The Data Access Portal has information in 3 columns. An outline of the content in these columns is provided above. When first entering the search interface, all potential datasets are listed. Datasets are indicated in the map and results tabulation elements which are located in the middle column. The order of results can be modified using the "Sort by" option in the left column. On top of this column is normally relevant guidance information to user presented as collapsible elements.
If the user want to refine the search, this can be done by constraining the bounding box search. This is done in the map - the listing of datasets is automatically updated. Date constraints can be added in the left column. For these to take effect, the user has to push the button marked search. In the left column it is also possible to specific text elements to search for in the datasets. Again pushing the button marked "Search" is necessary for these to take action. Complex search patterns can be constructed by changing the operators used in the text field and prefixing words with '+' and '-' to indicate whether they have to be present or should not be present in the results.
Other elements indicated in the left and right columns are facet searches, i.e. these are keywords that are found in the datasets and all datasets that contain these specific keywords in the appropriate metadata elements are listed together. Further refinement can be done using full text, date or bounding box constraints. Individuals, organisations and data centres involved in generating or curating the datasets are listed in the facets in the right column.
Citation of data and service
If you use data retrieved through this portal, please acknowledge the efforts of the data portal and the data centres contributing.
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
author,
title,
year of publication,
publisher (for data this is often the archive where it is housed),
edition or version,
access information (a URL or persistent identifier, e.g. DOI if provided)
SPUB Hornsund, RIS-ID: 11029 LONG-TERM OCEANOGRAPHIC MONITORING IN HORNSUND REGION
Institutions: Institute of Geophysics, Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2021-11-10T08:53:37Z
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Abstract:
A set of inter calibrated temperature in-depth profiles in Hornsund Fjord.We used all of our CTD sensors (Valeport: 1 CTD; RBR: 3 CTD, 2TD, 6 T; SeaBird 1CT; SAIV A/S: 1 CTD), at the same time in a stable position at stable depths for 24 hours measurement. SAIV A/S conductivity data was different from the rest. Because for CTD in-depth profile Valeport and SAIV A/S were used we made comparable CTD in-depths profiles for these two CTD sensors. Based on comparison plots for temperature and conductivity from the same depths for all comparable in-depth profiles for these two sensors we add linear correction for temperature and conductivity data from SAIV A/S. After losing SAIV A/S sensor we made the same procedure for the new. Depth (UNESCO Technical Papers in Marine Science No. 44), salinity (UNESCO 1983), density (Millero and Poisson 1981, UNESCO 1981) were calculated based on a commonly used formula from pressure, temperature, and conductivity after data inter-calibration.
SPUB Hornsund, RIS-ID: 11029 LONG-TERM OCEANOGRAPHIC MONITORING IN HORNSUND REGION
Institutions: Institute of Geophysics, Institute of Geophysics, Polish Academy of Sciences
Last metadata update: 2021-11-10T08:53:34Z
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Abstract:
A set of inter calibrated salinity in-depth profiles in Hornsund Fjord.We used all of our CTD sensors (Valeport: 1 CTD; RBR: 3 CTD, 2TD, 6 T; SeaBird 1CT; SAIV A/S: 1 CTD), at the same time in a stable position at stable depths for 24 hours measurement. SAIV A/S conductivity data was different from the rest. Because for CTD in-depth profile Valeport and SAIV A/S were used we made comparable CTD in-depths profiles for these two CTD sensors. Based on comparison plots for temperature and conductivity from the same depths for all comparable in-depth profiles for these two sensors we add linear correction for temperature and conductivity data from SAIV A/S. After losing SAIV A/S sensor we made the same procedure for the new. Depth (UNESCO Technical Papers in Marine Science No. 44), salinity (UNESCO 1983), density (Millero and Poisson 1981, UNESCO 1981) were calculated based on a commonly used formula from pressure, temperature, and conductivity after data inter-calibration.
Coastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with ''land'', ''ice shelf'', ''ice tongue'' or ''rumple'''' attribute. Covering all land and ice shelves south of 60degS. Suitable for topographic mapping and analysis. Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.
This data set consists of an enhanced resolution digital elevation model (DEM) for the Greenland Ice Sheet, derived from sub-meter resolution, panchromatic stereoscopic imagery collected by the GeoEye-1, WorldView-1, -2, and -3 satellites operated by Maxar Technologies.
The DEM was created from in-track image pairs (i.e., both images collected minutes apart along the same orbital pass) and cross-track images (i.e., from different orbits) within the in-track imaging geometry and maximum time separation criteria. The DEM is registered to ATLAS/ICESat-2 L3A Land Ice Height, Version 5 (ATL06, V5) data collected in the summers of 2019 and 2020.
Institutions: British Antarctic Survey, British Antarctic Survey, NERC EDS UK Polar Data Centre
Last metadata update: 2021-05-25T00:00:00Z
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Abstract:
Two maps of surface elevation change for Thwaites Glacier, West Antarctica. Change is in metres between 2013-12-21 and 2017-07-11, and between 2017-07-11 and 2020-11-02.
