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We make a physical–mathematical analysis of the implications that the presence of a large number of tiny bubbles may have, when present, on the thin upper layer of the sea. In our oceanographic example, the bubbles are due to intense rain. It was found that the bubbles increase momentum dissipation in the near surface and affect the surface tension force. For short waves, the implications of increased vorticity are momentum exchanges between wave and mean flow and modifications to the wave dispersion relation. For the direct effect we have analyzed, the implications are estimated to be non-significant when compared to other processes of the ocean. However, we hint at the possibility that our analysis may be useful in other areas of research or practical application.

While moderate wind and wave conditions prevail in the eastern equatorial Pacific, modeling waves in this area remains challenging due to the presence of multiple wave systems converging from different parts of the ocean. This area is covered by swells originated far away including the storm belts of both hemispheres, coexisting with local generation due to the regular action of both the southern trade winds and the wind jets from Central America. In this context, our ability to predict waves in the area depends on the overall quality (i.e., at Pacific scale) of the meteorological input, and also on the skills of the wave model itself. Clearly any error at the remote generation areas translates into larger errors the further waves go, especially if attention is focused on coastal areas. A relevant aspect is that the traditional integral parameters do not offer the possibility to properly assess the errors associated with the different parts of the spectrum (e.g., wind sea and swell). To gain insight in this direction, we make use of partitioning techniques, which enables us to neatly cross-assign and evaluate three spectral components. Not surprisingly, the performance for the swell part is lower than that of the corresponding wind sea. This is further explored with a couple of tests modifying both the wind input and the wave model physics. We find that although at first sight the initial scheme (i.e., ST4) seems to provide the better estimate, the spectral analysis reveals a substantial underestimation of wind sea, compensated with a substantial overestimation of swell. This suggests a problem with too high winds and wave generation in the storm belts together with a likely lack of dissipation or dispersion of swell. In turn, local waves are generally underestimated due to a corresponding underestimation of the local winds. This insight emphasizes the need and advantages of evaluation methods able to look at the different sectors of the wave spectrum.

We carry out an inter-comparison of four different altimeters: Cryosat, Jason-2, Jason-3, and Sentinel-3. This inter-comparison is undertaken by checking the altimeter data against the wind and wave model results of a given area, the Mediterranean Sea, for a 1-year period. The four data sets are consistent for wind speed, but they show substantial differences with respect to wave heights. The verification of a Sentinel-3 pass close to the coast in the northern Adriatic Sea shows irregular, spiky, large, wave height values close to the coast. This problem worsens when using high-frequency altimeter data.

In February 2017, a wave buoy was deployed in the Southern Ocean, south of New Zealand at 52°45.71′S, 169°02.54′E. For 170 days, the moored buoy transmitted spectral and time domain observations, including measurements during a storm with a particularly large individual wave of 19.4-m crest-to-trough height. We present a detailed analysis of this storm and the measured and modelled spectra, also considering the probability of the occurrence of single large waves. After 170 days, the buoy broke free of its mooring and started drifting eastwards, still transmitting the essential data, thereby providing a unique opportunity to examine large wave events and their corresponding spectral conditions in the Southern Ocean on both moored and free-drifting platforms. The results are discussed quantitatively.

Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions. The work of UPC team included in this paper has been funded by the Ecosistema-BC Spanish Research Project (CTM2017-84275-R/MICINN-AEI-FEDER,UE) of the 2017 RETOS State Research Program.

