Search

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., Astrodynamics & Space Missions, Mathematical Geodesy and Positioning, Space Engineering

Sea state estimation (SSE) is significant to the development of autonomous ships, which can enhance the sustainable development of maritime transportation. Traditional model-based methods are limited by their drawbacks, such as high costs and inaccurate estimations. The deep learning model shows superior performance, but it requires that the sample quantity for each sea state should be almost the same. Since the occurrence probability of each state is different, the ships mainly work in low sea states, and the collected ship motion data for different sea states are highly imbalanced. This work proposes a novel class-imbalanced ship motion data-based cross-scale model for SSE. The model consists of three major components: a multi-scale feature learning module, a cross-scale feature learning module, and a prototype classifier module. The multi-scale and cross-scale feature learning modules are designed to learn abundant coarse and fine-level features from the ship motion data. The prototype classifier is utilized to overcome the limitation of the conventional softmax classifier to produce better estimates. Our research highlights our model’s remarkable scalability and versatility with 30 publicly available datasets in time series classification, demonstrating superior performance over baseline methods in 21 cases. Notably, it outperformed ShapeNet by 5.72% and EDI by 26.3%. We further validated our model’s proficiency using ship motion datasets, consistently surpassing eight state-of-the-art baselines and five class-imbalanced learning methods. Ablation and sensitivity studies, emphasize the critical role of each model component. Our findings underscore the model’s robustness and its potential to advance time series classification in diverse domains.

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. In order 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.

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. In order 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.

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 3 1023 forwindspeedsof25–55 m s21.Whilethedragcoefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is signif-icantly 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.

Given the considerable range of applications within the European Union Copernicus system, sustained satellite altimetry missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to provide precision sea level, sea surface height, significant wave height, inland water heights and other products tailored to operational services in the ocean, climate, atmospheric and land Copernicus Services. Sentinel-6 provides enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The satellite and payload elements are explained including required performance and their operation. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter that uses an innovative interleaved mode. This enables radar data processing on two parallel chains the first provides synthetic aperture radar (SAR) processing in Ku-band to improve the received altimeter echoes through better along-track sampling and reduced measurement noise; the second provides a Low Resolution Mode that is fully backward-compatible with the historical reference altimetry measurements, allowing a complete inter-calibration between the state-of-the-art data and the historical record. A three-channel Advanced Microwave Radiometer for Climate (AMR–C) provides measurements of atmospheric water vapour to mitigate degradation of the radar altimeter measurements. The main data products are explained and pr, Optical and Laser Remote Sensing

Given the considerable range of applications within the European Union Copernicus system, sustained satellite altimetry missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to provide precision sea level, sea surface height, significant wave height, inland water heights and other products tailored to operational services in the ocean, climate, atmospheric and land Copernicus Services. Sentinel-6 provides enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The satellite and payload elements are explained including required performance and their operation. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter that uses an innovative interleaved mode. This enables radar data processing on two parallel chains the first provides synthetic aperture radar (SAR) processing in Ku-band to improve the received altimeter echoes through better along-track sampling and reduced measurement noise; the second provides a Low Resolution Mode that is fully backward-compatible with the historical reference altimetry measurements, allowing a complete inter-calibration between the state-of-the-art data and the historical record. A three-channel Advanced Microwave Radiometer for Climate (AMR–C) provides measurements of atmospheric water vapour to mitigate degradation of the radar altimeter measurements. The main data products are explained and pr, Optical and Laser Remote Sensing

Long‐term changes in ocean surface waves are relevant to society and climate research. Significant wave height climatologies and trends over 1992‐2017 are intercompared in four recent high‐quality global datasets using a consistent methodology. For two products based on satellite altimetry, including one from the European Space Agency Climate Change Initiative for Sea State, regional differences in mean climatology are linked to low and high sea states. Trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multi‐decadal observations at two buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all products. Plain Language Summary Changes to ocean waves over decades and longer are of considerable importance to climate, society and the marine economy. Accurate observations of waves spanning many decades are required to understand long‐term changes, but the challenges and cost of measuring waves worldwide with devices like buoys means that alternatives like Earth‐orbiting satellites become attractive. We compare two recently published global wave products derived from the same satellite observations, with two high quality products from computer simulations, and buoy measurements. Using a consistent methodology, we find important differences between the satellite products, and the simulations, in the reported average global wave conditions, and their evolution in time. The disagreement between the satellite products points to complex differences in the way satellite data are corrected, which raises questions about uncertainty in these products, and more generally, about what is our most reliable long‐term observat

Long‐term changes in ocean surface waves are relevant to society and climate research. Significant wave height climatologies and trends over 1992‐2017 are intercompared in four recent high‐quality global datasets using a consistent methodology. For two products based on satellite altimetry, including one from the European Space Agency Climate Change Initiative for Sea State, regional differences in mean climatology are linked to low and high sea states. Trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multi‐decadal observations at two buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all products. Plain Language Summary Changes to ocean waves over decades and longer are of considerable importance to climate, society and the marine economy. Accurate observations of waves spanning many decades are required to understand long‐term changes, but the challenges and cost of measuring waves worldwide with devices like buoys means that alternatives like Earth‐orbiting satellites become attractive. We compare two recently published global wave products derived from the same satellite observations, with two high quality products from computer simulations, and buoy measurements. Using a consistent methodology, we find important differences between the satellite products, and the simulations, in the reported average global wave conditions, and their evolution in time. The disagreement between the satellite products points to complex differences in the way satellite data are corrected, which raises questions about uncertainty in these products, and more generally, about what is our most reliable long‐term observat

Long‐term changes in ocean surface waves are relevant to society and climate research. Significant wave height climatologies and trends over 1992‐2017 are intercompared in four recent high‐quality global datasets using a consistent methodology. For two products based on satellite altimetry, including one from the European Space Agency Climate Change Initiative for Sea State, regional differences in mean climatology are linked to low and high sea states. Trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multi‐decadal observations at two buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all products. Plain Language Summary Changes to ocean waves over decades and longer are of considerable importance to climate, society and the marine economy. Accurate observations of waves spanning many decades are required to understand long‐term changes, but the challenges and cost of measuring waves worldwide with devices like buoys means that alternatives like Earth‐orbiting satellites become attractive. We compare two recently published global wave products derived from the same satellite observations, with two high quality products from computer simulations, and buoy measurements. Using a consistent methodology, we find important differences between the satellite products, and the simulations, in the reported average global wave conditions, and their evolution in time. The disagreement between the satellite products points to complex differences in the way satellite data are corrected, which raises questions about uncertainty in these products, and more generally, about what is our most reliable long‐term observat

