Hauteurs significatives de vagues (SWH) et vitesse du vent, mesurées le long de la trace par les satellites altimétriques CFOSAT (nadir), Sentinel-3A et Sentinel-3B, Jason-3, Saral-AltiKa, Cryosat-2 et HY-2B, en temps quasi-réel (NRT), sur une couverture globale (-66°S/66+N pour Jason-3, -80°S/80°N pour Sentinel-3A et Saral/AltiKa). Un fichier contenant les SWH valides est produit pour chaque mission et pour une fenêtre de temps de 3 heures. Il contient les SWH filtrées (VAVH), les SWH non filtrées (VAVH_UNFILTERED) et la vitesse du vent (wind_speed). Les mesures de hauteurs de vagues sont calculées à partir du front de montée de la forme d'onde altimétrique. Pour Sentinel-3A et 3B, elles sont déduites de l'altimètre SAR.

'''Short description:''' Multi-Year mono-mission satellite-based along-track significant wave height. Only valid data are included, based on a rigorous editing combining various criteria such as quality flags (surface flag, presence of ice) and thresholds on parameter values. Such thresholds are applied on parameters linked to significant wave height determination from retracking (e.g. SWH, sigma0, range, off nadir angle…). All the missions are homogenized with respect to a reference mission and in-situ buoy measurements. Finally, an along-track filter is applied to reduce the measurement noise. This product is based on the ESA Sea State Climate Change Initiative data Level 3 product (version 2) and is formatted by the WAVE-TAC to be homogeneous with the CMEMS Level 3 Near-real-time product. It is based on the reprocessing of GDR data from the following altimeter missions: Jason-1, Jason-2, Envisat, Cryosat-2, SARAL/AltiKa and Jason-3. CFOSAT Multi-Year dataset is based on the reprocessing of CFOSAT Level-2P products (CNES/CLS), inter-calibrated on Jason-3 reference mission issued from the CCI Sea State dataset. One file containing valid SWH is produced for each mission and for a 3-hour time window. It contains the filtered SWH (VAVH) and the unfiltered SWH (VAVH_UNFILTERED). '''DOI (product) :''' https://doi.org/10.48670/moi-00176

'''Short description:''' These products integrate wave observations aggregated and validated from the Regional EuroGOOS consortium (Arctic-ROOS, BOOS, NOOS, IBI-ROOS, MONGOOS) and Black Sea GOOS as well as from National Data Centers (NODCs) and JCOMM global systems (OceanSITES, DBCP) and the Global telecommunication system (GTS) used by the Met Offices. '''DOI (product) :''' https://doi.org/10.17882/70345

'''DEFINITION''' Volume transport across lines are obtained by integrating the volume fluxes along some selected sections and from top to bottom of the ocean. The values are computed from models’ daily output. The mean value over a reference period (1993-2014) and over the last full year are provided for the ensemble product and the individual reanalysis, as well as the standard deviation for the ensemble product over the reference period (1993-2014). The values are given in Sverdrup (Sv). '''CONTEXT''' The ocean transports heat and mass by vertical overturning and horizontal circulation, and is one of the fundamental dynamic components of the Earth’s energy budget (IPCC, 2013). There are spatial asymmetries in the energy budget resulting from the Earth’s orientation to the sun and the meridional variation in absorbed radiation which support a transfer of energy from the tropics towards the poles. However, there are spatial variations in the loss of heat by the ocean through sensible and latent heat fluxes, as well as differences in ocean basin geometry and current systems. These complexities support a pattern of oceanic heat transport that is not strictly from lower to high latitudes. Moreover, it is not stationary and we are only beginning to unravel its variability. '''CMEMS KEY FINDINGS''' The mean transports estimated by the ensemble global reanalysis are comparable to estimates based on observations; the uncertainties on these integrated quantities are still large in all the available products. At Drake Passage, the multi-product approach (product no. 2.4.1) is larger than the value (130 Sv) of Lumpkin and Speer (2007), but smaller than the new observational based results of Colin de Verdière and Ollitrault, (2016) (175 Sv) and Donohue (2017) (173.3 Sv). Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00247

'''Short description:''' For the Mediterranean Sea - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are processed homogeneously starting from the L2OCN products. '''DOI (product) :''' https://doi.org/10.48670/mds-00342

'''This product has been archived''' '''DEFINITION''' Estimates of Ocean Heat Content (OHC) are obtained from integrated differences of the measured temperature and a climatology along a vertical profile in the ocean (von Schuckmann et al., 2018). The regional OHC values are then averaged from 60°S-60°N aiming i) to obtain the mean OHC as expressed in Joules per meter square (J/m2) to monitor the large-scale variability and change. ii) to monitor the amount of energy in the form of heat stored in the ocean (i.e. the change of OHC in time), expressed in Watt per square meter (W/m2). Ocean heat content is one of the six Global Climate Indicators recommended by the World Meterological Organisation for Sustainable Development Goal 13 implementation (WMO, 2017). '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the ocean shapes our perspectives for the future (von Schuckmann et al., 2020). Variations in OHC can induce changes in ocean stratification, currents, sea ice and ice shelfs (IPCC, 2019; 2021); they set time scales and dominate Earth system adjustments to climate variability and change (Hansen et al., 2011); they are a key player in ocean-atmosphere interactions and sea level change (WCRP, 2018) and they can impact marine ecosystems and human livelihoods (IPCC, 2019). '''CMEMS KEY FINDINGS''' Since the year 2005, the upper (0-2000m) near-global (60°S-60°N) ocean warms at a rate of 1.0 ± 0.1 W/m2. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00235

