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Journal ArticleDOI

Estimating Wind Speed and Direction Using Wave Spectra

01 Feb 2020-Journal of Geophysical Research (John Wiley & Sons, Ltd)-Vol. 125, Iss: 2
TL;DR: In this article, the authors used spectral wave observations to estimate wind speed and direction based on the assumption of a universal shape of the wave energy spectrum in the equilibrium range and the presence of a logarithmic wind speed profile above the ocean surface.
Abstract: Compact wave buoys are increasingly used to provide monitoring of coastal and oceanic conditions by measuring surface waves in real time. Due to their relatively compact size, they are generally not suited to measure wind directly. However, since the wave field is intrinsically coupled to the wind field, wave measurements can serve as a proxy observation of ocean surface winds. In this study, we use spectral wave observations to estimate wind speed and direction based on the assumption of a universal shape of the wave energy spectrum in the equilibrium range and the presence of a logarithmic wind speed profile above the ocean surface. The wind speed and direction were estimated between 2014 and 2017 at more than a 100 coastal sites with colocated wave and wind observations. Estimates of wind speed and direction based on wave measurements have a root‐mean‐square error of 2 m/s for wind speeds between 3 and 12 m/s (and a relative error of 17% for wind speeds between 10 and 20 m/s) and up to 20° for wind speeds between 10 and 20 m/s. The accuracy of proxy measurements of wind depends on fetch, wave steepness, wave age, directional alignment between wind and dominant waves, and temporal variability of the wind. Further, we show that estimates of wind speed and direction improve considerably as the size of the buoy is reduced.
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Citations
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Journal ArticleDOI
TL;DR: In this paper, the authors present a recently deployed network of free-drifting satellite-connected surface weather buoys that provides long-dwell coverage of surface weather in the northern Pacific Ocean basin.

38 citations

Journal ArticleDOI
TL;DR: In this paper , the authors examined in situ observations of wave spectra spanning 2012-2021 in the western Arctic marginal ice zone (MIZ) and found that local wind waves are fetch-limited between ice floes with heights less than 1'm.
Abstract: The retreat of Arctic sea ice is enabling increased ocean wave activity at the sea ice edge, yet the interactions between surface waves and sea ice are not fully understood. Here, we examine in situ observations of wave spectra spanning 2012–2021 in the western Arctic marginal ice zone (MIZ). Swells exceeding 30 cm are rarely observed beyond 100 km inside the MIZ. However, local wind waves are observed in patches of open water amid partial ice cover during the summer. These local waves remain fetch-limited between ice floes with heights less than 1 m. To investigate these waves at climate scales, we conduct experiments varying wave attenuation and generation in ice with a global model including coupled interactions between waves and sea ice. A weak high-frequency attenuation rate is required to simulate the local waves in observations. The choices of attenuation scheme and wind input in ice have a remarkable impact on the extent of wave activity across ice-covered oceans, particularly in the Antarctic. As well as demonstrating the need for stronger constraints on wave attenuation, our results suggest that further attention should be directed towards locally generated wind waves and their role in sea ice evolution. This article is part of the theme issue ‘Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks’.

11 citations

Journal ArticleDOI
TL;DR: In this article, a distributed sensor network of over one hundred free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019 and the Spotter buoys used in the network represent a next generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature.
Abstract: A distributed sensor network of over one hundred free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open ocean regions. Despite the demand for better weather forecasts and climate data in our oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Due to the large expanse of our oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open ocean weather data set and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in our oceans.

8 citations

Journal Article
TL;DR: In this article, it is shown how the drag of the sea surface can be computed from the wind speed and the sea state, based on conservation of momentum in the boundary layer above the sea, which allows to relate the drag to the properties of the momentum exchange between the sea waves and the atmosphere.
Abstract: It is shown how the drag of the sea surface can be computed from the wind speed and the sea state. The approach, applicable both for fully developed and for developing seas, is based on conservation of momentum in the boundary layer above the sea, which allows one to relate the drag to the properties of the momentum exchange between the sea waves and the atmosphere.