Long‐term changes in ocean surface waves are relevant to society and climate research. Significant wave height climatologies and trends over 1992‐2017 are intercompared in four recent high‐quality global datasets using a consistent methodology. For two products based on satellite altimetry, including one from the European Space Agency Climate Change Initiative for Sea State, regional differences in mean climatology are linked to low and high sea states. Trends from the altimetry products, and two reanalysis and hindcast datasets, show general similarity in spatial variation and magnitude but with major differences in equatorial regions and the Indian Ocean. Discrepancies between altimetry products likely arise from differences in calibration and quality control. However, multi‐decadal observations at two buoy stations also highlight issues with wave buoy data, raising questions about their unqualified use, and more fundamentally about uncertainty in all products. Plain Language Summary Changes to ocean waves over decades and longer are of considerable importance to climate, society and the marine economy. Accurate observations of waves spanning many decades are required to understand long‐term changes, but the challenges and cost of measuring waves worldwide with devices like buoys means that alternatives like Earth‐orbiting satellites become attractive. We compare two recently published global wave products derived from the same satellite observations, with two high quality products from computer simulations, and buoy measurements. Using a consistent methodology, we find important differences between the satellite products, and the simulations, in the reported average global wave conditions, and their evolution in time. The disagreement between the satellite products points to complex differences in the way satellite data are corrected, which raises questions about uncertainty in these products, and more generally, about what is our most reliable long‐term observat

The Sea surface KInematics Multiscale monitoring (SKIM) satellite mission is designed to explore ocean surface current and waves. This includes tropical currents, notably the poorly known patterns of divergence and their impact on the ocean heat budget, and monitoring of the emerging Arctic up to 82.5°N. SKIM will also make unprecedented direct measurements of strong currents, from boundary currents to the Antarctic circumpolar current, and their interaction with ocean waves with expected impacts on air-sea fluxes and extreme waves. For the first time, SKIM will directly measure the ocean surface current vector from space. The main instrument on SKIM is a Ka-band conically scanning, multi-beam Doppler radar altimeter/wave scatterometer that includes a state-of-the-art nadir beam comparable to the Poseidon-4 instrument on Sentinel 6. The well proven Doppler pulse-pair technique will give a surface drift velocity representative of the top meter of the ocean, after subtracting a large wave-induced contribution. Horizontal velocity components will be obtained with an accuracy better than 7 cm/s for horizontal wavelengths larger than 80 km and time resolutions larger than 15 days, with a mean revisit time of 4 days for of 99% of the global oceans. This will provide unique and innovative measurements that will further our understanding of the transports in the upper ocean layer, permanently distributing heat, carbon, plankton, and plastics. SKIM will also benefit from co-located measurements of water vapor, rain rate, sea ice concentration, and wind vectors provided by the European operational satellite MetOp-SG(B), allowing many joint analyses. SKIM is one of the two candidate satellite missions under development for ESA Earth Explorer 9. The other candidate is the Far infrared Radiation Understanding and Monitoring (FORUM). The final selection will be announced by September 2019, for a launch in the coming decade.

The Sea surface KInematics Multiscale monitoring (SKIM) satellite mission is designed to explore ocean surface current and waves. This includes tropical currents, notably the poorly known patterns of divergence and their impact on the ocean heat budget, and monitoring of the emerging Arctic up to 82.5°N. SKIM will also make unprecedented direct measurements of strong currents, from boundary currents to the Antarctic circumpolar current, and their interaction with ocean waves with expected impacts on air-sea fluxes and extreme waves. For the first time, SKIM will directly measure the ocean surface current vector from space. The main instrument on SKIM is a Ka-band conically scanning, multi-beam Doppler radar altimeter/wave scatterometer that includes a state-of-the-art nadir beam comparable to the Poseidon-4 instrument on Sentinel 6. The well proven Doppler pulse-pair technique will give a surface drift velocity representative of the top meter of the ocean, after subtracting a large wave-induced contribution. Horizontal velocity components will be obtained with an accuracy better than 7 cm/s for horizontal wavelengths larger than 80 km and time resolutions larger than 15 days, with a mean revisit time of 4 days for of 99% of the global oceans. This will provide unique and innovative measurements that will further our understanding of the transports in the upper ocean layer, permanently distributing heat, carbon, plankton, and plastics. SKIM will also benefit from co-located measurements of water vapor, rain rate, sea ice concentration, and wind vectors provided by the European operational satellite MetOp-SG(B), allowing many joint analyses. SKIM is one of the two candidate satellite missions under development for ESA Earth Explorer 9. The other candidate is the Far infrared Radiation Understanding and Monitoring (FORUM). The final selection will be announced by September 2019, for a launch in the coming decade.

Design optimization is crucial as offshore structures are exposed to deeper and harsher marine conditions. The structure behaviour is dependent on several joint environmental parameters (wind, wave, currents, etc.). Environmental contours are useful representations to provide multivariate design conditions. However, these contours may lead to different design points depending on the method used to compute them, and thus may be misleading to structural engineer. In this work, we propose to use a response meta-model for the inter-comparison of some state-of-the-art methods available for modelling multivariate extremes, in order to provide a straightforward methodology, focusing on the derivation of three-dimensional contours. The considered case study focuses on the tension in a mooring line of a semi-submersible platform. In a first step, the key met-ocean parameters and the associated load model of the tension in the mooring line are set-up. Several multivariate extreme analysis methods are then applied to derive the environmental contours. These methods are chosen in order to cover all the possible dependence cases, from extremal dependence to extremal independence. Conditional Extreme and several extreme value dependence function models are investigated. The physical-space Huseby contouring method is used to derive environmental surface. A comparison with the extreme load extrapolated from the meta-model is provided to assess the performance of each method.

Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

The Sea surface KInematics Multiscale monitoring (SKIM) satellite mission is designed to explore ocean surface current and waves. This includes tropical currents, notably the poorly known patterns of divergence and their impact on the ocean heat budget, and monitoring of the emerging Arctic up to 82.5°N. SKIM will also make unprecedented direct measurements of strong currents, from boundary currents to the Antarctic circumpolar current, and their interaction with ocean waves with expected impacts on air-sea fluxes and extreme waves. For the first time, SKIM will directly measure the ocean surface current vector from space. The main instrument on SKIM is a Ka-band conically scanning, multi-beam Doppler radar altimeter/wave scatterometer that includes a state-of-the-art nadir beam comparable to the Poseidon-4 instrument on Sentinel 6. The well proven Doppler pulse-pair technique will give a surface drift velocity representative of the top meter of the ocean, after subtracting a large wave-induced contribution. Horizontal velocity components will be obtained with an accuracy better than 7 cm/s for horizontal wavelengths larger than 80 km and time resolutions larger than 15 days, with a mean revisit time of 4 days for of 99% of the global oceans. This will provide unique and innovative measurements that will further our understanding of the transports in the upper ocean layer, permanently distributing heat, carbon, plankton, and plastics. SKIM will also benefit from co-located measurements of water vapor, rain rate, sea ice concentration, and wind vectors provided by the European operational satellite MetOp-SG(B), allowing many joint analyses. SKIM is one of the two candidate satellite missions under development for ESA Earth Explorer 9. The other candidate is the Far infrared Radiation Understanding and Monitoring (FORUM). The final selection will be announced by September 2019, for a launch in the coming decade.