'''DEFINITION''' The indicator of the Kuroshio extension phase variations is based on the standardized high frequency altimeter Eddy Kinetic Energy (EKE) averaged in the area 142-149°E and 32-37°N and computed from the DUACS delayed-time (CMEMS SEALEVEL_GLO_PHY_L4_MY_008_047) and near real-time (CMEMS SEALEVEL_GLO_PHY_L4_NRT _008_046) altimeter sea level gridded products. ""CONTEXT"" The Kuroshio Extension is an eastward-flowing current in the subtropical western North Pacific after the Kuroshio separates from the coast of Japan at 35°N, 140°E. Being the extension of a wind-driven western boundary current, the Kuroshio Extension is characterized by a strong variability and is rich in large-amplitude meanders and energetic eddies (Niiler et al., 2003; Qiu, 2003, 2002). The Kuroshio Extension region has the largest sea surface height variability on sub-annual and decadal time scales in the extratropical North Pacific Ocean (Jayne et al., 2009; Qiu and Chen, 2010, 2005). Prediction and monitoring of the path of the Kuroshio are of huge importance for local economies as the position of the Kuroshio extension strongly determines the regions where phytoplankton and hence fish are located. Unstable (contracted) phase of the Kuroshio enhance the production of Chlorophyll (Lin et al., 2014). ""CMEMS KEY FINDINGS"" The different states of the Kuroshio extension phase have been presented and validated by (Bessières et al., 2013) and further reported by Drévillon et al. (2018) in the Copernicus Ocean State Report #2. Two rather different states of the Kuroshio extension are observed: an ‘elongated state’ (also called ‘strong state’) corresponding to a narrow strong steady jet, and a ‘contracted state’ (also called ‘weak state’) in which the jet is weaker and more unsteady, spreading on a wider latitudinal band. When the Kuroshio Extension jet is in a contracted (elongated) state, the upstream Kuroshio Extension path tends to become more (less) variable and regional eddy kinetic energy level tends to be higher (lower). In between these two opposite phases, the Kuroshio extension jet has many intermediate states of transition and presents either progressively weakening or strengthening trends. In 2018, the indicator reveals an elongated state followed by a weakening neutral phase since then. '''DOI (product):''' https://doi.org/10.48670/moi-00222

'''Short description:''' The Reprocessed (REP) Mediterranean (MED) dataset provides a stable and consistent long-term Sea Surface Temperature (SST) time series over the Mediterranean Sea (and the adjacent North Atlantic box) developed for climate applications. This product consists of daily (nighttime), merged multi-sensor (L3S), satellite-based estimates of the foundation SST (namely, the temperature free, or nearly-free, of any diurnal cycle) at 0.05° resolution grid covering the period from 1st January 1981 to present (approximately one month before real time). The MED-REP-L3S product is built from a consistent reprocessing of the collated level-3 (merged single-sensor, L3C) climate data record (CDR) v.3.0, provided by the ESA Climate Change Initiative (CCI) and covering the period up to 2021, and its interim extension (ICDR) that allows the regular temporal extension for 2022 onwards. '''DOI (product) :''' https://doi.org/10.48670/moi-00314

'''Short description:''' In wavenumber spectra, the 1hz measurement error is the noise level estimated as the mean value of energy at high wavenumbers (below ~20km in term of wavelength). The 1hz noise level spatial distribution follows the instrumental white-noise linked to the Surface Wave Height but also connections with the backscatter coefficient. The full understanding of this hump of spectral energy (Dibarboure et al., 2013, Investigating short wavelength correlated errors on low-resolution mode altimetry, OSTST 2013 presentation) still remain to be achieved and overcome with new retracking, new editing strategy or new technology. '''DOI (product) :''' https://doi.org/10.48670/moi-00144

'''Short description:''' MEDSEA_ANALYSISFORECAST_WAV_006_017 is the nominal wave product of the Mediterranean Sea Forecasting system, composed by hourly wave parameters at 1/24º horizontal resolution covering the Mediterranean Sea and extending up to 18.125W into the Atlantic Ocean. The waves forecast component (Med-WAV system) is a wave model based on the WAM Cycle 6. The Med-WAV modelling system resolves the prognostic part of the wave spectrum with 24 directional and 32 logarithmically distributed frequency bins and the model solutions are corrected by an optimal interpolation data assimilation scheme of all available along track satellite significant wave height and 10m wind speed observations. The atmospheric forcing is provided by the operational ECMWF Numerical Weather Prediction model and the wave model is forced with hourly averaged surface currents and sea level obtained from MEDSEA_ANALYSISFORECAST_PHY_006_013 at 1/24° resolution. The model uses wave spectra for Open Boundary Conditions from GLOBAL_ANALYSIS_FORECAST_WAV_001_027 product. The wave system includes 2 forecast cycles providing twice per day a Mediterranean wave analysis and 10 days of wave forecasts. '''DOI (product)''': https://doi.org/10.48670/mds-00373