7 citations

Journal ArticleDOI
TL;DR: In this article, the authors extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record.
Abstract: Quality control measures for ocean waves observations are necessary to give confidence of their accuracy. It is common practice to detect anomalies or outliers in surface displacement observations by applying a standard deviation threshold. Besides being a purely statistical method, this quality control procedure is likely to flag extreme wave events erroneously, thereby impacting higher-order descriptions of the wave field. In this paper we extend the use of the statistical phase-space threshold, an established outlier detection method in the field of turbulence, to detect anomalies in a wave record. We show that a wave record in phase space (here defined as a diagram of displacement against acceleration) can be enclosed by a predictable ellipse where the major and minor axes are defined by the spectral properties of the wave field. By using the parameterized ellipse in phase space as a threshold to identify wave anomalies, this is a semiphysical filtering method. Wave buoy data obtained from a mooring deployed near King George Island, Antarctica [as part of the Antarctic Modeling Observation System (ATMOS)], and laser altimeter data obtained at the Northwest Shelf of Australia were used to demonstrate the functioning of the filtering methodology in identifying wave anomalies. Synthetic data obtained using a high-order spectral model are used to identify how extreme waves are positioned in phase space.

4 citations

References
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Journal ArticleDOI
TL;DR: In this paper, the vertical distribution of horizontal mean wind in the lowest 8 metres over a reservoir (1·6 km × 1 km) has been measured using sensitive anemometers freely exposed from a fixed mast in water 16 m deep, the fetch being more than 1 km.
Abstract: The vertical distribution of horizontal mean wind in the lowest 8 metres over a reservoir (1·6 km × 1 km) has been measured using sensitive anemometers freely exposed from a fixed mast in water 16 m deep, the fetch being more than 1 km. The resulting profiles are closely logarithmic, the small differences being systematic and possibly due to the thermal instability which existed when the measurements were made. The usual law for wind profiles in neutral stability is where u is the wind speed at height z, k is von Karman's constant, log z (0) the intercept on the log z axis, and u* the so-called friction velocity defined by τ0 = pu, τ0 being the surface drag and rH the density of the air. To characterize the profiles u*/k, their slope, was plotted in relation to z (0), their intercept; this allowed a direct comparison with other profiles, in particular those recently measured in a laboratory channel by Sibul. The agreement was better than expected and indicated that z (0) was comparatively independent of fetch and stability but was largely determined by u*. The relation between u* and z (0) agreed roughly with the simplest non-dimensional relation between them, gz (0)/u = constant, so that one is led to a generalized wind profile for flow over a water surface which specifies the drag, given the wind at one known height. An approximate value of the constant is 12·5. This expression can be compared with earlier work. The better wind-profile observations show rough agreement; the experimental scatter is necessarily large since a water surface is aerodynamically much smoother than most land surfaces, precision anemometry in difficult circumstances being required to provide sufficiently precise values. Oceanographic measurements of the tilt of water surfaces are in fair agreement at high wind speeds but at low wind speeds the data are conflicting. The early results which imply that the drag-coefficient (u/u2) increases with decreasing wind speed in light winds are thought to be in error; some support for this belief comes from recent estimates of drag using a modified ageostrophic technique, which agree roughly among themselves and with the general expression.

1,792 citations


"Estimating Wind Speed and Direction..." refers background in this paper

  • ...(4) Here, 𝜐 is the kinematic viscosity of air and 𝛼 is the Charnock parameter (Charnock, 1955; Edson et al., 2013)....

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  • ...Common values are 𝛽 (≈ 0.012, Juszko et al., 1995), 𝛼 (≈ 0.012, Charnock, 1955), and I(p) (≈ 2.5, Thomson et al., 2013), but it is expected that optimal values for this inversion depends on the observation platform used and the associated response to the surface wave field....