Over the past decade, model reanalysis data products have found widespread application in many areas of research and have often been used for the assessment of the past and present atmospheric climate. They produce reliable fields at high temporal resolution (1 hour), albeit generally at low-to-mid spatial resolution (0.25°-1.00°). On the other hand, climatological analyses, quite often down-scaled (up to few km) to represent conditions also in enclosed basins, lack the actual historical sequence of events and are often provided at poor temporal resolution (6 hours or daily).In this context, we investigated the possibility of using climate model data to scale ERA5 reanalysis wind (25-km and 1-hour resolution data) to assess the Mediterranean Sea wind and wave climate. We propose a statistical strategy to fuse ERA5 wind speeds over the sea with the past and future wind speeds produced by the COSMO-CLM (8-km and daily-mean data) climatological model. In the method, the probability density function of the ERA5 wind speed at each grid point is adjusted to match that of COSMO-CLM using a histogram equalization strategy. In this way, past ERA5 data are corrected to account for the COSMO-CLM wind distribution, while ERA5 scaled wind sequence can be also projected in the future with COSMO-CLM scenarios. Comparison with past observations of wind and waves confirms the validity of the adopted method.We have tested this strategy for the assessment of the changing wind and, after WAVEWATCH III model runs, also the wave climate in the northern Adriatic Sea, especially in front of Venice and the MOSE barriers. In general, this data fusion strategy may be applied to produce a scaled wind dataset in enclosed basins and improve past and scenario wave modeling applications based on any reanalysis wind data.

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.

On December 15, 2009, a very high wave crest was recorded by a local camera at the CNR-ISMAR oceanographic tower, 15 km offshore Venice in the Northern Adriatic Sea (Italy). The height of the estimated crest elevation appears well beyond the value (1,25·Hs) commonly used to identify a wave as freak. We document the wave event with a full description of the corresponding met-ocean conditions and related measurements, of which we provide a critical analysis., Measurement(s) atmospheric wind direction • atmospheric wind speed • wave Technology Type(s) weather station • acoustic AWAC system • waverider buoy • Camera Device Sample Characteristic - Environment coastal sea water Sample Characteristic - Location Adriatic Sea Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13415780

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.

The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.

We make a physical-mathematical analysis of the implications that the presence of a large number of tiny bubbles may have on the thin upper layer of the sea. In our oceanographic example the bubbles are due to an intense rain on an otherwise non-stormy surface; if stormy, other processes would take the role. For the direct effect we have analyzed, the implications are estimated non-significant when compared to other processes of the ocean. However, we hint to the possibility that our analysis may be useful in other areas of research or practical application.

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.

Reliable prediction of oceanic waves during severe marine storms has always been foremost for offshore platform design, coastal activities, and navigation safety. Indeed, many damaging accidents and casualties during storms were ascribed to the impact with abnormal and unexpected waves. However, predicting extreme wave occurrence is a challenging task, at first, because of their inherent randomness, and because the observation of large ocean waves, of primary importance to assess theoretical and numerical models, is limited by the costs and risks of deployment during severe open-ocean sea-state conditions.In the context of the EU-based Copernicus Marine Environment Monitoring Service (CMEMS) evolution, the LATEMAR project (https://www.mercator-ocean.fr/en/portfolio/latemar/) aimed at improving the modelling of large wave events during marine storms. Indeed, at present, operational systems only provide average and peak wave parameters, with no information on individual waves whatsoever. However, developments of the state-of-the-art third-generation wave models demonstrated that using the directional wave spectrum moments into theoretical statistical models for wave extremes, forecasters are able to accurately infer the expected shape and likelihood of the maximum waves during storms.The main purpose of the activity is therefore to provide the wave models WAM and WAVEWATCH III with common procedures to explicitly estimate the maximum wave heights for each sea state. LATEMAR achieved this goal by: performing an extensive assessment of the model maximum waves using field observations collected from an oceanographic tower; comparing WAM and WAVEWATCH III maximum wave estimates in the Mediterranean Sea; investigating the sensitivity of the maximum waves on the main sea state parameters. All model developments and evaluations resulting from this research project will be directly applicable to the wave model forecasting systems to expand their catalogue.

