Propagating waves on the surface of the ocean can be represented as a stochastic process, whose statistics are characterized by a spectrum. Measuring the wave spectrum, and quantities derived from the spectrum, are reviewed here. Observation begins by sensing some property of the sea surface over space and/or time. Visual observations, collected routinely since the mid 18th century, comprise the longerest running wave record. Measurement methods in the nearshore are advancing, including traditional methods using pressure and acoustic sensing, but also newer methods such as distributed acoustic sensing and lidar. Detailed, small scale wave physics can now be explored with measurement techniques using light, including stereo-imaging and polarimatry. The decrease in size, cost, and power consumption of microelectronics has propagated through to ocean wave instrumentation, most notably in wave buoys. Global networks of freely drifting miniature wave buoys offer novel observational power. Remote sensing techniques based on radar and lidar continue to evolve, and are widely deployed from land and on ships, aircraft, autonomous vehicles, and satellites. Spaceborne altimeters form one of the most important records of wave height, and a suite of suite of new spaceborne sensors are observing directional spectra across the globe with sampling akin to traditional altimetry. Aircraft and autonomous systems are providing strategic sampling capabilities, whether for detailed process studies or accessing extreme storm environments. The quality and quantity of ocean wave measurements has never been greater. This review will help you make sense of it all.

Abstract Propagating waves on the ocean surface can be represented as a stochastic process whose statistics are characterized by a spectrum. This paper reviews methods for measuring the wave spectrum and related quantities. Observations begin by sensing fluid dynamical properties of the sea surface over space and/or time. Visual observations, collected routinely since the mid‐18th century, comprise the longest‐running wave record. Nearshore measurement methods continue to advance, including traditional pressure and acoustic sensing as well as newer technologies like distributed acoustic sensing and LiDAR. Detailed small‐scale wave physics can now be explored with measurement techniques using light, including stereo‐imaging and polarimetry. Reductions in the size, cost, and power consumption of microelectronics have propagated through ocean wave instrumentation, most notably in wave buoys. Global networks of freely drifting miniature wave buoys offer novel observational capabilities. Remote sensing techniques based on radar and LiDAR continue to evolve and are widely deployed from land, ships, aircraft, autonomous vehicles, and satellites. Spaceborne altimeters form one of the most important records of wave height, and new spaceborne sensors now observe directional spectra globally with sampling akin to traditional altimetry. Aircraft and autonomous systems provide strategic sampling capabilities for detailed process studies and access to extreme storm environments. The quality and quantity of ocean wave measurements have never been greater. This review aims to help make sense of it all.

The surface wave investigation and monitoring (SWIM) instrument, onboard China and France Oceanography Satellite (CFOSAT), is a Ku-band real-aperture radar, with six beams that illuminate the ocean surface at near-nadir incidences ranging from 0 degrees to 10 degrees. In this study, we investigate the effect of rain on the normalized radar cross section (NRCS) measured by SWIM under both tropical cyclone (TC) and non-TC conditions. Rain primarily attenuates the radar backscatter from the ocean surface. Under non-TC conditions, when wind speeds are below 21 m/s, the NRCS reduction is small (<1 dB) during light to moderate rain (<5 mm/h), but becomes very significant (>4-5 dB) under heavy rain (>15 mm/h) conditions. The impact of rain generally decreases as wind speed increases, especially at the smallest incidence angle. At low wind speeds, the NRCS reduction is also sensitive to the incidence angle. Based on a simplified model and the differing sensitivities of NRCS to surface roughness at two near-nadir incidence angles, we find that rain also influences the surface signal at incidence angles below 10 degrees, in addition to the dominant effect of atmospheric attenuation, which leads to a consistent NRCS reduction across all wind speeds and incidence angles. Specifically, it contributes positively to NRCS at wind speeds above 7 m/s and negatively at lower wind speeds. This behavior is attributed to increased surface roughness from splashes and ring waves at low wind speeds, and to decreased roughness due to wave damping at moderate and high wind speeds. In TC environments, the NRCS tends to saturate under light to moderate rain rates (<5 mm/h) when wind speeds exceed approximately 35 m/s. In contrast, under heavy rain (>15 mm/h) conditions, the NRCS continues to decrease as wind speed increases. In both TC and non-TC conditions, beyond atmospheric attenuation, the impact of rain on surface roughness must be considered to fully explain the observed NRCS variations with wind and rain rate.

