'''Short description:''' Altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean with a 1Hz (~7km) and 5Hz (~1km) sampling. It serves in near-real time applications. This product is processed by the DUACS multimission altimeter data processing system. It processes data from all altimeter missions available (e.g. Sentinel-6A, Jason-3, Sentinel-3A, Sentinel-3B, Saral/AltiKa, Cryosat-2, HY-2B). The system exploits the most recent datasets available based on the enhanced OGDR/NRT+IGDR/STC production. All the missions are homogenized with respect to a reference mission. Part of the processing is fitted to the European Seas. (see QUID document or http://duacs.cls.fr [http://duacs.cls.fr] pages for processing details). The product gives additional variables (e.g. Mean Dynamic Topography, Dynamic Atmospheric Correction, Ocean Tides, Long Wavelength Errors) that can be used to change the physical content for specific needs (see PUM document for details) '''Associated products''' A time invariant product http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_NOISE_L4_STATIC_008_033 [http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_PHY_NOISE_L4_STATIC_008_033] describing the noise level of along-track measurements is available. It is associated to the sla_filtered variable. It is a gridded product. One file is provided for the global ocean and those values must be applied for Arctic and Europe products. For Mediterranean and Black seas, one value is given in the QUID document. '''DOI (product) :''' https://doi.org/10.48670/moi-00140

'''Short description:''' Mean Dynamic Topography that combines the global CNES-CLS-2022 MDT, the Black Sea CMEMS2020 MDT and the Med Sea CMEMS2020 MDT. It is an estimate of the mean over the 1993-2012 period of the sea surface height above geoid. This is consistent with the reference time period also used in the DUACS products '''DOI (product) :''' https://doi.org/10.48670/moi-00150

'''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

'''Short description:''' The IBI-MFC provides the biogeochemical multi-year (non assimilative) product for the Iberia-Biscay-Ireland region starting in 01/01/1993, extended every year to use available reprocessed upstream data and regularly updated on a monthly basis to cover the period up to month M-4 using an interim processing system. The model system is designed, developed and run by Mercator Ocean International, while the operational product post-processing and interim processing system are run by NOW Systems with the support of CESGA supercomputing centre. The biogeochemical model PISCES is run simultaneously with the ocean physical NEMO model, generating products at 1/36° horizontal resolution. The PISCES model is able to simulate the first levels of the marine food web, from nutrients up to mesozooplankton and it has 24 state variables. The product provides daily, monthly and yearly averages of the main biogeochemical variables. Additionally, climatological parameters (monthly mean and standard deviation) of these variables for the period 1993-2016 are delivered. '''DOI (Product)''': https://doi.org/10.48670/moi-00028

'''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:''' For the '''Mediterranean Sea''' Ocean '''Satellite Observations''', the Italian National Research Council (CNR – Rome, Italy), is providing multi-years '''Bio-Geo_Chemical (BGC)''' regional datasets: * '''''plankton''''' with the phytoplankton chlorophyll concentration (CHL) evaluated via region-specific algorithms (Case 1 waters: Volpe et al., 2019, with new coefficients; Case 2 waters, Berthon and Zibordi, 2004) and Phytoplankton Functional Types (PFT) evaluated via region-specific algorithm (Di Cicco et al. 2017) * '''''reflectance''''' with the spectral Remote Sensing Reflectance (RRS) * '''''transparency''''' with the diffuse attenuation coefficient of light at 490 nm (KD490) (for '''"multi'''" observations achieved via region-specific algorithm, Volpe et al., 2019) * '''''optics''''' including the IOPs (Inherent Optical Properties) such as absorption and scattering and particulate and dissolved matter (ADG, APH, BBP), via QAAv6 model (Lee et al., 2002 and updates) * '''''pp''''' with the Integrated Primary Production (PP) '''Upstreams''': SeaWiFS, MODIS, MERIS, VIIRS-SNPP & JPSS1, OLCI-S3A & S3B for the '''"multi"''' products, and OLCI-S3A & S3B for the '''"olci"''' products '''Temporal resolution''': daily '''Spatial resolution''': 1 km for '''"multi"''' and 300 meters for '''"olci"''' To find this product in the catalogue, use the search keyword '''"OCEANCOLOUR_MED_BGC_L3_MY"'''. '''DOI (product) :''' https://doi.org/10.48670/moi-00299

'''Short description''' The biogeochemical hindcast for global ocean is produced at Mercator-Ocean (Toulouse. France). It provides 3D biogeochemical fields since year 1993 at 1/4 degree and on 75 vertical levels. It uses PISCES biogeochemical model (available on the NEMO modelling platform). No data assimilation in this product. * Latest NEMO version (v3.6_STABLE) * Forcings: FREEGLORYS2V4 ocean physics produced at Mercator-Ocean and ERA-Interim atmosphere produced at ECMWF at a daily frequency * Outputs: Daily (chlorophyll. nitrate. phosphate. silicate. dissolved oxygen. primary production) and monthly (chlorophyll. nitrate. phosphate. silicate. dissolved oxygen. primary production. iron. phytoplankton in carbon) 3D mean fields interpolated on a standard regular grid in NetCDF format. The simulation is performed once and for all. * Initial conditions: World Ocean Atlas 2013 for nitrate. phosphate. silicate and dissolved oxygen. GLODAPv2 for DIC and Alkalinity. and climatological model outputs for Iron and DOC * Quality/Accuracy/Calibration information: See the related QuID '''DOI (product):''' https://doi.org/10.48670/moi-00019

'''Short description:''' This product consists of 3D fields of Particulate Organic Carbon (POC), Particulate Backscattering coefficient (bbp), Chlorophyll-a concentration (Chla), Downwelling Photosynthetic Available Radiation (PAR) and downwelling irradiance, at 0.25°x0.25° resolution from the surface to 1000 m. A neural network estimates the vertical distribution of Chla and bbp from surface ocean color measurements with hydrological properties and additional drivers. The SOCA-light models is used to integrate light. '''DOI (product):''' https://doi.org/10.48670/moi-00046

'''DEFINITION''' The omi_climate_sst_ibi_area_averaged_anomalies product for 2024 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1982 and averaged over the IBI areas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish areas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-CLIMATE-SST- IBI_v3.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the IBI areas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish areas built from re-processed ESA SST CCI, C3S (Embury et al., 2019). Anomalies are computed against the 1991-2020 reference period. The reference for this OMI can be found in the first and second issue of the Copernicus Marine Service Ocean State Report (OSR), Section 1.1 (Roquet et al., 2016; Mulet et al., 2018). '''CONTEXT''' Sea surface temperature (SST) is a key climate variable since it deeply contributes in regulating climate and its variability (Deser et al., 2010). SST is then essential to monitor and characterise the state of the global climate system (GCOS 2010). Long-term SST variability, from interannual to (multi-)decadal timescales, provides insight into the slow variations/changes in SST, i.e. the temperature trend (e.g., Pezzulli et al., 2005). In addition, on shorter timescales, SST anomalies become an essential indicator for extreme events, as e.g. marine heatwaves (Hobday et al., 2018). '''CMEMS KEY FINDINGS ''' The overall trend in the SST anomalies in this region is 0.012 ±0.002 °C/year over the period 1982-2024. '''DOI (product):''' https://doi.org/10.48670/moi-00256

'''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