Over the past decade, reanalysis data products have found widespread application in many areas of research and have often been used for the assessment of the past and present climate. They produce reliable atmospheric fields at high temporal resolution, albeit at low-to-mid spatial resolution. On the other hand, climatological analyses, quite often down-scaled to represent conditions also in enclosed basins, lack the historical sequence of stormy events and are often provided at poor temporal resolution.In this context, we investigated the possibility of using the ERA5 reanalysis 10-m wind (25-km and 1-hour resolution data) to assess the Mediterranean Sea wind climate (past and scenario). We propose a statistical strategy to relate ERA5 wind speeds over the sea to the past and future wind speeds produced by the COSMO-CLM (8-km and 6-hour resolution data) climatological model. In particular, the probability density function of the ERA5 wind speed at each grid point is adjusted to match that of COSMO-CLM. In this way, past ERA5 winds are corrected to account for the COSMO-CLM energy, while ERA5 scaled wind sequence can be projected in the future with COSMO-CLM scenario energy. Comparison with past observations confirms the validity of the adopted method.In the Venezia2021 project, we have applied this strategy for the assessment of the changing wind and, after WAVEWATCH III model runs, also the wave climate in the Northern Adriatic Sea, especially in front of Venice and the MOSE barriers, under two IPCC (RCP 4.5 and 8.5) scenarios.In general, this strategy may be applied to produce a scaled wind dataset in enclosed basins and improve past wave modeling applications based on any reanalysis wind data.

On 12 November 2019, an exceptional flood event occurred in Venice, second only to the one that occurred on 4 November 1966. The maximum recorded sea level value of 189 cm above local datum resulted in the flooding of more than 85% of the pedestrian surface of the historical city. Moreover, with four extremely high tides since 11 November 2019, this has been the worst week for flooding in Venice ever since 1872, when official statistics were first produced. The event that struck Venice and the northern Adriatic Sea on 12 November 2019, although having certain conditions seemingly typical of the events that cause exceptional high waters, also had some peculiar characteristics not observed before and therefore it requires an in-depth analysis. Several factors made this event exceptional: an in-phase timing of the peak of the storm surge and the astronomical tide; an anomalously high monthly mean sea level in the Adriatic Sea induced by a steady low-pressure and wind systems over the Mediterranean Sea associated with large-scale low-frequency atmospheric dynamics; a deep low-pressure system over the central-southern Tyrrhenian Sea that generated strong sirocco (south-easterly) winds along the main axis of the Adriatic Sea pushing the waters towards north; a fast-moving local depression - and the associated wind perturbation - travelling in the north-westward direction along the Italian coast that may have forced long ocean waves (e.g., edge wave); and very strong winds (100 km h-1 on average, with gusts reaching 110 km h-1) over the Lagoon of Venice which led to a further rise in water levels and damage to the historic city. In this study, a large set of available observations and the high-resolution numerical simulations are used to quantify the influence of these drivers on the peak flood event and to investigate the peculiar weather and sea conditions over the Mediterranean Sea during the Venice floods of November 2019.

In the context of the Copernicus Program, EUMETSAT prioritizes the creation of an ocean color infrastructure for system vicarious calibration (OC-SVC). This work aims to reply to this need by proposing the European Radiometry Buoy and Infrastructure (EURYBIA). EURYBIA is designed as an autonomous European infrastructure operating within the Marine Optical Network (MarONet) established by University of Miami (Miami, FL, USA) based on the Marine Optical Buoy (MOBY) experience and NASA support. MarONet addresses SVC requirements in different sites, consistently and in a traceable way. The selected EURYBIA installation is close to the Lampedusa Island in the central Mediterranean Sea. This area is widely studied and hosts an Atmospheric and Oceanographic Observatory for long-term climate monitoring. The EURYBIA field segment comprises off-shore and on-shore infrastructures to manage the observation system and perform routine sensors calibrations. The ground segment includes the telemetry center for data communication and the processing center to compute data products and uncertainty budgets. The study shows that the overall uncertainty of EURYBIA SVC gains computed for the Sentinel-3 OLCI mission under EUMETSAT protocols is of about 0.05% in the blue-green wavelengths after a decade of measurements, similar to that of the reference site in Hawaii and in compliance with requirements for climate studies.

Starting from a quick historical perspective, I frame the present situation among meteorologists and oceanographers, joined by the crucial role of the sea surface interface. Hinting to its dynamics, I then focus on the key process of white-capping. I stress how much we still have to learn, discussing in particular the relevance of rain as an example of a process whose implications, for white-capping hence spray, are practically ignored. I frame the related situation, also with practical examples and applications.

