scholarly journals In situ measurements of directional wave spectra from an unmanned aerial system

2021 ◽  
Author(s):  
Clarence Collins ◽  
Katherine Brodie
Keyword(s):  
Single Point ◽  
Field Research ◽  
Ocean Waves ◽  
Adaptive Method ◽  
Technical Note ◽  
Sea Surface ◽  
Unmanned Aerial System ◽  
Frequency Spectra ◽  
Directional Spectrum ◽  
Data Adaptive

This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the ability to measure the directional-frequency spectrum of sea surface waves based on the motion of a floating unmanned aerial system (UAS). The UAS used in this effort was custom built and designed to land on and take off from the sea surface. It was deployed in the vicinity of an operational wave sensor, the 8 m* array, at the US Army Engineer Research and Development Center (ERDC), Field Research Facility (FRF) in Duck, NC. While on the sea surface, an inertial navigation system (INS) recorded the response of the UAS to the incoming ocean waves. Two different INS signals were used to calculate one-dimensional (1D) frequency spectra and compared against the 8 m array. Two-dimensional (2D) directional-frequency spectra were calculated from INS data using traditional single-point-triplet analysis and a data adaptive method. The directional spectrum compared favorably against the 8 m array.

The directional spectrum of ocean waves, and processes of wave generation

1962 ◽  
Vol 265 (1322) ◽  
pp. 286-315 ◽  
Keyword(s):  
Pressure Fluctuations ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Wave Generation ◽  
Air Pressure ◽  
Sea Surface ◽  
Shear Instability ◽  
Main Stage ◽  
Sea Waves ◽  
Directional Spectrum

This paper describes some recent observations of the directional spectrum of sea waves and of air pressure fluctuations at the sea surface, and discusses their implications for theories of wave generation. The angular spread of the wave energy in the generating area is found to be comparable with the ‘resonance angle’ sec -1 ( σU/g ) ( σ = wave frequency, U = wind speed) but lies slightly below it in the middle range of frequencies. The best fit to the directional spectrum F ( σ, ɸ ) is shown to be a cosine-power law: F ( σ, ɸ ) ∝ cos 2s (1/2 ɸ ), where s decreases as σ in ­ creases. At the higher frequencies the total spectrum satisfies the equilibrium law: F ( σ ) ∝ σ -5 . The initial stages of wave generation are attributed to turbulence in the air stream, and the main stage of growth to the shear instability mechanism described by Miles. At the highest frequencies the form of the spectrum suggests that wave breaking plays a predominant part, as proposed by Phillips. The broadening of the angular distribution at the highest frequencies may also be due partly to third-order ‘resonant’ interactions among components of the wave spectrum . The air-pressure fluctuations are nearly in phase with the vertical displacement of the sea surface (over most of the frequency range) and are consistent with the shear-flow model proposed by Miles. The turbulent component of the air pressure is much smaller than was previously supposed.

Directional spectrum of wind-generated ocean waves

1964 ◽  
Vol 19 (3) ◽  
pp. 452-464
Author(s):  
Mahinder S. Uberoi
Keyword(s):  
North Atlantic ◽  
Digital Computer ◽  
Ocean Waves ◽  
Sea Surface ◽  
Published Data ◽  
Directional Spectrum ◽  
Empirical Prediction ◽  
The North ◽  
Optical Computer ◽  
The North Atlantic

Two sets of published data on an area 2700ft. by 1800ft. of sea surface in the North Atlantic are analysed by an optical computer which gives directly the directional spectrum. The results are compared with (i) those of other investigators obtained laboriously by using a digital computer, (ii) the frequency spectrum, and (iii) an empirical prediction.

scholarly journals Matchup Characteristics of Sea Surface Salinity Using a High-Resolution Ocean Model

2021 ◽  
Vol 13 (15) ◽  
pp. 2995
Author(s):  
Frederick M. Bingham ◽  
Severine Fournier ◽  
Susannah Brodnitz ◽  
Karly Ulfsax ◽  
Hong Zhang
Keyword(s):  
High Resolution ◽  
Time Window ◽  
Single Point ◽  
Ocean Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Argo Floats ◽  
Statistical Measures ◽  
Salinity Difference

