Effect of Surface Waves on Air–Sea Momentum Exchange. Part II: Behavior of Drag Coefficient under Tropical Cyclones

AbstractThis paper models the impact of the presence of foam on the short-wave component of surface waves and momentum exchange in the atmospheric boundary layer at high winds. First, physical experiments were carried out in a wind-wave flume in which foam can be artificially produced at the water surface. Tests were conducted under high-wind-speed conditions where equivalent 10-m wind speed ranged from 12 to 38 m s−1, with measurements made of the airflow parameters, the frequency–wavenumber spectra of the surface waves, the foam coverage of the water surface, and the distribution of the foam bubbles. Analysis of the resulting data indicates that the surface drag coefficient correlates with the fraction of foam coverage and the mean square slope (MSS) of the water surface, and that, at a certain wind speed, the MSS decreases with an increase in the fraction of foam coverage. Based on these results, we suggest a simple model for eddy viscosity in the turbulent boundary layer over a fractionally foam-covered wave surface. The measurements in a laboratory environment are shown to be in good agreement with the predictions of a quasi-linear model of the atmospheric boundary layer over a waved water surface that adopts this eddy viscosity. Adaptation of the proposed model to field conditions is discussed, and the synergetic effect of foam at the water surface and spray in the marine atmospheric boundary layer on ocean surface resistance at high winds is estimated so as to be able to explain the observed peaking dependence of the surface drag coefficient on the 10-m wind speed.

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Impact of Shoaling Ocean Surface Waves on Wind Stress and Drag Coefficient in Coastal Waters: 2. Tropical Cyclones

Journal of Geophysical Research Oceans ◽

10.1029/2020jc016223 ◽

2020 ◽

Vol 125 (7) ◽

Author(s):

Xuanyu Chen ◽

Isaac Ginis ◽

Tetsu Hara

Keyword(s):

Drag Coefficient ◽

Surface Waves ◽

Tropical Cyclones ◽

Wind Stress ◽

Coastal Waters ◽

Ocean Surface ◽

Ocean Surface Waves

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Effect of surface waves on Charnock coefficient under tropical cyclones

Geophysical Research Letters ◽

10.1029/2004gl020988 ◽

2004 ◽

Vol 31 (20) ◽

Cited By ~ 31

Author(s):

Il-Ju Moon

Keyword(s):

Surface Waves ◽

Tropical Cyclones ◽

Effect Of Surface

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EFFECT OF SURFACE WAVES FROM A MOVING OBJECT ON ITS IMAGE DURING RECONSTRUCTION USING APERTURAL SYNTHESIS

Автометрия ◽

10.15372/aut20180309 ◽

2018 ◽

Keyword(s):

Surface Waves ◽

Moving Object ◽

Effect Of Surface

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Genetic Programming based Drag Model with Improved Prediction Accuracy for Fluidization Systems

International Journal of Chemical Reactor Engineering ◽

10.1515/ijcre-2016-0210 ◽

2017 ◽

Vol 15 (2) ◽

Cited By ~ 1

Author(s):

R. R. Sonolikar ◽

M. P. Patil ◽

R. B. Mankar ◽

S. S. Tambe ◽

B. D. Kulkarni

Keyword(s):

Pressure Drop ◽

Genetic Programming ◽

Drag Coefficient ◽

Prediction Accuracy ◽

Volume Fraction ◽

Solid Volume Fraction ◽

Superior Performance ◽

Momentum Exchange ◽

Drag Model ◽

Parameter Ranges

Abstract The drag coefficient plays a vital role in the modeling of gas-solid flows. Its knowledge is essential for understanding the momentum exchange between the gas and solid phases of a fluidization system, and correctly predicting the related hydrodynamics. There exists a number of models for predicting the magnitude of the drag coefficient. However, their major limitation is that they predict widely differing drag coefficient values over same parameter ranges. The parameter ranges over which models possess a good drag prediction accuracy are also not specified explicitly. Accordingly, the present investigation employs Geldart’s group B particles fluidization data from various studies covering wide ranges of Re and εs to propose a new unified drag coefficient model. A novel artificial intelligence based formalism namely genetic programming (GP) has been used to obtain this model. It is developed using the pressure drop approach, and its performance has been assessed rigorously for predicting the bed height, pressure drop, and solid volume fraction at different magnitudes of Reynolds number, by simulating a 3D bubbling fluidized bed. The new drag model has been found to possess better prediction accuracy and applicability over a much wider range of Re and εs than a number of existing models. Owing to the superior performance of the new drag model, it has a potential to gainfully replace the existing drag models in predicting the hydrodynamic behavior of fluidized beds.