This study aims at characterizing the distinctive features of a spatio-temporal nonlinear wave surface. We analyze wind-generated 3-D wave fields observed during the passage of an atmospheric front, which led to a wide directional spreading of wave energy. Data were acquired from the ocean research station Socheongcho-ORS (Yellow Sea) with a stereo wave imaging system. They 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 rogue waves we identified in the data. In particular, we provide for the first time an empirical estimate of the extent of the horizontal sea surface spanned by rogue waves. We also propose and assess a novel strategy to determine from the 3-D wave spectrum the vertical current profile, to be then used to map the spectrum on intrinsic frequencies.

The wind and wave climatology of the Red Sea is derived from a validated 30-yr high-resolution model simulation. After describing the relevant features of the basin, the main wind and wave systems are identified by using an innovative spectral partition technique to explain their genesis and characteristics. In the northern part of the sea, wind and waves of the same intensity are present throughout the year, while the central and southern zones are characterized by a marked seasonality. The partition technique allows the association of a general decrease in the energy of the different wave systems with a specific weather pattern. The most intense decrease is found in the northern storms, which are associated with meteorological pulses from the Mediterranean Sea.

We use our previous numerical and measuring experience and the evidence from a rather unique episode at sea to summarise our doubts on the present physical approach in wave modelling. The evidence strongly suggests that generation by wind and dissipation by white-capping have a different physics than presently considered. Most of all they should be viewed as part of a single physical process.

Within the progressive improvement in wave modeling we focus on the attenuation of swell waves by rain. Till now ignored, the process is shown to be relevant, especially for the correct estimate of swell. Following the practical impossibility of devoted field experiments, we exploit the global model results over a period of more than four years to extract the tiny signal associated to the attenuation by rain. A direct comparison of the ratio model by altimeter significant wave heights versus the encountered rain amount hints to a marked related dependence. A proper quantification of the related physical effect requires a multiple step procedure that we describe in detail. We check the reliability of the results, and we provide the related source function ready for implementation in operational wave models.

On 12 November 2019, an exceptional flood event took place in Venice, second only to the one that occurred on 4 November 1966. Moreover, with four extremely high tides since 11 November 2019, this was the worst week for flooding in Venice since the beginning of sea level records (1872). The event that struck Venice and the northern Adriatic Sea on 12 November 2019, although having certain conditions seemingly typical of the events causing exceptional high waters, had some peculiar characteristics not observed before, which deserved an in-depth analysis. Several factors made this event exceptional: the in-phase timing between the peak of the storm surge and the astronomical tide; a deep low-pressure cyclone over the central-southern Tyrrhenian Sea that generated strong Sirocco (south-easterly) winds along the main axis of the Adriatic Sea, pushing waters to the north; a fast-moving local depression – and the associated wind perturbation – travelling in the north-westward direction over the Adriatic Sea along the Italian coast, generating a meteotsunami; very strong winds (28 m s − 1 on average with 31 m s − 1 gusts) over the Lagoon of Venice, which led to a rise in water levels and damages to the historic city; and an anomalously high monthly mean sea level in the Adriatic Sea, induced by a standing low-pressure and wind systems over the Mediterranean Sea, that was associated with large-scale low-frequency atmospheric dynamics. In this study, the large set of available observations and high-resolution numerical simulations have been used to quantify the contribution of the mentioned drivers to the peak of the flood event and to investigate the peculiar weather and sea conditions over the Mediterranean Sea during the Venice floods of November 2019.

We analyse high rate (20 Hz) altimeter derived sea level information, both from Synthetic Aperture Radar (SAR) altimetry missions and Low Resolution Mode missions, in an inner sea and coastal environment. They are compared versus measured and high resolution model data. After a compact description of the relevant physical processes affecting the local sea level values, we focus on three specific passes on the Adriatic Sea, East of Italy. Our main finding is that altimeters and models provide both valuable, partially overlapping, but complementary, information to be exploited in parallel with a double purpose: to progressively approach the truth and to ensure the parallel improvement of both sources. From altimeter data there is a very strong suggestion that the spatial, and implicitly temporal, variability of the fields is much higher than shown by models. The reasons are discussed.