Improving wave forecasting in the polar oceans is crucial for coupled earth system and climate monitoring. There is still a strong uncertainties on wave variability in the Marginal Ice Zone (MIZ) and polar oceans. The wave scatterometer SWIM of CFOSAT, provide directional wave spectra, which are very useful to improve the wave forecast in the MIZ and the validation of using wave/ice interactions source term in the MFWAM model. The aim of this work is firstly to assess the impact of using the ice probability products provided by CFOSAT in the MFWAM wave model, and secondly to calibrate and validate the source term for wave attenuation induced by sea ice based on Yue et al (2022) implemented in the MFWAM model. Several MFWAM model simulations have been performed in a global configuration during boreal and austral winter and summer seasons. Different ice probability or fraction forcings provided by the IFS atmospheric system and CFOSAT have been tested in the MFWAM model, while sea ice thickness is provided by the Copernicus Marine Service global ocean reanalysis GLORYS. Significant Wave height (SWH) validation of MFWAM model simulations have been carried out using Sentinel-3 altimetry data, which has good coverage of polar regions. The results show a significant improvement in the bias and scatter index of SWH in Antarctica for Weddell and Ross Seas. The assimilation of SWIM wave spectra enhances the improvement of SWH in the polar oceans, particularly in the Ross Sea, Weddell Sea in Antarctica and Beaufort Sea in the Arctic ocean. In this work we also analyzed wave attenuation by sea ice. Validation with Sentinel-3 in the Weddell Sea during the boreal summer shows a good performance of the MFWAM model with the wave/ice ineractions term compared with the simulation without interactions. The analysis of wave attenuation by sea ice was carried out in the Arctic in the Sprtizbergen archipelago area, where observations from drifting buoys (Open Met buoys) have been used to validate the MFWAM model performance. The results show good consistency between the MFWAM model and the drifting buoys. Further analysis regarding to the impact of using wave/ice interactions on ocean circulation has been conducted with ocean mixed layer model. More discussions and conclusions will be summarized in the final presentation.

The estimation of speckle noise or its suppression is a crucial need to estimate geophysical parameters from radar remote sensing. This is particularly important for the ocean wave spectra retrieval from measured radar backscatter coefficients, as speckle noise can completely dominate the signal in certain conditions. Such measurements are performed by the spaceborne Surface Waves Investigation and Monitoring (SWIM) radar, a near-nadir looking, conical scanning instrument carried by the China France Oceanography Satellite (CFOSAT) dedicated to the measurement of directional spectra of ocean waves from the analysis of backscattered fluctuations. In this study, we compare empirical results on the speckle spectrum obtained from the SWIM observations using three different types of acquisition and a theoretical model. We show that a cross-spectral method is efficient for estimating the speckle energy spectrum with a look separation of the order of 13 ms but shows some limits when this time lag is increased to about 40 ms because of the limited footprint overlap. In the case of an azimuthal scanning geometry like SWIM, the speckle energy increases by several orders of magnitude in a sector of about +/- 15 degrees close to the along-track direction. From the theoretical model, we conclude that this is due to the decrease of the Doppler bandwidth in this look geometry and that the variance of the surface scatterer velocities limits the speckle energy increase. It also explains the sensitivity to wind speed of the speckle energy in this azimuthal sector. The almost linear decrease of speckle energy with wavenumber is explained by the spectral response of the radar impulse, slightly modified by range decimation and resampling applied in the first steps of processing. Close to the along-track direction, the variation of speckle energy with latitude is mainly explained by the variation in the integration time imposed by the SWIM onboard command. The model results also show that the impact of Earth's rotation on the speckle noise is small. Finally, we show that the speckle correction has an impact on the shape of the wave spectrum derived from the SWIM inversion.

Ocean waves are essential elements across the air-sea interface, regulating momentum and energy transfer. The mixture of wind sea and ocean swell coupled with surface winds results in diverse sea state conditions that modify the local air-sea interaction. Previous classifications of wind waves and swells are mostly binary that are insufficient to represent the complexity of sea states. In this study, we utilize wind and wave measurements from the China-France Oceanography Satellite (CFOSAT) to construct an observational wind-wave ensemble. Four key parameters: wind speed, significant wave height, inverse wave age, and spectral width are selected out of six variables based on their correlations. Employing the unsupervised learning of k-means clustering, global sea states are categorized into six distinct classes. These classes, characterized by unique centroids and separated in the feature space, represent specific wind regimes and degrees of wave development. Global occurrence highlights that each sea state is region-specific, bridging the spatial gap of swell and wind sea dominated areas, respectively. This new grouping scheme complements the traditional wind sea and/or swell classification by resolving the diversity of wave regimes. The six-class classification enables us to identify transitional states and hybrid conditions that may have been overlooked in the binary classification scheme, which shall help investigate the impact of ocean waves on the air-sea interaction under varying sea states.

