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Sea level rise and sea state variability due to climate change and global warming are major research topics in the scientific community. Wind speed (WS) and significant wave height (SWH) are usable parameters to monitor the sea state threats and the impact of the ocean weather conditions in coastal areas. GNSS reflectometry (GNSS-R) has shown considerable promise as a remote sensing technique for ocean parameters estimation. Multiple studies have been successfully conducted in the recent two decades by using GNSS-R ground-based, airborne and spaceborne data to retrieve geophysical properties of the sea surface.The focus of this study is to investigate the Doppler shift of the reflected signal as observable to estimate the Doppler spread (DS) and determine its correlation with sea state changes, making use of GNSS-R airborne data in coastal areas. An additional aim is to study the possibility of using the Doppler spread as a metric for coherent GNSS reflectometry for applications such as precise altimetry and precise total electron content (TEC) estimates. An experiment was conducted from the 12th to the 19th of July 2019 along Opal Coast, between the cities of Calais and Boulogne-sur-Mer, France. The experiment consisted of multiple flights at an altitude of ~780m (a.m.s.l). The direct and reflected signals were received by dual-polarized (Right-Handed and Left-Handed Circular Polarizations) antenna mounted on a gyrocopter.A software receiver is used to process the direct and reflected signals from the right-hand channel. The resulting in-phase (I) and quadrature (Q) components (at 50 Hz rate) of the reflected signals are analyzed in the spectral domain every ten seconds to obtain the relative Doppler shift and power estimates. The coherence is established by analyzing the phase observations obtained from I and Q. The sensitivity of the reflected signal estimates and the sea state is determined by the correlation between the Doppler Spread with wind speed and significant wave height. The latter two were obtained from the atmospheric, land and oceanic climate model, ERA5, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF).Initial results have shown promising performance at a calm sea (WS: 2.9 m/s and SWH: 0.26 m) and grazing angles. Satellites with low elevations (E < 10°) present a Doppler Spread of 0.3 Hz and its Pearson correlations with respect to WS and SHW are 0.89 and 0.75, respectively. The performance is relatively poor for high elevation events (E > 30°). The DS increases up to 2.1 Hz and the correlation decrease to 0.55 and 0.42 respectively. Coherence conditions are still under study; however, preliminary phase analysis reveals coherent observations at events with elevations below 15° and sea state with a significant wave height of 0.26 m.

The article presents a study investigating the level of variation in sea state parameters encountered by sailing ships crossing the oceans. The sea state parameters have been obtained from a reanalysis, in this case the ERA5. The study is based on the use of different interpolation schemes to compute parameters in geographical positions off the fixed grid. It is shown that the variation in sea state parameters can be significant. Consequently, in case of sailing ships, covering relatively long distances in a short time (30-60 minutes), it is recommended to rely on bilinear interpolation rather than nearest neighbour. The variation in the sea state parameters is, in fact, at a level which means that the normal assumption of a stationary seaway in periods up to 3 hours likely is violated for ships sailing the typical service speed (15 – 20+ knots).

Spaceborne synthetic aperture radar (SAR) is a powerful tool for monitoring marine environmental parameters of the seas. The ability to work independently of sun illumination, cloud coverage and atmospheric conditions, as well as the capability of delivering spatial information, makes SAR one of the most perceptive instruments. The newest methods for processing SAR data with increased precision allow sea state fields to be estimated with local variabilities. For large areas in oceans where no in-situ measurements and only forecast predictions are available, this information is indispensable for global shipping and over human activity. Due to newest developments, the derived meteo-marine parameters can be transferred to weather services and to a ship’s bridge several minutes after acquisition, where the ship route can be optimized. The study presents a method and application for estimating series of integrated sea state parameters from satellite-borne SAR, allow processing of data from different satellites and modes in near real time (NRT). The developed Sea State Processor (SSP) estimates total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second moment wave periods, mean wave period and period of wind sea. The algorithm was applied for the Sentinel-1 (S1) C-band Interferometric Wide Swath Mode (IW), Extra Wide (EW) and Wave Mode (WM) Level-1 (L1) products and also extended to the X-band TerraSAR-X (TSX) StripMap (SM) mode. The scenes are processed in raster and result in continuous sea state fields with the exception of S1 WV. Each 20 km × 20 km WV imagette, acquired every 100 km along the orbit, presents averaged values for each sea state parameter. The SSP was tuned and validated using two independent global wave models WAVEWATCH-3 (NOAA) and CMEMS (Copernicus) and NDBC buoys. The accuracy of Hs reaches an RMSE of 0.25 m by comparison with models (S1 WV); comparisons to NDBC worldwide buoys result into an RMSE of 0.31 m. Due to implemented parallelization, a fine rater step for scene processing can be practical applied: for example, S1 IW scene with coverage of 200 km × 250 km can be processed using raster step of 1 km (corresponds to ~50.000 subscenes) during minutes. The DLR Ground Station “Neustrelitz” applies SSP as part of a near real-time demonstrator service that involves a fully automated daily provision of surface wind and sea state parameters estimates from S1 IW for the North and Baltic Sea. All results and the presented methods are novel and provide a wide field for applications and implementations in prediction systems.

