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Wind-waves are a main driver of coastal environment changes. Wave setup and runup contribute to coastal hazards such as coastal flooding during extreme water level (EWL) events. Wave characteristics used to estimate wave setup are sensitive to changes in water depth in shallow waters. However, wind-waves models used for historical simulations and projections typically do not account for water level changes whether from tides, storm surges, or long-term sea level rise. In this study, the sensitivity of projected changes in wind-wave characteristics to the non-linear interactions between wind-waves and water level changes is investigated along the Atlantic European coastline. For this purpose, a global wave model is dynamically downscaled over the northeastern Atlantic for the 1950–2100 period and for two climate change scenarios (SSP1-2.6 and SSP5-8.5). Twin experiments are performed by accounting (or not) for hourly variations of water level from regional ocean simulations in the regional wave model. The largest impacts of wave-water level interactions are found in the Bay of Mont-Saint-Michel in France, due to a large tidal range of 10 m. At this location and during an historical extreme event, significant wave height was found to be up to 1 m higher (or +25 %) when considering water level variations, leading to an increase in wave setup by between +8.4 cm and +14.7 cm, depending on the value of the beach slope used. At the end of the 21st century under SSP5-8.5 scenario, the wave simulation including water level variations exhibits an increase in extreme significant wave heights and wave setup values by up to +20 % and +10 % respectively. These results are found for many coastal points of the large continental shelf where shallow-water dynamics prevail, and especially so in macro-tidal areas.

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.

The Southern Ocean has a profound impact on the Earth's climate system. Its strong winds, intense currents, and fierce waves are critical components of the air-sea interface and contribute to absorbing, storing, and releasing heat, moisture, gases, and momentum. Owing to its remoteness and harsh environment, this region is significantly undersampled, hampering the validation of prediction models and large-scale observations from satellite sensors. Here, an unprecedented data set of simultaneous observations of winds, surface currents, and ocean waves is presented, to address the scarcity of in situ observations in the region-https://doi.org/10.26179/5ed0a30aaf764 (Alberello et al., 2020c) and https://doi.org/10.26179/5e9d038c396f2 (Derkani et al., 2020). Records were acquired underway during the Antarctic Circumnavigation Expedition (ACE), which went around the Southern Ocean from December 2016 to March 2017 (Austral summer). Observations were obtained with the wave and surface current monitoring system WaMoS-II, which scanned the ocean surface around the vessel using marine radars. Measurements were assessed for quality control and compared against available satellite observations. The data set is the most extensive and comprehensive collection of observations of surface processes for the Southern Ocean and is intended to underpin improvements of wave prediction models around Antarctica and research of air-sea interaction processes, including gas exchange and dynamics of sea spray aerosol particles. The data set has further potentials to support theoretical and numerical research on lower atmosphere, air-sea interface, and upper-ocean processes. .

As part of the Copernicus Marine Service, WAVERYS is the multi-year wave reanalysis that provides global wave data with a fine grid resolution of 1/5°. This wave reanalysis covers the period 1993–2019 and disseminates 3-h integrated wave parameters describing the sea state at the ocean surface. The wave model used is the version 4 of the model MFWAM, which is driven by sea ice fraction and wind provided by the atmospheric reanalysis ERA5. The WAVERYS includes the assimilation of altimeter wave data and directional wave spectra provided by Sentinel-1. The wave reanalysis includes also wave-current interactions by using 3-h surface current forcing provided by the ocean reanalysis GLORYS. This paper highlights the assessment of wave parameters provided by the WAVERYS. The validation has been performed with independent altimeter significant wave heights and buoy wave data. The results show the good accuracy of scatter index of SWH (significant wave height) which is 8.7% in comparison with HY-2A altimeter. Moreover, we point out that scatter index of SWH from the WAVERYS is improved by about 9% with respect to the ERA5 wave dataset. We also indicate the good accuracy of swell propagation thanks to the assimilation of directional wave spectra. An analysis has been conducted for wave-current interactions and also discussions about extreme values and trend of time series are suggested.