We investigate the ocean wave field under Hurricane SAM (2021). Whilst measurements of waves under Tropical Cyclones (TCs) are rare, an unusually large number of quality in situ and remote measurements are available in that case. First, we highlight the good consistency between the wave spectra provided by the Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China-France Oceanography Satellite (CFOSAT), the in situ spectra measured by National Data Buoy Center (NDBC) buoys, and a saildrone. The impact of strong rains on SWIM spectra is then further investigated. We show that whereas the rain definitely affects the normalized radar cross section, both the innovative technology (beam rotating scanning geometry) and the post-processing processes applied to retrieve the 2D wave spectra ensure a good quality of the resulting wave spectra, even in heavy rain conditions. On this basis, the satellite, airborne and in situ observations are confronted to the analytical model proposed by Kudryavtsev et al (2015). We show that a trapped wave mechanism may be invoked to explain the large significant wave height observed in the right front quadrant of Hurricane SAM.

Surface waves investigation and monitoring (SWIM) can provide global wave spectra, but under small sea conditions, the presence of parasitic peaks at low wavenumbers, surfboard effects, and residual speckle noise lead to performance degradation of SWIM wave height spectrum products. To reduce the impacts of the above factors on the SWIM wave height spectrum, in this article, a convolution neural network (CNN) method based on BU-Net is proposed for calibrating SWIM omnidirectional wave height spectra with buoy measurements under sea states (wind wave mainly/swell mainly) and sea surface conditions (wind speed from 9 to 19 m/s, and significant wave height (SWH) from 0.8 to 3.4–4.2 m). The calibration results show that the impact of the above factors on the SWIM omnidirectional wave height spectrum can be corrected. The correlation coefficients between the corrected SWIM beams 6°, 8°, and 10° and the buoy mean omnidirectional wave height spectrum are all greater than 0.90, and the relative error of the peak wavenumber is within 10%. The relative error of the integrated energy is mostly less than 20%. In addition, the performance of spectral integration parameters (effective wave height $H_{s}$ , and energy wave period $T_{m-10}$ ) of each spectral beam of SWIM has been verified using Meteo-France WAve Model (MFWAM) reanalysis data. The validation results show that RMSE of $H_{s}$ and $T_{m-10}$ , for the corrected SWIM beam 6° (8°, 10°) under wind wave sea conditions are 0.31 m (0.32, 0.25 m) and 0.50 s (0.51, 0.49 s), respectively; those for swell cases are 0.16 m (0.16, 0.13 m) and 0.87 s (0.77, 0.72 s), respectively.

Tropical cyclones (TCs) are extreme events that generate, because of their movement, complex wave fields. The Surface Wave Investigation and Monitoring (SWIM) instrument is a real aperture radar that provides unprecedented detailed information about the waves with dominant wavelength between 70 and 500 m in all directions at the global scale. In this study we collocated 3 years of SWIM data with 67 TCs in the Northern Hemisphere to analyze the impact of the TC characteristics on the wave field. TCs have been classified into three different classes (slow, moderate speed, and fast) estimated based on the ratio between the maximum sustained wind and the displacement velocity. In order to analyze the characteristics of the wave field in the space domain, the observations have been separated according to the distance with the TC center and the quadrant. The results show that the characteristics of the TCs impact the wave field: the more favorable conditions for trapped wave phenomenon appears to be under moderate speed TC conditions. In slow and moderate speed TCs, close to the center the directional spectra are mono-modal and tend to become bi- or multi-modal when the distance to the center increases whereas in fast-moving TCs, the directional spectra are always bi- or multi-modal. Omni-directional spectra show similarities with fetch-limited spectra in slow and moderate speed TCs whereas in fast-moving TCs, because of the presence of mixed-sea, the decrease of energy with frequency is less steep than in fetch-limited conditions.

This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields.

Since 2018, for the first time, space measurements of colocated wind vectors and wave spectral characteristics are available thanks to the French/Chinese CFOSAT mission, which carries a wind scatterometer (SCAT) and a wave scatterometer (SWIM). Four years after its launch, CFOSAT data processing has been improved to reach a high level quality, leading to a reprocessing of the whole mission dataset. This paper focuses on the CFOSAT SWIM data reprocessing, the product performance, now homogeneous over mission lifetime, the complementarity with SAR observations and some scientific contributions to oceanography.

