The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created. The v06.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website. The data set should be cited using the following references: 1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019 2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001

This dataset contains the Gravimetric Mass Balance (GMB) gridded product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). The Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021) The GMB gridded product comprises time series of ice mass changes for cells of polar-stereographic grid with a sampling of 50x50 km² covering the entire AIS. A GMB basin product is also available as a separate dataset. Groh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736

The CO2_EMMA dataset comprises of level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using the ensample median algorithm EMMA to produce a merged SCIAMACHY and GOSAT XCO2 Level 2 product, as part of the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the product is v2.2, and forms part of the Climate Research Data Package 4. The EMMA algorithm has been applied to level 2 data from multiple XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This merged SCIAMACHY and GOSAT XCO2 Level 2 product is primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). For further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR).

This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Antarctic region, derived from the AMSR-E satellite instrument. It consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the AMSR-E instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset. Please note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). A second sea ice dataset has also been produced from the SSM/I instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility. The project team warns potential users that the AMSR-E SIC time-series is less mature than the SSM/I one, and that the former should be used with extra care, possibly after visual inspection or comparison to other data sources (such as the SSM/I time series during the overlap period)

The European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci) has accurately determined the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified sea surface temperatures (SSTs) to a quality suitable for climate research. This GHRSST (Group for High Resolution Sea Surface Temperature) Multi-Product Ensemble (GMPE) dataset was produced by the ESA SST_cci project to facilitate comparison of its own spatially complete analyses with other level 4 SST analysis products. It provides the median and standard deviation of the ensemble of input analyses, differences between the individual analyses and the median, and gradients in the input data and the median. The outputs are provided on a 0.25˚ regular latitude-longitude grid. The product extends from 1 September 1981 to 31 December 2016. The product was generated using the following inputs: ESA SST_cci Analysis version 2.0; ESA SST_cci Analysis version 1.1; E.U. Copernicus Marine Environment Monitoring Service (CMEMS) SST information (the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Reprocessing); National Centers for Environmental Information (NCEI) Advanced Very High Resolution Radiometer (AVHRR) Optimal Interpolation (OI) Global Blended SST Analysis; Canada Meteorological Center (CMC) 0.2-degree Global Foundation SST Analysis; Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) Analysis version 2.2.0.0 (10 realisations); Japan Meteorological Agency (JMA) Merged satellite and in-situ Data Global Daily SST (MGDSST) Analysis. Full details of the data used to generate this product are provided in the associated documentation.

This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. The data covers the period from March 2017 to May 2018 and is provided for TCCON (Total Carbon Column Observing Network) validation sites only. A full global dataset is in production. For further information on the dataset, please see the linked documentation. This data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO).

The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies. This dataset contains all their Version 2.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies. Data products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided. This data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.) Please note, this dataset has been superseded. Later versions of the data are now available.

This dataset consists of Land Surface Temperature (LST) data with uncertainty estimates, from the MODIS instrument on NASA's Aqua satellite. It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques. The Level 2 Land Surface Temperature data in this dataset has been retrieved from MODIS Collection 6 L1B calibrated radiances, in the context of the GlobTemperature project, but new uncertainty estimates have been added as part of the EUSTACE project. This version of the LST dataset is v2.1 of the GT_MYG_2P product, with earlier versions produced under the GlobTemperature project. It consists of a complete set of LST and accompanying auxiliary (AUX) datafiles for the MODIS-Aqua mission for the period from 2002 until 2016. An equivalent dataset is also available for MODIS-Terra.

This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period between 11/1991 - 04/2012. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file. The dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .

The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets. The v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document. The data set should be cited using all three of the following references: 1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070 3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014