Long-term changes of wind-generated ocean waves have important consequences for marine engineering, coastal management, ship routing, and marine spatial planning. It is well-known that the multi-annual variability of wave parameters in the North Atlantic is tightly linked to natural fluctuations of the atmospheric circulation, such as the North Atlantic Oscillation. However, anthropogenic climate change is also expected to influence sea states over the long-term through the modification of atmospheric and ocean circulation and melting of sea ice. Due to the relatively short duration of historical sea state observations and the significant multi-decadal variability in the sea state signal, disentangling the anthropogenic signal from the natural variability is a challenging task. In this article, the literature on inter-annual to multi-decadal variability of sea states in the North Atlantic is reviewed using data from both observations and model reanalysis.

Heaving buoy wave energy converters (WEC) are floating oscillators, commonly modeled as single-degree-of-freedom vibrating systems. As the wave frequencies change according to the sea state, these devices must be controlled to maximize energy absorption. A new short-term reactive loading control technique is proposed that maximizes power absorption. The control is realized through tuning the effective stiffness of the vibrating system; thus, adjusting its natural frequency to meet the incident waves energy frequency achieving near-to-resonance operation and maximum power absorption. This stiffness is adjusted using an external stiffness, whose value is varied by a continuously variable transmission (CVT) mechanism connected to the buoy. The system equations were derived then solved analytically to calculate the controller bandwidth. Experiments demonstrated promising results for near-resonance tuning at different input frequencies. Results show that an optimized damping value exists at which power absorption can be significantly increased. The WEC equipped with the proposed reactive controller can provide faster tuning actions than long-term techniques. It also works on longer time intervals than phase-control methods; hence, reducing the continuous demands from the PTO system.

The coupling between the ocean activity driven by winds and the solid Earth generates seismic signals recorded by seismometers worldwide. The 2–10 s period band, known as secondary microseism, represents the largest background seismic wavefield. While moving over the ocean, tropical cyclones generate particularly strong and localized sources of secondary microseisms that are detected remotely by seismic arrays. We assess and compare the seismic sources of P, SV, and SH waves associated with typhoon Ioke (2006) during its extra-tropical transition. To understand their generation mechanisms, we compare the observed multi-phase sources with theoretical sources computed with a numerical ocean wave model, and we assess the influence of the ocean resonance (or ocean site effect) and coastal reflection of ocean waves. We show how the location and lateral extent of the associated seismic source is period- and phase-dependent. This information is crucial for the use of body waves for ambient noise imaging and gives insights about the sea state, complementary to satellite data., The authors locate the maximum seismic energy imprint and lateral extent of the seismic sources generated by Typhoon Ioke. Based on this data set, they present a new tool to shed light on the generation mechanism of secondary microseisms body waves.

This study proposes the design of a tidal turbine station keeping system based on the adoption of a tensioned mooring system. Damping is introduced to investigate its effect on the reduction in the peak load experienced by tidal turbines during their operational lives in high-energy wave–current environments. A neutrally buoyant turbine is supported using a tensioned cable-based mooring system, where tension is introduced using a buoy fully submersed in water. The loads on the turbine rotor blades and buoy are calculated using a wave and current-coupled model. A modelling algorithm is proposed based on inverted pendulums, which respond to various sea state conditions, to study the behaviour of the system as well as the loads on blades. The results indicate that the tensioned mooring system reduces the peak thrust on the turbine and validates the applicability of the model.

