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The generation of ocean surface waves by wind has been studied for a century, giving rise to wave forecasting and other crucial applications. However, the reacting force of swell waves on the turbulence in the marine atmospheric boundary layer (ABL) remains unknown partly due to the unclear magnitude and profile of wave-coherent (WC) stress. In this study, the intersection frequency between the energy-containing range and inertial subrange range in the turbulent spectra is identified based on the attached eddy model (AEM), as the intersection modulated by swell wave could help to comprehend the physical process between the ocean surface wave and the marine ABL. Using observations from a fixed platform located in the South China Sea, this study shows that the intersection when the WC stress accounts for a lower proportion of the total wind stress (<10%) follows U/(2πz) given by AEM, where U is the wind speed and z is the height. While the intersection depends on the drag coefficient of WC stress for the case, WC stress accounts for a large part of the total wind stress (>10%). Considering the unclear magnitude and profile of WC stress, this study derives a new function to depict the WC stress. Significance Statement: Turbulence located in the energy-containing range of the spectra is the primary source of momentum, heat, and water vapor fluxes between the ocean and marine atmospheric boundary layer (ABL). Thus, a better understanding of the turbulent structure within the wave boundary layer can help us accurately parameterize those fluxes. In addition to absorbing energy from the marine ABL, waves, especially swell waves, influence the turbulent structure. However, until now, the turbulent structure is unclear due to the unclear wave-coherent stress size and profile. In this study, a function that can depict the wave-coherent stress is proposed. We found that the wave-coherent stress can modulate the intersection between the energy-containing range and the inertial subrange range in the turbulent spectra. [ABSTRACT FROM AUTHOR]

The Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in "low-resolution" (LR) and synthetic aperture radar "high-resolution" (HR) modes onboard S6-MF. The consistency and uncertainties associated with these measurements of sea state are examined in a region of the eastern North Pacific. Discrepancies in mean significant wave height (Hs, 0.01 m) and root-mean-square deviation (0.06 m) between J3 and S6-MF LR are found to be small compared to differences with buoy data (0.04, 0.29 m). S6-MF HR data are found to be highly correlated with LR data (0.999) but affected by a nonlinear sea state-dependent bias. However, the bias can be explained robustly through regression modelling based on Hs. Subsequent triple collocation analysis (TCA) shows very little difference in measurement error (0.18 ± 0.03 m) for the three altimetry datasets, when analysed with buoy data (0.22 ± 0.02 m) and ERA5 reanalysis (0.27 ± 0.02 m), although statistical precision, limited by total collocations (N = 535), both obscures interpretation and motivates the use of a larger dataset. However, we identify uncertainties in the collocation methodology, with important consequences for methods such as TCA. Firstly, data from some commonly used buoys are found to be statistically questionable, possibly linked to erroneous buoy operation. Secondly, we develop a methodology based on altimetry data to show how statistically outlying data also arise due to sampling over local sea state gradients. This methodology paves the way for accurate collocation closer to the coast, bringing larger collocation sample sizes and greater statistical robustness. [ABSTRACT FROM AUTHOR]

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach. [ABSTRACT FROM AUTHOR]

The sea-surface roughness or drag coefficient is ascribed to the effect of various components of ocean waves. Many studies have been focused on the investigation of the dependence of drag coefficient on sea states that are usually denoted by wave age. However, no universally accepted relationship has been obtained up to now and the results are significantly scattered or even contradicted. We reviewed the parameterizations of sea-surface roughness as a function of wave age, and found that the phase speed at spectral peak cp is an important parameter to characterize the drag coefficient. For the same wave age, drag coefficient increases with increasing cp. Contrary to the traditional concept, the older waves with greater cp possesses higher sea-surface roughness for the same wind speed because more wave components participate the air–sea interaction and intensify the wind stress. With the buoy meansurements and the theory of equilibrium range of wind waves, we estimated fricition velocity and proposed that the frequency bandwidth and spectral width of the wave spectrum are more suitable parameters than the traditional wind speed and wave age to be used to parameterize drag coefficient. This study provides a new way to estimate wind stress through the reliable spectra of ocean waves. [ABSTRACT FROM AUTHOR]

We have explored the earliest stages of wind wave generation in the open sea, from the first initial wavelets appearing on an otherwise flat surface or low, smooth undulations until the practically fully developed conditions for the very low range of wind speeds we have considered. We suggest the minimal wind speed for the appearance of the first wavelets to be close to 1.8 m s−1. The peculiar conditions associated with the development of coastal sea breezes allow us to consider the local waves as generated under time-limited conditions. The 2D spectra measured during these very early stages provide the first evidence of an active Phillips process generation in the field. After appearing in these very early stages, wavelets quickly disappear as soon as the developing wind waves take a leading role. We suggest that this process is due to the strong spatial gradients in the surface orbital velocity, which impedes the instability mechanism at the base of their formation, while at a later stage of development, these gradients decrease and wavelets reappear. On a decadal perspective, the progressive decrease of the intensity of the sea breezes in the northern Adriatic Sea, where we have carried out our measurements, is associated with the steadily milder winters, and therefore not sufficiently cold local sea temperatures in early summer. Significance Statement: We have explored for the first time the earliest stages of wind wave generation (millimeter scale) in the open sea. This was possible with the combination of the daily sea breeze development and the availability of an oceanographic tower 15 km offshore. The minimum wind speed for wave generation was 1.8 m s−1, lower than previously assumed. The data provide strong indications on the different stages of the generation process, offering measured and visual evidence, under these very light wind conditions, of the Phillips one. The presence of wind-related ripples, essential for remote sensing measurements, turns out to be dependent on the stage of generation. [ABSTRACT FROM AUTHOR]

Ocean waves have long been a research topic, and numerous formulas of the ocean wave spectrum have been widely developed to provide new prospects for ocean experiments and the advancement of radar probing. Nonetheless, the wave spectra developed by researchers fall short of the standards set by remote sensing specialists, mainly due to the limitation of capturing the surface roughness influenced by both short and long waves, prompting ongoing efforts to develop a model covering a diverse scale of wavenumbers in the absence of a generally recognized reference formula. In response, a standard two-scale formulation of wave frequency spectra (WFS) was introduced, where wave height and spectral peak period are determined by sea state. The proposed composite WFS holds the potential to incorporate directional spreading, contributing to the angular distribution of ocean wave energy in the form of directional WFS, making it applicable for ocean modeling. In an effort to investigate directionality effects, an array of well-established spreading functions, including cosine-squared, half-cosine 2s, parameterized half-cosine 2s, hyperbolic secant-squared, and composite structured functions, has been developed here for numerical modeling of random ocean media (ROM) surface roughness and synthesized for their spectral scattering distribution mode, encompassing scattering pattern, scattering orientation, and fractal roughness properties. Nonetheless, the generated ROM models, each varying due to inherent limitations in directional WFS formulation and numerical approximations, demonstrate indeterminacy and unpredictability in surface features, posing challenges for accurately synthesizing ROM roughness patterns. These challenges intensify under varying sea states and different directional WFS formulas, leading to a situation where no single synthesized composite ROM model consistently outperforms the others, rendering them imprecise frameworks for analyzing roughness patterns and investigating texture electromagnetic interactions within the realm of remote sensing. As an approach, a pattern-sensitive fusion method is proposed, employing a multi-scale transform domain (MTD) fusion scheme that leverages the learning potential of a deep super resolution network. The objective is to fuse the reconstructed ROM roughness models, generating an optimal roughness while maintaining their scattering pattern, scattering orientation, and dominant directionality, pivotal for texture consistency and, consequently, the backscattering properties from the synthetic aperture radar (SAR) viewpoint. To validate the reliability of ROM modeling and its roughness synthesis, including the texture fusion and raw data generation, a comprehensive objective quality assessment technique is utilized. These assessments demonstrate the complete consistency of the simulation results with the underlying spectral theory, highlighting their potential contribution to projects related to ocean radar probing and remote sensing.