Extreme sea levels (ESLs) are a major threat for coastal and low-lying regions. Climate change induced sea level (SL) rise will increase the frequency of ESLs. Projections of ESLs are thus of great interest for coastal risk assessment and decision-making. SL projections are typically produced using global climate models (GCMs). However, GCMs do not explicitly resolve key processes driving ESL changes at the coast (e.g. waves, tides). In this study, a regional model IBI-CCS is set up to refine SL projections of a GCM over the north-eastern Atlantic region bordering western Europe using dynamical downscaling. For a more complete representation of processes driving coastal ESL changes, tides and atmospheric surface pressure forcing are explicitly resolved in IBI-CCS in addition to the ocean general circulation. Furthermore, to include the wave setup contribution to ESLs, a dynamical downscaling of a wave global model is performed over the same north-eastern Atlantic domain using the currents and sea level outputs of the IBI-CCS regional ocean model. All the regional simulations are performed over the 1950 to 2100 period for two climate change scenarios (SSP1-2.6 and SSP5-8.5).Comparisons to reanalyses and observations over the 1993-2014 indicate that ESLs are satisfactorily represented in the regional simulations. In a second phase, the projected changes in ESLs are analyzed, particularly in term of changes in return levels and return periods. The coupling effects between the key processes driving ESL changes at the coast are investigated. We notably assess the influence of the wave setup contribution to ESLs and to projected changes in ESLs and to their return periods. In addition, the impact of accounting for hourly sea level changes in the wave regional model on ESLs and projections of ESLs is estimated.

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.

Launched in 2018, the CFOSAT mission provides information at global scale about the sea-state and waves main characteristics such as height, wavelength and direction. This information is derived from the normalized cross-section of the ocean surface radar backscattered signal measured by the on-board SWIM instrument. However, waves main characteristics are not sufficient to accurately describe the sea-state and extra parameters should be considered such as waves mean square slope (mss). It is well documented that the surface waves slope distribution, hence the mss, can be related to the normalized cross-section. In this work, it is assumed that the waves slope distribution is almost Gaussian and a two parameters Student law is fitted to the SWIM measurements. The inversion of these two parameters gives an information about the mss and the deviation of the slope distribution from the Gaussian distribution. The results on the mss will be compared to results derived from optical models and the differences will be discussed.

International audience; The CFOSAT (China France Oceanography Satellite) mission launched in 2018 now routinely provides at the global scale, directional spectra of ocean waves. The principle is based on the analysis of the normalized radar cross-section measured by the instrument SWIM (Surface Waves Investigation and Monitoring), a near-nadir pointing Ku-Band real-aperture scanning radar. From the ocean wave spectra derived from SWIM, the principal parameters of ocean wave spectra as significant wave height, peak wavelength, and peak direction are now available to better characterize the sea-state. However, it is known that these principal parameters are not sufficient not fully characterize the distribution of wave energy and understand or validate the physical processes impacting its evolution during growth order decay. Here we show that the parameters characterizing the shape of the wave spectra (e.g directional and frequency spread) can be estimated at the global scale from the SWIM measurements. We also show that they can provide consistent values of the Benjamin-Feir index, an index proposed to estimate the probability of extreme waves. Similarities of differences with the shape parameters of the MFWAM numerical wave model are also discussed.

The Southern ocean is a complex ocean region with uncertainties related to surface wind forcing and fluxes exchanges at the air/sea interface. The improvement of wind wave generation in this ocean region is crucial for climate studies. With CFOSAT satellite mission, the SWIM instrument provides directional wave spectra for wavelengths from 70 to 500 m, which shed light on the role of correcting the wave direction and peak wave number of dominant wave trains in the wind-waves growth phase. This consequently induced a better energy transfer between waves and a significant bias reduction of wave height in the Southern Ocean (Aouf et al. 2020). The objective of this work is to extend the analysis of the impact of the assimilation of wave number components from SWIM wave partitions on the ocean/wave coupling. To this end, coupled simulations of the wave model MFWAM and the ocean model NEMO are performed during the southern winter period of 2019 (May-July). We have examined the MFWAM/NEMO coupling with and without the assimilation of the SWIM mean wave number components. Several coupling processes related to Stokes drift, momentum flux stress and wave breaking inducing turbulence in the ocean mixing layer have been analyzed. We also compared the coupled runs with a control run without wave forcing in order to evaluate the impact of the assimilation. The results of coupled simulations have been validated with satellite Sea Surface Temperature and available surface currents data over the southern ocean. We also investigated the impact of the assimilation during severe storms with unlimited fetch conditions.Further discussions and conclusions will be commented in the final paper.Aouf L., New directional wave satellite observations : Towards improved wave forecasting and climate description in Southern Ocean, Geophysical Research Letters, DOI: 10.1029/2020GL091187 (in production). What do you want to do ? New mail

