'''Short description:''' For the Global Ocean- In-situ observation yearly delivery in delayed mode. The In Situ delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for temperature and salinity measurements. These data are collected from main global networks (Argo, GOSUD, OceanSITES, World Ocean Database) completed by European data provided by EUROGOOS regional systems and national system by the regional INS TAC components. It is updated on a yearly basis. The time coverage has been extended in the past by integration of EN4 data for the period 1950-1990. Acces through CMEMS Catalogue after registration: http://marine.copernicus.eu/ '''Detailed description: ''' Ocean circulation models need information on the interior of the ocean to be able to generate accurate forecast. This information is only available from in-situ measurement. However this information is acquired all around the world and not easily available to the operational users. Therefore, INS TAC , by connecting to a lot of international networks, collects, controls and disseminates the relevant in-situ data to operational users . For reanalysis purposes, operational centres needs to access to the best available datasets with the best possible coverage and where additional quality control procedures have been performed. This dataset suits research community needs Each year, a new release of this product is issued containing all the observations gathered by the INS TAC global component operated by Coriolis. '''Processing information:''' From the near real time INS TAC product validated on a daily and weekly basis for forecasting purposes, a scientifically validated product is created . It s a ""reference product"" updated on a yearly basis. This product has been controlled using an objective analysis (statistical tests) method and a visual quality control (QC). This QC procedure has been developed with the main objective to improve the quality of the dataset to the level required by the climate application and the physical ocean re-analysis activities. It provides T and S weekly gridded fields and individual profiles both on their original level and interpolated level. The measured parameters, depending on the data source, are : temperature, salinity. The reference level of measurements is immersion (in meters) or pressure (in decibars). The EN4 data were converted to the CORA NetCDF format without any additional validation. '''Quality/accuracy/calibration information:''' The process is done in two steps using two different time windows, corresponding to two runs of objective analysis, with an additional visual QC inserted between. The first run was done on a window of three weeks, to capture the most doubtful profiles which were then checked visually by an operator to decide whether or not it was bad data or real oceanic phenomena. The second run was done on a weekly basis to fit the modelling needs. '''Suitability, Expected type of users / uses: ''' The product is designed for assimilation into operational models operated by ocean forecasting centres for reanalysis purposes or for research community. These users need data aggregated and quality controlled in a reliable and documented manner.

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description :''' For the '''Global''' Ocean '''Satellite Observations''', ACRI-ST company (Sophia Antipolis, France) is providing '''Chlorophyll-a''' and '''Optics''' products [1997 - present] based on the '''Copernicus-GlobColour''' processor. * '''Chlorophyll and Bio''' products refer to Chlorophyll-a, Primary Production (PP) and Phytoplankton Functional types (PFT). Products are based on a multi sensors/algorithms approach to provide to end-users the best estimate. Two dailies Chlorophyll-a products are distributed: ** one limited to the daily observations (called L3), ** the other based on a space-time interpolation: the '''Cloud Free'''' (called L4). * '''Optics''' products refer to Reflectance (RRS), Suspended Matter (SPM), Particulate Backscattering (BBP), Secchi Transparency Depth (ZSD), Diffuse Attenuation (KD490) and Absorption Coef. (ADG/CDM). * The spatial resolution is 4 km. For Chlorophyll, a 1 km over the Atlantic (46°W-13°E , 20°N-66°N) is also available for the '''Cloud Free''' product, plus a 300m Global coastal product (OLCI S3A & S3B merged). *Products (Daily, Monthly and Climatology) are based on the merging of the sensors SeaWiFS, MODIS, MERIS, VIIRS-SNPP&JPSS1, OLCI-S3A&S3B. Additional products using only OLCI upstreams are also delivered. * Recent products are organized in datasets called NRT (Near Real Time) and long time-series in datasets called REP/MY (Multi-Years). The NRT products are provided one day after satellite acquisition and updated a few days after in Delayed Time (DT) to provide a better quality. An uncertainty is given at pixel level for all products. To find the '''Copernicus-GlobColour''' products in the catalogue, use the search keyword '''GlobColour''''. See [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-OC-QUID-009-030-032-033-037-081-082-083-085-086-098.pdf QUID document] for a detailed description and assessment. '''DOI (product) :''' https://doi.org/10.48670/moi-00072