Sea level rise and sea state variability, resulting from climate change and global warming, are critical research areas. However, current techniques for observing and monitoring these phenomena have limitations in terms of spatial and temporal resolution, particularly in dynamic coastal zones. GNSS Reflectometry (GNSS-R) is an emerging bistatic radar-based technique that utilizes the GNSS direct (transmitter-receiver) and reflected (transmitter-reflection point-receiver) signals to extract properties of the reflecting surface. This study explores the potential of airborne GNSS-R as a means to monitor sea state in coastal areas by using the Doppler spread and reflectivity as observables. The paper aims to derive a sea state factor from the reflected signal power and the Doppler shift distribution to analyze its correlation with wind speed and significant wave height data obtained from the ERA5 model. The experiment involved four flights conducted along the coast between Calais and Boulogne-sur-Mer, France, in July 2019. A GNSS software receiver processes the direct and reflected signals, tracking and re-tracking the reflected signals with the aid of a specular reflection model. The resulting in-phase and quadrature components are analyzed in the spectral domain every minute to estimate the power, the surface reflectivity, and the relative Doppler shift. The findings reveal that the sea state factor and Doppler spreading are sensitive to sea state conditions, correlated with the ERA5 parameters, and influenced by the elevation angle of GNSS satellites. At low elevations (E<10°), the sea state factor demonstrates an inverse relationship (anti-correlation) with the wind speed and significant wave height, while the Doppler distribution shows a correlation with these parameters. Both correlations decrease with increasing elevation angle. This research underscores the potential of airborne GNSS-R for monitoring sea state variability in coastal areas enhancing our understanding of the relationships between GNSS-R measurements and sea state parameters. [ABSTRACT FROM AUTHOR]

Sea level rise and sea state variability, resulting from climate change and global warming, are critical research areas. However, current techniques for observing and monitoring these phenomena have limitations in terms of spatial and temporal resolution, particularly in dynamic coastal zones. GNSS Reflectometry (GNSS-R) is an emerging bistatic radar-based technique that utilizes the GNSS direct (transmitter-receiver) and reflected (transmitter-reflection point-receiver) signals to extract properties of the reflecting surface. This study explores the potential of airborne GNSS-R as a means to monitor sea state in coastal areas by using the Doppler spread and reflectivity as observables. The paper aims to derive a sea state factor from the reflected signal power and the Doppler shift distribution to analyze its correlation with wind speed and significant wave height data obtained from the ERA5 model. The experiment involved four flights conducted along the coast between Calais and Boulogne-sur-Mer, France, in July 2019. A GNSS software receiver processes the direct and reflected signals, tracking and re-tracking the reflected signals with the aid of a specular reflection model. The resulting in-phase and quadrature components are analyzed in the spectral domain every minute to estimate the power, the surface reflectivity, and the relative Doppler shift. The findings reveal that the sea state factor and Doppler spreading are sensitive to sea state conditions, correlated with the ERA5 parameters, and influenced by the elevation angle of GNSS satellites. At low elevations (E

The Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in “low-resolution” (LR) and synthetic aperture radar “high-resolution” (HR) modes onboard S6-MF. The consistency and uncertainties associated with these measurements of sea state are examined in a region of the eastern North Pacific. Discrepancies in mean significant wave height (Hs, 0.01 m) and root-mean-square deviation (0.06 m) between J3 and S6-MF LR are found to be small compared to differences with buoy data (0.04, 0.29 m). S6-MF HR data are found to be highly correlated with LR data (0.999) but affected by a nonlinear sea state-dependent bias. However, the bias can be explained robustly through regression modelling based on Hs. Subsequent triple collocation analysis (TCA) shows very little difference in measurement error (0.18 ± 0.03 m) for the three altimetry datasets, when analysed with buoy data (0.22 ± 0.02 m) and ERA5 reanalysis (0.27 ± 0.02 m), although statistical precision, limited by total collocations (N = 535), both obscures interpretation and motivates the use of a larger dataset. However, we identify uncertainties in the collocation methodology, with important consequences for methods such as TCA. Firstly, data from some commonly used buoys are found to be statistically questionable, possibly linked to erroneous buoy operation. Secondly, we develop a methodology based on altimetry data to show how statistically outlying data also arise due to sampling over local sea state gradients. This methodology paves the way for accurate collocation closer to the coast, bringing larger collocation sample sizes and greater statistical robustness.

The wind stress is a measure of the intensity of air-sea momentum transfer and functions as a sea surface drag to resist the atmospheric flow. The wind stress generates the sea state but also depends on the sea state. Under the action of a tropical cyclone (TC), however, the sea state is extremely severe and highly uncertain, particularly under shallow water conditions. It can hardly be regarded as a direct consequence of the wind speed only. This study investigates the spatial variation of the wind stress under the action of a TC moving from deep to shallow waters by coupling the well-known WaveWatch III (WWIII) model with the extended atmospheric wave boundary layer model (eAWBLM), which has been well developed in recent years. An idealized TC is first introduced as the forcing wind to pursue the objective of the study. The sea state that affects the wind stress is shown to include the total wind wave energy, the high-frequency wave energy dissipation due to fluid viscosity, the energy dissipation due to wave breaking, the wave age, the mean wave steepness, and the misalignment of wind and wave directions. It is demonstrated that the wind stress reaches relatively large values in the front-left quadrant of the TC covered region in both deep and shallow waters. The time delay of the ocean surface responding to wind forcing results in younger and steeper waves in the left and rear quadrants of the TC, which leads to relatively large values of the surface drag coefficient. The surface drag coefficient decreases if the wind and the dominant wave directions are misaligned. The numerical model is also applied to the study of Hurricane Ivan (2004) generated ocean waves and satisfactory results are obtained owing to a more accurate evaluation of the wind stress by considering its dependence on the sea state. [ABSTRACT FROM AUTHOR]

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach.

