AndreaBozzo/ceres-open-data-index huggingface dataset:
ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction â viewable snow (SCFV) from ATSR-2 (1995 â 2003), version 1.0

This dataset contains Daily Snow Cover Fraction of viewable snow from ATSR-2, produced by the Snow project of the ESA Climate Change Initiative programme.  Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel.The global SCFV product is available at 0.01Â° grid size (about 1 km) for all land areas, excluding Antarctica and Greenland ice sheet. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 1995 â 2003. The SCFV product is based on Along-Track Scanning Radiometer 2 (ATSR-2) data aboard the ERS-2 satellite. The retrieval method of the snow_cci SCFV product from ATSR-2 data has been further developed and improved based on the ESA GlobSnow approach (MetsÃ¤mÃ¤ki et al. 2015) and complemented with a pre-classification module. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (MetsÃ¤mÃ¤ki et al. 2015), defined as SCDA2.3. All cloud-free pixels are then used for the snow extent mapping, using spectral bands centred at about 659 nm and 1.61 Âµm, and an emissive band centred at about 10.85 Âµm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud-free pixels which are clearly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include adaptation of the retrieval method for mapping in forested areas the SCFV. Permanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the grid size of the SCFV product. Water areas are masked if more than 30% of the grid cell is classified as water, permanent snow and ice areas are masked if more than 50% is identified as such areas in the aggregated map. The product uncertainty for observed land areas is provided as unbiased root mean square error (RMSE) per grid cell in the ancillary variable.The SCFV product aims to serve the needs of users working with the cryosphere and climate research and monitoring activities, including the assessment of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.The Norwegian Computing Center (Norsk Regnesentral, NR) is responsible for the SCFV product development and generation from ATSR-2 data. The Remote Sensing Research Group of the University of Bern supported the development. ENVEO IT GmbH developed and prepared all auxiliary data sets used for the product generation.There are a few days without any ATSR-2 acquisitions in the years 1995, 1996, 1999, 2000, 2001, 2002 and 2003.
ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover Maps in Africa (Eastern Sahel region) at 10m spatial resolution for 2019 in Geotiff format, v1.2

This dataset contains high resolution (HR) land cover (LC) maps of a subregion of Africa, produced by the ESA High Resolution Land Cover (HRLC) Climate Change Initiative (CCI) project.  This consists of the following products:1) HRLC10: High Resolution Land Cover Maps at 10m spatial resolution for year 2019 (also referred to as static maps).2) Associated uncertainty products.They cover the geographic range (0.1Â°S â 18.1Â°N; 9.9Â°E â 43.3Â°E).The data are provided as both GeoTIFF tiles following the Sentinel-2 MGRS tiling scheme and as a GeoTiff format mosaic. These maps are also referred to as static maps.
ESA High Resolution Land Cover Climate Change Initiative (High_Resolution_Land_Cover_cci): High Resolution Land Cover Maps in Siberia (Northern Siberia region) at 10m spatial resolution for 2019 in Geotiff format, v1.2

This dataset contains high resolution (HR) land cover (LC) maps of a subregion of Siberia, produced by the ESA High Resolution Land Cover (HRLC) Climate Change Initiative (CCI) project.  It consists of the following products:1) HRLC10: High Resolution Land Cover Maps at 10m spatial resolution for year 2019 (also referred to as static maps).2) Associated uncertainty products.They cover the geographic range (51.3Â°N â 75.7Â°N; 64.4Â°E â 93.4Â°E).The data are provided as both GeoTIFF tiles following the Sentinel-2 MGRS tiling scheme and as a GeoTiff format mosaic. These maps are also referred to as static maps.
ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly velocity from 2017 to 2020, derived from Sentinel-1, v1

