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The Mediterranean Sea is a primary source of food, ecosystem services and economic activities and one of the most active cydogenetic regions in the world, where the influence of orographic and morphological features of the relatively small basin plays an important role. Together with the explosive cyclogenesis, tropical-like cyclones (also called Mediterranean Hurricanes or Medicanes) are among the strongest types of storms that can be found in the Mediterranean basin, occurring predominantly in the Ionian, Balearic and Tyrrhenian sub-basins. Similarly to tropical cyclones (Hurricanes or Typhoons), these cyclonic structures are characterized by strong rotating and translating wind fields, which often lead to a combination of remotely generated swell waves and locally generated wind waves, often referred to as crossing sea states. Despite the well-known potential of Medicanes to cause significant damage near islands and coastal zones, which is predicted to intensify as a result of climate change, to date the characterization of maximum individual waves generated during these events is still lacking. In this study, we carry out the first analysis of the large-scale geographical distribution of wave maxima within the wave fields generated during three recent Medicane events using the WAVEWATCH III® spectral wave model forced by ERA5 reanalysis winds, also investigating the influence of crossing sea states on the maximum wave amplitudes with novel statistical formulations developed for such conditions. Our results show that, as in the case of tropical cyclones, several regions of the cyclone field are characterized by crossing sea states, whose role in the formation of the maximum individual waves occurring near the eye of the storm was found to be confined. Furthermore, extreme wave predictions accounting for the local crossing conditions yield differences up to 5% compared to standard statistical distributions. [ABSTRACT FROM AUTHOR]

Wave crests of unexpected height and steepness pose a danger to activities at sea, and long-term field measurements provide important clues for understanding the environmental conditions that are conducive to their generation and behavior. We present a novel dataset of high-frequency laser altimeter measurements of the sea surface elevation gathered over a period of 18 years from 2003 to 2020 on an offshore platform in the central North Sea. Our analysis of crest height distributions in the dataset shows that mature, high sea states with high spectral steepness and narrow directional spreading exhibit crest height statistics that significantly deviate from standard second-order models. Conversely, crest heights in developing sea states with similarly high steepness but wide directional spread correspond well to second-order theory adjusted for broad frequency bandwidth. The long-term point time series measurements are complemented with space–time stereo video observations from the same location, collected during five separate storm events during the 2019/20 winter season. An examination of the crest dynamics of the space–time extreme wave crests in the stereo video dataset reveals that the crest speeds exhibit a slowdown localized around the moment of maximum crest elevation, in line with prevailing theory on nonlinear wave group dynamics. Extending on previously published observations focused on breaking crests, our results are consistent for both breaking and nonbreaking extreme crests. We show that wave crest steepness estimated from time series using the linear dispersion relation may overestimate the geometrically measured crest steepness by up to 25% if the crest speed slowdown is not taken into account. Significance Statement: Better understanding of the statistics and dynamical behavior of extreme ocean surface wave crests is crucial for improving the safety of various operations at sea. Our study provides new, long-term field evidence of the combined effects of wave field steepness and directionality on the statistical distributions of crest heights in storm conditions. Moreover, we show that the dynamical characteristics of extreme wave crests are well described by recently identified nonlinear wave group dynamics. This finding has implications, for example, for wave force calculations and the treatment of wave breaking in numerical wave models. [ABSTRACT FROM AUTHOR]

This paper proposes a method to infer the future change in the wind-wave climate using reanalysis wind corrected to statistically match data from a regional climate model (RCM). The method is applied to the sea surface wind speed of the reanalysis ERA5 from the European Centre for Medium-Range Weather Forecasts. The correction is determined from a quantile mapping between ERA5 and the RCM at any given point in the geographical space. The issues that need to be addressed to better understand and apply the method are discussed. Corrected ERA5 wind fields are eventually used to force a spectral wave numerical model to simulate the climate of significant wave height. The correction strategy is implemented over the Adriatic Sea (a semi-enclosed basin of the Mediterranean Sea) and includes the present-day period (1981–2010) and the near-future period (2021–2050) under the two IPCC RCP4.5 and RCP8.5 concentration scenarios. Evaluation against observations of wind and waves gives confidence in the reliability of the proposed approach. Results confirm the evolution toward an overall decrease in storm wave severity in the basin, especially under RCP8.5 and in its northern area. It is expected that the methodology may be applied to other reanalyses, RCMs (including multi-model ensembles), or seas with similar characteristics. [ABSTRACT FROM AUTHOR]