In order to make better use of sea state data and avoid misjudgment of sea state caused by complex factors, Self-Organizing Mapping mixed kernel KMeans (SOM-Gaussian and Polynomial Kernel-KMeans, SGPK-KMeans) algorithm has been construsted on the basis of KMeans, kernel skills and Self-organizing Mapping (SOM) neural network for complex sea state data. It overcomes the following problems, for example, KMeans has poor clustering effect on complex data, kernel KMeans needs to specify the number of clusters and is sensitive to the initial clustering center. With the sea state data clustering experiment, the cluste ring effect of SGPK-KMeans algorithm is compared with that of classical KMeans, singlecore KMeans and SOM neural network algorithms. The findings show that SGPK-KMeans has a more stable effect on sea state data clustering and can identify outliers in the data more accurately. [ABSTRACT FROM AUTHOR]

We present four 140-yr wind-wave climate simulations (1961–2100) forced with surface wind speed and sea ice concentration from two CMIP6 GCMs under two different climate scenarios: SSP1–2.6 and SSP5–8.5. A global three-grid system is implemented in WAVEWATCH III to simulate the wave–ice interactions in the Arctic and Antarctic regions. The models perform well in comparison with global satellite altimeter and in situ buoys climatology. The comparison with traditional trend analyses demonstrates the present GCM-forced wave models' ability to reproduce the main historical climate signals. The long-term datasets allow a comprehensive description of the twentieth- and twenty-first-century wave climate and yield statistically robust trends. Analysis of the latest IPCC ocean climatic regions highlights four regions where changes in wave climate are projected to be most significant: the Arctic, the North Pacific, the North Atlantic, and the Southern Ocean. The main driver of offshore wave climate change is the wind, except for the Arctic where the significant sea ice retreat causes a sharp increase in the projected wave heights. Distinct changes in the wave period and the wave direction are found in the Southern Hemisphere, where the poleward shift of the Southern Ocean westerlies causes an increase in the wave period of up to 5% and a counterclockwise change in wave direction of up to 5°. The new CMIP6 forced wave models improve in performance compared to previous CMIP5 forced wave models, and will ultimately contribute to a new CMIP6 wind-wave climate model ensemble, crucial for coastal adaptation strategies and the design of future marine offshore structures and operations. Significance Statement: The purpose of this study is to advance the understanding of ocean wind-wave climate evolution over the twentieth and twenty-first centuries and to effectively communicate the long-term impacts of climate change in diverse wind-wave climatic regions across the globe. The 140-yr continuous model results produced in this work are crucial to studying changes in extreme sea states and investigating the relationship between interdecadal periodic oscillations and long-term climate trends. The dataset produced can be used to gain further insight into the substantial long-term changes of the polar wind-wave climate caused by the rapid decrease of sea ice coverage, and the evolution of the directional changes in the sea states triggered by climate change. [ABSTRACT FROM AUTHOR]

The Southern Hemisphere temperature has experienced obvious changes with great spatial differences over the past several decades. Most regions show extreme warming, especially those located at 35°–55°S. In contrast, subsurface cooling exists between 15° and 35°S in the Indian and Pacific basins. The subsurface temperature and salinity change can be divided into spiciness change and heave components. The results show the warming due to isopycnal movement being largely offset by significant spiciness cooling at middepth. Surface warming and subduction into the interior ocean account for subsurface spiciness cooling near 45°S, while surface freshening and penetration along isopycnals are more important to the subsurface spiciness cooling farther north. The isobaric temperature change is associated with pure warming and pure heaving, and the subsurface cooling observed in the Indian and Pacific subtropics is predominantly attributed to pure heaving. This study provides a quantitative estimate of the relative contribution of surface temperature, salinity change, and circulation adjustment in subsurface temperature change, highlighting the importance of circulation change in producing subsurface cooling. Further research is needed to understand why different processes dominate in different ocean sections. Significance Statement: While the global ocean is warming, the subsurface temperature change exhibits a significant regional disparity. This paper attempts to explain the deep-reaching warming at 35°–55°S and cooling at 15°–35°S based on three historical observation datasets. We find that the cooling mostly occurs between 400 and 1000 m in the south Indian and Pacific subtropics (15°–35°S), which is attributed to pure heaving, indicating the importance of circulation change in these regions. The midlatitude warming (35°–55°S) is mainly caused by the pure warming process, which is related to heat uptake at the subpolar surface and northward and downward heat transport. The spiciness cooling near 45°S is mainly driven by the subduction of the surface warming signal while the freshening process has a stronger impact on spiciness cooling farther north. [ABSTRACT FROM AUTHOR]

• Wind and wave renewable energy combination more efficient in the European Atlantic. • Coastal sites. • Satellite altimetry can provide wind and wave energy resource estimates. • The wave energy of swell is less variable than that of the wind sea. In this study, the combined wind and wave energy potential assessment is presented for various locations in European coastal waters. The objective is to investigate the feasibility of satellite altimetry-based assessments of combined wind/wave renewable energy potential on the European shelf. The study is motivated by the potential reduction in energy supply variability by combining wind and wave. The method consists of using a homogenized multi-mission altimeter database available by the European Space Agency Sea State Climate Change Initiative (Sea_State_cci) that comprises 26 years of data, from January 1991 to December 2018, that allows extending the time range and spatial coverage to estimate site wind and wave power densities. An empirical model is used to estimate the wave energy period from the altimeter Ku band significant wave height and radar backscatter coefficient required to compute the wave power density. The results show that wind/wave energy is relatively correlated in the Mediterranean but not in the North Atlantic sites studied. Thus, the Western North Atlantic sites are the most adequate places for wind and wave farms, from the point of view of combined exploitation. The different characteristics of the studied sites show some correspondence between variability and mean wave power, which is an essential input to a marine renewable energy strategy in any jurisdiction. The level of overall variability decreases with an increase in mean wave power, related to the higher power swell waves are not highly correlated with the local wind. [ABSTRACT FROM AUTHOR]

High-precision GNSS (global navigation satellite e system) measurements can be used for remote sensing and nowadays play a significant role in atmospheric sounding (station data, radio occultation observations) and sea surface altimetry based on reflectometry. A limiting factor of high-precision reflectometry is the loss of coherent phase information due to sea-state-induced surface roughness. This work studies airborne reflectometry observations recorded over coastal waters to examine the sea-state influence on Doppler distribution and the coherent residual phase retrieval. From coherent observations, the possibility of zenith total delay inversion is also investigated, considering the hydrostatic mapping factor from the Vienna mapping function and an exponential vertical decay factor depending on height receiver changes. The experiment consists of multiple flights performed along the coast between the cities of Calais and Boulogne-sur-Mer, France, in July 2019. Reflected signals acquired in a right-handed circular polarization are processed through a model-aided software receiver and passed through a retracking module to obtain the Doppler and phase-corrected signal. Results from grazing angle observations (elevation < 15°) show a high sensitivity of Doppler spread with respect to sea state with correlations of 0.75 and 0.88 with significant wave height and wind speed, respectively. An empirical Doppler spread threshold of 0.5 Hz is established for coherent reflections supported by the residual phase observations obtained. Phase coherence occurs in 15% of the observations; however, the estimated zenith total delay for the best event corresponds to 2.44 m, which differs from the typical zenith total delay (2.3 m) of 5%. [ABSTRACT FROM AUTHOR]

