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CryoSat-2

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  • This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2017. The surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, and 2016-2017), and five-year means are also provided (2011-2015, 2012-2016, 2013-2017), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots. The algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012

  • This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from satellite (ERS‐1, ERS‐2, Envisat and Cryosat) radar altimetry. The ice mask is based on the GEUS/GST land/ice/ocean mask provided as part of national mapping projects, and based on 1980’s aerial photography. The data from ERS and Envisat are based on a 5‐year running average, using combined algorithms of repeat‐track (RT), along‐track (AT) or cross‐over (XO) algorithms, and include propagated error estimates. It is important to note that different processing algorithms were applied to the ERS‐1, ERS‐2, Envisat and CryoSat data; for details see the Product User Guide (PUG), available on the CCI website and in the documentation section here. For ERS‐1, the radar data were processed using a cross‐over algorithm (XO) only. For ERS‐2 data and Envisat data in repeat mode, a combination of RT and XO algorithms was applied, followed by filtering. For across‐mission (i.e. ERS‐2‐Envisat) combinations, and for Envisat operating in a drifting orbit, an AT and XO combination was applied (the difference between RT and AT algorithms is that AT use reference tracks and searches for data in the vicinity of this track). For CryoSat data a binning/gridding and plane fit method has been applied, following by weak filtering (0.05 degree resolution).

  • This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from SARAL-AltiKa for 2013-2017. This new experimental product of surface elevation change is based on data from the AltiKa-instrument onboard the France (CNES)/Indian (ISRO) SARAL satellite. The AktiKa altimeter utilizes Ka-band radar signals, which have less penetration in the upper snow. However, the surface slope and roughness has an imprint in the derived signal and the new product is only available for the flatter central parts of the Greenland ice sheet. The corresponding SEC grid from Cryosat-2 is included for comparison. The algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012. The approach used here corresponds to Least Squares Method (LSM) 5 described in the paper, in which the slope within each grid cell is accounted for by subtraction of the GIMP DEM; the data are corrected for both backscatter and leading edge width; and the LSM is solved at 1 km grid resolution (2 km search radius) and averaged in the post-processing to 5 km grid resolution and with a correlation length of 20 km.

  • These files are gridded topography, rates of surface elevation change, and errors as 500m and 1km posting determined from surface elevation measured by swath processing of data acquired by the interferometric radar altimeter CryoSat-2. The gridded products cover the Greenland Ice Sheet between 2011 and 2016. These data have been processed by the University of Edinburgh and are made publicly available as part of a European Space Agency funded project involving the University of Edinburgh, isardSat UK, University of Leeds-CPOM, ENVEO. Gridded elevation and elevation change over the CryoSat-2 LRM sector of the Greenland Ice Sheet are provided by CPOM. This dataset is part of ESA''s CryoTop Evolution project.

  • These files are surface elevation determined from swath processing of data acquired by the interferometric radar altimeter CryoSat-2. The data have been collected and processed over the Antarctic Ice Sheet between 2011 and 2016. These data have been processed by the University of Edinburgh and are made publicly available as part of the European Space Agency funded project CryoTop and CryoTop Evolution involving the University of Edinburgh, isardSat UK, University of Leeds-CPOM, ENVEO.

  • These files are gridded topography, rates of surface elevation change, and errors as 500m and 1km posting determined from surface elevation measured by swath processing of data acquired by the interferometric radar altimeter CryoSat-2. The gridded products cover the Antarctic Ice Sheet between 2011 and 2016. These data have been processed by the University of Edinburgh and are made publicly available as part of a European Space Agency funded project involving the University of Edinburgh, isardSat UK, University of Leeds-CPOM, ENVEO. Gridded elevation and elevation change over the CryoSat-2 LRM sector of the Antarctic Ice Sheet are provided by CPOM.

  • These files are surface elevation determined from swath processing of data acquired by the interferometric radar altimeter CryoSat-2. The data have been collected and processed over the Greenland Ice Sheet between 2011 and 2016. These data have been processed by the University of Edinburgh and are made publicly available as part of the European Space Agency funded CryoSat+ CryoTop Evolution STSE Study (ESA Contract 4000116874) involving the University of Edinburgh, isardSat UK, University of Leeds-CPOM, ENVEO.

  • 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 at Level 3C (L3C). 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 gridded on a Lambeth Azimuthal Equal Area grid 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 provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). 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 monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2017. Data are only available for the NH winter months, October - April.

  • This dataset provides a Climate Data Record of Sea Ice Thickness for the NH 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 for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2017.