'''Short description:''' For the '''Global''' Ocean '''Satellite Observations''', Brockmann Consult (BC) is providing '''Bio-Geo_Chemical (BGC)''' products based on the ESA-CCI inputs. * Upstreams: SeaWiFS, MODIS, MERIS, VIIRS-SNPP, OLCI-S3A & OLCI-S3B for the '''""multi""''' products. * Variables: Chlorophyll-a ('''CHL'''), Phytoplankton Functional types and sizes ('''PFT''') and Reflectance ('''RRS'''). * Temporal resolutions: '''daily''', '''monthly'''. * Spatial resolutions: '''4 km''' (multi). * Recent products are organized in datasets called Near Real Time ('''NRT''') and long time-series (from 1997) in datasets called Multi-Years ('''MY'''). To find these products in the catalogue, use the search keyword '''""ESA-CCI""'''. '''DOI (product) :''' https://doi.org/10.48670/moi-00282

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR), in Rome, distributes surface chlorophyll concentration (mg m-3) derived from multi-sensor (MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS, and Sentinel3A-OLCI at 300m of resolution) (at 1 km resolution) and Sentinel3A-OLCI (at high resolution, 300m) Rrs spectra. Chlorophyll datasets are obtained by means of the Mediterranean Ocean Colour regional algorithms: an updated version of the MedOC4 (Case 1 waters, Volpe et al., 2019, with new coefficients) and AD4 (Case 2 waters, Berthon and Zibordi, 2004). Discrimination between the two water types is performed by comparing the satellite spectrum at pixel-by-pixel level with the average water type spectral signature from in situ measurements for both water types. Reference insitu dataset is MedBiOp (Volpe et al., 2019) where pure Case II spectra are selected using a k-mean cluster analysis (Melin et al., 2015). Merging of Case 1 and Case 2 information is performed estimating the Mahalanobis distance between the observed and reference spectra and using it as weight for the final merged value. This product identifies the average chlorophyll content of the surface layer as defined by the first optical depth (roughly one fifth of the euphotic depth). For multi-sensor observations, single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged with a technique aimed at smoothing the differences among different sensors. The current day data temporal consistency is evaluated as Quality Index (QI): QI=(CurrentDataPixel-ClimatologyDataPixel)/STDDataPixel where QI is the difference between current data and the relevant climatological field as a signed multiple of climatological standard deviations (STDDataPixel). '''Processing information:''' Multi-sensor products are constituted by MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS and Sentinel3A-OLCI. For consistency with NASA L2 dataset, BRDF correction was applied to Sentinel3A-OLCI prior to band shifting and multi sensor merging. Hence, the single sensor OLCI data set is also distributed after BRDF correction. Single sensor NASA Level-2 data are destriped and then all Level-2 data are remapped at 1 km spatial resolution (300m for OLCI) using cylindrical equirectangular projection. Afterwards, single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged with a technique aimed at smoothing the differences among different sensors. This technique is developed by The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR, Rome). Then geophysical fields (i.e. chlorophyll, kd490, bbp, aph and adg) are estimated via state-of-the-art algorithms for better product quality. '''Description of observation methods/instruments:''' Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so-called ocean colour, which is affected by the presence of phytoplankton. '''Quality / Accuracy / Calibration information:''' A detailed description of the calibration and validation activities performed over this product can be found on the CMEMS web portal. '''Suitability, Expected type of users / uses:''' This product is meant for use for educational purposes and for the managing of the marine safety, marine resources, marine and coastal environment and for climate and seasonal studies. '''Dataset names:''' *dataset-oc-med-chl-multi-l3-chl_1km_daily-rt-v02 *dataset-oc-med-chl-olci-l3-chl_300m_daily-rt-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant '''DOI (product) :''' https://doi.org/10.48670/moi-00111

'''Short description:''' For the Baltic Sea- The DMI Sea Surface Temperature L3S aims at providing daily multi-sensor supercollated data at 0.03deg. x 0.03deg. horizontal resolution, using satellite data from infra-red radiometers. Uses SST satellite products from these sensors: NOAA AVHRRs 7, 9, 11, 14, 16, 17, 18 , Envisat ATSR1, ATSR2 and AATSR. '''DOI (product) :''' https://doi.org/10.48670/moi-00154

