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  • This v2.1 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 and 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 SST's to a quality suitable for climate research. This CDR Version 2.1 product supercedes the CDR Version 2.0 product. 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/ . When citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x

  • The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area developed from satellite observations. The MODIS Fire_cci v5.0 grid products described here are derived from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001 to 2016. This is the first time that MODIS 250m resolution images are used for global burned area (BA) mapping. This dataset is a gridded product, derived from the MODIS Fire_cci v5.0 pixel product by summarising its burned area information into a regular grid covering the Earth for 15-day periods with 0.25 degree resolution. Information on burned area is included in 23 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land_Cover_cci v1.6.1 product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation. Please note, a new version of this dataset (v5.1) is now available.

  • This Infrared Atmospheric Sounding Interferometer (IASI) methane dataset contains height-resolved and column-averaged volume mixing ratios of atmospheric methane (CH4). It also includes column-averaged water vapour (H2O), a scale factor for the HDO (water vapour isotopologue) volume mixing ratio profile, surface temperature, effective cloud fraction, effective cloud-top pressure and scale factors for two systematic residual spectra which are jointly retrieved from the spectral range 1232.25-1290.00 cm-1 by the Rutherford Appleton Laboratory (RAL) IASI optimal estimation methane retrieval scheme. The dataset additionally contains selected a priori values and uncertainties adopted in the optimal estimation scheme and retrieval output diagnostics such as the retrieval cost and the averaging kernels. This work was funded by the National Centre for Earth Observation (NCEO) under the UK Natural Environment Research Council (NERC) with additional funding from EUMETSAT. Data were produced by the United Kingdom Research and Innnovation (UKRI) Science and Technology Facilities Council (STFC) Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL). This is version 2.0 of the dataset.

  • This v2.1 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) 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 and 04/2012. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files). 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. This CDR Version 2.1 product supercedes the CDR v2.0 product. 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/ . When citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x

  • This dataset consists of a global daily analysis of surface air temperature for the whole Earth since 1850, based on combined information from satellite and in situ data sources, including uncertainty estimates. This is v1.0 of the product, which has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project. This product provides global mean air temperature data on a regular lat-lon grid with a grid spacing of 0.25 degrees, and provides daily data from 1850 to 2015. Uncertainty estimates are also provided, with both a 'total' uncertainty, and an ensemble of 10 samples. The mean temperature data and uncertainty estimates provided are consistent across a broad range of space and time scales from daily 0.25° to multidecadal global averages. The coverage is significantly better than is available from station data alone, and covers land, ocean and ice areas. This data has been derived using a statistical method to estimate air temperatures at all places and times. It takes into account uncertainty in the input data sets covering errors in the in situ measurements, land station homogenisation and errors in the air temperatures estimated from satellite data . Although the statistical model estimates temperatures at all locations, the product is not globally complete, as areas with too few data to provide a reliable air temperature estimate have been masked out.