SWIM CFOSAT innovative instrument has already shown its reliability and data quality interest through several publications since its launch in end 2018. Its nadir data are delivered to CMEMS since July 2019 in a L2P/L3. Similarly to other nadir missions AltiKa, Jason3, HY2B, S3…, these easy to use products are based on a selection of valid data from quality criteria, and bias alignment to buoys networks. They are provided in near real time (3h) and with a 1Hz sampling.In 2021, the CFOSAT project team is happy to provide to CMEMS, in addition to the mission full products, a user friendly product, with preselected valid datasets of directional wave spectra and related parameters, and additional information directly derived from the calval expertises upstream. Thanks to it, non expert users should be able to have a simple access to this new product and easy compare it to SAR Wavemode L3 products already in the CMEMS catalogue.This presentation is a user friendly approach to describe the added value, the future improvements planned and the potential of such product for non experts applications.

The CFOSAT (China France Oceanography Satellite) mission launched in 2018 now routinely provides at the global scale, directional spectra of ocean waves. The principle is based on the analysis of the normalized radar cross-section measured by the instrument SWIM (Surface Waves Investigation and Monitoring), a near-nadir pointing Ku-Band real-aperture scanning radar. From the ocean wave spectra derived from SWIM, the principal parameters of ocean wave spectra as significant wave height, peak wavelength, and peak direction are now available to better characterize the sea-state. However, it is known that these principal parameters are not sufficient not fully characterize the distribution of wave energy and understand or validate the physical processes impacting its evolution during growth order decay. Here we show that the parameters characterizing the shape of the wave spectra (e.g directional and frequency spread) can be estimated at the global scale from the SWIM measurements. We also show that they can provide consistent values of the Benjamin-Feir index, an index proposed to estimate the probability of extreme waves. Similarities of differences with the shape parameters of the MFWAM numerical wave model are also discussed.

In spite of continuous improvements of ocean wave models in the last decades, large errors still remain in particular under strongly forced conditions, often encountered in the Southern Ocean, where strong westerly winds generate some of the fiercest waves on Earth in almost unlimited fetch conditions. The newly launched China‐France Oceanography SATellite (CFOSAT) provides directional spectra of ocean waves for both wind seas and swells. Compared to Synthetic Aperture Radar (SAR), it can resolve shorter wavelengths in all directions, which dominate in non‐fully developed wind waves. Here, the assimilation of these CFOSAT wave number components is proved to bring more accurate predictions of wave growth compared to the assimilation of significant wave height alone. A notable reduction of model bias is found in the Southern Ocean, especially in the Pacific Ocean sector. Results further exhibit a downward shift of the wave age, consistent with theoretical wave growth curves. Plain Language Summary This work focuses on the importance of using directional wave observations to improve model wave prediction in the Southern Ocean. The results indicate a significant impact on the transition from a wind‐dependent sea to a well‐developed sea. A direct consequence of this work will concern a better understanding of the wave climate in the Southern Ocean and therefore an improvement of coupled ocean/waves/atmosphere systems.