Many wind wave spectrum models provide excellent wave height prediction given the input of wind speed and wave age. Their quantification of the surface roughness, on the other hand, varies considerably. The ocean surface roughness is generally represented by the mean square slope, and its direct measurement in open ocean remains a challenging task. Microwave remote sensing from space delivers ocean surface roughness information. Satellite platforms offer global coverage in a broad range of environmental conditions. This paper presents low-pass mean square slope (LPMSS) data obtained by spaceborne microwave altimeters and reflectometers operating at L, Ku, and Ka bands (about 1.6, 14, and 36 GHz). The LPMSS data represent the spectrally integrated ocean surface roughness with 11, 95, and 250 rad m−1 upper cutoff wavenumbers, and the maximum wind speeds are 80, 29, and 25 m s−1, respectively. A better understanding of the ocean surface roughness is important to the goal of improving wind wave spectrum modeling. The analysis presented in this paper shows that over two orders of magnitude of the wavenumber range (0.3–30 rad m−1), the spectral components follow a power function relating the dimensionless spectrum and the ratio between wind friction velocity and wave phase speed. The power function exponent is about 0.38, which is considerably smaller than unity as expected from the classical equilibrium spectrum function. It may suggest that wave breaking is not only an energy sink but also a source of roughness generation covering a wideband of wavelengths about 20 m and shorter. Significance Statement: This paper presents low-pass mean square slope (LPMSS) data obtained by spaceborne microwave altimeters and reflectometers operating at L, Ku, and Ka bands (about 1.6, 14, and 36 GHz). The LPMSS data represent the spectrally integrated ocean surface roughness with 11, 95, and 250 rad m−1 upper cutoff wavenumbers, and the maximum wind speeds are 80, 29, and 25 m s−1, respectively. A better understanding of the ocean surface roughness is important to the goal of improving wind wave spectrum modeling that is critical to the investigation of air–sea interaction and ocean remote sensing. The analysis presented in this paper suggests that wave breaking is not only an energy sink but also a generation source of surface roughness covering a wide band of wavelengths about 20 m and shorter. [ABSTRACT FROM AUTHOR]

A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation. [ABSTRACT FROM AUTHOR]

Ocean wave measurements are of major importance for a number of applications including climate studies, ship routing, marine engineering, safety at sea, and coastal risk management. Depending on the scales and regions of interest, a variety of data sources may be considered (e.g., in situ data, Voluntary Observing Ship observations, altimeter records, numerical wave models), each one with its own characteristics in terms of sampling frequency, spatial coverage, accuracy, and cost. To combine multiple source of wave information (e.g., for data assimilation scheme in numerical weather prediction models), the error characteristics of each measurement system need to be defined. In this study, we use the triple collocation technique to estimate the random error variance of significant wave heights from a comprehensive collection of collocated in situ, altimeter, and model data. The in situ dataset is a selection of 122 platforms provided by the Copernicus Marine Service In Situ Thematic Center. The altimeter dataset is the ESA Sea State CCI version1 L2P product. The model dataset is the WW3-LOPS hindcast forced with bias-corrected ERA5 winds and an adjusted T475 parameterization of wave generation and dissipation. Compared to previous similar analyses, the extensive (∼250 000 entries) triple collocation dataset generated for this study provides some new insights on the error variability associated to differences in in situ platforms, satellite missions, sea state conditions, and seasonal variability. [ABSTRACT FROM AUTHOR]

We identify and characterize an error in the National Data Buoy Center (NDBC) wave records due to the sustained tilt of a buoy under high winds. We use a standard, operational 3-m aluminum discus buoy from NDBC with two wave systems, one gimballed, and the other strapped down but uncorrected. By comparing the two, we find that the most extreme significant wave heights are systematically overestimated. The overestimation is shown to be confined to a region around the peak frequency in the spectra: 0.05–0.15 Hz. Wave direction and directional spread are unaffected. A bias due to tilt error can be observed starting at winds of 10 m s−1 or wave heights of 4 m. The bias increases as a function of wind speed and wave height, i.e., the bias is +10% when winds are 20 m s−1. Very high waves and winds are relatively rare, so while the tilt error does not affect overall statistics and basic analyses it could potentially affect analysis sensitive to the extremes. A correction is derived for significant wave height, which is a quadratic function of wind speed. The correction is shown to reduce wave heights in uncorrected records, but is found inadequate for general use. There is evidence of tilt error at other NDBC stations, but the full extent of prevalence in the record is not known at this time. [ABSTRACT FROM AUTHOR]

The momentum flux to the ocean interior is commonly assumed to be identical to the momentum flux lost from the atmosphere in traditional atmosphere, ocean, and coupled models. However, ocean surface gravity waves (hereafter waves) can alter the magnitude and direction of the ocean-side stress (τoc) from the air-side stress (τa). This is rarely considered in coupled climate and forecast models. Based on a 30-yr wave hindcast, the redistribution of the global wind stress and turbulent kinetic energy (TKE) flux by waves was investigated. Waves play a more important role in the windy oceans in middle and high latitudes than that in the oceans in the tropics (i.e., the central portion of the Pacific and Atlantic Oceans). On average, the relative difference between τoc and τa, &#9447τ, can be up to 6% in middle and high latitudes. The frequency of occurrence of &#9447τ. 9% can be up to 10% in the windy extratropics. The directional difference between τoc and τa exceeds 3.58 in the middle and high latitudes 10% of the time. The difference between τoc and τa becomes more significant closer to the coasts of the continents due to strong wind gradients. The friction velocity-based approach overestimates (underestimates) the breaking-induced TKE flux in the tropics (middle and high latitudes). The findings presented in the current study show that coupled climate and Earth system models would clearly benefit from the inclusion of a wave model. [ABSTRACT FROM AUTHOR]

The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean-wave (Modular Ocean Model 6-WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2-3 Ã--10-3 for wind speeds of 25-55 m s-1. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 458, a feature that is underestimated by current models of sea state-dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state-dependent parameterizations of the drag coefficient in tropical cyclone conditions. [ABSTRACT FROM AUTHOR]

The characteristics of wave spectra in the swell-dominated seas in the Chancay Bay, Peru, and off the coast of Hambantota, Sri Lanka, were studied based on in situ measurements. According to the characteristics of the spectral shapes, the measured wave spectra were divided into single- and double-peaked spectra. For the single-peaked measured spectra, many widely used wave spectrum models were adopted to fit the measured wave spectra. By comparing the fitting results with the measured wave spectra, these wave spectra were insufficient for describing the peak enhancement or the high-frequency tail shape of the measured spectra. The spectral shape parameters were found to play an important role in the expression of the spectrum models. The peak enhancement factor γ in the Joint North Sea Wave Project (JONSWAP) spectra could adjust the peak height of the spectrum and the shape parameter m of the spectrum high-frequency tail in the Wallops spectra made the wave spectrum more flexible. Therefore, an improved single-peaked wave spectrum was proposed by combining the JONSWAP and Wallops spectra. It performed better than other spectrum models in describing the swell and has advantages in both the wave characteristic parameters and wave spectral shapes. The spectrum peak width parameter σ was relatively consistent in the two measurement stations and both around 0.24. Moreover, the proposed model overcame the limitations of the excessively high estimated slope in the high-frequency range of the Wallops spectrum; the shape parameter m of the spectrum high-frequency tail is primarily distributed in the range (1, 5). For the double-peaked measured spectra, the Ochi–Hubble spectrum was found to work better than the Torsethaugen spectrum. [ABSTRACT FROM AUTHOR]