We consider the observation and analysis of oceanic rogue waves collected within spatio-temporal (ST) records of 3D wave fields. This class of records, allowing a sea surface region to be retrieved, is appropriate for the observation of rogue waves, which come up as a random phenomenon that can occur at any time and location of the sea surface. To verify this aspect, we used three stereo wave imaging systems to gather ST records of the sea surface elevation, which were collected in different sea conditions. The wave with the ST maximum elevation (happening to be larger than the rogue threshold 1.25Hs) was then isolated within each record, along with its temporal profile. The rogue waves show similar profiles, in agreement with the theory of extreme wave groups. We analyze the rogue wave probability of occurrence, also in the context of ST extreme value distributions, and we conclude that rogue waves are more likely than previously reported; the key point is coming across them, in space as well as in time. The dependence of the rogue wave profile and likelihood on the sea state conditions is also investigated. Results may prove useful in predicting extreme wave occurrence probability and strength during oceanic storms.

The wind climatology of the Red Sea is described based on a 30-year high-resolution regional reanalysis generated using the Advanced Weather Research Forecasting model. The model was reinitialized on a daily basis with ERA-Interim global data and regional observations were assimilated using a cyclic three-dimensional variational approach. The reanalysis products were validated against buoy and scatterometers data. We describe the wind climatology and identify four major systems that determine the wind patterns in the Red Sea. Each system has a well-defined origin, and consequently different characteristics along the year. After analysing the relevant features of the basin in terms of their climatology, we investigate possible long-term trends in each system. It is found that there is a definite tendency towards lowering the strength of the wind speed, but at a different rate for different systems and periods of the year.

The wave climatology of the Red Sea is described based on a 30-year hindcast generated using WAVEWATCH III configured on a 5-km resolution grid and forced by Red Sea reanalysis surface winds from the advanced Weather Research and Forecasting model. The wave simulations have been validated using buoy and altimeter data. The four main wind systems in the Red Sea characterize the corresponding wave climatology. The dominant ones are the two opposite wave systems with different genesis, propagating along the axis of the basin. The highest waves are generated at the centre of the Red Sea as a consequence of the strong seasonal winds blowing from the Tokar Gap on the African side. There is a general long-term trend toward lowering the values of the significant wave height over the whole basin, with a decreasing rate depending on the genesis of the individual systems.

Improving intensity simulation and forecast of tropical cyclones has always been a challenge, although in recent years the track forecasts have been remarkably improved. In this study, we explore the sensitivity of typhoon simulation to three physical processes using a fully coupled atmosphere-ocean-wave model. Two storms, a strong and a weak one, have been chosen. The effects of wave breaking induced sea spray, ocean vertical mixing associated with nonbreaking surface waves, and sea surface cooling due to intense rainfall are assessed by means of a set of numerical experiments. The results show and confirm that sea spray leads to an increase of typhoon intensity by enhancing the air-sea heat flux, while nonbreaking wave-induced vertical mixing and rainfall lead to a decrease. Each process can be relevant, depending on wind and wave conditions. These can vary dramatically when typhoons interact with not sufficiently well-defined coastal areas, typically an archipelago. Compared with the control runs, when all the three physical processes are considered, the (absolute) difference between the modeled sea level pressure and best track data is reduced from 26.05 to 0.70 hPa for typhoon Haiyan, and from −9.42 to −8.67 hPa for typhoon Jebi. We have found a steady overestimate of the dimensions of the typhoons. We have verified an extreme sensitivity to the initial conditions, especially when small differences in the typhoon track may imply different relevance of the physical processes, like the ones we have considered, governing the evolution of the storm.