What: Eighty wind-wave scholars from 22 countries met to report on their latest results, both as applications and wave physics, discussing not only the present state of the art, but mainly the lines along which future actions, in particular the interactions between ocean and atmosphere, should be directed. Nonlinear wave-wave interactions have been for a long while the focus of much work and attention, but they seem to have now lost their spin. Suitably prepared experiments in the laboratory, or better a wind wave tank, can be used to derive general results on wind-wave interactions. The availability of reanalysis wave spectra has allowed a reliable estimate of the expected extreme and freak waves at any location throughout the globe (under present climate conditions). [Extracted from the article]

• A long-term global assessment of maximum wave heights is provided for the first time. • The assessment relies on ERA-Interim dataset and statistical models for wave extremes. • We verified the reanalysis-based wave maxima against observations in the Pacific Ocean. • We quantify maximum wave heights extent, highlighting the role of spectral parameters. • We show the relevance of accounting for the short-crestedness of oceanic waves. Very large waves populate world oceans and challenge seafarers and offshore structures, but their long-term and global assessment is uneasy because of the scarcity of observations and their narrow time-coverage. Modern model reanalysis datasets with high spatio-temporal extent and resolution represent a valuable tool for this scope. In this paper, we use for the first time reanalysis datasets to provide a long-term and global statistical assessment of the maximum wave parameters, namely crest, crest-to-trough and envelope heights. In particular, we rely on the ERA-Interim directional wave spectra that are used to estimate the parameters of the probability distributions of wave maxima. To represent the customary single-point observations we use time extreme statistical models, while to account for the three-dimensional geometry and short-crestedness of stormy ocean waves, the statistical models are extended to space-time. In order to evaluate the accuracy of the reanalysis-based wave maxima estimates we verify them against buoy and stereo-video wave observations gathered in the North Pacific Ocean. We then provide the global assessment of maximum crest, crest-to-trough and envelope heights during typical and extreme conditions, showing the regions attaining the largest values, which we show are located in the mid-latitude storm belts, in particular in the North Atlantic Ocean. With respect to previous wave climate studies that focused on the significant wave height only, in this study we quantify the maximum wave height extent, also highlighting the role of mean wave steepness and kurtosis (measures of nonlinearity) and spectral bandwidth (measure of irregularity). Beside this, we show that the contribution of the short-crestedness is significant and that taking it into account may be relevant for the safety of navigation, ship routing and marine structural design. [ABSTRACT FROM AUTHOR]

Stereo wave imaging of the sea surface elevation has become an effective instrumentation to gather small- and medium-range 3-D wind wave data. Indeed, fruitful applications of stereo techniques have provided new insights into directional wave spectra, space–time distributions of wave maxima, and small-scale wave statistics. So far, however, stereo systems have been deployed mainly on fixed structures (e.g. oceanographic platforms or lighthouses) in order to simplify the installation and maintenance procedures. Nonetheless, advances in stereo calibration and processing suggest that stereo deployments are also feasible onboard moving vessels, thus broadening the impact of these observations on the study of wind waves. In this context, this study aims at discussing how the stereo processing designed to gather reliable wave data from fixed structures should be managed to operate on a moving structure. In particular, estimate of stereo cameras orientation and position with respect to the mean sea plane is of utmost importance. We discuss this aspect by using a synthetic sea state and stereo data collected during an oceanographic campaign onboard a research vessel. Results suggest that, without complementary data sources for ship motion compensation, the sea surface elevation field should include at least about sixteen spatial (2-D) waves to gather a robust estimate of the mean sea plane and consequently realistic wave parameters (e.g. the significant wave height). In this respect, our results provide also insight into the uncertainty of estimates in case of a limited number of 2-D waves is collected by the stereo system. Finally, applications of stereo wave imaging on a moving structure are discussed, with particular emphasis on the collection of space–time wave fields for assessment of numerical models and operational wave observation onboard vessels. [ABSTRACT FROM AUTHOR]