Offshore wind energy, as a clean and renewable resource, offers numerous advantages over onshore wind energy due to higher wind speeds and greater turbine capacity. However, the inadequate representation of wave-atmosphere interaction within the marine-atmospheric boundary layer may constrain wind resource assessments and, consequently, the design and layout of offshore wind turbines. By using the third-generation spectral wave model WAVEWATCH III, high-resolution numerical experiments which are capable of resolving the wind turbine foundation have been conducted to explore the blocking impact of wind turbine foundation on downstream wind stress. The findings provided significant insights into the factors influencing this effect, including foundation diameter, sea state, water depth, and wave directional spreading. Specifically, higher model resolution enables a more detailed characterization of wind stress distribution behind wind turbines. Increasing the foundation diameter resulted in a reduction of downstream wind stress. Notably, changes in wind stress exhibit a strong dependence on the sea state. The use of double periodic boundary conditions for the simulation domain enables an approximate representation of the entire wind farm by using a single turbine. Model results indicate that after waves pass through 20 turbines, domain-averaged wind stress decreases by approximately 3%, a figure that increases to 6% after passing through 50 turbines. The findings suggest the need to explore to what extent the changes in wind stress can alter wind profiles and how to parameterize the blocking impact of turbine foundations in wave models. This could have significant implications for wind farm site selection and layout design. • The wind turbine foundation can change the downstream wind stress by blocking the ocean surface waves. • The reduction of downstream wind stress induced by wind turbines depends on sea state, specifically the inverse wave age. • Broad directional spreading shortens the sheltered zone and reduces wind stress less than narrow directional spreading. • The wave blocking by turbine foundations in reduces wind stress by 3% with 20 turbines per row and 6% with 50 turbines per row. [ABSTRACT FROM AUTHOR]

The lifting pipe is a key component of deep sea mining whose dynamic response directly affects the safety of the lifting operation. The objective of this paper was to investigate the effects of heave motion and sailing velocity of mining vessel and the buffer mass on the dynamic response of lifting pipe. First, an equivalent model of the lifting pipe was established, and the natural frequency and dynamic response of the lifting pipe equivalent model were determined with consideration of the wave action by the method of separated variables. Secondly, the reliability of the equivalent model was verified by simulating a 5000 m stepped pipe with OrcaFlex software. Then the dynamic displacement, axial tension, axial stress of the lifting pipe under different sea conditions and sailing velocities were studied, and the main factors affecting the dynamic response of the pipe described. By comparing the simulation results of actual and equivalent models, the equivalent model can be used to analyze the longitudinal vibration characteristics of the lifting pipe. The sailing velocity of the mining vessel has little effect on the dynamic response of the lifting pipe, but the surface wave has a significant effect. [ABSTRACT FROM AUTHOR]

The development of wind wave (i.e., sea state) inside an intense tropical cyclone (TC) is the dominant contributor to the sea surface roughness and thus significantly impacts the air–sea interaction. The sea state is known to vary with TC characteristics (intensity, size, and translation speed); however, comprehensive knowledge of the influence of TC characteristics on the sea state and sea surface roughness is quite limited, largely because of the lack of observations. In this study, numerical experiments are performed to investigate the influence of TC characteristics on the sea state and the sea surface roughness under a range of idealized TCs. The numerical results indicate that the sea states are systematically younger for a more intense or smaller TC, and their azimuthal variation is predominantly determined by the TC translation. The dependence of the sea surface roughness on wind speed shows systematic variations with the TC characteristics, which are most significant for a moderately moving TC. [ABSTRACT FROM AUTHOR]

Recent developments on calibration and partitioning of the signal between the wave and current contributions significantly improve the accuracy of geophysical retrievals from Sentinel‐1 Synthetic Aperture Radar‐based Doppler shift measurements in the open ocean. In this study, we revise the Sentinel‐1B Interferometric Wide products acquired from December 2017 to January 2018 along the coastal zone of northern Norway. We find that the satellite attitude is responsible for 30% of the variation in the Doppler shift observations, while the antenna pattern can describe an additional 15%. The residual variation after recalibration is about 3.8 Hz, corresponding to 0.21–0.15 m/s radial velocity (RVL) depending on the incidence angle. Using recalibrated Sentinel‐1 observations, collocated with near‐surface wind from MetCoOp‐Ensemble Prediction System and sea state from MyWaveWAM, we develop an empirical function (CDOP3SiX) for estimating the sea‐state‐induced Doppler shift. CDOP3SiX improves the accuracy of sea state contribution estimates under mixed wind fetch conditions and demonstrates that the Norwegian Coastal Current can be detected in the Sentinel‐1 derived ocean surface current RVL maps. Moreover, two anticyclonic mesoscale eddies with radial velocities of about 0.5 m/s are detected. The surface current patterns are consistent with the collocated sea surface temperature observations. The Doppler shift observations from Sentinel‐1 can therefore be used to study ocean surface currents in the coastal zone with a 1.5 km spatial resolution. Plain Language Summary: Knowledge of ocean surface currents is crucial for studies of volume, heat and salt transport, tracking pollutants, and fisheries. The Doppler shift from Sentinel‐1 Synthetic Aperture Radar (SAR) observations can be used to retrieve information about ocean surface currents. Challenging calibration and lack of algorithms for separating the wave and current contributions have limited the application of this observation‐based method. Recent developments on calibration showed promising improvements in the accuracy of the signal. In this study, we apply this recent calibration method to Sentinel‐1B scenes and develop an algorithm applicable for the challenging conditions in the coastal zone. We found that the signal from the Norwegian Coastal Current can be detected in the Sentinel‐1 derived ocean surface current radial velocity fields. Also, we demonstrated the potential of SAR data for observing eddies with diameter of about 40–70 km. The Sentinel‐1 derived surface currents express meandering structures and boundaries in consistence with the satellite‐based sea surface temperature field. Comparison with the ocean model also reveals reasonable agreement, especially for the major surface current features. Therefore, given accurate calibration and new algorithm for removal of the wind and wave contribution, the Sentinel‐1 observations can be used for monitoring ocean surface currents in the coastal zone with high spatial resolution. Key Points: The Sentinel‐1 Doppler shift observations are used to retrieve information about the ocean surface currents in the coastal zoneMesoscale eddies are detected in the Synthetic Aperture Radar‐derived ocean surface current radial velocity fieldsCombination of the wind and wave information from collocated models improves the accuracy of the wave‐induced contribution estimates [ABSTRACT FROM AUTHOR]

Wind-wave development is governed by the fetch- or duration-limited growth principle that is expressed as a pair of similarity functions relating the dimensionless elevation variance (wave energy) and spectral peak frequency to fetch or duration. Combining the pair of similarity functions, the fetch or duration variable can be removed to form a dimensionless function of elevation variance and spectral peak frequency, which is interpreted as the wave energy evolution with wave age. The relationship is initially developed for quasi-neural stability and quasi-steady wind forcing conditions. Further analyses show that the same fetch, duration, and wave-age similarity functions are applicable to unsteady wind forcing conditions, including rapidly accelerating and decelerating mountain gap wind episodes and tropical cyclone (TC) wind fields. Here it is shown that with the dimensionless frequency converted to dimensionless wavenumber using the surface wave dispersion relationship, the same similarity function is applicable in all water depths. Field data collected in shallow to deep waters and mild to TC wind conditions and synthetic data generated by spectrum model computations are assembled to illustrate the applicability. For the simulation work, the finite-depth wind-wave spectrum model and its shoaling function are formulated for variable spectral slopes. Given wind speed, wave age, and water depth, the measured and spectrum-computed significant wave heights and the associated growth parameters are in good agreement in forcing conditions from mild to TC winds and in all depths from deep ocean to shallow lake. Significance Statement: This paper presents a growth function and spectrum model to describe wind-wave development in all water depths. Their applicability covers a wide range of wind forcing conditions including steady, accelerating, decelerating, and tropical cyclone events. Support for the unified spectrum model and growth function is presented with field observations and numerical computations. [ABSTRACT FROM AUTHOR]