'''DEFINITION''' The sea level ocean monitoring indicator has been presented in the Copernicus Ocean State Report #8. The ocean monitoring indicator on regional mean sea level is derived from the DUACS delayed-time (DT-2024 version, “my” (multi-year) dataset used when available) sea level anomaly maps from satellite altimetry based on a stable number of altimeters (two) in the satellite constellation. These products are distributed by the Copernicus Climate Change Service and the Copernicus Marine Service (SEALEVEL_GLO_PHY_CLIMATE_L4_MY_008_057). The time series of area averaged anomalies correspond to the area average of the maps in the Irish-Biscay-Iberian (IBI) Sea weighted by the cosine of the latitude (to consider the changing area in each grid with latitude) and by the proportion of ocean in each grid (to consider the coastal areas). The time series are corrected from regional mean GIA correction (weighted GIA mean of a 27 ensemble model following Spada et Melini, 2019). The time series are adjusted for seasonal annual and semi-annual signals and low-pass filtered at 6 months. Then, the trends/accelerations are estimated on the time series using ordinary least square fit.The trend uncertainty is provided in a 90% confidence interval. It is calculated as the weighted mean uncertainties in the region from Prandi et al., 2021. This estimate only considers errors related to the altimeter observation system (i.e., orbit determination errors, geophysical correction errors and inter-mission bias correction errors). The presence of the interannual signal can strongly influence the trend estimation considering to the altimeter period considered (Wang et al., 2021; Cazenave et al., 2014). The uncertainty linked to this effect is not considered. ""CONTEXT "" Change in mean sea level is an essential indicator of our evolving climate, as it reflects both the thermal expansion of the ocean in response to its warming and the increase in ocean mass due to the melting of ice sheets and glaciers (WCRP Global Sea Level Budget Group, 2018). At regional scale, sea level does not change homogenously. It is influenced by various other processes, with different spatial and temporal scales, such as local ocean dynamic, atmospheric forcing, Earth gravity and vertical land motion changes (IPCC WGI, 2021). The adverse effects of floods, storms and tropical cyclones, and the resulting losses and damage, have increased as a result of rising sea levels, increasing people and infrastructure vulnerability and food security risks, particularly in low-lying areas and island states (IPCC, 2022a). Adaptation and mitigation measures such as the restoration of mangroves and coastal wetlands, reduce the risks from sea level rise (IPCC, 2022b). In IBI region, the RMSL trend is modulated by decadal variations. As observed over the global ocean, the main actors of the long-term RMSL trend are associated with anthropogenic global/regional warming. Decadal variability is mainly linked to the strengthening or weakening of the Atlantic Meridional Overturning Circulation (AMOC) (e.g. Chafik et al., 2019). The latest is driven by the North Atlantic Oscillation (NAO) for decadal (20-30y) timescales (e.g. Delworth and Zeng, 2016). Along the European coast, the NAO also influences the along-slope winds dynamic which in return significantly contributes to the local sea level variability observed (Chafik et al., 2019). ""KEY FINDINGS "" Over the [1999/02/20 to 2023/12/31] period, the area-averaged sea level in the IBI area rises at a rate of 3.6 ± 0.8 mm/yr with an acceleration of 0.15 ± 0.06 mm/yr². This trend estimation is based on the altimeter measurements corrected from global GIA correction (Spada et Melini, 2019) to consider the ongoing movement of land. T The TOPEX-A is no longer included in the computation of regional mean sea level parameters (trend and acceleration) with version 2024 products due to potential drifts, and ongoing work aims to develop a new empirical correction. Calculation begins in February 1999 (the start of the TOPEX-B period). '''DOI (product):''' https://doi.org/10.48670/moi-00252

'''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

'''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

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the Global Ocean- In-situ observation delivered in delayed mode. This In Situ delayed mode product integrates the best available version of in situ oxygen, chlorophyll / fluorescence and nutrients data '''DOI (product) :''' https://doi.org/10.17882/86207

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' This product is a REP L4 global total velocity field at 0m and 15m. It consists of the zonal and meridional velocity at a 3h frequency and at 1/4 degree regular grid. These total velocity fields are obtained by combining CMEMS REP satellite Geostrophic surface currents and modelled Ekman currents at the surface and 15m depth (using ECMWF ERA5 wind stress). 3 hourly product, daily and monthly means are available. This product has been initiated in the frame of CNES/CLS projects. Then it has been consolidated during the Globcurrent project (funded by the ESA User Element Program). '''DOI (product) :''' https://doi.org/10.48670/moi-00050 '''Product Citation:''' Please refer to our Technical FAQ for citing products: http://marine.copernicus.eu/faq/cite-cmems-products-cmems-credit/?idpage=169.