This product is established from one of the SMOS product: the optical thickness. The optical thickness or VOD is obtained directly from SMOS data by use of the multi-angular capability. For low vegetation (grass, crops,...) it is linked mainly to the water content while for forested areas it is more linked to the above ground biomass (AGB). The product is a yearly aggregation of AGB derived using different references (ESA BIOMASS CCI, Avitabile AGB estimates etc...) and is available for SMOS life time (2010 - now)

This product contains average 10 days & monthly salinity field based on L2P products, ascending and descending orbits being processed separately. ** This product is no longer available, see below **

This product contains average 10 days & monthly salinity field corrected from land-sea contamination and latitudinal bias, based on L2Q products, ascending and descending orbits being processed separately. ** This product is no longer available, see below **

This product is radio frequency interference (RFI) probability for each angle bin computed daily and based on a monthly moving window average. Ascending and descending orbits are processed separately, and only in full polarization. ** This product is no longer available, see below **

This product is an intermediate product, that provides, in daily files, SSS with qualification flags (associated confidence classes) which allow selecting valid data before averaging. Ascending and descending orbits are processed separately ** This product is no longer available, see below **

Level 2 sub-skin Sea Surface Temperature derived from AVHRR on Metop, global and provided in full-resolution swath (1 km at nadir), in GHRSST compliant netCDF format. The satellite input data has successively come from Metop-A, Metop-B and Metop-C level 1 data processed at EUMETSAT. SST is retrieved from AVHRR infrared channels (3.7, 10.8 and 12.0 µm) using a multispectral algorithm and a cloud mask. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, Sea Surface Temperature from an analysis, together with a radiative transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. The quality of the products is monitored regularly by daily comparison of the satellite estimates against buoy measurements.The product format is compliant with the GHRSST Data Specification (GDS) version 2. Users are advised to use data only with quality levels 3,4 and 5.

This product is the daily product of soil moisture, and contains filtered data. The retrievals are based on a multi-orbit retrieval algorithm. A detection of freeze and snow is performed and added to the flags. Ascending and descending orbits are processed separately.

The Ocean Colour Climate Change Initiative project aims to: Develop and validate algorithms to meet the Ocean Colour GCOS ECV requirements for consistent, stable, error-characterized global satellite data products from multi-sensor data archives. Produce and validate, within an R&D context, the most complete and consistent possible time series of multi-sensor global satellite data products for climate research and modelling. Optimize the impact of MERIS data on climate data records. Generate complete specifications for an operational production system. Strengthen inter-disciplinary cooperation between international Earth observation, climate research and modelling communities, in pursuit of scientific excellence. The ESA OC CCI project is following a data reprocessing paradigm of regular re-processings utilising on-going research and developments in atmospheric correction, in-water algorithms, data merging techniques and bias correction. This requires flexibility and rapid turn-around of processing of extensive ocean colour datasets from a number of ESA and NASA missions to both trial new algorithms and methods and undertake the complete data set production. Read more about the Ocean Colour project on ESA's project website. https://climate.esa.int/en/projects/ocean-colour/.

This product is the daily product of soil moisture. The retrievals are based on a multi-orbit retrieval algorithm. Ascending and descending orbits are processed separately.

The SARWAVE project is developing a new sea state processor from SAR images to be applied over open ocean, sea ice, and coastal areas, and exploring potential synergy with other microwave and optical EO products.