In this article, we present implementation details of a generative satellite maritime propagation channel model at L-band. In an earlier paper, we presented the parameterization of the channel model for the narrowband case based on recordings of GPS L1 $C/N_{0}$ time-series in different sea state conditions. Additionally, we performed wider band measurements using GPS E5a (≈10 Mcps—chips per second— > 20 MHz bandwidth) and obtained estimations of power delay profiles. Due to lack of dynamic range and delay resolution, in these measurements, no conclusive information was gathered on the time spreading caused by the channel. What was clear is that the time spreading was not significant outside the first signal chip, i.e., $\approx 0.1~\mu \text{s}$. Still wideband modeling is required within this spreading range. Now, we want to extend the model to the wideband case. To achieve this goal, we have used a rough surface scattering model applicable to sea surfaces and employed it to characterize the time dispersion to be expected. Additionally, we also used this scattering model to help verify the validity of the existing Doppler spread model. Furthermore, ship movements in the waves play a role. We try and analyze this issue. Finally, we present a detailed discussion on various implementation issues we came across when coding the simulator. [ABSTRACT FROM AUTHOR]

Sea state estimation is beneficial for marine systems to enhance on-board decision-making and improve work efficiency. In the era of ship intelligence, artificial intelligence has greatly promoted the technology of sensing environment, such as by using the deep learning. However, it is difficult to collect enough motion data from a marine system to train a deep learning model. In addition, the model for sea state estimation is trained using the data from a specific marine system; applying the model directly to another marine system may result in performance degradation. In this paper, a supervised transfer learning based framework for sea state estimation (STLSSE) is proposed. The STLSSE focuses on knowledge transfer when the collected data for the source marine system is sufficient but the collected data of the target marine system is scarce. In STLSSE, a data pairing algorithm is proposed to determine the relationship of the source and the target marine system. Based on these paired data, a Siamese convolutional neural network, including a new proposed residual fully convolutional network and two novel attention modules, is designed for the semantic alignment. Moreover, the conventional contrastive loss is improved to characterize the distributions when there are only few samples in the target marine system. The extensive comparisons between STLSSE and state-of-the-art transfer learning approaches show its superior performance. The comparisons with state-of-the-art attention modules has verified the competitiveness of the proposed attention modules. The key parameters and each component of STLSSE are emphasized in the ablation and sensitivity studies. [ABSTRACT FROM AUTHOR]

In this article, complex random polar media (CRPM) are synthesized by a forward numerical modeling based on the fractal statistical properties of the marginal ice zone (MIZ) in terms of its energy balance under sea state conditions. The proposed modeling was carried out by the parallel processing of a modified JONSWAP directional spectrum function in a two-dimensional hybrid domain. As a novel approach, the scattering formulation has been modified in the form of a two-scale implementation, which is optimized by the product of cosine-power and Gamma probability distribution function (PDF). As a result, a composite model of CRPM under different sea state conditions, including wind speed and direction, has been made possible. Due to the high dynamics of CRPM under sea state conditions, the presence of high entropy samples in the form of random roughness fluctuations is inevitable. These highly textured areas not only reduce the ability to resolve fine details but also make the interpretation difficult from a remote sensing point of view. According to the importance of synthetic aperture radar in the observation of MIZ and analysis of scattering properties, the spectral distribution modeling of these roughness anomalies and their electromagnetic interactions, along with surface tension synthesis, are presented here. Meanwhile, several objective quality metrics under different sea state conditions have been derived. The results show that the sea state not only changes the spectral components, but also affects their contribution to the roughness fluctuations and texture compositions. In short, this is for the first time that the composite modeling of CRPM based on directional spectrum function under sea state conditions along with electromagnetic interactions investigation and its pertinent texture analysis has been done.

The provision of reliable results from numerical wave models implemented over vast ocean areas can be considered as a time-consuming process. In this regard, the estimation of areas with maximum similarity in wave climate spatial areas and the determination of associated representative point locations for these areas can play an important role in climate research and in engineering applications. To deal with this issue, we apply a state-of-the-art clustering method, Geo-SOM, to determine geographical areas with similar wave regimes, in terms of mean wave direction (MWD), mean wave period (T0), and significant wave height (Hs). Although this method has many strengths, a weakness is related to detection and accounting of the most extreme and rare events. To resolve this deficiency, an initial preprocessing method (called PG-Geo-SOM) is applied. To evaluate the performance of this method, extreme wave parameters, including Hs and T0, are calculated. We simulate the present climate, represented as 1979 to 2017, compared to the future climate, 2060–98, following the Intergovernmental Panel on Climate Change (IPCC) future scenario RCP8.5 in the northwestern Atlantic Ocean. In this approach, the wave parameter data are divided into distinct groups, or clusters, motivated by their geographical positions. For each cluster, the centroid spatial point and the time series of data are extracted, for Hs, MWD, and T0. Extreme values are estimated for 5-, 10-, 25-, 50-, and 100-yr return periods, using Gumbel, exponential, and Weibull stochastic models, for both present and future climates. Results show that for parameter T0, the impact of climate change for the study area is a decreasing trend, while for Hs, in coastal and shelf areas up to about 1000 km from the coastline, increasing trends are estimated, and in open-ocean areas, far from the coast, decreasing trends are obtained. [ABSTRACT FROM AUTHOR]

Understanding current environmental conditions is essential for autonomous ships, among which real-time estimation of sea conditions is a key aspect. Considering the ship as a large wave buoy, the sea state can be estimated from motion responses without extra sensors installed. This task is challenging since the relationship between the wave and the ship motion is hard to model. Existing methods include a wave buoy analogy (WBA) method, which assumes linearity between wave and ship motion, and a machine learning (ML) approach. Since the data collected from a vessel in the real world are typically limited to a small range of sea states, the ML method might fail when the encountered sea state is not in the training dataset. This article proposes a hybrid approach that combines the above two methods. The ML method is compensated by the WBA method based on the uncertainty of estimation results, and thus, the failure can be avoided. Real-world historical data from the Research Vessel Gunnerus are applied to validate the approach. Results indicate that the hybrid approach improves the estimation accuracy. [ABSTRACT FROM AUTHOR]