Design optimization is crucial as offshore structures are exposed to deeper and harsher marine conditions. The structure behaviour is dependent on several joint environmental parameters (wind, wave, currents, etc.). Environmental contours are useful representations to provide multivariate design conditions. However, these contours may lead to different design points depending on the method used to compute them, and thus may be misleading to structural engineer. In this work, we propose to use a response meta-model for the inter-comparison of some state-of-the-art methods available for modelling multivariate extremes, in order to provide a straightforward methodology, focusing on the derivation of three-dimensional contours. The considered case study focuses on the tension in a mooring line of a semi-submersible platform. In a first step, the key met-ocean parameters and the associated load model of the tension in the mooring line are set-up. Several multivariate extreme analysis methods are then applied to derive the environmental contours. These methods are chosen in order to cover all the possible dependence cases, from extremal dependence to extremal independence. Conditional Extreme and several extreme value dependence function models are investigated. The physical-space Huseby contouring method is used to derive environmental surface. A comparison with the extreme load extrapolated from the meta-model is provided to assess the performance of each method.

Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

The Sea surface KInematics Multiscale monitoring (SKIM) satellite mission is designed to explore ocean surface current and waves. This includes tropical currents, notably the poorly known patterns of divergence and their impact on the ocean heat budget, and monitoring of the emerging Arctic up to 82.5°N. SKIM will also make unprecedented direct measurements of strong currents, from boundary currents to the Antarctic circumpolar current, and their interaction with ocean waves with expected impacts on air-sea fluxes and extreme waves. For the first time, SKIM will directly measure the ocean surface current vector from space. The main instrument on SKIM is a Ka-band conically scanning, multi-beam Doppler radar altimeter/wave scatterometer that includes a state-of-the-art nadir beam comparable to the Poseidon-4 instrument on Sentinel 6. The well proven Doppler pulse-pair technique will give a surface drift velocity representative of the top meter of the ocean, after subtracting a large wave-induced contribution. Horizontal velocity components will be obtained with an accuracy better than 7 cm/s for horizontal wavelengths larger than 80 km and time resolutions larger than 15 days, with a mean revisit time of 4 days for of 99% of the global oceans. This will provide unique and innovative measurements that will further our understanding of the transports in the upper ocean layer, permanently distributing heat, carbon, plankton, and plastics. SKIM will also benefit from co-located measurements of water vapor, rain rate, sea ice concentration, and wind vectors provided by the European operational satellite MetOp-SG(B), allowing many joint analyses. SKIM is one of the two candidate satellite missions under development for ESA Earth Explorer 9. The other candidate is the Far infrared Radiation Understanding and Monitoring (FORUM). The final selection will be announced by September 2019, for a launch in the coming decade.

Design optimization is crucial as offshore structures are exposed to deeper and harsher marine conditions. The structure behaviour is dependent on several joint environmental parameters (wind, wave, currents, etc.). Environmental contours are useful representations to provide multivariate design conditions. However, these contours may lead to different design points depending on the method used to compute them, and thus may be misleading to structural engineer. In this work, we propose to use a response meta-model for the inter-comparison of some state-of-the-art methods available for modelling multivariate extremes, in order to provide a straightforward methodology, focusing on the derivation of three-dimensional contours. The considered case study focuses on the tension in a mooring line of a semi-submersible platform. In a first step, the key met-ocean parameters and the associated load model of the tension in the mooring line are set-up. Several multivariate extreme analysis methods are then applied to derive the environmental contours. These methods are chosen in order to cover all the possible dependence cases, from extremal dependence to extremal independence. Conditional Extreme and several extreme value dependence function models are investigated. The physical-space Huseby contouring method is used to derive environmental surface. A comparison with the extreme load extrapolated from the meta-model is provided to assess the performance of each method.

Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

Strong winds may be biased in atmospheric models. Here the ECMWF coupled wave-atmosphere model is used (1) to evaluate strong winds against observations, (2) to test how alternative wind stress parameterizations could lead to a more accurate model. For the period of storms Kaat and Lilli (23 to 27 January 2014), we compared simulated winds with in-situ – moored buoys and platforms - and satellite observations available from the North Atlantic. Five wind stress parameterizations were evaluated. The first result is that moderate simulated winds (5-20 m s-1) match with all observations. However, for strong winds (above 20 m s-1), mean differences appear, as much as -7 m s-1 at 30 m s-1. Significant differences also exist between observations, with buoys and ASCAT-KNMI generally showing lower wind speeds than the platforms and other remote sensing data used in this study (AMSR2, ASCAT-RSS, WindSat, SMOS and JASON-2). It is difficult to conclude which dataset should be used as a reference. Even so, buoy and ASCAT-KNMI winds are likely to underestimate the real wind speed. The second result is that common wave-age dependent parameterizations produce unrealistic drags and are not appropriate for coupling, whereas a newly empirically-adjusted Charnock parameterization leads to higher winds compared to the default ECMWF parameterization. This proposed new parameterization may lead to more accurate results in an operational context.

Strong winds may be biased in atmospheric models. Here the ECMWF coupled wave-atmosphere model is used (1) to evaluate strong winds against observations, (2) to test how alternative wind stress parameterizations could lead to a more accurate model. For the period of storms Kaat and Lilli (23 to 27 January 2014), we compared simulated winds with in-situ – moored buoys and platforms - and satellite observations available from the North Atlantic. Five wind stress parameterizations were evaluated. The first result is that moderate simulated winds (5-20 m s-1) match with all observations. However, for strong winds (above 20 m s-1), mean differences appear, as much as -7 m s-1 at 30 m s-1. Significant differences also exist between observations, with buoys and ASCAT-KNMI generally showing lower wind speeds than the platforms and other remote sensing data used in this study (AMSR2, ASCAT-RSS, WindSat, SMOS and JASON-2). It is difficult to conclude which dataset should be used as a reference. Even so, buoy and ASCAT-KNMI winds are likely to underestimate the real wind speed. The second result is that common wave-age dependent parameterizations produce unrealistic drags and are not appropriate for coupling, whereas a newly empirically-adjusted Charnock parameterization leads to higher winds compared to the default ECMWF parameterization. This proposed new parameterization may lead to more accurate results in an operational context.

