small Perturbation Method (SPM) were used to estimate the backscattering coefficient of the large-scale and small-scale roughness respectively. Moreover, the ‘tilting effect’ caused by the slope of large-scale roughness should be corrected when we calculated the backscattering contribution of the small-scale roughness. Backscattering coefficient of the MTSM was the sum of backscattering contribution of both scale roughness surface. The MTSM was tested and validated by the advanced integral equation model (AIEM) for dielectric randomly rough surface, the results indicated that, the MTSM accuracy were in good agreement with AIEM when incident angle was less than 30&amp;deg; (<i>&amp;theta;<sub>i</sub></i>&amp;thinsp;&amp;lt;30&amp;deg;) and the surface roughness was small (<i>ks</i>&amp;thinsp;=&amp;thinsp;0.354).

INVESTIGATION OF SURFACE ROUGHNESS IMPACT ON MEAN WIND FLOW USING RNG k-ε MODEL

2016 ◽  
Vol 78 (9) ◽  
Author(s):  
Sheikh Ahmad Zaki Shaikh Salim ◽  
Ahmad Zaki Jaafar ◽  
Ahmad Faiz Mohammad ◽  
Sukri Mohamed Mat Ali ◽  
Azli Abd Razak
Keyword(s):  
Surface Roughness ◽  
Streamwise Velocity ◽  
Navier Stokes ◽  
Future Research ◽  
Small Scale ◽  
Wind Flow ◽  
Roughness Elements ◽  
The Impact ◽  
Scale Roughness ◽  
Packing Densities

Wind flow in the urban boundary layer is influenced by both large- and small-scale surface roughness. In this study, Reynolds-averaged Navier-Stokes simulations using the renormalisation group (RNG) k-ε model were performed to study the wind flow in square arrays with small-scale roughness elements at the front and back of cubical obstacles at packing densities of 25.0% and 30.9%. The presence of small-scale roughness reduces streamwise velocity but increases turbulent kinetic energy. Moreover, small vortices are formed within the canopy because of small-scale roughness. The generated streamwise velocity profiles are similar at packing densities of 25.0% and 30.9%, but the drag coefficient is higher in the latter case. In brief, the impact of small-scale roughness on urban wind flow is considerable. The results of this study can contribute to future research on wind flow, particularly in the urban environment.  

scholarly journals Ice scallops: a laboratory investigation of the ice–water interface

2019 ◽  
Vol 873 ◽  
pp. 942-976 ◽  
Author(s):  
Mitchell Bushuk ◽  
David M. Holland ◽  
Timothy P. Stanton ◽  
Alon Stern ◽  
Callum Gray
Keyword(s):  
Boundary Layer ◽  
Small Scale ◽  
Water Interface ◽  
Surface Geometry ◽  
Interface Evolution ◽  
Ice Surface ◽  
Primary Finding ◽  
Formation And Evolution ◽  
Ice Water ◽  
Shear Production

Ice scallops are a small-scale (5–20 cm) quasi-periodic ripple pattern that occurs at the ice–water interface. Previous work has suggested that scallops form due to a self-reinforcing interaction between an evolving ice-surface geometry, an adjacent turbulent flow field and the resulting differential melt rates that occur along the interface. In this study, we perform a series of laboratory experiments in a refrigerated flume to quantitatively investigate the mechanisms of scallop formation and evolution in high resolution. Using particle image velocimetry, we probe an evolving ice–water boundary layer at sub-millimetre scales and 15 Hz frequency. Our data reveal three distinct regimes of ice–water interface evolution: a transition from flat to scalloped ice; an equilibrium scallop geometry; and an adjusting scallop interface. We find that scalloped-ice geometry produces a clear modification to the ice–water boundary layer, characterized by a time-mean recirculating eddy feature that forms in the scallop trough. Our primary finding is that scallops form due to a self-reinforcing feedback between the ice-interface geometry and shear production of turbulent kinetic energy in the flow interior. The length of this shear production zone is therefore hypothesized to set the scallop wavelength.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

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