This dataset contains monthly gridded ice velocity maps of the Antarctic Ice Sheet derived from Sentinel-1 data acquired between 2017-01-01 and 2020-08-31.  It was generated by ENVEO, as part of the ESA Antarctic Ice Sheet Climate Change Initiative project (Antarctic_Ice_Sheet_cci).The surface velocity is derived by applying feature tracking techniques using Sentinel-1 synthetic aperture radar (SAR) data acquired in the Interferometric Wide (IW) swath mode. Ice velocity is provided at 200m grid spacing in Polar Stereographic projection (EPSG: 3031). The horizontal velocity components are provided in true meters per day, towards easting and northing direction of the grid. The vertical displacement is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz, along with maps showing the magnitude of the horizontal components, the valid pixel count and uncertainty. The product combines all ice velocity maps, based on 6- and 12-day repeats, acquired within a single month in a monthly averaged product.
ESA Ozone Climate Change Initiative (Ozone CCI): Merged Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 2

This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. The data are  zonal mean time series (10Â° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The merged monthly zonal mean data (MMZM) include merged ozone profiles in 10Â° latitude zones for each month, on the ozone-CCI pressure grid from 250 hPa to 1 hPa, and the parameters which characterize the uncertainty of the merged profiles. In Phase I of the ESA CCI Programme, the dataset has been created for 2 years, 2007 and 2008.The merged monthly zonal mean data are structured into monthly netcdf files with self-explanatory names. For example, the file âESACCI-OZONE-L3-LP-MERGED-MZM-200801-fv0002.ncâ contains merged monthly zonal mean data for January 2008. In addition to the variables of the merged data, the profiles from individual instruments with their uncertainty parameters are also included (for the altitude range 250-1 hPa used in data merging).
Sentinel-5P Level-3 NO2 Surface Monthly Product - V2

Contains binned Level-2 TROPOMI NO2 Surface retrievals. The L3 binning algorithm weighs individual pixels with the overlap area of the pixel and the Level-3 grid cell. The weighing and count vectors are used to apply this weighted average consistently, see http://stcorp.github.io/harp/doc/html/libharp_product.html?
ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction â viewable snow (SCFV) from AATSR (2002 â 2012), version 1.0

This dataset contains Daily Snow Cover Fraction of viewable snow from AATSR, produced by the Snow project of the ESA Climate Change Initiative programme.  Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at 0.01Â° grid size (about 1 km) for all land areas, excluding Antarctica and Greenland ice sheet. The coastal zones of Greenland are included. The SCFV time series provides daily products for the period 2002 â 2012. The SCFV product is based on Advanced Along-Track Scanning Radiometer (AATSR) data aboard the Envisat satellite. The retrieval method of the snow_cci SCFV product from AATSR data has been further developed and improved based on the ESA GlobSnow approach (MetsÃ¤mÃ¤ki et al. 2015) and complemented with a pre-classification module. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (MetsÃ¤mÃ¤ki et al. 2015), defined as SCDA2.3. All cloud-free pixels are then used for the snow extent mapping, using spectral bands centred at about 659 nm and 1.61 Âµm, and an emissive band centred at about 10.85 Âµm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud-free pixels which are clearly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Improvements to the GlobSnow algorithm implemented for snow_cci version 1 include adaptation of the retrieval method for mapping in forested areas the SCFV.Permanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the grid size of the SCFV product. Water areas are masked if more than 30% of the grid cell is classified as water, permanent snow and ice areas are masked if more than 50% is identified as such areas in the aggregated map. The product uncertainty for observed land areas is provided as unbiased root mean square error (RMSE) per grid cell in the ancillary variable.The SCFV product aims to serve the needs of users working with the cryosphere and climate research and monitoring activities, including the assessment of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.The Norwegian Computing Center (Norsk Regnesentral, NR) is responsible for the SCFV product development and generation from AATSR data. The Remote Sensing Research Group of the University of Bern supported the development. ENVEO IT GmbH developed and prepared all auxiliary data sets used for the product generation.There are a few days without any AATSR acquisitions in the years 2002, 2003, 2004, 2006, 2008, 2010 and 2012.
ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product (2018-2020), version 3.00

