AndreaBozzo/ceres-open-data-index huggingface dataset:
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Glacier from COSMO-SkyMed for 2012-2014, v1.0

This dataset contains ice velocity time series of then Jakobshavn glacier in Greenland, derived from intensity-tracking of COSMO-SkyMed data acquired between 2/6/2012 and 25/12/2014.  The ice velocity data is derived using 4-day COSMO-SkyMed offset-tracking pairs.   It has been produced as part of the ESA Greenland Ice sheet CCI project. The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 250m grid spacing. Image pairs with a repeat cycle of 4 days have been used.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 DTU Space.  For further details, please consult the document:T. Nagler, et al., Product User Guide (PUG) for the Greenland_Ice_Sheet_cci project of ESA's Climate Change Initiative, version 2.0.
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the  Jakobshavn Glacier between 2017-06-03 and 2017-09-08, generated using Sentinel-2 data, v1.1

This dataset contains optical ice velocity time series and seasonal product of the Jakobshavn Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-03 and 2017-09-08.  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): Optical ice velocity of the  Helheim Glacier between 2017-05-01 and 2017-08-29, generated using Sentinel-2 data, v1.1

This dataset contains optical ice velocity time series and seasonal product of the Helheim Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-05-01 and 2017-08-29. 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 79-Fjord Glacier for 2015-2017 from Sentinel-1 data, v1.1

This dataset contains a time series of ice velocities for the 79-Fjord Glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between January 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 Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic 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 geographic 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 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).
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2014-2015, v1.0

This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2014-2015, derived from Sentinel-1 SAR data, as part of 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). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities.
ESA Lakes Climate Change Initiative (Lakes_cci):  Lake products, Version 1.1

This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. This is version 1.1 of the dataset.Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and   functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are:â¢	Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes.â¢	Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide.â¢	Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. â¢	Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. â¢	Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.
ESA Ozone Climate Change Initiative (Ozone CCI): SCIAMACHY Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1

This dataset comprises gridded limb ozone monthly zonal mean profiles from the SCIAMACHY instrument on ENVISAT. 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-SCIAMACHY_ENVISAT-MZM-2008-fv0001.ncâ contains monthly zonal mean data for SCIAMACHY in 2008.
ESA Ozone Climate Change Initiative (Ozone CCI): GOMOS Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1

This dataset comprises gridded limb ozone monthly zonal mean profiles from the GOMOS 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-GOMOS_ENVISAT-MZM-2008.ncâ contains monthly zonal mean data for GOMOS in 2008.
ESA Ozone Climate Change Initiative (Ozone CCI): ACE Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1

This dataset comprises gridded limb ozone monthly zonal mean profiles from the ACE FTS instrument on the SCISAT satellite. 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-ACE_FTS_SCISAT-MZM-2008-fv0001.ncâ contains monthly zonal mean data for ACE in 2008.
ESA Ozone Climate Change Initiative (Ozone CCI): ODIN/SMR 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 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-SMR_ODIN-MZM-2008-fv0001.ncâ contains monthly zonal mean data for ODIN/SMR in 2008.
ESA Lakes Climate Change Initiative (Lakes_cci):  Lake products, Version 2.0.2

This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2020, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. This is version 2.0.2 of the dataset.   The five thematic climate variables included in this dataset are:â¢ Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change.â¢ Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. .â¢ Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality.â¢ Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality.â¢ Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat OLI, ERS, MODIS Terra/Aqua and Metop.Detailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website  and in Carrea, L., CrÃ©taux, JF., Liu, X. et al. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies. Sci Data 10, 30 (2023). https://doi.org/10.1038/s41597-022-01889-z
ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from AATSR (Advanced Along-Track Scanning Radiometer), level 3 collated (L3C) global product (2002-2012), version 3.00