75 pages, 8 figures, 3 tables, 6 appendixes, supplement https://doi.org/10.5194/esd-12-1295-2021-supplement.-- Code and data availability: The python code that was used for the analysis and to create the plots is available at https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi, 2021) and as a Renku project https://renkulab.io/projects/ACE-ASAID/spca-decomposition (last access: 29 March 2021; Volpi and Landwehr, 2021). For the availability of the data used in this study please refer to Tables B1 to B8 in Appendix B, The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question, Rafel Simó, Marina Zamanillo, Pau Cortés-Greus, and Pablo Rodríguez-Ros were supported by the Spanish Ministry of Science through the BIOGAPS project (CTM2016-81008-R), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Buoys provide key observations of wind speed over the ocean and are routinely used as a source of validation data for satellite wind products. However, the movement of buoys in high seas and the airflow over waves might cause inaccurate readings, raising concern when buoys are used as a source of wind speed comparison data. The relative accuracy of buoy winds is quantified through a triple collocation (TC) exercise comparing buoy winds to winds from ASCAT and ERA5. Differences between calibrated buoy winds and ASCAT are analyzed through separating the residuals by anemometer height and testing under high wind-wave and swell conditions. First, we converted buoy winds measured near 3, 4, and 5 m to stress-equivalent winds at 10 m (U10S). Buoy U10S from anemometers near 3 m compared notably lower than buoy U10S from anemometers near 4 and 5 m, illustrating the importance of buoy choice in comparisons with remote sensing data. Using TC calibration of buoy U10S to ASCAT in pure wind-wave conditions, we found that there was a small, but statistically significant difference between height adjusted buoy winds from buoys with 4 and 5 m anemometers compared to the same ASCAT wind speed ranges in high seas. However, this result does not follow conventional arguments for wave sheltering of buoy winds, whereby the lower anemometer height winds are distorted more than the higher anemometer height winds in high winds and high seas. We concluded that wave sheltering is not significantly affecting the winds from buoys between 4 and 5 m with high confidence for winds under 18 ms−1. Further differences between buoy U10S and ASCAT winds are observed in high swell conditions, motivating the need to consider the possible effects of sea state on ASCAT winds.

An integrated methodological approach to the development of a coastal flood early-warning system is presented in this paper to improve societal preparedness for coastal flood events. The approach consists of two frameworks, namely the Hindcast Framework and the Forecast Framework. The aim of the former is to implement a suite of high-credibility numerical models and validate them according to past flooding events, while the latter takes advantage of these validated models and runs a plethora of scenarios representing distinct sea-state events to train an Artificial Neural Network (ANN) that is capable of predicting the impending coastal flood risks. The proposed approach was applied in the flood-prone coastal area of Rethymno in the Island of Crete in Greece. The performance of the developed ANN is good, given the complexity of the problem, accurately predicting the targeted coastal flood risks. It is capable of predicting such risks without requiring time-consuming numerical simulations, the ANN only requires the offshore wave characteristics (height, period and direction) and sea-water-level elevation, which can be obtained from open databases. The generic nature of the proposed methodological approach allows its application in numerous coastal regions.

This paper describes the detailed analysis for the design of a linear generator developed for a Surface Riding Wave Energy Converter (SR-WEC), which was designed to improve energy capture over a wider range of sea states. The study starts with an analysis of the power take-off (PTO) control strategy to harness the maximum output power from given sea states. Passive, reactive, and discrete PTO control are explored. For the random wave excitation and limited sliding distance of the generator, the discrete strategy provides the highest average power output. The paper discusses the sizing requirement for the linear generator. Based on the force and power rating of the system and the application requirements, a slotless permanent magnet tubular generator is designed for the wave energy converter., To be published in Energy Conversion Congress and Expo 2021

