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  • The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 2 aerosol products from the ATSR-2 instrument on the ERS-2 satellite, derived using the ORAC algorithm, version 4.01. It covers the period from 1995-2003 For further details about these data products please see the linked documentation.

  • This dataset contains monthly-averaged land surface temperatures (LSTs) and their uncertainty estimates from multiple Infra-Red (IR) instruments on satellites in Geostationary Earth Orbit (GEO) and Low Earth Orbiting (LEO) sun-synchronous (a.k.a. polar orbiting) satellites. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. LST fields are provided at 3 hourly intervals each day (00:00 UTC, 03:00 UTC, 06:00 UTC, 09:00 UTC, 12:00 UTC, 15:00 UTC, 18:00 UTC and 21:00 UTC). Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and the solar geometry angles. The product is based on merging of available GEO data and infilling with available LEO data outside of the GEO discs. Inter-instrument biases are accounted for by cross-calibration with the IASI instruments on METOP and LSTs are retrieved using a Generalised Split Window algorithm from all instruments. As data towards the edge of the GEO disc is known to have greater uncertainty, any datum with a satellite zenith angle of more than 60 degrees is discarded. All LSTs included have an observation time that lies within +/- 30 minutes of the file nominal Universal Time. Data from the following instruments is included in the dataset: geostationary, Imagers on Geostationary Operational Environmental Satellite (GOES) 12 and GOES 13, Advanced Baseline Imager (ABI) on GOES 16, Spinning Enhanced Visible Infra-Red Imager (SEVIRI) on Meteosat Second Generation (MSG) 1, MSG 2, MSG 3, and MSG 4, Japanese Advanced Meteorological Imager (JAMI) on Multifunctional Transport Satellite MTSAT) 1, and MTSAT 2; and polar, Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat), Moderate-resolution Imaging Spectroradiometer (MODIS) on Earth Observation System (EOS) - Aqua and EOS - Terra, Sea and Land Surface Temperature Radiometer SLSTR on Sentinel-3A and Sentinel-3B. However, it should be noted that which instruments contribute to a particular product file depends on depends on mission start and end dates and instrument downtimes. Dataset coverage starts on 1st January 2009 and ends on 31st December 2020. LSTs are provided on a global equal angle grid at a resolution of 0.05° longitude and 0.05° latitude. The dataset coverage is nominally global over the land surface but varies depending on satellite and instrument availability and coverage. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. The dataset was produced by the University of Leicester (UoL) and data were processed in the UoL processing chain. The Geostationary data were produced by the Instituto Português do Mar e da Atmosfera (IPMA) before being merged into the final dataset. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.

  • This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) level 3 uncollated data (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 - 12/2016. This Level 3 Uncollated (L3U) product provides these SST data on a 0.05 regular latitude-longitude grid with a single orbit 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/ .

  • Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 GOS SRPR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). This proxy version of the product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. For more information regarding the differences between the baseline and alternative algorithms please see the GHG-CCI data products webpage. The data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. As well as containing the key product, the product file contains information relevant for the use of the data, such as the vertical layering and averaging kernels. The parameters which are retrieved simultaneously with XCH4 are also included (e.g. surface albedo), in addition to retrieval diagnostics like quality of the fit and retrieval errors. For further details on the product, including the RemoTeC algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/

  • The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 2 aerosol products from ATSR-2, using the ORAC algorithm, version 3.02. For further details about these data products please see the linked documentation.

  • 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 their Version 3.1 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. This data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)

  • 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 their Version 4.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. This data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)

  • 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 dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project. It provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2017. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information.

  • 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).