The MetOp First Generation (FG) is a European multi-satellite program jointly established by ESA and EUMETSAT, comprising three satellites, MetOp -A, -B and -C. The primary sensor onboard MetOp-FG, the Advanced Very High Resolution Radiometer/3 (AVHRR/3) contributed by NOAA, measures Earth emissions and reflectances in 5 out of 6 available bands (centered at 0.63, 0.83, 1.61, 3.7, 11 and 12 microns), in a swath of 2,600km from an 817km altitude. These data are collected in a Full Resolution Area Coverage (FRAC) mode, with pixel size of 1.1km at nadir. MetOp-A launched on 19 October 2006 is the first in the MetOp-FG series. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) Level 2 Preprocessed (L2P) SST product is derived at the full AVHRR FRAC resolution and reported in 10 minute granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). Subskin SSTs are derived using the regression Nonlinear SST (NLSST) algorithm, which employs three bands (3.7, 11 and 12 microns) at night and two bands (11 and 12 microns) during the day. The ACSPO AVHRR FRAC L2P product is monitored and validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam) https://www.star.nesdis.noaa.gov/socd/sst/iquam , in another NOAA system, SST Quality Monitor (SQUAM) https://www.star.nesdis.noaa.gov/socd/sst/squam . SST imagery and clear-sky masking are continuously evaluated, and checked for consistency with other sensors and platforms, in the NOAA ACSPO Regional Monitor for SST (ARMS) system https://www.star.nesdis.noaa.gov/socd/sst/arms . MetOp-A orbital characteristics and AVHRR/3 sensor performance are tracked in the NOAA 3S system ( https://www.star.nesdis.noaa.gov/socd/sst/3s ).The L2P Near Real Time (NRT) SST files are archived at PO.DAAC with 3-6 hours latency, and then replaced by the Re-ANalysis (RAN) SST after about 2 months later with identical file names. Two features can be used to identify them: different file name time stamps and netCDF global attribute metadata source=NOAA-NCEP-GFS for NRT and source=MERRA-2 for RAN. A reduced size (0.45GB/day), equal-angle gridded (0.02-deg resolution) ACSPO L3U product is available at https://doi.org/10.5067/GHMTA-3US28

These products contain global non time critical (NTC) reprocessed (REP) Level 2P skin Sea Surface Temperature (SST) derived from SLSTR-A on Copernicus Sentinel-3 at full-resolution swath (1 km at nadir) in GHRSST compliant NetCDF format. All SSTs from the Sea and Land Surface Temperature Radiometer (SLSTR) series of instruments are SST skin measurements. For more details please see “What is SST?” on the GHRSST web pages. At night, the skin temperature is typically a few tenths of a degree cooler than the temperature measured by in situ systems; in the day, the skin can be considerably higher if strong diurnal warming is present. The SLSTRs are dual-view self-calibrating radiometers with SST retrieved from spectral bands at nominally 3.74, 10.85 and 12 µm (referred to as S7, S8 & S9). Corrections for water vapour atmospheric absorption are performed using a triple window at night, and a split window during the day as the 3.7 µm channel is not used due to solar contamination. All pixels in the dual-view part of the swath are viewed twice, via nadir and oblique views with different atmospheric path lengths, allowing for correction for aerosol effects. Consequently, there are four possible retrieved SSTs, referred to as N2 (nadir-only 11 µm and 12 µm), N3 (nadir-only 3.7 µm, 11 µm and 12 µm), D2 (dual-view 11 µm and 12 µm) and D3 (dual-view 3.7 µm, 11 µm and 12 µm). The L2P file contains the best SST available for each pixel and flags are included to identify which retrieval is used. If the observation is in the nadir-only / single-view part of swath then "sst_algorithm_types" is N2 or N3, and if the observation is in the dual-view part of swath then "sst_algorithm_types" is D2 or D3. For D2 or D3 pixels it is possible to generate their N2 or N3 equivalent by subtracting the value in the "dual_nadir_sst_difference" field. Users are advised to use only QL = 5 dual-view SSTs for reference sensor applications and to use single-view (all quality levels) and quality level 3 and 4 dual-view data only for other qualitative analysis. Users are reminded to apply the SSES bias adjustments as SLSTR-B is harmonised to SLSTR-A through SSES. Users can consider using the "theoretical_uncertainty" for weighting observations rather than the simple SSES standard deviation values. Primary access to data is via the EUMETSAT Data Store (linked below). Other access methods can be found in the EUMETSAT Product Navigator https://navigator.eumetsat.int/product/EO:EUM:DAT:0582?query=slstr&results=22&s=advanced. Please also read the EUMETSAT SLSTR Product Notices (linked below) as they provide a lot of useful information. All products currently contain SLSTRA-MAR-L2P-v1.0 as the GHRSST Collection ID in the file metadata, which will be revised in a future release.