Sea surface salinity (SSS) satellite measurements are validated using in situ observations usually made by surfacing Argo floats. Validation statistics are computed using matched values of SSS from satellites and floats. This study explores how the matchup process is done using a high-resolution numerical ocean model, the MITgcm. One year of model output is sampled as if the Aquarius and Soil Moisture Active Passive (SMAP) satellites flew over it and Argo floats popped up into it. Statistical measures of mismatch between satellite and float are computed, RMS difference (RMSD) and bias. The bias is small, less than 0.002 in absolute value, but negative with float values being greater than satellites. RMSD is computed using an “all salinity difference” method that averages level 2 satellite observations within a given time and space window for comparison with Argo floats. RMSD values range from 0.08 to 0.18 depending on the space–time window and the satellite. This range gives an estimate of the representation error inherent in comparing single point Argo floats to area-average satellite values. The study has implications for future SSS satellite missions and the need to specify how errors are computed to gauge the total accuracy of retrieved SSS values.

scholarly journals Impact of Sea Spray and Sea Surface Roughness on the Upper Ocean Response to Super Typhoon Haitang (2005)

2021 ◽  
Author(s):  
Lianxin Zhang ◽  
Xuefeng Zhang ◽  
William Perrie ◽  
Changlong Guan ◽  
Bo Dan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Ocean Waves ◽  
Sea Surface ◽  
Sea Spray ◽  
Upper Ocean ◽  
Surface Cooling ◽  
Super Typhoon ◽  
Sea Surface Roughness ◽  
Momentum Fluxes ◽  
The Right

AbstractA coupled ocean-wave-sea spray model system is used to investigate the impacts of sea spray and sea surface roughness on the response of the upper ocean to the passage of the super typhoon Haitang. Sea spray mediated heat and momentum fluxes are derived from an improved version of Fairall’s heat fluxes formulation (Zhang et al., 2017) and Andreas’s sea spray-mediated momentum flux models. For winds ranging from low to extremely high speeds, a new parameterization scheme for the sea surface roughness is developed, in which the effects of wave state and sea spray are introduced. In this formulation, the drag coefficient has minimal values over the right quadrant of the typhoon track, along which the typhoon-generated waves are longer, smoother, and older, compared to other quadrants. Using traditional interfacial air-sea turbulent (sensible, latent, and momentum) fluxes, the sea surface cooling response to typhoon Haitang is overestimated by 1 °C, which can be compensated by the effects of sea spray and ocean waves on the right side of the storm. Inclusion of sea spray-mediated turbulent fluxes and sea surface roughness, modulated by ocean waves, gives enhanced cooling along the left edges of the cooling area by 0.2 °C, consistent with the upper ocean temperature observations.

Scanning laser wave recorder with registration of “instantaneous” sea surface profiles

2021 ◽  
Author(s):  
V.V. Sterlyadkin ◽  
K.V. Kulikovsky ◽  
A.V. Kuzmin ◽  
E.A. Sharkov ◽  
M.V. Likhacheva
Keyword(s):  
Spatial Scales ◽  
Wind Waves ◽  
Single Point ◽  
Video Recording ◽  
Surface Profile ◽  
Weather Conditions ◽  
Sea Surface ◽  
Sea Waves ◽  
Wide Range ◽  
Wave Recorder

AbstractA direct optical method for measuring the “instantaneous” profile of the sea surface with an accuracy of 1 mm and a spatial resolution of 3 mm is described. Surface profile measurements can be carried out on spatial scales from units of millimeters to units of meters with an averaging time of 10−4 s. The method is based on the synchronization of the beginning of scanning a laser beam over the sea surface and the beginning of recording the radiation scattered on the surface onto the video camera matrix. The heights of all points of the profile are brought to a single point in time, which makes it possible to obtain “instantaneous” profiles of the sea surface with the frequency of video recording. The measurement technique and data processing algorithm are described. The errors of the method are substantiated. The results of field measurements of the parameters of sea waves are presented: amplitude spectra, distribution of slopes at various spatial averaging scales. The applied version of the wave recorder did not allow recording capillary oscillations, but with some modernization it will be possible. The method is completely remote, does not distort the properties of the surface, is not affected by wind, waves and sea currents, it allows you to measure the proportion of foam on the surface. The possibility of applying the proposed method at any time of the day and in a wide range of weather conditions has been experimentally proved.

