'''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 0.1° resolution global grid. It includes observations by polar orbiting (NOAA-18 & NOAAA-19/AVHRR, METOP-A/AVHRR, ENVISAT/AATSR, AQUA/AMSRE, TRMM/TMI) and geostationary (MSG/SEVIRI, GOES-11) satellites . 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.3 more datasets are available that only contain "per sensor type" data : Polar InfraRed (PIR), Polar MicroWave (PMW), Geostationary InfraRed (GIR) '''DOI (product) :''' https://doi.org/10.48670/moi-00164

'''This product has been archived''' For operational and online products, please visit https://marine.copernicus.eu '''Short description:''' For The Global Ocean - The GHRSST Multi-Product Ensemble (GMPE) system has been implemented at the Met Office which takes inputs from various analysis production centres on a routine basis and produces ensemble products at 0.25deg.x0.25deg. horizontal resolution. A large number of sea surface temperature (SST) analyses are produced by various institutes around the world, making use of the SST observations provided by the Global High Resolution SST (GHRSST) project. These are used by a number of groups including: numerical weather prediction centres; ocean forecasting groups; climate monitoring and research groups. There is a requirement to develop international collaboration in this field in order to assess and inter-compare the different analyses, and to provide uncertainty estimates on both the analyses and observational products. The GMPE system has been developed for these purposes and is run on a daily basis at the Met Office, producing global ensemble median and standard deviations for SST on a regular 1/4 degree resolution global grid. '''DOI (product) :''' https://doi.org/10.48670/moi-00166

La loi du 27 février 2002 relative à la démocratie de proximité fixe comme premier objectif du recensement de la population la publication tous les ans des chiffres des populations légales : population municipale, population comptée à part et population totale. Ces chiffres sont calculés pour la France, toutes ses communes et circonscriptions administratives. La population municipale comprend les personnes ayant leur résidence habituelle sur le territoire de la commune. Elle inclut les personnes sans abri ou résidant habituellement dans des habitations mobiles recensées sur le territoire de la commune ainsi que les détenus dans les établissements pénitentiaires de la commune. C'est la population statistique comparable à la population sans double compte des précédents recensements. La population comptée à part comprend certaines personnes dont la résidence habituelle est dans une autre commune mais qui gardent un lien de résidence avec la commune. Elle comprend, par exemple, les élèves ou étudiants majeurs qui logent pour leurs études dans une autre commune mais dont la résidence familiale est située sur le territoire de la commune ou les personnes résidant dans une maison de retraite située dans une autre commune mais qui ont conservé une résidence familiale sur le territoire de la commune. Il est important de dénombrer à part de telles situations, d'abord pour clarifier quelle est véritablement la commune de résidence mais aussi pour ne pas produire des doubles comptes entre deux communes quand on additionne leurs populations. La population totale est la somme de la population municipale et de la population comptée à part. Les populations légales millésimées "n" sont diffusées fin décembre "n+2" pour les communes, cantons, arrondissements, départements et régions de France. Les résultats statistiques du recensement "n" sont diffusés au cours du second semestre "n+3".

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''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) 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 Global Ocean. (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_NOISE_L4_NRT_OBSERVATIONS_008_032 [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-00147

The EMODnet Bathymetry portal is operated and further developed by a European partnership. This comprises members of the SeaDataNet consortium together with organisations from marine science, the hydrographic survey community, and industry. The partners combine expertises and experiences of collecting, processing, and managing of bathymetric data together with expertises in distributed data infrastructure development and operation and providing OGC services (WMS, WFS, and WCS) for viewing and distribution. SeaDataNet is a leading infrastructure in Europe for marine & ocean data management, initiated and managed by the National Oceanographic Data Centres (NODC's). It is actively operating and further developing a Pan-European infrastructure for managing, indexing and providing access to ocean and marine data sets and data products, acquired via research cruises and other in-situ observational activities. The basis of SeaDataNet is interconnecting Data Centres into a distributed network of data resources with common standards for metadata, vocabularies, data transport formats, quality control methods and flags, and access. SeaDataNet is aiming for an extensive coverage of available data sets for the various marine environmental disciplines, such as physical oceanography, marine chemistry, biology, biodiversity, geology, geophysics and bathymetry. This is implemented by seeking active cooperation at a national scale with institutes and at a European scale with communities, that are engaged in data management for these disciplines, and by seeking opportunities for including their data centres and data collections in the SeaDataNet metadata and data provision.