This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat). 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 Envisat 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. AATSR achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath 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 25th July 2002 and ends on 8th April 2012. There is a twelve day gap in the dataset due to Envisat mission extension orbital manoeuvres from 21st October 2010 to 1st November 2010. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.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): Monthly land surface temperature from  MODIS (Moderate resolution Infra-red Spectroradiometer) on Terra, level 3 collated (L3C) global product (2000-2018), version 3.00

This dataset contains monthly-averaged land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System â Terra (Terra). 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 Terra equator crossing times which are 10:30 and 22:30 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. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath 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.The monthly dataset starts from March 2000 and ends  December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window 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): Merged Level 3 Limb Ozone Semi-Monthly Mean Profiles, Version 2

This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. The Merged Semi-Monthly Mean (MSMM) dataset is created using measurements from limb sensors participating in Ozone_cci project, for years 2007-2008.First, the ozone profiles from individual instruments are averaged in 10Â° x 20Â° latitude-longitude zones over half-month time intervals, and then merged.The merged semi-monthly mean ozone profiles are structured into yearly netcdf files with self-explanatory names. For example, the file âESACCI-OZONE-L3-LP-SMM-2008-fv0002.ncâ contains the semi-monthly mean ozone profiles 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).
PROBA-V S1 NDVI TOC 100 m COG: NDVI Data corrected for atmospheric effects with the SMAC (Simplified Method for Atmosheric Corrections) algorithm, COG format - Collection 2

Level 3 data products are variables mapped on uniform space-time grid scales and are the result of combining multiple scenes (e.g. S1/S10) to cover the userâs region of interest.
ESA Sea Level Climate Change Initiative (Sea_Level_cci): Oceanic Indicators of Mean Sea Level Changes,  Version 2.0

As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a number of oceanic indicators of mean sea level changes have been produced from merging satellite altimetry measurements of sea level anomalies.  The oceanic indicators dataset consists of static files covering the whole altimeter period, describing the evolution of the project's monthly sea level anomaly gridded product (see separate dataset record).The oceanic indicators that are provided are: 1) the temporal evolution of the global Mean Sea Level (MSL) DOI: 10.5270/esa-sea_level_cci-IND_MSL_MERGED-1993_2015-v_2.0-201612 ;2) the geographic distribution of Mean Sea Level changes (MSLTR) DOI: 10.5270/esa-sea_level_cci-IND_MSLTR_MERGED-1993_2015-v_2.0-201612 ;3) Maps of the amplitude and phase of the annual cycle (MSLAMPH) DOI: 10.5270/esa-sea_level_cci-IND_MSLAMPH_MERGED-1993_2015-v_2.0-201612.The complete collection of v2.0 products from the Sea Level CCI project can be referenced using the following  DOI: 10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612.When using or referring to the SL_cci products, please mention the associated DOIs and also use the following citation where a detailed description of the SL_cci project and products can be found:Ablain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., FaugÃ¨re, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993â2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.For further information on the Sea Level CCI products, and to register for these products please email: info-sealevel@esa-sealevel-cci.org
ESA Sea Level Climate Change Initiative (Sea_Level_cci): Time series of gridded Sea Level Anomalies (SLA), Version 2.0

As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a multi-satellite merged time series of monthly gridded Sea Level Anomalies (SLA) has been produced from satellite altimeter measurements. The Sea Level Anomaly grids have been calculated after merging the altimetry mission measurements together into monthly grids, with a spatial resolution of 0.25 degrees.   This version of the product is Version 2.0.  The following DOI can be used to reference the monthly Sea Level Anomaly product: DOI: 10.5270/esa-sea_level_cci-MSLA-1993_2015-v_2.0-201612The complete collection of v2.0 products from the Sea Level CCI project can be referenced using the following DOI: 10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612When using or referring to the Sea Level cci products, please mention the associated DOIs and also use the following citation where a detailed description of the Sea Level_cci project and products can be found:Ablain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., FaugÃ¨re, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993â2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.For further information on the Sea Level CCI products, and to register for these projects please email: info-sealevel@esa-sealevel-cci.org