Global navigation satellite system reflectometry (GNSS-R) is able to achieve intensive and high-frequency measurements of global sea levels. The sea state bias (SSB) makes the measurement uncertain. Based on ship-borne GNSS-R observations in China’s Seas, we obtained reflected signal delay. We constructed a new mean sea surface (MSS) reflection surface model to calculate the modeled reflection delay. By combining the observation and modeled reflection delay, we separated and quantified the SSB. The SSB was approximately 1.3 m for spring and summer alternate seasons in China’s Seas, with obvious differences in the spatial distribution of sea area, latitude, and distance from shore. Based on the quantified SSB and sea state parameters, we introduced reflection incident angle parameter and constructed a new parameter model of SSB suitable for GNSS-R. We applied the parameter model to predict variations in delay SSB. The parameter model had a variance explanation rate of approximately 70%, it can reliably predict large-scale SSB variations, and it performed better in higher elevation scenarios. This letter proposes a regional approach to quantify GNSS-R delay SSB and to predict its variations, and it is expected to be applied to GNSS-R satellite altimetry to support SSB correction. [ABSTRACT FROM AUTHOR]

Sea state affects the coasts of all maritime regions, and it impacts anthropic infrastructures and influences the activities carried out in the sea as well as in its proximity. Sea-state monitoring is therefore important for a number of reasons, including the need to validate weather forecast models and study the impact of sea waves on anthropic infrastructures such as ports. In this letter, we combined the measurements of sea state collected with Ocean Seismic Integrated System (OS-IS), a seismic-based system developed by AGI (Assist in Gravitation and Instrumentation) srl and INGV (National Institute for Geophysics and Volcanology), with those obtained using a Wave Radar system. The aim was to prove that this combination could enhance the efficacy and reliability of sea monitoring, thanks to the complementarity of the two types of measurements in terms of area covered and spatial resolution. More specifically, the sea-state parameters provided by OS-IS were compared with those provided by a Wave Radar system. OS-IS data were collected from three microseismic stations installed near the Gulf of La Spezia, on the Ligurian Coast, whereas the Wave Radar system was installed at the center of the Cinque Terre National Park at about 12 km from the OS-IS system. The comparison between the measurements of significant wave height ($H_{s}$) and peak period ($T_{p}$) showed a good agreement, with a correlation index close to 0.9. The residual difference highlights the complementarity of the two systems and the potential of an integrated system that includes both. In particular, OS-IS provides measurements over large, offshore areas, whereas the Wave Radar System provides high spatial-resolution measurements over areas near the coast. [ABSTRACT FROM AUTHOR]

This letter describes the wave reflection induced by the breakwater of the Port of Civitavecchia in the Tyrrhenian Sea, Italy, using a $X$ -band wave radar. The wave radar system detected a complex structure of reflected waves that is composed of three spectral components and was generated by the complex structure of the breakwater. By applying a filter in the $\omega - k$ domain, it was possible to filter out the component of the incident waves to analyze the total component of reflected waves. Applying specific filters also made it possible to separate the spectral components of the single reflected waves. Bandpass filters were built to select each spectral component based on only the direction of the incident and reflected wave components. Starting from the separated spectral components, the reflection coefficients related to the measurement campaign were estimated and compared with the theoretical coefficients. The results confirm the potential of a radar system to resolve a complex sea state and provide a synoptic analysis of wave propagation processes over a wide measurement domain. Furthermore, this letter opens the way for new studies on the interaction between incident waves and coastal infrastructure. [ABSTRACT FROM AUTHOR]

Considering that the motion state and the stress of floating hose are complex under the combined action of winds, waves and currents, the dynamic simulation analysis of offshore floating hose oil transportation system was thereby carried out through the method of joint simulation based on AQWA and OrcaFlex.The numerical model was established to analyze the frequency domain of oil tanker by AQWA, and to perform the time domain analysis on the coupling motion between floating hose, oil tanker, buoy and mooring line by OrcaFlex.The results show that the influence of wind, waves and currents on the floating hose tension increases nonlinearly.The maximum tension points of the floating hose oil transportation system are at both ends of the hose.The tension acting on the hose can be obviously reduced and the drift distance can be shortened by setting securing anchors along the line.Through the analysis on the offshore floating hose oil transportation system with the transportation distance of 1 100 m, based on this method and model, it can be concluded that the optimal hose length is 1 300 m, the hose drift distance is about 300 m when no securing anchor is set along the line, and the safety requirements can be met under 4-level sea state.The research results can provide certain reference for the dynamic simulation analysis of such offshore floating hose oil transportation system.

Sea wave monitoring is key in many applications in oceanography such as the validation of weather and wave models. Conventional in situ solutions are based on moored buoys whose measurements are often recognized as a standard. However, being exposed to a harsh environment, they are not reliable, need frequent maintenance, and the datasets feature many gaps. To overcome the previous limitations, we propose a system including a buoy, a micro-seismic measuring station, and a machine learning algorithm. The working principle is based on measuring the micro-seismic signals generated by the sea waves. Thus, the machine learning algorithm will be trained to reconstruct the missing buoy data from the micro-seismic data. As the micro-seismic station can be installed indoor, it assures high reliability while the machine learning algorithm provides accurate reconstruction of the missing buoy data. In this work, we present the methods to process the data, develop and train the machine learning algorithm, and assess the reconstruction accuracy. As a case of study, we used experimental data collected in 2014 from the Northern Tyrrhenian Sea demonstrating that the data reconstruction can be done both for significant wave height and wave period. The proposed approach was inspired from Data Science, whose methods were the foundation for the new solutions presented in this work. For example, estimating the period of the sea waves, often not discussed in previous works, was relatively simple with machine learning. In conclusion, the experimental results demonstrated that the new system can overcome the reliability issues of the buoy keeping the same accuracy.

The fate of the beaches around the world has paramount importance as they are one of the main assets for touristic activities and act as a natural barrier for coastal protection in front of marine storms. Climate change could put them at risk as sea levels rise and changes in the wave characteristics may dramatically modify their shape. In this work, a new methodology has been developed to determine the flooding of sandy beaches due to changes in sea level and waves. The methodology allows a cost-effective and yet accurate estimation of the wave runup for a wide range of beach equilibrium profiles and for different seagrass coverage. This, combined with regional projections of sea level and wave evolution, has allowed a quantification of the future total water level and coastline retreat for 869 beaches across the Balearic Islands for the next decades as a function of greenhouse gases emission scenario. The most pessimistic scenario (RCP8.5) at the end of the century yields an averaged percentage of flooded area of 66% under mean conditions which increases up to 86% under extreme conditions. Moreover, 72 of the 869 beaches of the region would permanently disappear while 314 would be completely flooded during storm episodes. Under a moderate scenario of emissions (RCP4.5), 37 beaches would permanently disappear while 254 would disappear only during storm episodes. In both cases, the average permanent loss of beach surface at the end of the century would be larger than 50%, rising over 80% during storm conditions. The results obtained for the Balearic Islands can be extrapolated to the rest of the Mediterranean as the beaches in all the regions have similar characteristics and will be affected by similar changes in sea level and wave climate. These projections indicate that adaptation plans for beach areas should be put in place as soon as possible.