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the European Ocean - Sea Surface Temperature Mono-Sensor L3 Observations. One SST file per 24h per area and per sensor (bias corrected) closest to the original resolution: SLSTR-A, AMSR2, SEVIRI, AVHRR_METOP_B, AVHRR18_G, AVHRR_19L, MODIS_A, MODIS_T, VIIRS_NPP. One SST file per file window per area and per sensor (bias corrected) closest to the original resolution , while still manageable in terms volume over the processed area. '''Description of observation methods/instruments:''' The METOP_B derived SSTs are not bias corrected because METOP_B is used as the reference sensor for the correction method. '''DOI (product) :''' https://doi.org/10.48670/moi-00162

Gridded Distribution of Species as reported during the Article 17 of the Habitats Directive (92/43/EEC) covering the period 2001 to 2006. The data covers the EU 25. All Member States are requested by the Habitats Directive (92/43/EEC) to monitor habitat types and species considered to be of Community interest. Article 17 of the Habitats Directive 92/43/EEC requires that every 6 years Member States prepare reports to be sent to the European Commission on the implementation of the Directive. The Article 17 report for the period 2001-2006 for the first time includes assessments on the conservation status of the habitat types and species of Community interest. Information on the data quality of the 2001-2006 reporting round is available at http://bd.eionet.europa.eu/article17.

'''Short description:''' This product provides daily (nighttime), gap-free (Level-4, L4) maps of foundation Sea Surface Temperature (SST) - that is, the SST free from diurnal warming - over the Mediterranean Sea, at high (HR, 1/16°) and ultra-high (UHR, 1/100°) spatial resolutions, covering the period from 2008 to present. Each map represents nighttime SST values (centered at 00:00 UTC) and is produced by the Italian National Research Council – Institute of Marine Sciences (CNR-ISMAR). L4 maps are generated by selecting only the highest-quality SST observations from upstream Level-2 (L2) data acquired within a short local nighttime window, in order to minimize cloud contamination and avoid the effects of the diurnal cycle. The main L2 sources currently ingested include SLSTR from Sentinel-3A and -3B, VIIRS from NOAA-21, NOAA-20, and Suomi-NPP, AVHRR from Metop-B and -C, and SEVIRI. A two-step algorithm allows to interpolate SST data at high and ultra-high spatial resolution, applying statistical techniques (Buongiorno Nardelli et al., 2013; Buongiorno Nardelli et al., 2015). Additionally, from 2024 onwards, an improved first-guess field has been used in the generation of the MED UHR L4 data, enhancing the product's spatial resolution of SST features and the accuracy of SST gradients via machine learning techniques (Fanelli et al., 2024). '''DOI (product) :''' https://doi.org/10.48670/moi-00172

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''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 wave length). 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 European Ocean- The L3 multi-sensor (supercollated) product is built from bias-corrected L3 mono-sensor (collated) products at the resolution 0.02 degrees. If the native collated resolution is N and N < 0.02 the change (degradation) of resolution is done by averaging the best quality data. If N > 0.02 the collated data are associated to the nearest neighbour without interpolation nor artificial increase of the resolution. A synthesis of the bias-corrected L3 mono-sensor (collated) files remapped at resolution R is done through a selection of data based on the following hierarchy: AVHRR_METOP_B, VIIRS_NPP, SLSTRA, SEVIRI, AVHRRL-19, MODIS_A, MODIS_T, AMSR2. This hierarchy can be changed in time depending on the health of each sensor. '''DOI (product) :''' https://doi.org/10.48670/moi-00163