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Journal ArticleDOI
TL;DR: In this paper, the nature of the equilibrium range is reexamined, using the dynamical insights into wave-wave interactions, energy input from the wind and wave-breaking that have been developed since 1960.
Abstract: Recent measurements of wave spectra and observations by remote sensing of the sea surface indicate that the author's (1958) conception of an upper-limit asymptote to the spectrum, independent of wind stress, is no longer tenable. The nature of the equilibrium range is reexamined, using the dynamical insights into wave–wave interactions, energy input from the wind and wave-breaking that have been developed since 1960. With the assumption that all three of these processes are important in the equilibrium range, the wavenumber spectrum is found to be of the form , where p ∼ ½ and the frequency spectrum is proportional to u*gσ−4. These forms have been found by Kitaigorodskii (1983) on a quite different dynamical basis; the latter is consistent with the form found empirically by Toba (1973) and later workers. Various derived spectra, such as those of the sea-surface slope and of an instantaneous line traverse of the surface, are also given, as well as directional frequency spectra and frequency spectra of slope.The theory also provides expressions for the spectral rates of action, energy and momentum loss from the equilibrium range by wave-breaking and for the spectrally integrated rates across the whole range. These indicate that, as a wave field develops with increasing fetch or duration, the momentum flux to the underlying water by wave-breaking increases asymptotically to a large fraction of the total wind stress and that the energy flux to turbulence in the water, occurring over a wide range of scales, increases logarithmically as the extent of the equilibrium range increases. Interrelationships are pointed out among different sets of measurements such as the various spectral levels, the directional distributions, the total mean-square slope and the ratio of downwind to crosswind mean-square slopes.Finally, some statistical characteristics of the breaking events are deduced, including the expected length of breaking fronts (per unit surface area) with speeds of advance between c and c+dc and the number of such breaking events passing a given point per unit time. These then lead to simple expressions for the density of whitecapping, those breaking events that produce bubbles and trails of foam, the total number of whitecaps passing a given point per unit time and, more tenuously, the whitecap coverage.

858 citations


"Estimating Wind Speed and Direction..." refers background in this paper

  • ...As a result, the momentum transfer (or wind stress) directly affects the form of the spectral tail (Makin et al., 1995)....

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Journal ArticleDOI
TL;DR: Waves in Oceanic and Coastal Waters by Holthuijsen, Leo H. as discussed by the authors is a book about oceanic and coastal waters with a focus on linear wave theory (coastal waters).
Abstract: (PDF) Waves in Oceanic and Coastal WatersWaves in Oceanic and Coastal WatersWaves in Oceanic and Coastal Waters by Holthuijsen, Leo H ...Waves in Oceanic and Coastal Waters (February 5, 2007 ...Linear wave theory (coastal waters) (Chapter 7) Waves in ...Waves In Oceanic And CoastalThis page intentionally left blank UNAM Campus SisalWaves in Oceanic and Coastal Waters eBook by Leo H ...Waves in Oceanic and Coastal Waters: Amazon.co.uk ...Bing: Waves In Oceanic And CoastalWaves in Oceanic and Coastal Waters: Holthuijsen, Leo H ...WAVES IN OCEANIC AND COASTAL WATERS, by Leo H. Holthuijsen ...Waves in Oceanic and Coastal Waters: Holthuijsen, Leo H ...Waves in Oceanic and Coastal Waters by Leo H. Holthuijsen(PDF) Waves in Oceanic and Coastal Waters, by Leo H ...Waves in Oceanic and Coastal Waters NASA/ADSWaves in Oceanic and Coastal Waters KnovelWaves in Oceanic and Coastal Waters: Holthuijsen, Leo ...9780521129954-Waves in Oceanic and Coastal WatersStatistics (Chapter 4) Waves in Oceanic and Coastal Waters

656 citations


"Estimating Wind Speed and Direction..." refers background in this paper

  • ...…by wave breaking Sdiss and nonlinear wave-wave interaction Snl, which may be approximated through a spectral energy balance of the form (e.g., Holthuijsen, 2010): dE dt = Sin + Snl + Sdiss (1) where E(𝑓 ) is the spectral energy density in the frequency domain 𝑓 and all terms in equation…...