International audience; The China France Oceanography Satellite (CFOSAT) launched in 2018 now routinely provides directional ocean wave spectra at the global scale. It consists of analyzing the normalized radar cross-section measured by the near-nadir pointing Ku-Band real-aperture scanning radar SWIM (Surface Waves Investigation and Monitoring). The significant wave height, dominant wavelength and direction are provided as the main parameters, but here we analyze additional parameters, namely the frequency width of the omni-directional spectra, the directional spread of the dominant waves, and the related Benjamin-Feir index. This latter was proposed in the literature to estimate the probability of extreme waves. We discuss the geographical distributions of these parameters, their relation with sea-state conditions, and their similarities and diferences with respect to the same parameters obtained from the MFWAM numerical wave model and buoy data. Wef ind that the SWIM omni-directional spectra are narrower and more peaked than the model spectra and that these differences are more obvious in the high sea-state conditions encoun31tered in the Southern Ocean. We nd that under the intense conditions of the Southern Ocean, the SWIM directional spread at the peak is the smallest for swell, the largest for young wind seas, and takes intermediate values for mature wind seas. The directional Benjamin-Feir index is similar for SWIM and MFWAM, but this is mainly due to compensating effects in the parameters contributing to this index. The results indicate that these shape parameters may be used in the future to better describe the wave space-time evolution.

The archive file includes the 6-hourly quality controlled SWIM wave spectra and file of data from SWIM-nadir. Each file SWI_date is in ascii format with header line with date, longitude, latitude, signal parameters. each header line is followed by a matrix values (30 lines for frequencies by 24 columns for directions) which gives the wave spectrum density of energy. The frequency range starts from f(1)=0.035Hz with an geometrical increase of 1.1 (f(i)=1.1*f(i-1)). The wave direction starts from 7.5° with step of 15°. The file name "altidata_swim_nadir_201904-05 includes the data from SWIM nadir (in ascii format) which gives date (year_month_day_hour_minutes), latitude, longitude, Significant wave height, wind speed, altimeter number.

As part of the Copernicus Marine Core service, WAVERYS is the multi-year wave reanalysis that aims to provide global wave data with a grid resolution of 1/5°. The wave reanalysis covers the period of 1993-2018 and provides 3-hourly classical integrated wave parameters describing the sea state at the ocean surface. The wave model used is the V4 version of the model MFWAM, which is driven by atmospheric forcing (winds and ice fraction) from ECMWF ERA5 reanalysis. This latter has showed a significant improvement regarding to the previous reanalysis ERA-Interim. WAVERYS includes the assimilation of altimeters wave data available during the period starting from Topex-Poseidon until Sentinel-3A missions. Directional wave spectra from Synthetic Aperture Radar (SAR) of Sentinel-1A and 1B missions are also assimilated. This is the first time that such directional wave spectra are used in a global wave reanalysis.Further, WAVERYS uses a 3 hour surface current forcing provided by ocean reanalysis GLORYS12 implemented by Mercator-Ocean in the frame of Copernicus Marine Service with a grid resolution of 1/12°. The wave reanalysis is high skilled for ocean regions with dominant wave-currents interactions. Preliminary validation tests have shown improvement by 15% in scatter index for large scale high currents areas. This paper will give detailed characteristics of the wave system and will insist on the benefits of taking into account ocean currents and a physics calibrated for realistic swell propagation.

One of the challenges of the Iberia-Biscay-Ireland (IBI) Monitoring Forecasting Centre in CMEMS phase 2 is the implementation of the assimilation of altimeter wave data in the wave forecast system. In this work we explored the impact of the assimilation of altimeter wave data in the IBI domain. We ran the Météo France version of the WAM wave model (MFWAM) in the IBI domain for 2018 and 2019, with data assimilated from the Jason 2 and 3, Saral, Cryosat 2 and Sentinel 3 altimeters. This high-resolution (0.05 degree) configuration was forced by 0.05 degree ECMWF winds, and boundary conditions were provided by a 0.1 degree global model run. We also included refraction from currents generated with the NEMO-IBI ocean circulation model. We present results with and without wave–current interactions. Validation against both buoy data and the HaiYang 2 altimeter shows that the assimilation of data leads to a marked reduction in scatter index and model bias compared to the run without data assimilation; the gains from including currents meanwhile are modest. The data assimilation scheme presently implemented in MFWAM uses an optimal interpolation algorithm where constant model and observational errors are assumed. To add some sophistication, we experimented with non-constant background errors derived from a model ensemble. Though the effect was small, the method suggests a way to improve the data assimilation performance without substantially altering the algorithm.