The self-organizing map (SOM) technique is considered and extended to assess the extremes of a multivariate sea wave climate at a site. The main purpose is to obtain a more complete representation of the sea states, including the most severe states that otherwise would be missed by a SOM. Indeed, it is commonly recognized, and herein confirmed, that a SOM is a good regressor of a sample if the frequency of events is high (e.g., for low/moderate sea states), while a SOM fails if the frequency is low (e.g., for the most severe sea states). Therefore, we have considered a trivariate wave climate (composed by significant wave height, mean wave period and mean wave direction) collected continuously at the Acqua Alta oceanographic tower (northern Adriatic Sea, Italy) during the period 1979-2008. Three different strategies derived by SOM have been tested in order to capture the most extreme events. The first contemplates a pre-processing of the input data set aimed at reducing redundancies; the second, based on the post-processing of SOM outputs, consists in a two-step SOM where the first step is applied to the original data set, and the second step is applied on the events exceeding a given threshold. A complete graphical representation of the outcomes of a two-step SOM is proposed. Results suggest that the post-processing strategy is more effective than the pre-processing one in order to represent the wave climate extremes. An application of the proposed two-step approach is also provided, showing that a proper representation of the extreme wave climate leads to enhanced quantification of, for instance, the alongshore component of the wave energy flux in shallow water. Finally, the third strategy focuses on the peaks of the storms. [ABSTRACT FROM AUTHOR]

In this paper, an observational space-time ensemble of sea surface elevations is investigated in search of the highest waves of the sea state. Wave data were gathered by means of a stereo camera system, which was installed on top of a fixed oceanographic platform located in the Adriatic Sea (Italy). Waves were measured during a mature sea state with an average wind speed of 11 m s−1. By examining the space-time ensemble, the 3D wave groups have been isolated while evolving in the 2D space and grabbed 'when and where' they have been close to the apex of their development, thus exhibiting large surface displacements. The authors have selected the groups displaying maximal crest height exceeding the threshold adopted to define rogue waves in a time record, that is, 1.25 times the significant wave height ( H s). The records at the spatial positions where such large crests occurred have been analyzed to derive the empirical distributions of crest and wave heights, which have been compared against standard statistical linear and nonlinear models. Here, the maximal observed wave crests have resulted to be outliers of the standard statistics, behaving as isolated members of the sample, apparently uncorrelated with other waves of the record. However, this study has found that these unexpectedly large wave crests are better approximated by a space-time model for extreme crest heights. The space-time model performance has been improved, deriving a second-order approximation of the linear model, which has provided a fair agreement with the empirical maxima. The present investigation suggests that very large waves may be more numerous than generally expected. [ABSTRACT FROM AUTHOR]

Wave observations and modeling have recently demonstrated that wave extremes of short-crested seas are poorly predicted by statistics of time records. Indeed, the highest waves pertain to wave groups at focusing that have space-time dynamics. Therefore, the statistical prediction of extremes of short-crested sea states should rely on the multidimensional random wave fields' assumption. To adapt wave extreme statistics to the space-time domain, theoretical models using parameters of the directional wave spectrum have been recently developed. In this paper, the influence of metocean forcings (wind conditions, ambient current, and bottom depth) on these parameters and hence on wave extremes is studied with a twofold strategy. First, parametric spectral formulations [Pierson-Moskowitz and Joint North Sea Wave Project (JONSWAP) frequency spectra with cos2 directional distribution function] are considered to represent the dependence of wave extremes upon wind speed, fetch, and space domain size. Afterward, arbitrary conditions are simulated by using the SWAN numerical model adapted to store the spectral parameters, and the effects on extremes of current- and depth-induced shoaling are investigated. Preliminarily, the space-time extremes prediction model adopted is assessed by means of numerical simulations of Gaussian random seas. Compared to the significant wave height of the sea state and for a given space domain size, results show that space-time extremes are enhanced by opposite currents, whereas they are weakened by increasing wind conditions (wind speed and fetch) and by depth-induced shoaling. In this respect, the remarkable contribution to wave extremes of the size of the space domain is substantiated. [ABSTRACT FROM AUTHOR]