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Journal ArticleDOI
TL;DR: In this paper, the authors investigated the exchange of momentum between the atmosphere and ocean using data collected from four oceanic field experiments and obtained direct covariance estimates of momentum fluxes and wind profiles during three of them.
Abstract: This study investigates the exchange of momentum between the atmosphere and ocean using data collected from four oceanic field experiments. Direct covariance estimates of momentum fluxes were collected in all four experiments and wind profiles were collected during three of them. The objective of the investigation is to improve parameterizations of the surface roughness and drag coefficient used to estimate the surface stress from bulk formulas. Specifically, the Coupled Ocean–Atmosphere Response Experiment (COARE) 3.0 bulk flux algorithm is refined to create COARE 3.5. Oversea measurements of dimensionless shear are used to investigate the stability function under stable and convective conditions. The behavior of surface roughness is then investigated over a wider range of wind speeds (up to 25 m s−1) and wave conditions than have been available from previous oversea field studies. The wind speed dependence of the Charnock coefficient α in the COARE algorithm is modified to , where m = 0.017 m−1 ...

499 citations


"Estimating Wind Speed and Direction..." refers background or methods in this paper

  • ...…u∗ values to surface wind speeds, we assume a logarithmic wind speed profile U(z) so that U(z) = u∗ 𝜅 ln ( z z0 ) , (3) where 𝜅 = 0.41 is the Von Karman constant and z0 is the ocean surface roughness length, which is typically parametrized as (Edson et al., 2013) z0 = 0.11 𝜐 u∗ + 𝛼 u2∗ g ....

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  • ...For wind speed below 3 m/s the viscous stress dominates, while the wave-induced stress (or form drag) is responsible for the majority of momentum exchange between the wind and the ocean surface for U10 ≳ 7 m/s (Donelan et al., 2006; Edson et al., 2013; Wu, 1969)....

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  • ...41 is the Von Karman constant and z0 is the ocean surface roughness length, which is typically parametrized as (Edson et al., 2013)...

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  • ...Here, υ is the kinematic viscosity of air and α is the Charnock parameter (Charnock, 1955; Edson et al., 2013)....

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  • ...(4) Here, 𝜐 is the kinematic viscosity of air and 𝛼 is the Charnock parameter (Charnock, 1955; Edson et al., 2013)....

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Journal ArticleDOI
TL;DR: In this paper, a simple, computationally efficient method is proposed as a standard procedure for the routine analysis of pitch-and-roll buoy wave data, which yields four directional model-free parameters per frequency: the mean direction, the directional width, the skewness, and the kurtosis of the directional energy distribution.
Abstract: A simple, computationally efficient method is proposed as a standard procedure for the routine analysis of pitch-and-roll buoy wave data. The method yields four directional model-free parameters per frequency: the mean direction, the directional width, the skewness, and the kurtosis of the directional energy distribution. For most applications these parameters provide sufficient directional information. The estimation procedure and error characteristics of the parameter estimates are discussed and illustrated with computer simulated data. An optional interpretation of the combination of skewness and kurtosis as an indicator of uni-modality of the directional energy distribution is suggested and illustrated with field observations.

423 citations


"Estimating Wind Speed and Direction..." refers methods in this paper

  • ...We use the lowest-order Fourier coefficients of the directional distribution to estimate the mean direction for each frequency (e.g., Kuik et al., 1988): 𝜃(𝑓 ) = 270◦ − 180 ◦ 𝜋 atan2 ( b1( 𝑓 ) a1( 𝑓 ) ) (13) where a1 and b1 are the Fourier coefficients....

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