A stable data adaptive method for matched‐field array processing in acoustic waveguides

1989 ◽  
Vol 85 (S1) ◽  
pp. S17-S17
Author(s):  
C. L. Byrne ◽  
R. I. Brent ◽  
C. Feuillade ◽  
D. R. DelBalzo
Keyword(s):  
Array Processing ◽  
Adaptive Method ◽  
Acoustic Waveguides ◽  
Data Adaptive

From Single Point Gauge to Spatio-Temporal Measurement of Ocean Waves: Prospects and Perspectives

2014 ◽  
Author(s):  
Paul C. Liu ◽  
J. C. Nieto Borge ◽  
German Rodriguez ◽  
Keith R. MacHutchon ◽  
Hsuan S. Chen
Keyword(s):  
Paradigm Shift ◽  
New World ◽  
Single Point ◽  
Ocean Waves ◽  
Data System ◽  
Preliminary Attempt ◽  
Recent Advancement ◽  
New Challenges ◽  
Spatio Temporal ◽  
Temporal Measurement

With the recent advancement of spatial measurements of ocean waves, we are clearly facing new challenges regarding how to handle an expanded new data system when it becomes widely available. In this paper we wish to present a preliminary attempt at confronting these prospects. Because the data is still very limited at present and also conceptually new, it’s a new, unfamiliar, and unrelenting world to pursue. We need a paradigm shift away from our familiar single-point conceptualization in order to effective approach the new world of truly spatial ocean waves.

scholarly journals Predicting ocean waves along the US east coast during energetic winter storms: sensitivity to whitecapping parameterizations

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 691-715 ◽  
Author(s):  
Mohammad Nabi Allahdadi ◽  
Ruoying He ◽  
Vincent S. Neary
Keyword(s):  
East Coast ◽  
Ocean Waves ◽  
Source Terms ◽  
Frequency Spectra ◽  
Winter Storms ◽  
Wave Parameters ◽  
The Us ◽  
Wind Input ◽  
Simulation Results ◽  
Us East Coast

Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the Simulating Waves Nearshore (SWAN) wave model is evaluated for waves generated along and off the US east coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use “Komen” and “Westhuysen” to denote these two approaches). Observations of wave parameters and frequency spectra at four National Data Buoy Center (NDBC) buoys are used to evaluate simulation results. Model–data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the east coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the “slanting fetch” effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available source terms (wind input, whitecapping, and quadruplet) in models and their interaction. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

scholarly journals Predicting Ocean Waves along the U.S. East Coast During Energetic Winter Storms: sensitivity to Whitecapping parameterizations

2018 ◽  
Author(s):  
Mohammad Nabi Allahdadi ◽  
Ruoying He ◽  
Vincent S. Neary
Keyword(s):  
East Coast ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Spectral Energy ◽  
Frequency Spectra ◽  
Winter Storms ◽  
Wave Parameters ◽  
Wind Input ◽  
Simulation Results ◽  
The U.S

Abstract. The performance of two methods for quantifying whitecapping dissipation incorporated in the SWAN wave model is evaluated for waves generated along and off the U.S. East Coast under energetic winter storms with a predominantly westerly wind. Parameterizing the whitecapping effect can be done using the Komen-type schemes, which are based on mean spectral parameters, or the saturation-based (SB) approach of van der Westhuysen (2007), which is based on local wave parameters and the saturation level concept of the wave spectrum (we use Komen and Westhuysen to denote these two approaches). Observations of wave parameters and frequency spectra at four NDBC buoys are used to evaluate simulation results. Model-data comparisons show that when using the default parameters in SWAN, both Komen and Westhuysen methods underestimate wave height. Simulations of mean wave period using the Komen method agree with observations, but those using the Westhuysen method are substantially lower. Examination of source terms shows that the Westhuysen method underestimates the total energy transferred into the wave action equations, especially in the lower frequency bands that contain higher spectral energy. Several causes for this underestimation are identified. The primary reason is the difference between the wave growth conditions along the East Coast during winter storms and the conditions used for the original whitecapping formula calibration. In addition, some deficiencies in simulation results are caused along the coast by the slanting fetch effect that adds low-frequency components to the 2-D wave spectra. These components cannot be simulated partly or entirely by available wind input formulations. Further, the effect of boundary layer instability that is not considered in the Komen and Westhuysen whitecapping wind input formulas may cause additional underestimation.

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