The SWIM (Surface Waves Investigation and Monitoring) carried by the CFOSAT (Chinese-French Oceanography Satellite) is designed to obtain the nadir wave height and directional spectrum. This work first introduces the efficiency of deep learning technique to improve wave height and spectrum observation from CFOSAT. A set of deep learning neural networks (DNN) are established and trained to improve the accuracy of SWIM nadir wave height. According to the assessment based on independent buoy observations, the DNN reduces the root mean square error (RMSE) of significant wave height by 32.2% (from 0.26 m to 0.17 m), and the scatter index by 25.7% (from 14 % to 10 %). The result shows that the bias is significantly decreased from 0.11 m to -0.02 m. To correct the SWIM wave spectra, 6 months of NDBC frequency spectra have been used to obtain 19 sets of DNN, each of them is corresponding to one effective frequency of SWIM accordingly. Each set of DNN contains 14 hidden layers with the input as the energy from the different beams 6°, 8° and 10°. Then, the DNN forms a new combined spectrum based on wave spectra of all beams of the SWIM instrument. The independent assessment shows that the wave spectra which come from the 19 sets of DNN significantly reduced the relative error (RE) by 10% to 46% in comparison with beam 10°, which has the best accuracy performance among all the beams. The deep learning technique is also used as a quality control procedure before the assimilation of SWIM wave data. The Siamese convolution neural network (CNN) connected with a deep learning neural network (DNN) is applied to perform such comparison and verification for the SWIM directional spectra. The SWIM directional wave spectra are considered as the 2-dimensional “energy-pictures” with a matrix dimension of 17 frequencies and 9 directions. The Siamese CNN network is made up of 2 pairs of convolution layer and pooling layer, in which the 32 groups of convolution kernels are used to generate one-dimensional features from the directional wave spectra. Both wave spectra of SWIM instrument and wave model are inputted into the same Siamese CNN network, being transformed into 2 sets of features accordingly. Then the features would go to the DNN to generate the index of the similarity. This gives a quantitative description of how different between the SWIM directional spectra and the ones from wave model. Through the training of 26014 pairs of directional wave spectra, the Siamese CNN and DNN have showed a consistency of 78% to 86% with the “partition distance” method in the independent testing data, but with a much faster computation speed. We revealed that the Siamese technique increases the number of wave spectra passing through the verification than the “partition distance” method. This will ensure larger impact of the assimilation of SWIM data in the analysis and forecast period. The case study by running the wave model MFWAM using Siamese network and “partition distance” in assimilation is investigated.

One of the main challenges of the Copernicus Marine Service is the implementation of coupled ocean/waves systems that accurately estimate the momentum and energy fluxes provided by the atmosphere to the ocean. This study aims to investigate the impact of forcing the Nucleus for European Modelling of the Ocean (NEMO) ocean model with forecasts from the wave model of Meteo-France (MFWAM) to improve classical air-sea flux parametrizations, these latter being mostly driven by the 10-m wind. Three wave-related processes, namely, wave-state-dependent stress, Stokes drift-related effects (Stokes-Coriolis force, Stokes drift advection on tracers and on mass), and wave-state-dependent surface turbulence, are examined at a global scale with a horizontal resolution of 0.25°. Three years of sensitivity simulations (2014–2016) show positive feedback on sea surface temperature (SST) and currents when the wave model is used. A significant reduction in SST bias is observed in the tropical Atlantic Ocean. This is mainly due to the more realistic momentum flux provided by the wave model. In mid-latitudes, the most interesting impact occurs during the summer stratification, when the wind is low and the wave model produces a reduction in the turbulence linked with wave breaking. Magnitudes of the large-scale currents in the equatorial region are also improved by 10% compared to observations. In general, it is shown that using the wave model reduces on average the momentum and energy fluxes to the ocean in tropical regions, but increases them in mid-latitudes. These differences are in the order of 10 to 20% compared with the classical parametrizations found in stand-alone ocean models.