The aim of the present study is to analyze the impact of the mooring system on the power extraction of a WEC (Wave Energy Converter). A comparison has been carried out between the scenarios of non moored hull and moored hull: for the latter case, the mooring system dynamics has been evaluated by means of a Deep Neural Network, which compares the time histories of two identical simulations (one with the mooring and the other without). This has allowed to include the influence of the mooring on the equations of motion of the hull. By coupling the equations of motion of the device with the equations of the Power Takeoff (PTO), it was possible to estimate the productivity of the WEC system for a given sea state. The results on productivity for various sea states were then compared in order to make some considerations on the influence of the mooring on the operational conditions of the system. In a future perspective, this methodology can be used as a tool for design and evaluation of mooring systems for WEC systems.

This article attempts to analyze the influence of the anisotropic effects of the ocean wave surface on SAR altimetry backscatter coefficient (Sigma-0) measurements, which has not been intensively addressed in publications. Data of Sentinel-3A, Cryosat-2, and Jason-3 altimeters allocated by the WW3 numeric wave model were analyzed, and the patterns of Sigma-0 with respect to the wave direction were acquired under ∼2 m significant wave height. The ocean waves were classified into six categories, among which the moderate swell and short win-wave cases were analyzed intensively. Swell-dominated ocean surface shows less randomness than the wind-wave-dominated ocean surface. Clear and significant sinusoid trends are found in the Sigma-0 and SSB patterns of both operational modes (SAR mode and PLRM mode) of the Sentinel-3A altimeter for the moderate swell case, indicating the sensitivity of Sigma-0 and SSB measurements to the anisotropic features of the altimeter measurements. The anisotropic pattern in the Sentinel-3A PLRM Sigma-0 is somewhat counterintuitive, but the analysis of Jason-3 altimeter data would show similar results. Additionally, by comparing the anisotropic patterns of two orthogonally polarized SAR altimeters (Sentinel-3A and Cryosat-2), we could draw the conclusion that the Sigma-0 measurements are not sensitive to the polarization mode. As for the SSHA patterns, no clear sinusoid could be identified for the moderate swell. A possible explanation is that the SSB pattern may be overwhelmed in the complicated factors that can influence the SSHA pattern.

The search for renewable energy supplies for today’s global energy demand, particularly ocean wave energy for coastal areas, has become undeniably widespread in the last two decades. The Caspian Sea represents an immense opportunity for using ocean renewable energy, especially considering its long shoreline. In this study, the locations with maximum potential wave energy were chosen in the central, eastern, and western zones of the Caspian Sea’s southern coasts. Accordingly, the wave and bathymetric data were used as the input to calculate the oscillating surge wave energy converter’s flap geometric dimensions based on previous studies. Then, the geometric model was designed, and then the wave energy converters were modeled in the Wave Energy Converter Simulator (WEC-Sim) module in the MATLAB software. Furthermore, eight models in each sea state were simulated to find the best value of the PTO damping coefficient, which led to the highest capture factor. Finally, all the external forces on the WEC’s flap and the converter’s power output results were compared, taking into account the effects of the flap height on the total power output. It was found that Nowshahr port has more potential than the Anzali and Amirabad ports, as the converter’s absorbed power proved to be 16.7 kW/m (Capture factor = 63%) at this site. Consequently, by conducting a comparative analysis between the selected sites, the excitation, radiation damping, and power take-off forces were scrutinized. The results show that the highest applied forces to the converter’s flap occurred at Nowshahr port, followed by the Anzali and Amirabad ports, due to the directional characteristics of the waves at the central coasts of the Caspian Sea.

As one of the main sensors for continuous maritime measurements of sea state parameters, high-frequency surface wave radar (HFSWR) also plays an important role in ship detection and tracking. Compact HFSWR often suffers from missing targets, especially when the target appears near the Doppler region with heavy sea clutter or near another target in a multi-target scenario. To address this problem, an automatic ship detection method based on time–frequency (TF) analysis is presented in this paper. The TF target ridge areas are extracted in the TF image via the eigenvalues of the Hessian matrix, image edge detection, and local maximum search. Then, whether ship signals exist in the TF ridges or not is decided by a decision threshold that is calculated by fitting the probability distribution function (PDF) of sea clutter in the TF domain. The proposed TF method can separate TF ridges of similar Doppler frequency and performs constant false alarm rate (CFAR) detection for TF targets, which facilitates detecting these targets that are masked by sea clutter and other large targets. Experimental results show that the number of detected ships that match with the automatic identification system (AIS) records is four times more than that obtained by the conventional constant false alarm rate (CFAR) detectors and 1.3 times more than that by the state-of-the-art TF method in consideration of approximately the same number of detected targets.