The Level 4 merged microwave wind product is a complete set of hourly global 10-m wind maps on a 0.25x0.25 degree latitude-longitude grid, spanning 1 Jan 2010 through the end of 2020. The product combines background neutral equivalent wind fields from ERA5, daily surface current fields from CMEMS, and stress equivalent winds obtained from several microwave passive and active sensors to produce hourly surface current relative stress equivalent wind analyses. The satellite winds include those from recently launched L-band passive sensors capable of measuring extreme winds in tropical cyclones, with little or no degradation from precipitation. All satellite winds used in the analyses have been recalibrated using a large set of collocated satellite-SFMR wind data in storm-centric coordinates. To maximize the use of the satellite microwave data, winds within a 24-hour window centered on the analysis time have been incorporated into each analysis. To accomodate the large time window, satellite wind speeds are transformed into deviations from ERA5 background wind speeds interpolated to the measurement times, and then an optical flow-based morphing technique is applied to these wind speed increments to propagate them from measurement to analysis time. These morphed wind speed increments are then added to the background wind speed at the analysis time to yield a set of total wind speeds fields for each sensor at the analysis time. These individual sensor wind speed fields are then combined with the background 10-m wind direction to yield vorticity and divergence fields for the individual sensor winds. From these, merged vorticity and divergence fields are computed as a weighted average of the individual vorticity and divergence fields. The final vector wind field is then obtained directly from these merged vorticity and divergence fields. Note that one consequence of producing the analyses in terms of vorticity and divergence is that there are no discontinuities in the wind speed fields at the (morphed) swath edges. There are two important points to be noted: the background ERA5 wind speed fields have been rescaled to be globally consistent with the recalibrated AMSR2 wind speeds. This rescaling involves a large increase in the ERA5 background winds beyond about 17 m/s. For example, an ERA5 10 m wind speed of 30 m/s is transformed into a wind speed of 41 m/s, and a wind speed of 34 m/s is transformed into a wind speed of about 48 m/s. Besides the current version of the product is calibrated for use within tropical cyclones and is not appropriate for use elsewhere. This dataset was produced in the frame of ESA 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.

“SMOS Near Real Time Level 2 swath wind speed” (SMOS L2WS NRT) products, which are SMOS retrieved surface wind speed gridded maps with a spatial sampling of 1/4°x 1/4° and consisting of orbital segments (containing parts of ascending and descending half orbits) following the granularity of the SMOS Level 1B near real time (NRT) data products. SMOS L2WS NRT products are available within 4 to 6 hours 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).

This dataset provides detections of fronts derived from low resolution optimally interpolated remote sensing microwave SST L4 from REMSS over North Atlantic region. The data are available through HTTP and FTP; access to the data is free and open. In order to be informed about changes and to help us keep track of data usage, we encourage users to register at: https://forms.ifremer.fr/lops-siam/access-to-esa-world-ocean-circulation-project-data/ This dataset was generated by OceanDataLab and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 4 (L4) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, gridded over a global regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all available altimeters on a monthly basis (using the L2P products also available). These L4 products are meant for statistics and visualization. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2021 ( Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

In 1967, E.Postel, researcher at the OSTPM (Scientific and Technical Office for Maritime Fisheries) set up a data collection system on albacore catches by French fleets. JC Dao and FX Bard continued this work within CNEXO (National Center for the Exploitation of Oceans) and then at IFREMER from 1984. This information was transmitted by fishing professionals via logbooks, on the basis of volunteering (Dao, 1971, Bard, 1977). In 1982, the European Community put in place a mandatory system of declarations of fishing effort and catches via logbooks (EC Regulation No. 2057 in Sanchez and Santurtun, 2013). As a result, the two systems persisted between 1982 and 1986, with European logbooks gradually supplanting logbooks

These datasets contain 4D (x, y, z, t) weekly temperature and marine heatwaves (MHW) categories estimated from the surface up to 300-m depth, at a 0.25°x0.25° horizontal grid resolution and for 4 areas of interest that are: • Area 1 (around the Madeira Islands): 30°N-35°N, 15°W-20°W • Area 2 (Tropical Pacific Ocean): 30°S-30°N, 120°E-130°W • Area 3 (Mediterranean Sea): 40°N-45°N, 15°W-20°W • Area 4 (Global): 82.875°S-89.875°N, 0.125°E-359.875°E The weekly MHW are centered on the date of the file (±3days). For the temperature reconstruction, 2 approaches have been used: - for the regional areas, the temperature has been computed with a 2 steps method: a first estimate of the vertical temperature profiles by using a machine learning approach (Multi-Layer Perceptron (MLP)) and then, a combination of this field with in situ temperature profiles observations through an optimal interpolation algorithm. The Copernicus Marine Service ARMOR3D dataset was used as the targeted temperature field for the MLP. The input data used are: • First step: ◦ SST data are from daily OSTIA analyses [from Copernicus Marine Service: SST_GLO_SST_L4_REP_OBSERVATIONS_010_011 product] interpolated over the 0.25°x0.25° targeted grid resolution; ◦ SLA data are from the Copernicus Marine Service product SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047/dataset-duacs-rep-global-merged-allsat-phy-l4 • Second step: ◦ The in situ data are from the Copernicus Marine Service In Situ TAC and contains several observations type: CTD, Argo floats, drifting buoys, moorings, marine mammals). - For the global area, the temperature comes from the Copernicus Marine Service product ARMOR3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 (https://doi.org/10.48670/moi-00052). The MHW categories are derived from the Hobday’s method [Hobday et al.,2018] for the 4 areas. Each MHW event is classified among four categories (moderate to extreme), identified in terms of multiples of the local difference between the 90th percentile and climatological values, and defined as moderate (1-2×, Category I), strong (2-3×, Category II), severe (3-4×, Category III), and extreme (>4×, Category IV). When the category is zero, this means that there is no MHW. The period 1993-2021 is used as a baseline for defining the climatology to be as close as possible to the 30-year period suggested by Hobday. This choice is motivated by the need of altimetry data to constrain the vertical temperature reconstruction, which is required for most ocean reanalyses as well, therefore the baseline period slightly differs from the one used for the 2D atlas.

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.

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 2P (L2P) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution, separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2022021 (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).