'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The low resolution ocean physics analysis and forecast for the North-West European Shelf is produced using a forecasting ocean assimilation model, with tides, at 7 km horizontal resolution. The ocean model is NEMO (Nucleus for European Modelling of the Ocean), using the 3DVar NEMOVAR system to assimilate observations. These are surface temperature, vertical profiles of temperature and salinity, and along track satellite sea level anomaly data. The model is forced by lateral boundary conditions from the UK Met Office North Atlantic Ocean forecast model and by the CMEMS Baltic forecast product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=BALTICSEA_ANALYSISFORECAST_PHY_003_006 BALTICSEA_ANALYSISFORECAST_PHY_003_006]. The atmospheric forcing is given by the operational UK Met Office Global Atmospheric model. The river discharge is from a daily climatology. Further details of the model, including the product validation are provided in the [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-NWS-QUID-004-001.pdf CMEMS-NWS-QUID-004-001]. Products are provided as hourly instantaneous and daily 25-hour, de-tided, averages. The datasets available are temperature, salinity, horizontal currents, sea level, mixed layer depth, and bottom temperature. Temperature, salinity and currents, as multi-level variables, are interpolated from the model 51 hybrid s-sigma terrain-following system to 24 standard geopotential depths (z-levels). Grid-points near to the model boundaries are masked. The product is updated daily, providing a 6-day forecast and the previous 2-day assimilative hindcast. See [http://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-NWS-PUM-004-001_002.pdf CMEMS-NWS-PUM-004-001_002] for further details. '''Associated products:''' This model is coupled with a biogeochemistry model (ERSEM) available as CMEMS product [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_ANALYSISFORECAST_BGC_004_002 NWSHELF_ANALYSISFORECAST_BGC_004_002] A reanalysis product is available from: [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NWSHELF_MULTIYEAR_PHY_004_009 NWSHELF_MULTIYEAR_PHY_004_009]. '''DOI (product) :''' https://doi.org/10.48670/moi-00057

'''DEFINITION''' Heat transport across lines are obtained by integrating the heat 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 PetaWatt (PW). '''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. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00245

'''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

'''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 Remote Sensing Reflectances (Rrs), and diffuse attenuation coefficient of light at 490 nm (kd490) for multi-sensor (MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS, Sentinel3A-OLCI at 300m of resolution) (at 1 km resolution) and Sentinel3A-OLCI observations (at 300m resolution). Exclusively for multi-sensor also the absorption of phytoplankton (aph443), Gelbstoff material (adg443), and the particulate backscattering (bbp443) coefficients at 443 nm are provided. Rrs is defined as the ratio of upwelling radiance and downwelling irradiance at any wavelength (412, 443, 490, 555, and 670 nm for multi-sensor, and 400, 412, 443, 490, 510, 560, 620, 665, 674, 681 and 709 nm for OLCI) and can also be expressed as the ratio of normalized water leaving Radiance (nLw) and the extra-terrestrial solar irradiance (F0). Kd490 is defined as the diffuse attenuation coefficient of light at 490 nm, and is a measure of the turbidity of the water column. It is related to the presence of scattering particles via the ratio between Rrs at 490 and 555 nm (490 and 560 nm for OLCI). For multi-sensor observations Kd490 is achieved via Mediterranean regional algorithm developed by GOS on the basis of MedBiOp in situ dataset (Volpe et al., 2019). 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). Inherent Optical Properties (aph443, adg443 and bbp443 at 443nm) are derived via QAAv6 model. '''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 Sentinel3A-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-opt-multi-l3-rrs412_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-rrs443_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-rrs490_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-rrs510_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-rrs555_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-rrs670_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-kd490_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-bbp443_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-adg443_1km_daily-rt-v02 *dataset-oc-med-opt-multi-l3-aph443_1km_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs400_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs412_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs443_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs490_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs510_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs560_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs620_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs665_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs674_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs681_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-rrs709_300m_daily-rt-v02 *dataset-oc-med-opt-olci-l3-kd490_300m_daily-rt-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant '''DOI (product) :''' https://doi.org/10.48670/moi-00115

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' You can find here the CMEMS Global Ocean Ensemble Reanalysis product at ¼ degree resolution : monthly means of Temperature, Salinity, Currents and Ice variables for 75 vertical levels, starting from 1993 onward. Global ocean reanalyses are homogeneous 3D gridded descriptions of the physical state of the ocean covering several decades, produced with a numerical ocean model constrained with data assimilation of satellite and in situ observations. These reanalyses are built to be as close as possible to the observations (i.e. realistic) and in agreement with the model physics The multi-model ensemble approach allows uncertainties or error bars in the ocean state to be estimated. The ensemble mean may even provide for certain regions and/or periods a more reliable estimate than any individual reanalysis product. The four reanalyses, used to create the ensemble, covering “altimetric era” period (starting from 1st of January 1993) during which altimeter altimetry data observations are available: * GLORYS2V4 from Mercator Ocean (Fr); * ORAS5 from ECMWF; * GloSea5 from Met Office (UK); * and C-GLORSv7 from CMCC (It); These four products provided four different time series of global ocean simulations 3D monthly estimates. All numerical products available for users are monthly or daily mean averages describing the ocean. '''DOI (product) :''' https://doi.org/10.48670/moi-00024