Wave energy is largely untapped, and together with the offshore wind farms, has a great renewable energy potential globally. However, due to the fluctuating nature of the wave power, designing a robust wave energy converter (WEC) without overloading both power take-off (PTO) system and electric generator is highly challenging. Although battery storage systems can be considered on the electrical side, mechanical energy storage is also required to reduce the peak power that has an impact on the rotating shaft design and the ratings of the generator hence the inverter. This paper provides a dynamic model of a hydraulic PTO system in WECs and analyses the mechanical output power characteristics and subsystem efficiencies under various wave conditions. Two mechanical energy storage options are considered in the analysis by adding inertia and changing the size of gas accumulator. A fully submerged point absorbed WEC with hydraulic PTO system is proposed and simulated using these mechanical energy storage methods under four distinct levels of wave conditions (sea states). It was found that, both storage methods can effectively reduce power variation, and their size has a significant impact on the efficiency of the hydrodynamic system and the performance of PTO system. Moreover, if the size of the tuning gas accumulator is selected appropriately, the resonance impact of added inertia can be eliminated without impacting power absorption bandwidth under most sea states.

The objective of this research was to develop a new methodology to assess the progression of damage to sloped coastal structures such as revetments, dikes, and mound breakwaters by applying dimensional analysis. The adequacy of the derived functional relationship was verified with the same experimental data (rock layer over impermeable dikes under irregular waves and four dike slopes) originally used to obtain the Van de Meer stability formula. The method addresses the epistemic uncertainty of the damage evolution model and its dependence on the experimental design and technique, the non-dimensional incident sea-state characteristics at the foot of the slope, relative water depth, relative wave height, wave steepness, sea-state persistence, and number of waves. It is specific to each dike slope. Specifically, the scarcity of experimental data in shallow water conditions are considered. Accordingly, the sigmoid function is proposed as an alternate model to quantify the progression. In the current state of knowledge, it is uncertain how the formulas based on lab-experiments perform for realworld design conditions. More research in the form of further test series is thus necessary to explore this new approach in greater depth., Spanish State Research Agency (SRA) PID2019-107508GB-I00/SRA/10.13039/501100011033, University of Granada

The significant wave height (SWH) of oceans is the main parameter in describing the sea state, which has been widely used in the establishment of ocean process models and the field of navigation and transportation. However, traditional methods such as satellite radar altimeters and buoys cannot achieve SWH estimations with high spatial and temporal resolution. Recently, the spaceborne Global Navigation Satellite System reflectometry (GNSS-R) has provided an opportunity to estimate SWH with a rapid global coverage and high temporal resolution observations, particularly with the Cyclone Global Navigation Satellite System (CYGNSS) mission. In this paper, SWH was estimated using the polynomial function relationship between SWH from ERA5 and Delay-Doppler Map Average (DDMA) as well as Leading Edge Slope (LES) from CYGNSS data. Then, the SWH estimated from CYGNSS data was validated by ERA-Interim data, AVISO data, and buoy data. The results showed that the average correlation coefficient of CYGNSS SWH was 0.945, and the average RMSE was 0.257 m when compared to the ERA-Interim SWH data. The RMSE was 0.423 m and the correlation coefficient was 0.849 when compared with the AVISO SWH. The correlation coefficient with the buoy data was 0.907, and the RMSE was 0.247 m. This method can provide suitable SWH estimation data for ocean dynamics research and ocean environment prediction.