Strong winds may be biased in atmospheric models. Here the ECMWF coupled wave-atmosphere model is used (1) to evaluate strong winds against observations, (2) to test how alternative wind stress parameterizations could lead to a more accurate model. For the period of storms Kaat and Lilli (23 to 27 January 2014), we compared simulated winds with in-situ – moored buoys and platforms - and satellite observations available from the North Atlantic. Five wind stress parameterizations were evaluated. The first result is that moderate simulated winds (5-20 m s-1) match with all observations. However, for strong winds (above 20 m s-1), mean differences appear, as much as -7 m s-1 at 30 m s-1. Significant differences also exist between observations, with buoys and ASCAT-KNMI generally showing lower wind speeds than the platforms and other remote sensing data used in this study (AMSR2, ASCAT-RSS, WindSat, SMOS and JASON-2). It is difficult to conclude which dataset should be used as a reference. Even so, buoy and ASCAT-KNMI winds are likely to underestimate the real wind speed. The second result is that common wave-age dependent parameterizations produce unrealistic drags and are not appropriate for coupling, whereas a newly empirically-adjusted Charnock parameterization leads to higher winds compared to the default ECMWF parameterization. This proposed new parameterization may lead to more accurate results in an operational context.

Several equivalent equations for the evolution of the wave-averaged current momentum have been proposed, implemented, and used. In contrast, the equation for the total momentum, which is the sum of the current and wave momenta, has not been widely used because it requires a less practical wave forcing. In an update on previous derivations, Mellor proposed a new formulation of the wave forcing for the total momentum equation. Here, the authors show that this derivation misses a leading-order term that has a zero depth-integrated value. Corrected for this omission, the wave forcing is equivalent to that in the first paper by Mellor. When this wave forcing effect on the currents is approximated it leads to an inconsistency. This study finally repeats and clarifies that the vertical integration of several various forms of the current-only momentum equations are consistent with the known depth-integrated equations for the mean flow momentum obtained by subtracting the wave momentum equation from the total momentum equation. Several other claims in prior Mellor manuscripts are discussed.

During the first observation period of the HyMeX programme, the Mediterranean coasts of Spain were impacted by several heavy precipitating events (HPEs). The most damaging one occurred during IOP 8 resulting in cumulative rainfall amounts over 180 mm in the area of Murcia Valencia. Numerical simulations using a high-resolution atmospheric model provide a very realistic representation of the mesoscale convective systems (MCSs) at the origin of this HPE and of the associated low-level conditions, consisting in two cold sectors surrounding a warm sector. This study provides a detailed analysis of the mechanisms of deep convection initiation and maintenance between 1200 UTC 28 September and 0000 UTC 29 September 2012. On the coastal mountainous area, the conditionally unstable inflow feeding the MCS is uplifted by the relief whereas at sea, a strong low-level convergence plays the same role. At the coast, cold pools are generated and strengthened by a strong low-level jet (LLJ) carrying cold dense air parcels from the Gulf of Lion and by evaporation and cooling under the precipitating systems. These cold pools play a key role in triggering the deep convection, either by directly uplifting the air masses or by deflecting the inflow horizontally. They largely control the localisation and distribution of the heavy precipitation at sea near Valencia. A weak barrier wind over the cold pools and a secondary cyclonic circulation result in a bending of the convergence line at sea, in agreement with radar observations. A sensitivity study to a more realistic representation of the sea state in the air sea exchanges shows that the LLJ is decelerated by the increased sea-surface roughness, resulting in cold pools extending further at sea and shifting the precipitation patterns 50 km offshore.

Several equivalent equations for the evolution of the wave-averaged current momentum have been proposed, implemented, and used. In contrast, the equation for the total momentum, which is the sum of the current and wave momenta, has not been widely used because it requires a less practical wave forcing. In an update on previous derivations, Mellor proposed a new formulation of the wave forcing for the total momentum equation. Here, the authors show that this derivation misses a leading-order term that has a zero depth-integrated value. Corrected for this omission, the wave forcing is equivalent to that in the first paper by Mellor. When this wave forcing effect on the currents is approximated it leads to an inconsistency. This study finally repeats and clarifies that the vertical integration of several various forms of the current-only momentum equations are consistent with the known depth-integrated equations for the mean flow momentum obtained by subtracting the wave momentum equation from the total momentum equation. Several other claims in prior Mellor manuscripts are discussed.

Ships and ice monitoring is of key importance in numerous applications, such as maritime traffic control, prevention of illegal activities, climate change studies, and maritime security. In this work, the feasibility of near real-time ocean target detection from a constellation of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) images is demonstrated by addressing the two following points: 1) simulation of the revisit time allowed by constellations of GNSS-R instruments; 2) derivation and implementation of an ocean target detector aimed at identifying inhomogeneous features inside the delay-Doppler map. The revisit time is computed by simulating a realistic mission as a function of the constellation size and the number of receiving channels of the GNSS-R instrument. The proposed ocean target detection algorithm consists of four steps - pre-processing, pre-screening, selection, and geolocation - and is validated using actual U. K. TechDemoSat-1 data., Peer Reviewed, Postprint (published version)

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., This study addresses a novel application of global navigation satellite system-reflectometry (GNSS-R) delay-Doppler maps (DDMs), namely sea target detection. In contrast with other competing remote sensing technologies, such as synthetic aperture radar and optical systems, typically exploited in the field of sea target detection, GNSS-R systems could be employed as satellite constellations, so as to fulfill the temporal requirements for near real-time ships and sea ice sheets monitoring. In this study, the revisit time offered by GNSS-R systems is quantitatively evaluated by means of a simulation analysis, in which three different realistic GNSS-R missions are simulated and analyzed. Then, a sea target detection algorithm from spaceborne GNSS-R DDMs is described and assessed. The algorithm is based on a sea clutter compensation step and uses an adaptive threshold to take into account spatial variations in the sea background and/or noise statistics. Finally, the sea target detector algorithm is tested and validated for the first time ever using experimental GNSS-R data from the U.K. TechDemoSat-1 dataset. Performance is assessed by providing the receiver operating characteristic curves, and some preliminary experimental results are presented., Peer Reviewed, Postprint (published version)

Several equivalent equations for the evolution of the wave-averaged current momentum have been proposed, implemented, and used. In contrast, the equation for the total momentum, which is the sum of the current and wave momenta, has not been widely used because it requires a less practical wave forcing. In an update on previous derivations, Mellor proposed a new formulation of the wave forcing for the total momentum equation. Here, the authors show that this derivation misses a leading-order term that has a zero depth-integrated value. Corrected for this omission, the wave forcing is equivalent to that in the first paper by Mellor. When this wave forcing effect on the currents is approximated it leads to an inconsistency. This study finally repeats and clarifies that the vertical integration of several various forms of the current-only momentum equations are consistent with the known depth-integrated equations for the mean flow momentum obtained by subtracting the wave momentum equation from the total momentum equation. Several other claims in prior Mellor manuscripts are discussed.

