'''Short description:''' The IBI-MFC provides a high-resolution wave reanalysis product for the Iberia-Biscay-Ireland (IBI) area starting in 01/01/1980 and being regularly extended on a yearly basis. The model system is run by Nologin with the support of CESGA in terms of supercomputing resources. The Multi-Year model configuration is based on the MFWAM model developed by Météo-France (MF), covering the same region as the IBI-MFC Near Real Time (NRT) analysis and forecasting product and with the same horizontal resolution (1/36º). The system assimilates significant wave height (SWH) altimeter data and wave spectral data (Envisat and CFOSAT), supplied by MF. Both, the MY and the NRT products, are fed by ECMWF hourly winds. Specifically, the MY system is forced by the ERA5 reanalysis wind data. As boundary conditions, the NRT system uses the 2D wave spectra from the Copernicus Marine GLOBAL forecast system, whereas the MY system is nested to the GLOBAL reanalysis. The product offers hourly instantaneous fields of different wave parameters, including Wave Height, Period and Direction for total spectrum; fields of Wind Wave (or wind sea), Primary Swell Wave and Secondary Swell for partitioned wave spectra; and the highest wave variables, such as maximum crest height and maximum crest-to-trough height. Besides, air-sea fluxes are provided. Additionally, climatological parameters of significant wave height (VHM0) and zero -crossing wave period (VTM02) are delivered for the time interval 1993-2016. '''DOI (Product)''': https://doi.org/10.48670/moi-00030

'''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:''' For the Global Ocean - The product contains monthly Level-4 sea surface wind and stress fields at 0.25 degrees horizontal spatial resolution. The monthly averaged wind and stress fields are based on monthly average ECMWF ERA5 reanalysis fields, corrected for persistent biases using all available Level-3 scatterometer observations from the Metop-A, Metop-B and Metop-C ASCAT, QuikSCAT SeaWinds and ERS-1 and ERS-2 SCAT satellite instruments. The applied bias corrections, the standard deviation of the differences and the number of observations used to calculate the monthly average persistent bias are included in the product. '''DOI (product) :''' https://doi.org/10.48670/moi-00181

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Description:''' This product is a NRT L4 global total velocity field at 0m and 15m. It consists of the zonal and meridional velocity at a 6h frequency and at 1/4 degree regular grid produced on a daily basis. These total velocity fields are obtained by combining CMEMS NRT satellite Geostrophic Surface Currents and modelled Ekman current at the surface and 15m depth (using ECMWF NRT wind). 6 hourly product, daily and monthly mean 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-00049

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Operational Mercator Ocean biogeochemical global ocean analysis and forecast system at 1/4 degree is providing 10 days of 3D global ocean forecasts updated weekly. The time series is aggregated in time, in order to reach a two full year’s time series sliding window. This product includes daily and monthly mean files of biogeochemical parameters (chlorophyll, nitrate, phosphate, silicate, dissolved oxygen, dissolved iron, primary production, phytoplankton, PH, and surface partial pressure of carbon dioxyde) over the global ocean. The global ocean output files are displayed with a 1/4 degree horizontal resolution with regular longitude/latitude equirectangular projection. 50 vertical levels are ranging from 0 to 5700 meters. * NEMO version (v3.6_STABLE) * Forcings: GLOBAL_ANALYSIS_FORECAST_PHYS_001_024 at daily frequency. * Outputs mean fields are interpolated on a standard regular grid in NetCDF format. * 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[http://marine.copernicus.eu/documents/QUID/CMEMS-GLO-QUID-001-028.pdf] '''DOI (product) :''' https://doi.org/10.48670/moi-00015

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The ibi_omi_tempsal_sst_area_averaged_anomalies product for 2021 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1993 and averaged over the Iberia-Biscay-Irish Seas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish Seas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-ATL-SST.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the European North West Shelf Seas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish Seas built from the ESA Climate Change Initiative (CCI) (Merchant et al., 2019) and Copernicus Climate Change Service (C3S) initiatives. Anomalies are computed against the 1993-2014 reference period. '''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 0.011 ±0.001 °C/year over the period 1993-2021. '''DOI (product):''' https://doi.org/10.48670/moi-00256

'''Short description:''' This product consists of 3D fields of Particulate Organic Carbon (POC), Particulate Backscattering coefficient (bbp) and Chlorophyll-a concentration (Chla) at depth. The reprocessed product is provided at 0.25°x0.25° horizontal resolution, over 36 levels from the surface to 1000 m depth. A neural network method estimates both the vertical distribution of Chla concentration and of particulate backscattering coefficient (bbp), a bio-optical proxy for POC, from merged surface ocean color satellite measurements with hydrological properties and additional relevant drivers. '''DOI (product):''' https://doi.org/10.48670/moi-00046

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' Experimental altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean with a 5Hz (~1.3km) sampling. All the missions are homogenized with respect to a reference mission (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 Atmosphic Correction, Ocean Tides, Long Wavelength Errors, Internal tide, …) that can be used to change the physical content for specific needs This product was generated as experimental products in a CNES R&D context. It was processed by the DUACS multimission altimeter data processing system. '''DOI (product) :''' https://doi.org/10.48670/moi-00137

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' This RRS product is defined as the ratio of upwelling radiance and downwelling irradiance at 412, 443, 490, 510, 560 and 665 nm wavebands (corresponding to MERIS), and can also be expressed as the ratio of normalized water leaving Radiance (nLw) and the extra-terrestrial solar irradiance (F0). The ESA Climate Change Initiative is a 2-part programme aiming to produce “climate quality” merged data records from multiple sensors. The Ocean Colour project within this programme has a primary focus on chlorophyll in open oceans, using the highest quality Rrs merging process to date. This uses a combination of bandshifting to a reference sensor and temporally-weighted bias correction to align independent sensors into a coherent and minimally-biased set of reflectances. These are derived from level 2 data produced by SeaDAS l2gen (SeaWiFS) and Polymer (MODIS, VIIRS, MERIS and OLCI-3A) , and the resulting Rrs bias corrected. '''Processing information:''' ESA-CCI Rrs raw data are provided by Plymouth Marine Laboratory, currently at 4km resolution. These are processed to produce CMEMS representations using the same in-house software as in the operational processing. The entire CCI data set is consistent and processing is done in one go. Both OC CCI and the REP product are versioned. Standard masking criteria for detecting clouds or other contamination factors have been applied during the generation of the Rrs, i.e., land, cloud, sun glint, atmospheric correction failure, high total radiance, large solar zenith angle (70deg), large spacecraft zenith angle (56deg), coccolithophores, negative water leaving radiance, and normalized water leaving radiance at 560 nm 0.15 Wm-2 sr-1 (McClain et al., 1995). For the regional products, a variant of the OC-CCI chain is run to produce high resolution data at the 1km resolution necessary. '''DOI (product) :''' https://doi.org/10.48670/moi-00077

'''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