The SMOS WRF product is available in Near Real Time to support tropical cyclones (TC) forecasts. It is generated within 4 to 6 hours from sensing from the SMOS L2 swath wind speed products (SMOS L2WS NRT), in the so-called "Fix (F-deck)" format compatible with the US Navy's ATCF (Automated Tropical Cyclone Forecasting) System. The SMOS WRF "fixes" to the best-track forecasts contain : the SMOS 10-min maximum-sustained winds (in knots) and wind radii (in nautical miles) for the 34 kt (17 m/s), 50 kt (25 m/s) and 64 kt (33 m/s) winds per geographical storm quadrants, and for each SMOS pass intercepting a TC in all the active ocean basins. See the complete description the "SMOS Wind Data Service Product Description Document" ( http://www.smosstorm.org/Document-tools/SMOS-Wind-Data-Service-Documentation ).

This product contains weekly salinity field, based on SMOS satellite data, and ISAS (In-Situ Analysis System). The L4OS SMOS-OI product contains global Level 4 analyses of the of the Sea Surface Salinity (SSS), Sea Surface Density (SSD) and Sea Surface Spiciness (SSSp), along with Sea Surface Absolute Salinity (SSA), Conservative Temperature (SCT), surface thermal expansion coefficient (alpha) and haline contraction coefficient (beta). The SSS product is obtained using an optimal interpolation (OI) algorithm, that combines ISAS in situ SSS OI analyses and Soil Moisture Ocean Salinity (SMOS) satellite image to reduce large scale and temporally varying bias. The SSS L4 product outcome is then combined with satellite SST products to compute thermodynamic sea water parameters using TEOS-10 (Kolodziejczyk et al., 2021). Products from reprocessing RE07 are available for the period 01/2011 - 05/2021. Products from operational (OPER) processing are available since 06/2021. Reprocessed products and operational products are derived using the same algorithm and configuration, hence ensuring the temporal continuity. The base products, for all the CATDS-PDC (Centre Aval de Traitement des Données SMOS - Production & Dissemination Center) processing chains, are the SMOS L1B products from ESA (European Space Agency). From these, brightness temperatures at various incidence angles are reconstructed. The Sea Surface Salinity (SSS) are retrieved from multi-angular brightness temperatures through a maximum likehood Bayesian approach in which measured Tb and Tb simulated using a forward direct model are compared (see Zine et al. 2008 for a general description of the retrieval method, and pro_con table for a summary of the similarities/differences with respect to ESA level 2 ocean salinity processing).

This product is a daily product of root zone soil moisture representative of the 0-1 m depth of the soil. The base products, for all the CATDS-PDC (Centre Aval de Traitement des Données SMOS - Production & Dissemination Center) processing chains, are the SMOS L1B products from ESA (European Space Agency). The L4SM RZSM is the daily product of root zone soil moisture (m3/m3) representative of the 0-1 m depth of the soil. The product contains also a quality index taking into account the presence of Radio Frequency Interference (RFI), low quality of retrieval of the input surface soil moisture, and a high fraction of non-nominal surfaces. Products from reprocessing RE07 are available for the period 01/2010 - 05/2021. Products from operational (OPER) processing are available since 06/2021. Reprocessed products and operational products are derived using the same algorithm and configuration, hence ensuring the temporal continuity.

This product contains daily salinity fields from a 9 days temporal gaussian average, corrected from land-sea contamination and latitudinal bias, based on L2Q products, mixing ascending and descending orbits. The base products, for all the CATDS-PDC (Centre Aval de Traitement des Données SMOS - Production & Dissemination Center) processing chains, are the SMOS L1B products from ESA (European Space Agency). From these, brightness temperatures at various incidence angles are reconstructed. The Sea Surface Salinity (SSS) are retrieved from multi-angular brightness temperatures through a maximum likehood Bayesian approach in which measured Tb and Tb simulated using a forward direct model are compared (see Zine et al. 2008 for a general description of the retrieval method, and pro_con table for a summary of the similarities/differences with respect to ESA level 2 ocean salinity processing). Products from reprocessing RE07 are available for the period 02/2010 - 05/2021. Products from operational (OPER) processing are available since 06/2021. Reprocessed products and operational products are derived using the same algorithm and configuration, hence ensuring the temporal continuity.

This product provides a “Final” (Refined) Level-2 Sea Surface Temperature (SST) (currently identified by "v8.2" within the file name) for the Group for High Resolution Sea Surface Temperature (GHRSST) Project, which is derived from the Advanced Microwave Scanning Radiometer 2 (AMSR2) by Remote Sensing Systems (RSS, or REMSS). AMSR2 was launched on 18 May 2012, onboard the Global Change Observation Mission - Water (GCOM-W) satellite developed by the Japan Aerospace Exploration Agency (JAXA). The GCOM-W mission aims to establish the global and long-term observation system to collect data, which is needed to understand mechanisms of climate and water cycle variations, and demonstrate its utilization. AMSR2 onboard the first generation of the GCOM-W satellite will continue Aqua/AMSR-E observations of water vapor, cloud liquid water, precipitation, SST, sea surface wind speed, sea ice concentration, snow depth, and soil moisture. AMSR2 is a remote sensing instrument for measuring weak microwave emission from the surface and the atmosphere of the Earth. The antenna of AMSR2 rotates once per 1.5 seconds and obtains data over a 1450 km swath. This conical scan mechanism enables AMSR2 to acquire a set of daytime and nighttime data with more than 99% coverage of the Earth every 2 days. The “Final” SSTs are processed when RSS receives the atmospheric model National Center for Environmental Prediction (NCEP) Final Analysis (FNL) Operational Global Analysis. The NCEP wind directions are particularly useful for retrieving more accurate SSTs and wind speeds.

Distribution of predicted suitable habitat for six cold-water-coral, six deep-water fish and one sponge species, on the North Atlantic (18°N to 76°N and 36°E to 98°W). For each species, predicted habitat distribution was obtained for present-day conditions (1951-2000) and for the future climate refugias, i.e. the areas that were predicted as suitable both for present-day and forecasted future (2081-2010) conditions. The dataset gathers 26 raster layers created on the same grid of 25km * 25km resolution, downgraded from source layers (3km *3km resolution) that were created within the work package 3 of EU ATLAS project. The presence (value=1) of climate refugia and the relative cover (value ranging from 0 to 1) of present-day suitable habitat was extracted in gridsquares. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.

Presence of deep-sea mining exploration zones on the North Atlantic (18°N to 76°N and 36°E to 98°W). These areas correspond to the three polymetallic sulphides exploration contracts on the Mid-Atlantic Ridge, attributed to Poland, France and Russia. Each of the three contract areas is divided into 100 squares of 10km by 10km. Source polygons originated from the International Seabed Authority. The presence (value=1) of deep-sea mining was extracted in 25km * 25km gridsquares. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.