One of the most promising techniques for the analysis of Spatio-Temporal ocean wave fields is stereo vision. Indeed, the reconstruction accuracy and resolution typically outperform other approaches like radars, satellites, etc. However, it is computationally expensive so its application is typically restricted to the analysis of short pre-recorded sequences. What prevents such methodology from being truly real-time is the final 3D surface estimation from a scattered, non-equispaced point cloud. Recently, we studied a novel approach exploiting the temporal dependence of subsequent frames to iteratively update the wave spectrum over time. Albeit substantially faster, the unpredictable convergence time of the optimization involved still prevents its usage as a continuously running remote sensing infrastructure. In this work, we build upon the same idea, but investigating the feasibility of a fully data-driven Machine Learning (ML) approach. We designed a novel Convolutional Neural Network that learns how to produce an accurate surface from the scattered elevation data of three subsequent frames. The key idea is to embed the linear dispersion relation into the model itself to physically relate the sparse points observed at different times. Assuming that the scattered data are uniformly distributed in the spatial domain, this has the same effect of increasing the sample density of each single frame. Experiments demonstrate how the proposed technique, even if trained with purely synthetic data, can produce accurate and physically consistent surfaces at five frames per second on a modern PC. [ABSTRACT FROM AUTHOR]

• Spatio-temporal maximum wave heights occur to the north-east of the cyclone's eye, where sea states are more energetic. • Individual waves with normalized extreme heights are met to the south/south-west of the moving cyclone. • Directional spread and bound nonlinear interactions play a significant role in producing extreme waves. • Different physical mechanisms can trigger high waves in the sea regions under cyclone winds. Principles of the spatio-temporal statistics are used to investigate the characteristics of short-term/range extreme sea waves and related sea-state parameters under cyclone winds (northern hemisphere). We base our analysis upon consistent stereo-imaging observations of the 3D (2D space + time) sea surface elevation field, and spectral wave model results in the Northwestern Pacific during tropical storm Kong-rey (2018). The focus is on the extreme value analysis of individual maximum sea surface elevations (crest heights) and maximum crest-to-trough wave heights. Results highlight the sea areas around the storm centre where the spatio-temporal highest waves are more likely, and, via scale analysis, the principal mechanisms responsible for the occurrence of extreme conditions in bimodal (composed of wind-sea and swell) and short-crested storm seas. We find that individual waves are the highest to the north-east of the translating cyclone, where sea states are more energetic. However, in the south/south-west of the centre, where opposing wind-sea/swell sea states dominate, directional spread and bound nonlinear interactions are enhanced. In this area, more extreme waves may occur, having the maximum crest and wave heights mean values in excess of 1.3 and 2.1 times the significant wave height, respectively. This set of results provides insights into the role of the dispersive and directional focusing enhanced by nonlinearities up to the second order as an effective mechanism for the formation of extreme waves under cyclone winds. To examine what physical mechanism is behind the generation of extreme waves in different regions around the cyclone, we also explore for comparison areas where nonlinear four-wave interactions are more likely to occur. [ABSTRACT FROM AUTHOR]