During the first observation period of the HyMeX programme, the Mediterranean coasts of Spain were impacted by several heavy precipitating events (HPEs). The most damaging one occurred during IOP 8 resulting in cumulative rainfall amounts over 180 mm in the area of Murcia Valencia. Numerical simulations using a high-resolution atmospheric model provide a very realistic representation of the mesoscale convective systems (MCSs) at the origin of this HPE and of the associated low-level conditions, consisting in two cold sectors surrounding a warm sector. This study provides a detailed analysis of the mechanisms of deep convection initiation and maintenance between 1200 UTC 28 September and 0000 UTC 29 September 2012. On the coastal mountainous area, the conditionally unstable inflow feeding the MCS is uplifted by the relief whereas at sea, a strong low-level convergence plays the same role. At the coast, cold pools are generated and strengthened by a strong low-level jet (LLJ) carrying cold dense air parcels from the Gulf of Lion and by evaporation and cooling under the precipitating systems. These cold pools play a key role in triggering the deep convection, either by directly uplifting the air masses or by deflecting the inflow horizontally. They largely control the localisation and distribution of the heavy precipitation at sea near Valencia. A weak barrier wind over the cold pools and a secondary cyclonic circulation result in a bending of the convergence line at sea, in agreement with radar observations. A sensitivity study to a more realistic representation of the sea state in the air sea exchanges shows that the LLJ is decelerated by the increased sea-surface roughness, resulting in cold pools extending further at sea and shifting the precipitation patterns 50 km offshore.

This paper investigates a novel application of Global Navigation Satellite System-Reflectometry (GNSS-R) in the fields of maritime surveillance and safety, and climate change analysis, namely sea target detection in near real-time. Potentialities of the recent GNSS-R technology in the detection of targets over the sea (large ships, sea ice sheets) in near real-time are explored by: 1) computing the revisit time achieved with constellations of GNSS-R satellites; 2) deriving, implementing and testing a sea target detection algorithm. The global average revisit time is evaluated by mission simulation in two realistic scenarios and is shown as a function of the number of parallel receiver channels and the number of GNSS-R satellites in orbit. The sea target detection algorithm consists of four steps - pre-processing, pre-screening, selection, and geolocation - and is tested using actual UK TechDemoSat-1 data., Peer Reviewed, Postprint (published version)

Sea state can influence the turbulent air–sea exchanges, especially the momentum flux, by modifying the sea-surface roughness. The high-resolution non-hydrostatic convection-permitting model MESO-NH is used here to investigate the impact of a more realistic representation of the waves on heavy precipitation during the Intense Observation Period (IOP) 16a of the first HyMeX Special Observation Period (SOP1). Several quasi-stationary mesoscale convective systems developed over the western Mediterranean region, two of them over the sea, and resulted in heavy precipitation on the French and Italian coasts on 26 October 2012. Three different bulk parametrizations are tested in this study: a reference case (NOWAV) without any wave effect, a parametrization taking into account theoretical wave effects (WAV) and a last one with realistic wave characteristics from the MFWAM analyses (WAM). Using a realistic wave representation in WAM significantly increases the roughness length and the friction velocity with respect to NOWAV and WAV. The three MESO-NH sensitivity experiments of the IOP16a show that this surface-roughness increase in WAM generates higher momentum fluxes and directly impacts the low-level dynamics of the atmosphere, with a slowdown of the 10 m wind, when and where the wind speed exceeds 10 m s−1 and the sea state differs from the idealized one. The turbulent heat fluxes are not significantly influenced by the waves, these fluxes being controlled by the moisture content rather than by the wind speed in the simulations. Although the convective activity is globally well reproduced by all the simulations, the difference in the low-level dynamics of the atmosphere influences the localization of the simulated heavy precipitation. Objective evaluation of the daily rainfall amount and of the 10 m wind speed against the observations confirms the positive impact of the realistic wave representation on this simulation of heavy precipitation.

Tension leg platform (TLP) superstructure and submerged areas are being subjected to wind and wave forces during their lifetime, yet the magnitude of each respective energy density affects the TLP response. The present work aims to study the influence of possible load combinations on the response of the TLP. In order to achieve this objective, the Joint North Sea Wave Project (JONSWAP) spectrum and Simiu and Leigh wind spectrum were used for the computation of wave and wind spectral densities. Airy wave theory and Morison equation were adopted for the calculation of wave kinematics and forces on the platform. The variable submergence, drag force in the Morison equation, tension fluctuation from large displacement were the sources of nonlinearities considered. Subsequently, mathematical formulation for the dynamic analysis of intact and a tether-missing TLP was developed in FORTRAN software. The nonlinear equation of motion was solved using Newmark-Beta scheme coded in the software. From our findings, the sea state with high significant wave height and wave period suppressed the effect of current and wind loads on the TLP motion response as compared to the sea state with low sea state parameters. The effect of wind drag force increases the surge and heave responses, but the overall influence of the current drag depends on the magnitude of the wave energy spectrum. There was no abrupt behaviour when a tether was missing although the loss of tether’s stiffness slightly affects the TLP motion and tension variation.

Sea state can influence the turbulent air–sea exchanges, especially the momentum flux, by modifying the sea-surface roughness. The high-resolution non-hydrostatic convection-permitting model MESO-NH is used here to investigate the impact of a more realistic representation of the waves on heavy precipitation during the Intense Observation Period (IOP) 16a of the first HyMeX Special Observation Period (SOP1). Several quasi-stationary mesoscale convective systems developed over the western Mediterranean region, two of them over the sea, and resulted in heavy precipitation on the French and Italian coasts on 26 October 2012. Three different bulk parametrizations are tested in this study: a reference case (NOWAV) without any wave effect, a parametrization taking into account theoretical wave effects (WAV) and a last one with realistic wave characteristics from the MFWAM analyses (WAM). Using a realistic wave representation in WAM significantly increases the roughness length and the friction velocity with respect to NOWAV and WAV. The three MESO-NH sensitivity experiments of the IOP16a show that this surface-roughness increase in WAM generates higher momentum fluxes and directly impacts the low-level dynamics of the atmosphere, with a slowdown of the 10 m wind, when and where the wind speed exceeds 10 m s−1 and the sea state differs from the idealized one. The turbulent heat fluxes are not significantly influenced by the waves, these fluxes being controlled by the moisture content rather than by the wind speed in the simulations. Although the convective activity is globally well reproduced by all the simulations, the difference in the low-level dynamics of the atmosphere influences the localization of the simulated heavy precipitation. Objective evaluation of the daily rainfall amount and of the 10 m wind speed against the observations confirms the positive impact of the realistic wave representation on this simulation of heavy precipitation.