This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3B. 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.Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel 3B equator crossing times which are 10:00 and 22:00 local solar time. 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 solar geometry angles, a quality flag, and land cover class.The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01Â° longitude and 0.01Â° latitude. SLSTRB achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. 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.Dataset coverage starts on 17th November 2018 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.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.
ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3A, level 3 collated (L3C) global product (2016-2020), version 3.00

This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3A. 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.Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel-3A equator crossing times which are 10:00 and 22:00 local solar time. 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 solar geometry angles, a quality flag, and land cover class.The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01Â° longitude and 0.01Â° latitude. SLSTRA achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. 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.Dataset coverage starts on 1st May 2016 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.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.
ESA Ozone Climate Change Initiative (Ozone CCI): ODIN/SMR (544.6 GHz) Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1

This dataset comprises gridded limb ozone monthly zonal mean profiles from the ODIN/SMR (544.6 GHz) instrument. The data are zonal mean time series (10Â° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10Â° latitude zones from 90Â°S to 90Â°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file âESACCI-OZONE-L3-LP-MZM-SMR_ODIN-544_6_GHz-2008-fv0001.ncâ contains monthly zonal mean data for ODIN/SMR at 544.6GHz in 2008.
ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection at 4km resolution, Version 6.0

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 the Version 6.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day, monthly and yearly composites) covering the period 1997 - 2022. It is computed from the Ocean Colour CCI Version 6.0 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within 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).
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the DÃ¸cker Smith Glacier between 2016-05-08 and 2016-05-18, generated using Sentinel-2 data, v1.0

This dataset contains an optical ice velocity time series for the DÃ¸cker Smith Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2016-05-08 and 2016-05-18.  It is part of the ESA Greenland Ice Sheet CCI project.The data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing.   The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.   The product was generated by S[&]T Norway.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2013-2014, v1.0

This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2013-2014, derived from RADARSAT-2 data, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.  The ice velocity data were derived from intensity-tracking of RADARSAT-2 data aquired between 21/1/2014 and 02/04/2014. The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E).  The horizontal velocity is provided in true meters per day, towards the Eastings and Northings direction of the grid; the vertical displacement, derived from a digital elevation model, is also provided.  Both a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided.  This product was generated by DTU Space - Microwaves and Remote Sensing.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the  Upernavik Glacier between 2017-07-15 and 2017-08-14, generated using Sentinel-2 data, v1.1

This dataset contains optical ice velocity time series and seasonal product of the Upernavik Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-07-15 and 2017-08-14.   It has been produced as part of the ESA Greenland Ice sheet CCI project. The data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing.  The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.The product was generated by S[&]T Norway.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the  Kangerlussuaq Glacier between 2017-07-21 and 2017-08-20, generated using Sentinel-2 data, v1.1

This dataset contains optical ice velocity time series and seasonal product of the Kangerlussuaq Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-07-21 and 2017-08-20. It has been produced as part of the ESA Greenland Ice sheet CCI project. The data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing.  The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.The data have been produced by S[&]T Norway.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Petermann Glacier for 2015-2017 from Sentinel-1 data, v1.1

This dataset contains a time series of ice velocities for the Petermann Glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between 22/1/2015-19/3/2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Helheim Glacier for 2015-2017 from Sentinel-1 data, v1.1

This dataset contains a time series of ice velocities for the Helheim Glacier in Greenland derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between between June 2015 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Glacier for 2014-2017 from Sentinel-1 data, v1.1

This dataset contains a time series of ice velocities for the Jakobshavn glacier in Greenland, generated from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired from October 2014 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Zachariae and 79Fjord area from ERS-1, ERS-2 and Envisat data for 1991-2011, v1.1

This dataset contains a time series of ice velocities for the Zachariae and 79Fjord area in Greenland derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 01/08/1991 and 07/02/2011. It provides components of the ice velocity and the magnitude of the velocity and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs have a repeat cycle between 1 and 35 days.  The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.The product was generated by GEUS (Geological Survey of Denmark and Greenland).