Reliable predictions of oceanic waves during storms have always been foremost for offshore design and operation, coastal hazards, and navigation safety. Indeed, many accidents that occurred during storms were ascribed to the impact with unforeseen large waves. In this context, the purpose of this study is to improve the present state extreme wave estimate from spectral wave models. We describe an implementation for the WAM model, and we investigate the use of WAM and WAVEWATCH III fed with common routines designed to evaluate the short-term/range maximum wave statistics. An extensive assessment of models' results in the Adriatic and North Sea is performed using time and space-time wave measurements, and through an intercomparison between WAM and WAVEWATCH III applied with three different input/dissipation source term parametrizations (ST3/4/6). Further, models' capabilities are investigated, and extreme waves characterized, in the Mediterranean Sea, aiming also at disentangling the wave spectrum bulk parameters that may point to favorable conditions for the generation of high waves. Based on the comparisons between model results and measurements, we conclude that for the model characterization of extremes, the accuracy of the significant wave height is pivotal; differences between models of other spectral parameters seem to have a minor effect. • We improve the present state extreme wave estimate from spectral wave models WAM and WAVEWATCH III®. • We aim at disentangling the wave spectrum bulk parameters that may point to favorable conditions for the generation of high waves. • Model capabilities are examined, and extreme waves characterized, in the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

There is general consensus that accurate model predictions of extreme wave events during marine storms can substantially contribute to avoiding or minimizing human losses and material damage. Reliable wave forecasts and hindcasts, together with statistical analysis of extreme conditions, are then of utmost importance for monitoring marine areas. In this study, we perform an analysis of the limitations of the available short-term/range extreme-value distributions suitable for space-time maximum wave and crest heights. In particular, we propose an improvement of the theoretical distributions by including upper bounds on the maximum heights that waves may reach. The modification of the space-time probability distributions and its impact for extreme-value assessment is discussed in the paper. We show that unbounded space-time distributions are still effective provided that the surface area included in the analysis has sides smaller than O(102 m). For wider surfaces, the use of the bounded distributions is consistent with the expected saturation of maximum heights that ocean waves attain. [ABSTRACT FROM AUTHOR]

We perform a critical analysis of the present approach in wave modeling and of the related results. While acknowledging the good quality of the best present forecasts, we point out the limitations that appear when we focus on the corresponding spectra. Apart from the meteorological input, these are traced back to the spectral approach at the base of the present operational models, and the consequent approximations involved in properly modeling the various physical processes at work. Future alternatives are discussed. We then focus our attention on how, given the situation, to deal today with the estimate of the maximum wave heights, both in the long term and for a specific situation. For this, and within the above limits, a more precise evaluation of the wave spectrum is shown to be a mandatory condition. [ABSTRACT FROM AUTHOR]

Given the growing availability of directional spectra of ocean waves, we explore two different statistical approaches to mine large spectra databases: Spectral Partitions Statistics (SPS) and Self-Organizing Maps (SOM). The first method is not new in the literature, while the second one is for the first time here applied to directional wave spectra. The main goal is to improve the characterization of the directional wave climate at a site, providing a more complete and consistent description than that obtained from traditional statistical methods based on integral spectral parameters (e.g., H s , T m , θ m). Indeed, while the use of integral parameters allows a direct application of standard techniques for statistical analysis, important information related to the physics of the processes may be overlooked (e.g., the presence of multiple wave systems, for instance locally and remotely generated). The two proposed methods do not exclude integral parameters analysis, but they further allow accounting for different events (e.g., with different genesis) independently. Although SPS and SOM are equally valid for both numerical model and observational data, we illustrate their potential using a 37-year long (1979–2015) model dataset of directional wave spectra at a study site in the western Mediterranean Sea. We show that standard integral parameters fail to show the complex and even multimodal conditions at this site, that are otherwise revealed by the directional spectra statistical analysis. Although the processing pathways and the resulting indicators of both SPS and SOM are substantially different, we observe that their results are mutually consistent, and provide a better insight into the physical processes at work. [ABSTRACT FROM AUTHOR]