Sea state can influence the turbulent air–sea exchanges, especially the momentum flux, by modifying the sea-surface roughness. The high-resolution non-hydrostatic convection-permitting model MESO-NH is used here to investigate the impact of a more realistic representation of the waves on heavy precipitation during the Intense Observation Period (IOP) 16a of the first HyMeX Special Observation Period (SOP1). Several quasi-stationary mesoscale convective systems developed over the western Mediterranean region, two of them over the sea, and resulted in heavy precipitation on the French and Italian coasts on 26 October 2012. Three different bulk parametrizations are tested in this study: a reference case (NOWAV) without any wave effect, a parametrization taking into account theoretical wave effects (WAV) and a last one with realistic wave characteristics from the MFWAM analyses (WAM). Using a realistic wave representation in WAM significantly increases the roughness length and the friction velocity with respect to NOWAV and WAV. The three MESO-NH sensitivity experiments of the IOP16a show that this surface-roughness increase in WAM generates higher momentum fluxes and directly impacts the low-level dynamics of the atmosphere, with a slowdown of the 10 m wind, when and where the wind speed exceeds 10 m s−1 and the sea state differs from the idealized one. The turbulent heat fluxes are not significantly influenced by the waves, these fluxes being controlled by the moisture content rather than by the wind speed in the simulations. Although the convective activity is globally well reproduced by all the simulations, the difference in the low-level dynamics of the atmosphere influences the localization of the simulated heavy precipitation. Objective evaluation of the daily rainfall amount and of the 10 m wind speed against the observations confirms the positive impact of the realistic wave representation on this simulation of heavy precipitation.

Recerca de models de reflectivitat radar en escenes marines per a simulació de sistemes SAR multicanal, [ANGLÈS] This paper aims to explain the concept of sea reflectivity, the physical model to characterize sea clutter and effects on backscattering coefficient changes in wavelength, grazing angle, polarization and sea conditions. Subsequently, we conducted an extensive search for sea backscattering models used for estimating the backscattering coefficient. It has implemented the necessary simulations to make a reasoned choice of model that best suited to a variety of environmental and operating conditions of radar SAR MTI. The most relevant results are also presented in graphical format and contrasted with the simulator maritime SAR images., [CASTELLÀ] El presente documento pretende explicar el concepto de reflectividad marina, el modelo físico del mar para poder caracterizar el clutter y los efectos sobre el coeficiente de retrodispersión de los cambios en longitud de onda, ángulo de depresión, la polarización y las condiciones del mar. Posteriormente, se ha realizado una extensa búsqueda de modelos de reflectividad marina que se utilizan para estimar el coeficiente de retrodispersión. Se ejecutan las simulaciones necesarias para poder hacer una elección justificada del modelo que más se adapta a una gran variedad de condiciones ambientales y de funcionamiento de los radares SAR MTI. Los resultados más relevantes también se presentan en formato grafico y se contrastan con el simulador de imágenes SAR marítimas., [CATALÀ] El present document pretén explicar el concepte de reflectivitat marina, el model físic del mar per poder caracteritzar el clutter i els efectes sobre el coeficient de retrodispersió σ^0 dels canvis en la longitud d’ona, angle de depressió, la polarització i les condicions de mar. Posteriorment, s’ha realitzat una extensa cerca dels models de reflectivitat marina que s’utilitzen per estimar el coeficient de retrodispersió. S’executen les simulacions necessàries per poder fer una elecció justificada del model que més s’adapta a una gran varietat de condicions ambientals i de funcionament dels radars SAR MTI. Els resultats més rellevants també es presenten en format gràfic i es contrasten amb un simulador d’imatges SAR marítimes.

To prepare and conduct shore operations in safe environment, it is important to possess an accurate sea state forecast. In this thesis it is assessed whether it is possible to estimate the real time sea state at a vessel, without using any instruments deployed in the water. As a matter of fact, in-situ measurements are not always possible, for example during pipeline installation, the vessel sails a few kilometres a day, therefore the options are restricted to methods which do not include in-situ instruments. To test and validate the methods developed in this thesis real time measurements were performed on the Audacia, a pipeline installation vessel belonging to Allseas, one of the world leaders in pipeline installation. The Audacia was laying pipe nearby the coast of Australia, close to wave buoy in the Julimar Field. Methods to extract wave field information from conventional nautical radars have been developed. It is possible to estimate a directional wave spectrum by using a temporal sequence of radar images, and following, statistical data representative of the sea state, such as the significant wave height and wave direction. However there is no unique relation between the radar images and the amount of energy in the directional wave spectrum, which result in an inaccurate signififcant wave height. In order to improve the directional wave spectrum estimations given by the X-Band radar used on board of the Audacia (Wavex from Miros), the possibility of using an extra measuring instrument to calibrate the energy is investigated. Two measuring devices are considered. - A down looking radar, recently installed below the helideck of the Audacia, measuring the single point surface elevation in vicinity of the vessel. (Radac WaveGuide) - The MRU sensors, which measure the wave induced vessel motions. (Ixsea Octans) It is investigated whether combining the data measured by one or the other device to the Xband radar data result in an improvement of the radar estimated, floating structures, offshore and dredging engineering, Mechanical, Maritime and Materials Engineering

To prepare and conduct shore operations in safe environment, it is important to possess an accurate sea state forecast. In this thesis it is assessed whether it is possible to estimate the real time sea state at a vessel, without using any instruments deployed in the water. As a matter of fact, in-situ measurements are not always possible, for example during pipeline installation, the vessel sails a few kilometres a day, therefore the options are restricted to methods which do not include in-situ instruments. To test and validate the methods developed in this thesis real time measurements were performed on the Audacia, a pipeline installation vessel belonging to Allseas, one of the world leaders in pipeline installation. The Audacia was laying pipe nearby the coast of Australia, close to wave buoy in the Julimar Field. Methods to extract wave field information from conventional nautical radars have been developed. It is possible to estimate a directional wave spectrum by using a temporal sequence of radar images, and following, statistical data representative of the sea state, such as the significant wave height and wave direction. However there is no unique relation between the radar images and the amount of energy in the directional wave spectrum, which result in an inaccurate signififcant wave height. In order to improve the directional wave spectrum estimations given by the X-Band radar used on board of the Audacia (Wavex from Miros), the possibility of using an extra measuring instrument to calibrate the energy is investigated. Two measuring devices are considered. - A down looking radar, recently installed below the helideck of the Audacia, measuring the single point surface elevation in vicinity of the vessel. (Radac WaveGuide) - The MRU sensors, which measure the wave induced vessel motions. (Ixsea Octans) It is investigated whether combining the data measured by one or the other device to the Xband radar data result in an improvement of the radar estimated, floating structures, offshore and dredging engineering, Mechanical, Maritime and Materials Engineering

Images of sea surface roughness-for example, obtained by synthetic aperture radars (SAR) or by radiometers viewing areas in and around the sun glitter-at times provide clear observations of meso- and sub-mesoscale oceanic features. Interacting with the surface wind waves, particular deformation properties of surface currents are responsible for those manifestations. Ignoring other sources of surface roughness variations, the authors limit their discussion to the mean square slope (mss) variability. This study confirms that vortical currents and currents with shear in the wind direction shall not be expressed in surface roughness images. Only divergent currents or currents with no divergence but strained in the wind direction can exhibit surface roughness signatures. More specifically, nondivergent currents might be traced with a 45 degrees sensitivity to the wind direction. A simple method is proposed in order to interpret high-resolution roughness images, where roughness variations are proportional to partial derivative u/partial derivative x + alpha partial derivative v/partial derivative y, a linear combination of the along-wind and crosswind current gradients. The polarization parameter a depends upon the sensor look direction and the directional properties of the surface waves selected by the sensor. The use of multiple look directions or possible acquisitions with different wind directions shall thus help to retrieve surface currents from surface roughness observations.