We suggest that there exists a natural bandwidth of wave trains, including trains of wind-generated waves with a continuous spectrum, determined by their steepness. Based on laboratory experiments with monochromatic waves, we show that, if no side-band perturbations are imposed, the ratio between the wave steepness and bandwidth is restricted to certain limits. These limits are consistent with field observations of narrow-banded wind-wave spectra if a characteristic width of the spectral peak and average steepness are used. The role of the wind in such modulation is also discussed.

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., Hs, Tm, θm). 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.

Surfactant layers with viscoelastic properties floating on the water surface dampen short gravity-capillary waves. Taking advantage of the known virtue of fish oil to still angry seas, a laboratory study has been made to analyse wind-wave generation and the interaction between wind waves, paddle waves, and airflow. This was done in a tank containing a thin fish-oil film uniformly spread on the water surface. The research was aimed, on the one hand, at quantifying for the first time the effectiveness of this surfactant at impeding the generation of wind waves and, on the other, at using the derived conditions to disentangle relevant mechanisms involved in the air–sea interaction. In particular, our main interest concerned the processes acting on the wind stress and on the wave growth. With oil on the water surface, we have found that in the wind-only condition (no paddle waves) the wave field does not grow from the rest condition. This equilibrium is altered by irregular paddle (long) waves, the generation and evolution of short waves (in clean water and with oil) being modified by their interaction with the orbital velocity of the long waves and their effect on the airflow. Paddle waves do grow under the action of wind, the amount being similar in clean and oily water conditions, a fact we ascribe to the similar distortion of the wind vertical profile in the two cases. We have also verified that the wind-supported stress on the oily water surface was able to generate a surface current, whose magnitude turns out to be comparable to the one in clean water. We stress the benefits of experiments with surfactants to explore in detail the physics at, and the exchanges across, the wavy and non-wavy air–water interface.

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.

Surfactant layers with viscoelastic properties floating on the water surface damp short gravity-capillary waves. Inspired by the known virtue of fish oil to still angry seas, a laboratory study has been made on wind wave generation and on the interaction between wind-waves, paddle-waves and airflow in a tank containing a thin fish oil film uniformly spread on the water surface. According to the Marangoni resonance-type damping mechanism, for oily surfaces the energy dissipation process is quite selective in wavenumbers, but its effects are not, since it spreads (although to a lesser extent) towards longer and shorter waves via nonlinear interactions and modification of the airflow profile. With a thin layer of oil on the surface, it is rather peculiar that in the wind-only condition (no paddle waves) the wave field does not grow from the rest condition. This equilibrium was altered by paddle (longer) waves, the generation and evolution of short waves (in clean water and with oil) being modified by their interaction with the orbital velocity of the longer waves and their effect on the airflow. Paddle waves did grow under the action of wind, how much being similar in clean and oily water conditions, a fact we ascribe to the similar distortion of the wind profile in the two cases. We have also found that wind-supported stress on the oily water surface was able to generate a surface current, whose magnitude turns out to be comparable to the one in clean water. Our results expand previous investigations on the same topic. We stress the benefit of experiments with surfactants to explore in detail the physics at, and the exchanges across, the wavy and no-wavy air-water interface.

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 .

This paper compares the performance of two wind and wave short range ensemble forecast systems for the Mediterranean Sea. In particular, it describes a six month verification experiment carried out by the U.K. Met Office and Italian Air Force Meteorological Service, based on their respective systems: the Met Office Global-Regional Ensemble Prediction System and the Nettuno Ensemble Prediction System. The latter is the ensemble version of the operational Nettuno forecast system. Attention is focused on the differences between the two implementations (e.g. grid resolution and initial ensemble members sampling) and their effects on the prediction skill. The cross-verification of the two ensemble systems shows that from a macroscopic point of view the differences cancel out, suggesting similar skill. More in-depth analysis indicates that the Nettuno wave forecast is better resolved but, on average, slightly less reliable than the Met Office product. Assessment of the added value of the ensemble techniques at short range in comparison with the deterministic forecast from Nettuno, reveals that adopting the ensemble approach has small, but substantive, advantages.