“SMOS Level 3 daily wind speed” (SMOS L3WS) products are daily composite maps of the collected SMOS L2 swath wind products for a specific day, provided with the same grid than the Level 2 wind data (SMOS L2WS NRT) but separated into ascending and descending passes. SMOS L3WS products are available the day after from sensing and are generated in NetCDF-4 format as described in the "SMOS Wind Data Service Product Description Document" (http://www.smosstorm.org/Document-tools/SMOS-Wind-Data-Service-Documentation ).

A prerequisite for a successful development of a multi-mission wind dataset is to ensure good inter-calibration of the different extreme wind datasets to be integrated in the product. Since the operational hurricane community is working with the in-situ dropsondes as wind speed reference, which are in turn used to calibrate the NOAA Hurricane Hunter Stepped Frequency Microwave Radiometer (SFMR) wind data, MAXSS has used the latter to ensure extreme-wind inter-calibration among the following scatterometer and radiometer systems: the Advanced Scatterometers onboard the Metop series (i.e., ASCAT-A, -B, and -C), the scatterometers onboard Oceansat-2 (OSCAT) and ScatSat-1 (OSCAT-2), and onboard the HY-2 series (HSCAT-A, -B); the Advanced Microwave Scanning Radiometer 2 onboard GCOM-W1(AMSR-2), the multi-frequency polarimetric radiometer (Windsat), and the L-band radiometers onboard the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) missions. In summary, a two-step strategy has been followed to adjust the high and extreme wind speeds derived from the mentioned scatterometer and radiometer systems, available in the period 2009-2020. First, the C-band ASCATs have been adjusted against collocated storm-motion centric SFMR wind data. Then, both SFMR winds and ASCAT adjusted winds have been used to adjust all the other satellite wind systems. In doing so, a good inter-calibration between all the systems is ensured not only under tropical cyclone (TC) conditions, but also elsewhere. This dataset was produced in the frame of the ESA funded Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project. The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidance and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction.

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 unequivocal Vulnerable Marine Ecosystems (VMEs) and VME likelihood based on indicator taxa records, on the North Atlantic (18°N to 76°N and 36°E to 98°W). Several datasets, originating from public databases, literature review and data call to ATLAS partners, were gathered to compute the presence of unequivocal VME habitats in 25km * 25 km cells for the ATLAS work package 3. One layer displays the unequivocal VMEs (value=4) and the assigned high (value=3), medium (value=2) or low (value=1) likelihood of gridsquares to host VMEs, indexed on indicator taxa records from public databases with the method detailed in Morato et al (2018). The second displays the confidence associated to the VME likelihood score, indexed on data quality as detailed in Morato et al (2018) (values for unequivocal VMEs thus 100% confidence=4; high confidence=3; medium confidence=2; low confidence=1). 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.

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.

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.

Planning units layers used for ATLAS EU prioritization scenarios on the North Atlantic (18°N to 76°N and 36°E to 98°W). This raster layer is designed on a grid of 25km * 25km resolution, that served to extract all the spatial data used prioritization. The 31 518 planning units (cells with value) corresponded to areas containing depths shallower or equal to 3500m, even if they could also contain deeper areas locally. For connectivity scenarios, only the planning units matching with the extent of available connectivity data were selected. One layer allocates planning units to the 13 geographical provinces (values ranging from 1 to 13) created for the purpose of prioritization. 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.

Distribution of catch from deep-sea impacting fishing on the North Atlantic (18°N to 76°N and 36°E to 98°W), for the period 2010-2015. The average of yearly fishing catch for the period 2010-2015 is displayed as an index on the ATLAS grid of 25km * 25km resolution. Source data originated from the Global Fisheries Landings V4.0 database. The dataset was filtered to select only the fishing gears that have an impact on large areas of the seafloor (dredges, bottom trawls, and Danish seines). Within each cell, all remaining catch records were summed to get the total catch rate of the considered year. 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.