Images of sea surface roughness-for example, obtained by synthetic aperture radars (SAR) or by radiometers viewing areas in and around the sun glitter-at times provide clear observations of meso- and sub-mesoscale oceanic features. Interacting with the surface wind waves, particular deformation properties of surface currents are responsible for those manifestations. Ignoring other sources of surface roughness variations, the authors limit their discussion to the mean square slope (mss) variability. This study confirms that vortical currents and currents with shear in the wind direction shall not be expressed in surface roughness images. Only divergent currents or currents with no divergence but strained in the wind direction can exhibit surface roughness signatures. More specifically, nondivergent currents might be traced with a 45 degrees sensitivity to the wind direction. A simple method is proposed in order to interpret high-resolution roughness images, where roughness variations are proportional to partial derivative u/partial derivative x + alpha partial derivative v/partial derivative y, a linear combination of the along-wind and crosswind current gradients. The polarization parameter a depends upon the sensor look direction and the directional properties of the surface waves selected by the sensor. The use of multiple look directions or possible acquisitions with different wind directions shall thus help to retrieve surface currents from surface roughness observations.

Images of sea surface roughness-for example, obtained by synthetic aperture radars (SAR) or by radiometers viewing areas in and around the sun glitter-at times provide clear observations of meso- and sub-mesoscale oceanic features. Interacting with the surface wind waves, particular deformation properties of surface currents are responsible for those manifestations. Ignoring other sources of surface roughness variations, the authors limit their discussion to the mean square slope (mss) variability. This study confirms that vortical currents and currents with shear in the wind direction shall not be expressed in surface roughness images. Only divergent currents or currents with no divergence but strained in the wind direction can exhibit surface roughness signatures. More specifically, nondivergent currents might be traced with a 45 degrees sensitivity to the wind direction. A simple method is proposed in order to interpret high-resolution roughness images, where roughness variations are proportional to partial derivative u/partial derivative x + alpha partial derivative v/partial derivative y, a linear combination of the along-wind and crosswind current gradients. The polarization parameter a depends upon the sensor look direction and the directional properties of the surface waves selected by the sensor. The use of multiple look directions or possible acquisitions with different wind directions shall thus help to retrieve surface currents from surface roughness observations.

Wind-generated waves at the sea surface are of outstanding importance for both their practical relevance in many aspects, such as coastal erosion, protection, or safety of navigation, and for their scientific relevance in modifying fluxes at the air-sea interface. So far, long-term changes in ocean wave climate have been studied mostly from a regional perspective with global dynamical studies emerging only recently. Here a global wave climate study is presented, in which a global wave model [Wave Ocean Model (WAM)] is driven by atmospheric forcing from a global climate model (ECHAM5) for present-day and potential future climate conditions represented by the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. It is found that changes in mean and extreme wave climate toward the end of the twenty-first century are small to moderate, with the largest signals being a poleward shift in the annual mean and extreme significant wave heights in the midlatitudes of both hemispheres, more pronounced in the Southern Hemisphere and most likely associated with a corresponding shift in midlatitude storm tracks. These changes are broadly consistent with results from the few studies available so far. The projected changes in the mean wave periods, associated with the changes in the wave climate in the middle to high latitudes, are also shown, revealing a moderate increase in the equatorial eastern side of the ocean basins. This study presents a step forward toward a larger ensemble of global wave climate projections required to better assess robustness and uncertainty of potential future wave climate change.

This paper presents an analysis of sea states carried out from extended wave measurements realized near the Wave Hub wave energy test facility in Cornwall (UK). The space directional information is derived from the spectro-directional processing of time-domain data provided by an array of four independent SEAWATCH Mini II displacement buoys separated by an approximate average distance of 500 m. It is observed that, even though the size of the array is small compared to the local wave trains' length, the estimation of the directional spectra - using maximum entropy and likelihood methods - may sometimes exhibit certain space variability over the array. It was also observed that the tidal currents variations produced a significant influence upon the wave directional estimation and wave spectral parameters. Spectro-directional partitioning and wave system tracking were subsequently applied and this emphasized the influence of tide variations upon the individual swells and wind-seas as measured by the buoys. This paper, therefore, also illustrates the relevance of applying partitioning and tracking procedures for the identification of wave systems in oceanographic and wave energy studies. (C) 2012 Elsevier Ltd. All rights reserved.

This paper presents an analysis of sea states carried out from extended wave measurements realized near the Wave Hub wave energy test facility in Cornwall (UK). The space directional information is derived from the spectro-directional processing of time-domain data provided by an array of four independent SEAWATCH Mini II displacement buoys separated by an approximate average distance of 500 m. It is observed that, even though the size of the array is small compared to the local wave trains' length, the estimation of the directional spectra - using maximum entropy and likelihood methods - may sometimes exhibit certain space variability over the array. It was also observed that the tidal currents variations produced a significant influence upon the wave directional estimation and wave spectral parameters. Spectro-directional partitioning and wave system tracking were subsequently applied and this emphasized the influence of tide variations upon the individual swells and wind-seas as measured by the buoys. This paper, therefore, also illustrates the relevance of applying partitioning and tracking procedures for the identification of wave systems in oceanographic and wave energy studies. (C) 2012 Elsevier Ltd. All rights reserved.

This paper presents an analysis of sea states carried out from extended wave measurements realized near the Wave Hub wave energy test facility in Cornwall (UK). The space directional information is derived from the spectro-directional processing of time-domain data provided by an array of four independent SEAWATCH Mini II displacement buoys separated by an approximate average distance of 500 m. It is observed that, even though the size of the array is small compared to the local wave trains' length, the estimation of the directional spectra - using maximum entropy and likelihood methods - may sometimes exhibit certain space variability over the array. It was also observed that the tidal currents variations produced a significant influence upon the wave directional estimation and wave spectral parameters. Spectro-directional partitioning and wave system tracking were subsequently applied and this emphasized the influence of tide variations upon the individual swells and wind-seas as measured by the buoys. This paper, therefore, also illustrates the relevance of applying partitioning and tracking procedures for the identification of wave systems in oceanographic and wave energy studies. (C) 2012 Elsevier Ltd. All rights reserved.