Remote sensing technologies are useful tools when gathering spatial and temporal information about dynamic coastal regions. A method is presented using an in-situ space-time drone imaging technique for evaluating wave periods and wavelengths of surface water waves in shallow urban coastal water environments. High-definition drone video imagery (viewed near-nadir) of shallow water waves was acquired and time synchronized with littoral video imagery. Drone video imagery records of a wave patch with reflected sun glint and non-affected sun glint surface water waves facets, staff gauges, and a simultaneously deployed line target were used to determine wave periods and wavelengths. Time series analyses was applied to the video derived time series imagery. Wave energy spectrums can be extracted and used to simulate synthetic images using a gravity wave model based upon a Weibull probability distribution that simulates the sea state. Applications in shallow water coastal environments continue to benefit from knowledge of wind driven water waves. Data extracted from the Banana River in Florida was used to determine the procedure and techniques.

We investigate how the extreme wave statistics of a combined windsea and swell appears to be different from the extreme wave statistics of the corresponding windsea and swell partitions. We consider the situation of following long-crested windsea and swell in laboratory experiments and in simulations using a high-order spectral method (HOSM). We also consider the situation of short-crested windsea and swell crossing at nearly right angle, corresponding to the sea state when the Prestige accident happened, in hindcast simulations combined with HOSM. For cases when the two wave systems do not interact much, the combined wave system appears to be more Gaussian than the corresponding partitioned wave systems, consistent with the central limit theorem. This result is found for kurtosis and exceedance probability of envelope and crest height.

This study investigates the mechanisms acting at the air–sea interface during a heavy precipitation event that occurred between 12 and 14 October 2016 over the north-western Mediterranean area and led to large amounts of rainfall (up to 300 mm in 24 h) over the Hérault region (southern France). The study case was characterized by a very strong (>20 m s−1) easterly to south-easterly wind at low level that generated very rough seas (significant wave height of up to 6 m) along the French Riviera and the Gulf of Lion. In order to investigate the role of the waves on air–sea exchanges during such extreme events, a set of numerical experiments was designed using the Météo-France kilometre-scale AROME-France numerical weather prediction model – including the WASP (Wave-Age-dependant Stress Parametrization) sea surface turbulent flux parametrization – and the WaveWatch III wave model. Results from these sensitivity experiments in the forced or coupled modes showed that taking the waves generated by the model into account increases the surface roughness. Thus, the increase in the momentum flux induces a slowdown of the easterly low-level atmospheric flow and a displacement of the convergence line at sea. Despite strong winds and a young sea below the easterly flow, the turbulent heat fluxes upstream of the precipitating system are not significantly modified. The forecast of the heaviest precipitation is finally modified when the sea state is taken into account; notably, in terms of location, this modification is slightly larger in the forced mode than in the coupled mode, as the coupling interactively balances the wind sea, the stress and the wind.

Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) acquired in wave mode (WV) and quad-polarization stripmap (QPS) mode default operates in quad-polarization (vertical–vertical (VV), vertical-horizontal (VH), horizontal-horizontal (HH) and horizontal-vertical (HV)) modes. To date, more than GF-3 SAR vignettes following about 110 orbits acquired in WV and QPS mode have been recorded during the mission from April 2016 to December 2017. In the vignettes, ocean surface waves signatures, that are wave-look patterns, are visible in cross-polarization (basically VH). These vignettes are collocated with surface sea state parameters simulated from numerical WAVEWATCH-III (WW3) wave model using a 0.1° grid. There are 11,269 matchups available for studying the relation between sea state parameters and SAR-derived parameters in VH-polarization. A well-known empirical CWAVE model, herein renamed as CPCWAVE_GF3, is adopted for sea state parameter retrieval from GF-3 SAR vignettes with the SAR parameters in the cross-polarization channel. The method yielded a significant correlation coefficient (COR) of 0.79 for wave height (SWH) and 0.72 for second-order cross-zero mean wave period (MWP). Validation against 76 moored buoys resulted in a 0.49 m RMSE of SWH with a 0.21 m scatter index (SI) and validation against 71 moored buoys resulted in a 1.01 s RMSE of MWP with a 0.13 s SI. The comparison of SWH with 116 footprints from the altimeter of Jason-2 also shows a 0.46 m RMSE of SWH with a 0.19 m SI. Our work demonstrates the feasibility of wave retrieval from GF-3 SAR using cross-polarization channels parameters.