Ocean waves play a key role in the exchange of heat and momentum fluxes between the ocean and atmosphere, expecially in extreme wind conditions. The availability of directional wave spectra from SWIM lead to a better description of wave systems nearby the trajectories of tropical cyclones as shown recently by Le Merle et al. 2022. Also the assimilation of these directional observations induced an improved forecast of integrated wave parameters and initial conditions from wind-sea to swell propagation. The objective of this work is to examine the impact of the wave-ocean coupling under cyclonic conditions in the Indian Ocean. Coupled simulations between the MFWAM wave model and the NEMO ocean model have performed over the 2020 and 2021 cyclonic seasons in indian ocean. We used an improved wave forcing by assimilating the directional wave spectra and the corresponding significant wave heights provided by the instrument SWIM of CFOSAT satellite. The impact of this enhanced wave forcing on the ocean circulation was compared with the one without CFOSAT data assimilation. The main coupling processes are wave-modified stress, Stokes drift and wave breaking induced turbulence. The results show that wave/ocean coupling leads to a significant increase of the ocean mixed layer along the trajectories of cyclones. This clearly induces a cooling of the upper ocean layers at the rear of the cyclones. The validation of key ocean parameters indicates an improvement in sea surface temperature compared to satellite data (OSTIA). We investigated the currents variability in the upper ocean following the trajectory of cyclone HEROLD. We also examined the impact of the coupling process driven by the wave breaking induced turbulence and investigated a better parametrization than the used one from Craig and Banner (1992). Further conclusions and comments will be discussed in the final presentation of this work.

Speckle noise is inherent to radar measurements. For applications which need both a high temporal and high spatial resolution, a classical method for the reduction of the speckle noise by filtering the backscattered signal may not be sufficient. In particular, when radar observations are used to estimate ocean wave spectra from relative fluctuations of the radar signal within a given footprint, a method must be implemented to correct for the speckle effect in the Fourier domain (i.e., density spectrum). A theoretical background to model the speckle density spectrum for a radar with near-nadir incidences was proposed by Jackson in 1981 but it is based on a stationary sea surface assumption and ignores the variation of the main factor in the four-frequency moment near the origin. In this article, we revisit this theoretical background to extend this model to a time-varying sea surface and alleviate some assumptions on the Fresnel phase formulation. The results from the model applied in the configuration of an airborne system indicate that not only the displacement of the radar but also the dynamic properties of the sea surfaces have a significant effect on the speckle noise spectrum in certain directions of observations. The effects depend on the radar look direction in azimuth, and on sea surface conditions (wind speed, wind direction with respect to the aircraft route, surface wave spectrum). This new model is validated against observations of the airborne near-nadir incidence scatterometer-Ku-band Radar for Observation of Surfaces (KuROS). We show in particular that the errors between the experimental estimation of the omni-directional speckle noise spectrum from KuROS and the prediction by our model are below 10%.

Abstract SWIM on board CFOSAT is the first spaceborne, low incidence, rotating scatterometer, aiming at measuring in near‐real time ocean waves spectra. With five off‐nadir beams at incidences between 2° and 10° plus one nadir beam, it covers the Earth in 13 days, including polar regions thanks to its polar orbit. This work aims at exploiting SWIM data over ice regions with two objectives. An off‐nadir data‐based sea‐ice flag is here proposed that allows, first, to eliminate sea‐ice polluted echoes for improving the wave spectrum retrieval, and second, to open perspectives for application of sea‐ice monitoring with near‐nadir Ku‐band active sensors. To this end, the signature of both open water and sea‐ice radar backscatter is parameterized into Geophysical Model Functions. Then, comparisons with observed profiles through a Bayesian scheme provide a probability of sea‐ice presence. After comparison with both model (ECMWF‐IFS) and radiometer (SSMI) derived reference data sets, the proposed flag is found to be ready for operational use. At latitudes greater than 40° in absolute value, the proposed flagging algorithm exhibits accuracies of approximately 98% for all beams compared to SSMI data. Beam to beam performances are characterized and show potential for the characterization of sea‐ice at Ku‐band.