English: The aim of this project is the simulation of the radar echo signal scattered by the sea surface which is called "Sea clutter". This project is related with the SAR MTI systems which are a type of radar systems whose main objective is the detection of moving targets. In order to be able of detecting moving targets in the sea, the first step is creating a sea clutter model in order to be able to evaluate how the sea is interfering in the detection of the moving targets. This project is only focused on modelling the sea reflectivity. This document tries to explain the models of sea clutter that are used nowadays. For this reason, the principal factors that affect the sea reflectivity are explained and the existent models of mean sea reflectivity are analysed. In addition, the different options of statistical distributions that exist for the sea clutter are analysed. The most used statistical distribution for the sea clutter is the K-distribution which is the one that will be generated in the simulator. Another important aspect of the project is the analysis of the clutter correlation because the sea reflectivity has both a temporal correlation and a spatial correlation. The main objective of the project is the creation of a sea clutter simulator using the IDL software. This simulator allows obtaining a sea reflectivity map after indicating the sea characteristics and radar parameters. For this reason, it is necessary to see an appropriate method that allows generating a K-distribution with a specific temporal and spatial correlation. Finally, the project also includes some simulation results which have been obtained with the created simulator., Castellano: Este proyecto tiene como objetivo la simulación de la señal de eco radar reflejada por la superficie del mar, denominada clutter marino. El proyecto se enmarca en el contexto de los sistemas SAR MTI, que son un tipo de radares que tiene como objetivo la detección de blancos móviles. Para poder detectar estos blancos móviles en el mar es necesario crear primero un modelo de clutter marino para poder evaluar como interfiere el mar en la detección de los blancos móviles. Este proyecto se centra únicamente en modelar la reflectividad marina. Este documento pretende explicar cuáles son los modelos que se consideran actualmente para el clutter marino. Por eso se explican cuáles son los factores principales que afectan a la reflectividad del mar y se analizan qué modelos empíricos de reflectividad media existen. También se analizan qué distribuciones estadísticas se utilizan para modelar el clutter de mar, la más utilizada de las cuáles es la distribución K. Otro aspecto importante es el análisis de la correlación del clutter puesto que la reflectividad marina tiene una cierta correlación tanto espacial como temporal. El principal objetivo del proyecto es el desarrollo de un simulador de clutter de mar en el programa IDL que permita obtener un mapa de reflectividad marina dadas unas ciertas características del mar y unos parámetros radar. Por este motivo el proyecto propone un procedimiento eficaz que permite generar una distribución K con una cierta correlación temporal y espacial. Finalmente también se incluyen los resultados obtenidos en las simulaciones realizadas con el simulador programado., Català: El present projecte té com a objectiu la simulació del senyal d'eco radar retornat per la superfície del mar, anomenat clutter marí. Aquest projecte s'emmarca en el context dels sistemes SAR MTI, que són un tipus de radar que tenen com a objectiu la detecció de blancs mòbils. Per tal de poder detectar blancs mòbils en el mar el primer pas és crear un model de clutter marí per tal de poder veure com el mar interfereix en la detecció dels blancs mòbils. Aquest projecte es centra només en la part de modelar la reflectivitat marina. Aquest document pretén explicar quins són els models que es consideren actualment de clutter marí. Per això s'expliquen quins són els factors principals que afecten a la reflectivitat del mar i s'analitzen quins models empírics de reflectivitat mitjana existeixen. També s'analitzen quines distribucions estadístiques s'utilitzen per modelar el clutter marí, la més utilitzada de les quals és la distribució K. Un altre aspecte important és l'anàlisi de la correlació del clutter ja que la reflectivitat del mar té una certa correlació temporal i espacial. El principal objectiu del projecte és el desenvolupament d'un simulador de clutter marí en el programa IDL que permeti obtenir un mapa de reflectivitat del mar donades unes característiques del mar i uns paràmetres radar. Per aquest motiu el projecte proposa un procediment eficient que permet generar una distribució K amb una certa correlació temporal i espacial. Finalment, també s'inclouen els resultats obtinguts en les simulacions realitzades amb el simulador programat.

Author Posting. © American Meteorological Society, 2008. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 38 (2008): 2164–2184, doi:10.1175/2008JPO3962.1., This is the second part of a two-part investigation of a coupled wind and wave model that includes the enhanced form drag of breaking waves. The model is based on the wave energy balance and the conservation of air-side momentum and energy. In Part I, coupled nonlinear advance–delay differential equations were derived, which govern the wave height spectrum, the distribution of breaking waves, and vertical air side profiles of the turbulent stress and wind speed. Numeric solutions were determined for mature seas. Here, numeric solutions for a wide range of wind and wave conditions are obtained, including young, strongly forced wind waves. Furthermore, the “spatial sheltering effect” is introduced so that smaller waves in airflow separation regions of breaking longer waves cannot be forced by the wind. The solutions strongly depend on the wave height curvature spectrum at high wavenumbers (the “threshold saturation level”). As the threshold saturation level is reduced, the effect of breaking waves becomes stronger. For young strongly forced waves (laboratory conditions), breaking waves close to the spectral peak dominate the wind input and previous solutions of a model with only input to breaking waves are recovered. Model results of the normalized roughness length are generally consistent with previous laboratory and field measurements. For field conditions, the wind stress depends sensitively on the wave height spectrum. The spatial sheltering may modify the number of breaking shorter waves, in particular, for younger seas., This work was supported by the U.S. National Science Foundation (Grant OCE- 0526177) and the U.S. Office of Naval Research (Grant N00014–06–10729).

Author Posting. © American Meteorological Society, 2008. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 38 (2008): 2164–2184, doi:10.1175/2008JPO3962.1., This is the second part of a two-part investigation of a coupled wind and wave model that includes the enhanced form drag of breaking waves. The model is based on the wave energy balance and the conservation of air-side momentum and energy. In Part I, coupled nonlinear advance–delay differential equations were derived, which govern the wave height spectrum, the distribution of breaking waves, and vertical air side profiles of the turbulent stress and wind speed. Numeric solutions were determined for mature seas. Here, numeric solutions for a wide range of wind and wave conditions are obtained, including young, strongly forced wind waves. Furthermore, the “spatial sheltering effect” is introduced so that smaller waves in airflow separation regions of breaking longer waves cannot be forced by the wind. The solutions strongly depend on the wave height curvature spectrum at high wavenumbers (the “threshold saturation level”). As the threshold saturation level is reduced, the effect of breaking waves becomes stronger. For young strongly forced waves (laboratory conditions), breaking waves close to the spectral peak dominate the wind input and previous solutions of a model with only input to breaking waves are recovered. Model results of the normalized roughness length are generally consistent with previous laboratory and field measurements. For field conditions, the wind stress depends sensitively on the wave height spectrum. The spatial sheltering may modify the number of breaking shorter waves, in particular, for younger seas., This work was supported by the U.S. National Science Foundation (Grant OCE- 0526177) and the U.S. Office of Naval Research (Grant N00014–06–10729).

Peer Reviewed