'''This product has been archived''' For operational and online products, please visit https://marine.copernicus.eu '''Short description:''' For the Global Ocean - the OSTIA diurnal skin Sea Surface Temperature product provides daily gap-free maps of: *Hourly mean skin Sea Surface Temperature at 0.25° x 0.25° horizontal resolution, using in-situ and satellite data from infra-red radiometers. The Operational Sea Surface Temperature and Ice Analysis (OSTIA) system is run by the Met Office. A 1/4° (approx. 28 km) hourly analysis of skin Sea Surface temperature (SST) is produced daily for the global ocean. The skin temperature of the ocean is the temperature measured by satellite infra-red radiometers and can experience a large diurnal cycle. The skin SST L4 product is created by combining: 1. the OSTIA foundation SST analysis which uses in-situ and satellite observations; 2. the OSTIA diurnal warm layer analysis which uses satellite observations; and 3. a cool skin model. OSTIA uses satellite data provided by the GHRSST project. '''DOI (product) :''' https://doi.org/10.48670/moi-00167

'''DEFINITION''' The temporal evolution of thermosteric sea level in an ocean layer is obtained from an integration of temperature driven ocean density variations, which are subtracted from a reference climatology to obtain the fluctuations from an average field. The products used include three global reanalyses: GLORYS, C-GLORS, ORAS5 (GLOBAL_MULTIYEAR_PHY_ENS_001_031) and two in situ based reprocessed products: CORA5.2 (INSITU_GLO_PHY_TS_OA_MY_013_052) , ARMOR-3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). The regional thermosteric sea level values are then averaged from 60°S-60°N aiming to monitor interannual to long term global sea level variations caused by temperature driven ocean volume changes through thermal expansion as expressed in meters (m). '''CONTEXT''' Most of the interannual variability and trends in regional sea level is caused by changes in steric sea level. At mid and low latitudes, the steric sea level signal is essentially due to temperature changes, i.e. the thermosteric effect (Stammer et al., 2013, Meyssignac et al., 2016). Salinity changes play only a local role. Regional trends of thermosteric sea level can be significantly larger compared to their globally averaged versions (Storto et al., 2018). Except for shallow shelf sea and high latitudes (> 60° latitude), regional thermosteric sea level variations are mostly related to ocean circulation changes, in particular in the tropics where the sea level variations and trends are the most intense over the last two decades. '''CMEMS KEY FINDINGS''' Significant (i.e. when the signal exceeds the noise) regional trends for the period 2005-2023 from the Copernicus Marine Service multi-ensemble approach show a thermosteric sea level rise at rates ranging from the global mean average up to more than 8 mm/year. There are specific regions where a negative trend is observed above noise at rates up to about -5 mm/year such as in the subpolar North Atlantic, or the western tropical Pacific. These areas are characterized by strong year-to-year variability (Dubois et al., 2018; Capotondi et al., 2020). Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00241

'''Short description:'''' Global Ocean- Gridded objective analysis fields of temperature and salinity using profiles from the reprocessed in-situ global product CORA (INSITU_GLO_TS_REP_OBSERVATIONS_013_001) using the ISAS software. Objective analysis is based on a statistical estimation method that allows presenting a synthesis and a validation of the dataset, providing a validation source for operational models, observing seasonal cycle and inter-annual variability. '''DOI (product) :''' https://doi.org/10.17882/46219

'''Short description:''' For the Global Ocean- Sea Surface Temperature L3 Observations . This product provides daily foundation sea surface temperature from multiple satellite sources. The data are intercalibrated. This product consists in a fusion of sea surface temperature observations from multiple satellite sensors, daily, over a 0.05° resolution grid. It includes observations by polar orbiting from the ESA CCI / C3S archive . The L3S SST data are produced selecting only the highest quality input data from input L2P/L3P images within a strict temporal window (local nightime), to avoid diurnal cycle and cloud contamination. The observations of each sensor are intercalibrated prior to merging using a bias correction based on a multi-sensor median reference correcting the large-scale cross-sensor biases. '''DOI (product) :''' https://doi.org/10.48670/mds-00329

'''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-00100