EM-APEX floats as autonomous vehicles have been used for profiling temperature, salinity, and current velocity for more than a decade. In the traditional method for processing horizontal current velocity from float measurements, signals of surface wave motion are removed as residuals. Here, a new data processing method is proposed for deriving the horizontal velocity of surface waves at the floats. Combined with the vertical acceleration measurements of waves, surface wave directional spectra E(f, θ) can be computed. This method is applied to the float measurements on the right of Typhoon Megi's 2010 track. At 0.6 days before the passage of Megi's eye to the floats, the fast-propagating swell may affect wind waves forced by the local storm wind. When the storm moves closer to the floats, the increasing wind speed and decreasing angle between wind and dominant wave direction may enhance the wind forcing and form a monomodal spectrum E(f). The peak frequency fp ~ 0.08 Hz and significant wave height > 10 m are found near the eyewall. After the passage of the eye to the floats, fp increases to >0.1 Hz. Although E(f) still has a single spectral peak at the rear-right quadrant of Megi, E(f, θ) at frequencies from 0.08 to 0.12 Hz has waves propagating in three different directions as a trimodal spectrum, partially due to the swell propagating from the rear-left quadrant. Enhancing the capability of EM-APEX floats to observe wave spectra is critical for exploring the roles of surface waves in the upper ocean dynamics in the future. [ABSTRACT FROM AUTHOR]

A series of experiments were conducted in a wind-wave tank facility in Marseilles (France) to study the effects of preexisting swell conditions (represented by long mechanically generated waves) on wind-wave growth with fetch. Both monochromatic and irregular (JONSWAP-type) long-wave conditions with different values of wave steepness have been generated in the presence of a constant wind forcing, for several wind velocities. A spectral analysis of temporal wave signals combined with airflow measurements allowed for the study of the evolution of both wave systems with the aim of identifying the interaction mechanisms transportable to prototype scale. In particular, a specific method is used to separate the two wave systems in the measured bimodal spectra. In fetch-limited conditions, pure wind-wave growth is in accordance with anterior experiments, but differs from the prototype scale in terms of energy and frequency variations with fetch. Monochromatic long waves are shown to reduce the energy of the wind-waves significantly, as it was observed in anterior laboratory experiments. The addition of JONSWAP-type long waves instead results in a downshift of the wind-wave peak frequency but no significant energy reduction. Overall, it is observed that the presence of long waves affects the wind-wave energy and frequency variations with fetch. Finally, in the presence of JONSWAP-type long waves, variations of wind-wave energy and peak frequency with fetch appear in close agreement with the wind-wave growth observed at prototype scale both in terms of variations and nondimensional magnitude. [ABSTRACT FROM AUTHOR]

The present work shows the derivation of general forms for the expressions of the first- and second-order corrections to the radar cross section (RCS) of the ocean surface at electromagnetically high sea states. An analysis of the morphology of the correction terms and their impact on the total RCS of the ocean surface is presented. It is shown that most of the visible impact on the total RCS of the ocean surface is due to first-order hydrodynamic terms and is concentrated between the Bragg peaks. Also, second-order hydrodynamic correction terms can increase the integral over the second-order region outside the dominant Bragg peak by up to 30% at extreme ocean conditions. Although comparison with field data was not conclusive, the presented results can improve the representation of electromagnetically large waves in the total RCS of the ocean surface without dismissing the analysis methods for height-restricted RCSs presented in the literature. [ABSTRACT FROM AUTHOR]

An examination of the applicability and accuracy of the empirical wave inversion method in the presence of swell waves is presented. The ability of the method to invert Doppler spectra to wave directional spectra and bulk wave parameters is investigated using 1-month data from a 12-MHz Wellen Radar (WERA) high-frequency (HF) radar system and in situ data from a wave buoy. Three different swell inversion models are evaluated from Lipa et al. (LPM), from Wang et al. (WFG), and empirical (EMP), an empirical approach introduced in this study. The swell inversions were carried out using two different scenarios: 1) a single beam from a single radar site and two beams from a single radar site, and 2) two beams from two sites (a single beam per site) intersecting each other at the buoy location. The LPM method utilizing two beams from two different sites was found to provide the best estimations of swell parameters (swell height RMS error: 0.24 m) and showed a good correlation with the partitioned swell in situ values. For the wind-wave inversion, the empirical method presented here is used with an empirical coefficient of 0.3, which seems to be suitable for universal application for all radar operating frequencies. The inverted swell parameters are used to create a swell spectrum that is combined with the inverted wind-wave spectrum to create a full directional wave spectrum. The wave inversion method presented in this study although empirical does not require calibration with in situ data and can be applied to any beam-forming system and operating frequency. [ABSTRACT FROM AUTHOR]

The state of prices and the development of a given economy depends largely on the gas and oil industry. Every day the gas and oil industry is growing and there is a growing need for platforms. In order for the platforms to pump gas and oil from the seabed unhindered, it is necessary to supply the platform which is done by supply vessels. In this paper, with the help of Petri nets and the tool “Yasper”, the dynamic process of supply and operation of supply vessels is simulated. Simulation is depending on the wind and wave conditions and the type of work that the supply vessel performs in cooperation with the platform. Input data are: Sea state, wind state, fuel consumption, type of vessel operation, distance from the mainland and the number of daily departures of the vessels from the port. The paper presents a model with discrete events in the process of supplying the platform, starting from the port and going out to sea until the work around the platform is completed and returning to the port. The report can provide information on the usability of the vessels and the approximate cost of the supply vessels on a voyage from port to the platform and back. [ABSTRACT FROM AUTHOR]

High-precision GNSS (global navigation satellite e system) measurements can be used for remote sensing and nowadays play a significant role in atmospheric sounding (station data, radio occultation observations) and sea surface altimetry based on reflectometry. A limiting factor of high-precision reflectometry is the loss of coherent phase information due to sea-state-induced surface roughness. This work studies airborne reflectometry observations recorded over coastal waters to examine the sea-state influence on Doppler distribution and the coherent residual phase retrieval. From coherent observations, the possibility of zenith total delay inversion is also investigated, considering the hydrostatic mapping factor from the Vienna mapping function and an exponential vertical decay factor depending on height receiver changes. The experiment consists of multiple flights performed along the coast between the cities of Calais and Boulogne-sur-Mer, France, in July 2019. Reflected signals acquired in a right-handed circular polarization are processed through a model-aided software receiver and passed through a retracking module to obtain the Doppler and phase-corrected signal. Results from grazing angle observations (elevation < 15°) show a high sensitivity of Doppler spread with respect to sea state with correlations of 0.75 and 0.88 with significant wave height and wind speed, respectively. An empirical Doppler spread threshold of 0.5 Hz is established for coherent reflections supported by the residual phase observations obtained. Phase coherence occurs in 15% of the observations; however, the estimated zenith total delay for the best event corresponds to 2.44 m, which differs from the typical zenith total delay (2.3 m) of 5%.

This article aims at providing an efficient algorithm for sea clutter segmentation in coherent radar images. Using multiphase interface motion models, we show that segmentation in the range–time–intensity map gives much more relevant results than segmentation in the range–Doppler Map and avoids the use of assumptions on the clutter frequency response. Several mathematical models are evaluated on real data corresponding to Douglas sea states of approximately 5. Dealing with diffuse interface motion models involving more than two phases allows us to take into account the low contrast, the interference noise, and the contour weakness that are typical of range–time–intensity map images. Sea clutter segmentation allows us, for instance, to obtain oceanographic parameters such as sea state, direction, and velocity of the swell and the wind. It can also be seen as preprocessing that may be useful for target detection. [ABSTRACT FROM AUTHOR]

A 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 and 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, and 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 proven. [ABSTRACT FROM AUTHOR]