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Wave Glider Observations of Surface Waves During Three Tropical Cyclones in the South China Sea

Water ◽

10.3390/w12051331 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1331 ◽

Cited By ~ 2

Author(s):

Di Tian ◽

Han Zhang ◽

Wenyan Zhang ◽

Feng Zhou ◽

Xiujun Sun ◽

...

Keyword(s):

Surface Wave ◽

South China Sea ◽

Surface Waves ◽

Tropical Cyclones ◽

South China ◽

Tangential Direction ◽

China Sea ◽

Wave Forecast ◽

Wave Glider ◽

The Right

Surface waves induced by tropical cyclones (TCs) play an important role in the air–sea interaction, yet are seldom observed. In the 2017 summer, a wave glider in the northern South China Sea successfully acquired the surface wave parameters when three TCs (Hato, Pakhar, and Mawar) passed though successively. During the three TCs, surface wave period increased from 4–6 s to ~8–10 s and surface wave height increased from 0–1 m to 3–8 m. The number of wave crests observed in a time interval of 1024 s decreased from 100–150 to 60–75. The sea surface roughness, a key factor in determining the momentum transfer between air and sea, increased rapidly during Hato, Pakhar, and Mawar. Surface waves rotated clockwise (anti-clockwise) on the right (left) side of the TC track, and generally propagated to the right side of the local cyclonic tangential direction relative to the TC center. The azimuthal dependence of the wave propagation direction is close to sinusoidal in a region within 50–600 km. The intersection angle between surface wave direction and the local cyclonic tangential direction is generally smallest in the right-rear quadrant of the TC and tends to be largest in the left-rear quadrant. This new set of glider wave observational data proves to be useful for assessing wave forecast products and for improvements in corresponding parameterization schemes.

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Structure of the Airflow above Surface Waves

Journal of Physical Oceanography ◽

10.1175/jpo-d-15-0135.1 ◽

2016 ◽

Vol 46 (5) ◽

pp. 1377-1397 ◽

Cited By ~ 64

Author(s):

Marc P. Buckley ◽

Fabrice Veron

Keyword(s):

Surface Waves ◽

Wind Waves ◽

Quadrant Analysis ◽

Momentum Exchange ◽

Turbulent Structures ◽

Mean Velocity ◽

Law Of The Wall ◽

Generate Surface ◽

Turbulent Momentum ◽

Sheltering Effect

AbstractIn recent years, much progress has been made to quantify the momentum exchange between the atmosphere and the oceans. The role of surface waves on the airflow dynamics is known to be significant, but our physical understanding remains incomplete. The authors present detailed airflow measurements taken in the laboratory for 17 different wind wave conditions with wave ages [determined by the ratio of the speed of the peak waves Cp to the air friction velocity u* (Cp/u*)] ranging from 1.4 to 66.7. For these experiments, a combined particle image velocimetry (PIV) and laser-induced fluorescence (LIF) technique was developed. Two-dimensional airflow velocity fields were obtained as low as 100 μm above the air–water interface. Temporal and spatial wave field characteristics were also obtained. When the wind stress is too weak to generate surface waves, the mean velocity profile follows the law of the wall. With waves present, turbulent structures are directly observed in the airflow, whereby low-horizontal-velocity air is ejected away from the surface and high-velocity fluid is swept downward. Quadrant analysis shows that such downward turbulent momentum flux events dominate the turbulent boundary layer. Airflow separation is observed above young wind waves (Cp/u*< 3.7), and the resulting spanwise vorticity layers detached from the surface produce intense wave-coherent turbulence. On average, the airflow over young waves (with Cp/u* = 3.7 and 6.5) is sheltered downwind of wave crests, above the height of the critical layer zc [defined by 〈u(zc)〉 = Cp]. Near the surface, the coupling of the airflow with the waves causes a reversed, upwind sheltering effect.

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