The availability of wide swath Significant wave heights (SWH) such as those retrieved in the frame of CFOSAT and HY2B satellite missions opens important perspectives for the improvement of operational wave forecasting. The objective of this work is to analyze the impact of the combined assimilation of wide swath SWH and directional wave spectra on the integrated wave parameters in the analysis and forecast periods. The results show a significant improvement of the SWH estimate in different ocean regions. We clearly showed the persistency of the assimilation up to 3 days in the forecast period. Most striking is the ability of the combined assimilation to effectively correct swell tracking for storm events, such as Hurricane Pablo in 2019.

Abstract This study focuses on ocean waves impacting the Moorea Island in French Polynesia, where coral reefs play an essential role in the biodiversity and protection of habitations. We investigate how the innovative Surface Waves Investigation and Monitoring (SWIM) instrument of the Chinese‐French Oceanography SATellite satellite enables to document on a multi‐annual basis, the spectral properties of ocean waves reaching the coasts of the Moorea Island. Our analysis is based on comparisons with in situ measurements (wave gauges deployed on the outer slope of the coral reef), and with other satellite observations (altimeter, Synthetic Aperture Radar [SAR]). Accounting for local masking effects, we show that SWIM provides relevant information on short swell or wind waves, which is missed by the SAR observations, in particular in high sea‐state conditions, owing to the dominant propagation direction being close to the azimuth. We, nevertheless, also find that wave properties in low sea‐state conditions are better documented by SAR than by SWIM. Such results are important to accurately measure and predict the wave conditions which fragilize the coral reefs and to evaluate the impact of extreme events on tropical islands and coral reefs.

The comparison and verification of ocean wave spectrum by remote sensing and in situ measurements at the spectral level are quite rare because the use of the traditional comparison method leads to very limited spatiotemporal matching pairs. In this article, a new comparison method is proposed. With this method, under different sea conditions (wind wave mainly/swell mainly) and sea surface conditions (wind speed smaller than 20 m/s and significant wave height from 1 to 7 m), mean directional wave height spectra from surface waves investigation and monitoring (SWIM) are compared at the spectral level to the buoy counterparts, in different classes of the sea state. This includes the comparison of the omnidirectional wave height spectrum and the directional function at the peak wavenumber. The comparison results show that, under medium and high sea conditions, wave directional spectra provided by the SWIM beams at 8° and 10° incidence have a high consistency with those from buoy data. Under low sea conditions, the measurement bias of SWIM wave directional spectra mainly comes from three phenomena that are, by order of importance, an abnormal lifting of spectral energy caused by nonwave components at low wave numbers (parasitic peak), from the nonlinear surfboard effect in the radar imaging mechanism, and from a slight underestimation of speckle noise spectral density.

The climate is evolving rapidly and there is a strong need of better description on momentum and heat fluxes exchanges between the ocean and the atmosphere. Recently directional wave observations from CFOSAT shed ligth on the improvement of dominant wave direction and better scaling of wind-wave growth in critical ocean areas such as the Southern Ocean (Aouf et al. 2021). This work examines the validation of coupled simulations between the ocean model NEMO and the wave model MFWAM including assimilation of directional wave observations. The coupling experiments have been performed for austral summer and fall seasons during 2020 and 2021. The objective of this work is on the one hand to assess the impact of waves on key parameters describing the ocean circulation and on the other hand to evaluate the contributions of different processes of the wave forcing (stress, Stokes drift and wave breaking inducing turbulence) on the mixing in upper ocean layers. The outputs of the coupled simulations have been validated with in situ observations of ocean surface currents, temperature and salinity. The results clearly reveals an improvement in the estimation of the Antarctic Circumpolar Current (ACC) with an increase in the intensity of the current for example in the region between Tasmania and Antarctica. We also observed a significant improvement of the surface currents in the tropics, for instance the ascending brazilian current. In other respects, we have examined the contribution of improved surface stress on inertial oscillations of the current in the Southern Ocean.Comparison of the surface currents from the coupled simulations with those provided by altimeters showed an increase in current intensity and a better description for small scales in regions of strong currents such as the Agulhas, ACC and Kuroshio regions. We also investigated the impact of wave forcing depending on the mixing layer length.Further discussions and conclusions will be presented in the final paper.

For the first time, co-located wind vectors and wave spectral characteristics are available thanks to the French/Chinese CFOSAT mission, which includes a wind scatterometer SCAT and a wave scatterometer SWIM. Three years after its launch, CFOSAT data is thoroughly qualified and various scientific work has been undertaken. This paper focuses on CFOSAT SWIM data, its performance and scientific contribution to oceanography, coastal and sea ice study.