The LATEMAR project aims at improving the modelling of large wave events during marine storms in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). Indeed, at present, CMEMS operational systems only release average and peak wave parameters, with no information on individual waves whatsoever. However, developments of the state-of-the-art third-generation wave models (WAVEWATCH III and SWAN, for instance) demonstrated that, using the directional wave spectrum and theoretical statistical models for wave extremes, forecasters can accurately infer the expected shape and likelihood of the maximum waves during marine storms. The main goal of the LATEMAR project is therefore to provide the wave models used by the CMEMS service (WAM and WAVEWATCH III) with the procedures to explicitly estimate the maximum wave heights for each sea state. Besides this, further goals of LATEMAR are the following: perform an extensive assessment of the modeled maximum wave events using observations collected from an oceanographic station; inter-compare WAM and WAVEWATCH III model performance in a test area (Mediterranean Sea); investigate the sensitivity on sea state parameters of the maximum waves. All model developments and evaluations resulting from this R&D project will be directly applicable to the wave model forecasting systems, extending thus the CMEMS product catalogue. [ABSTRACT FROM AUTHOR]

In this study, we use reanalysis datasets to characterize the maximum crest, crest-to-trough and envelope heights of sea states, on a global and long-term scale. In particular, we rely on the ERA-Interim directional wave spectra, which are used to estimate the parameters of the probability distributions of wave maxima. To represent the typical single-point observations we use time extreme theoretical models, while to take the three-dimensional geometry and short-crestedness of ocean waves into account, we adopt a space-time extreme model. In order to assess the confidence limits of the reanalysis-based wave maxima we verify them against buoy and stereo-video wave observations collected in the North Pacific Ocean. We provide the global assessment of maximum crest, crest-to-trough and envelope heights during typical and extreme conditions, showing where the largest values are attained, that is in the mid-latitude storm belts, in particular in the North Atlantic Ocean. With respect to previous wave climate studies that focused on the significant wave height only, in this study, besides quantifying the maximum wave heights in magnitude, we also highlight the role of wave parameters such as wave steepness and kurtosis (measures of nonlinearity) and spectral bandwidth (measure of irregularity). Finally, we stress the relevant contribution of the short-crestedness, which should be taken into account in assessing wave maxima for the safety of navigation, ship routing and marine structural design. [ABSTRACT FROM AUTHOR]

In the last few years we faced an increased popularity of stereo imaging as an effective tool to investigate wind sea waves at short and medium scales. Given the advances of computer vision techniques, the recovery of a scattered point-cloud from a sea surface area is nowadays a well consolidated technique producing excellent results both in terms of wave data resolution and accuracy. Nevertheless, almost all the subsequent analyses tasks, from the recovery of directional wave spectra to the estimation of significant wave height, are bound to two limiting conditions. First, wave data are required to be aligned to the mean sea plane. Second, a uniform distribution of 3D point samples is assumed. Since the stereo-camera rig is placed tilted with respect to the sea surface, perspective distortion do not allow these conditions to be met. Errors due to this problem are even more challenging if the optical instrumentation is mounted on a moving vessel, so that the mean sea plane cannot be simply obtained by averaging data from multiple subsequent frames. We address the first problem with two main contributions. First, we propose a novel horizon estimation technique to recover the attitude of a moving stereo rig with respect to the sea plane. Second, an effective weighting scheme is described to account for the non-uniform sampling of the scattered data in the estimation of the sea-plane distance. The interplay of the two allows us to provide a precise point cloud alignment without any external positioning sensor or rig viewpoint pre-calibration. The advantages of the proposed technique are evaluated throughout an experimental section spanning both synthetic and real-world scenarios. [ABSTRACT FROM AUTHOR]