As an extension of wave period inversion models based on altimetry data by an artificial neural network approach, a Deep Neural Network approach (DNN) mean wave period model is developed by introducing new parameters as DNN inputs. In addition to conventional altimeter-derived parameters such as significant wave height (SWH) and the normalized radar cross-section (NRCS) sigma0, the spatial (along-track) SWH gradient and SWH standard deviation (STD) for standard 1-s altimetry data are assumed to be responsible for random wave field dynamics and, thus, for the observed characteristic mean wave period. A comparison with in situ measurements of wave buoys shows higher accuracy of the novel DNN models by using these new parameters. The wave period estimation from DNN model is also consistent with the latest wave reanalysis and indicates less bias when compared to the buoys. The global mean wave steepness distribution from the DNN model shows good agreement with those provided by the wave reanalysis. The sensitivity of input variables sigma0, SWH, SWH gradient, and SWH STD on the results of the DNN model are also investigated. Perspectives on the DNN method for developing universal mission-independent wave period models are discussed. Objectives of the work The mean wave period is an important parameter for characterizing wave properties and can be retrieved from altimeter observations. Considering random wave field dynamics, we present a deep neural network (DNN) model for mean wave period retrieval by introducing the SWH gradient and standard deviation as the inputs. The mean wave period estimation of the DNN model shows good agreement with the latest wave reanalysis and less bias compared to buoys. In an attempt to make the DNN mean wave period retrieval model universal, a method of applying DNN model cross-altimetry missions is presented.

Editors: Karina von Schuckmann; Pierre-Yves Le Traon.-- Review Editors: Neville Smith (Chair); Ananda Pascual; Samuel Djavidnia; Jean-Pierre Gattuso; Marilaure Grégoire; Glenn Nolan., The authors would like to thank the Institut Cartogràfic i Geològic de Catalunya (ICGC) for providing data. Thanks are due to FCT/MCTES for the financial support to CESAM (UID/AMB/50017/2019), through national funds., Chapter 1: Introduction and the European Environment policy framework.-- CMEMS OSR4, Chapter 2: State, variability and change in the ocean.-- CMEMS OSR4, Chapter 3: Case studies.-- CMEMS OSR4, Chapter 4: Specific events 2018.

The fundamental role of the ocean for life and well-being on Earth is more and more recognised at the highest political level. In 2015, the United Nations (UN) Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development were adopted by world leaders. The SDG 14 ‘Conserve and sustainably use the oceans, seas and marine resources for sustainable development’ is dedicated to the oceans. The mention of the ocean in the Paris Agreement signed in 2016 marked a decisive milestone. In 2018, the UN Decade of Ocean Science for Sustainable Development (2021–2030) has been proclaimed (https://en.unesco.org/ocean-decade): The Intergovernmental Oceanographic Commission of UNESCO will gather ocean stakeholders worldwide behind a common framework to foster evidence-based policy-making. In fall 2019, the IPCC special report on ocean and cryosphere will be published, and will provide an opportunity to increase awareness and action before COP251 (already claimed as ‘Blue COP’).

The China-France Oceangraphy SATellite (CFOSAT) is an innovative satellite mission with wind and waves measurements on oceans. This paper aims to evaluate the first results of the assimilation of the wave data provided by CFOSAT in the wave model MFWAM. Model runs are implemented during the Calibration/Validation phase of the mission. The results are compared to the wave data from altimeters and buoys. The first results are promising and indicate a significant improvement of wave heights in the different ocean basins (high latitudes, intermediate latitudes and the tropics). Azimuthal cut-off sensitivity tests for the SWIM wave spectra are also examined in this study. We also discussed the impact of combined wave spectra and the ones from the incidence angles of SWIM (6, 8 and 10°). In other respects this study also investigate the complementary use of SWIM and SAR from CFOSAT and SAR from Sentinel-1 for combined assimilation in the wave model MFWAM

The Iberian Biscay Ireland (IBI) wave system has the challenge to improve wave forecast and the coupling with ocean circulation model dedicated to western european coast. The momentum and heat fluxes at the sea surface are strongly controlled by the waves and there is a need of using accurate sea state from wave model. This work describes the more recent version of the IBI wave system and highlight the performance of system in comparison with satellite altimeters and buoys wave data. The validation process has been performed for 1-year run of the wave model MFWAM with boundary conditions provided by the global wave system. The results show on the one hand a slightly improvement on significant wave height and peak period, and on the other hand a better surface stress for high wind conditions. This latter is a consequence of using a tail wave spectrum shaped as the Philipps wave spectrum for high frequency waves.