Stereo 3D reconstruction of ocean waves is gaining more and more popularity in the oceanographic community and industry. Indeed, recent advances of both computer vision algorithms and computer processing power now allow the study of the spatio-temporal wave field with unprecedented accuracy, especially at small scales. Even if simple in theory, multiple details are difficult to be mastered for a practitioner, so that the implementation of a sea-waves 3D reconstruction pipeline is in general considered a complex task. For instance, camera calibration, reliable stereo feature matching and mean sea-plane estimation are all factors for which a well designed implementation can make the difference to obtain valuable results. For this reason, we believe that the open availability of a well tested software package that automates the reconstruction process from stereo images to a 3D point cloud would be a valuable addition for future researches in this area. We present WASS ( http://www.dais.unive.it/wass ), an Open-Source stereo processing pipeline for sea waves 3D reconstruction. Our tool completely automates all the steps required to estimate dense point clouds from stereo images. Namely, it computes the extrinsic parameters of the stereo rig so that no delicate calibration has to be performed on the field. It implements a fast 3D dense stereo reconstruction procedure based on the consolidated OpenCV library and, lastly, it includes set of filtering techniques both on the disparity map and the produced point cloud to remove the vast majority of erroneous points that can naturally arise while analyzing the optically complex nature of the water surface. In this paper, we describe the architecture of WASS and the internal algorithms involved. The pipeline workflow is shown step-by-step and demonstrated on real datasets acquired at sea. [ABSTRACT FROM AUTHOR]

Stereo 3D reconstruction is continuously increasing its popularity in the study of mid-to small-scale sea waves. In the recent past, different approaches have been proposed to reconstruct the space-time sea surface elevation field from synchronized stereo frames. Usually, the reconstruction is performed by first recovering a dense and sparse 3D point cloud from stereo pairs and then by interpolating it into a regular grid. Even considering state-of-the-art methods, with typical image resolutions, it's unlikely to perform the first step in less than dozens of seconds (without paralellization), that can easily doubled if we include the subsequent interpolation step. This will limit the applicability of stereo based wave analysis for all the approaches (like monitoring or data assimilation) in which the time between the raw acquisition and the output of processed data is critical. In this paper, we propose a new method to directly estimate the sea surface spectrum over time from a sequence of stereo frames. We exploit the frequency dispersion relation of gravity waves and the (Non-uniform) Fast Fourier Transform to continuously update the 3D surface and 2D wavenumber spectrum estimations given a sparse set of matching features between the two frames. This effectively combines the two aforementioned steps with a performance gain of more than an order of magnitude while keeping a reconstruction accuracy that is extremely close to the current state-of-the-art approaches. Code is available at https://gitlab.com/fibe/wassfast. • WASSfast is a sea-waves 3D reconstruction method optimized for speed. • Wave spectrum is continuously estimated from a sparse set of stereo matches. • Extensive tests with real-data show good accuracy and 10× faster processing. [ABSTRACT FROM AUTHOR]

This research aims at characterizing the distinctive features of the spatio-temporal nonlinear wave surface during storm and typhoon conditions. We analyze wind-generated 3-D wave fields observed during the passage of an atmospheric front and the typhoon Talim in the Yellow Sea, which led to a wide directional and frequency spreading of the wave energy. Data were acquired in the Yellow Sea with stereo wave imaging systems aboard the ocean research stations Socheongcho-ORS and Gageocho-ORS. Observations include 3-D (i.e. 2-D + time) measurements of the sea surface elevation with high spatial and temporal resolution over a swath larger than any previous similar deployment. We examine the shape and the nonlinear properties of the wavenumber/frequency 3-D wave spectrum, and the characteristic spatial, temporal and spatio-temporal length scales of the wave field. We then focus on analyzing the probability of occurrence and the spatio-temporal size of the maximum and rogue waves we identified in the data. In particular, we provide an empirical estimate of the distribution and the horizontal extent of the sea surface spanned by rogue waves. The analysis is complemented by numerical model analysis of the wind and wave fields.Reference:Benetazzo, A., Bergamasco, F., Yoo, J., Cavaleri, L., Kim, S. S., Bertotti, L., Barbariol, F. and Shim, J. S.: Characterizing the signature of a spatio-temporal wind wave field, Ocean Model., 129, 104–123, doi:10.1016/j.ocemod.2018.06.007, 2018. [ABSTRACT FROM AUTHOR]