The work was funded by NERC projects NE/P011365/1 and NE/S006605/1.
This data product contains monthly ice sheet elevation change data for Antarctica derived from five radar altimetry missions (Geosat, ERS-1 and -2, Envisat and CryoSat-2) and two laser altimetry missions (ICESat and ICESat-2). Each time step and grid node includes relative error estimates and a quality flag that can be used to filter the data in space and time. The product is also provided with an estimate of static topography in the form of a digital elevation model (DEM), which was used to estimate monthly ice sheet elevation change. With a temporal coverage of 17 April 1985 to 16 December 2020, this product can be used to determine changes in ice sheet mass balance over time.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2021-03-15T00:00:00Z
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Abstract:
This dataset contains rates of mass change and cumulative mass change and their associated uncertainty for the Antarctic Ice Sheet (in its entirety and split into West Antarctica, East Antarctica and the Antarctic Peninsula), the Greenland Ice Sheet, and their sum between 1992 and 2020. The data are reconciled estimates of mass balance from three independent satellite-based techniques: altimetry, gravimetry and input-output method. This dataset is part of the Ice Sheet Mass Balance Intercomparison Exercise (IMBIE).
This work is an outcome of the Ice Sheet Mass Balance Inter-Comparison Exercise IMBIE) supported by the ESA Climate Change Initiative and the NASA Cryosphere Program. Andrew Shepherd was additionally supported by a Royal Society Wolfson Research Merit Award and the UK Natural Environment Research Council Centre for Polar Observation and Modelling (cpom30001).
This data set provides a comprehensive map for the Antarctic Ice Sheet of the short-term zone of migration of the grounding line (i.e., the transition boundary between grounded ice and ice floating in the ocean waters) over a given period due to changes in oceanic tide. This short-term variation in the grounding line is referred to in this data set as the “grounding zone.” The grounding zone is presented as polylines in an ESRI shapefile indicating the upstream and downstream bound of the variation in the grounding line for a given year. The data is based on an automatic delineation of thousands of grounding lines using Sentinel-1 A/B interferometric synthetic aperture radar (InSAR) data with a machine learning algorithm and supplemented by grounding lines from COSMO SkyMed InSAR data.
The transboundary Pumpqu/Arun River basin spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumpqu River flows. The river is named the Arun River once it enters Nepal. Five large hydropower projects (in total about 3,163 MW) are currently under construction or are planned for the Arun River valley. Rainfall and earthquake-induced landslides, landslide dammed lakes, and landslide-induced glacial lake outburst floods pose major risks to the smooth operation of these projects. This data set is a multitemporal landslide inventory covering the whole Pumpqu/Arun River basin. It was generated in support of the World Bank’s Risk Assessment of Landslides in the Upper Arun Hydropower Project.
These data are reconstructed seasonal Antarctic sea ice extent (SIE) for 1905 through 2020. They are provided along with uncertainty estimates and metadata that describe aspects of the reconstruction process that produced the SIE data. Reconstructed SIE ensembles are given for the entire Southern Ocean. The data files are available in comma-separated values format (.csv) and NetCDF-3 format (.nc).
Earth Observing System Data Information System, Earth Science Information Partners Program, NOAA/NASA Pathfinder Program (EOSDIS, ESIP, NOAA/NASA PATHFINDER)
As of 1 February 2022, this data set is retired and no longer available for download. We recommend using the MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR, Version 1 data set, located at https://nsidc.org/data/nsidc-0630/versions/1, as an alternative.
This Level-3 Equal-Area Scalable Earth-Grid (EASE-Grid) Brightness Temperature data set, collected since 09 July 1987, is a part of the NOAA/NASA Pathfinder Program. The data set consists of gridded data from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMIS) in three equal-area projections: Northern Hemisphere, Southern Hemisphere, and full global.
This data set consists of a water budget reanalysis for the High Mountain Asia (HMA) region spanning the years 2003 through 2020. Estimates are provided for more than 30 parameters, including storages; fluxes; snow depth, extent, and snow water equivalent; temperature (land surface, soil, snow, and ice); surface albedo; soil moisture; evapotranspiration; and streamflow.
The data were generated using the Noah Multi-Parameterization (Noah-MP) land surface model (Version 4.0.1), driven by precipitation estimates and hydrological inputs developed specifically for HMA.
This data set consists of a Northern Hemisphere subset of the Canadian Meteorological Centre (CMC) operational global daily snow depth analysis. Data include daily analyzed snow depths, as well as monthly means and climatologies of snow depth and estimated snow water equivalent (SWE).
This data set captures changes in glacier covered area across the state of Alaska for the period 1985 to 2020.The data set includes 18 biannual shapefiles each for overall glacier covered area, supraglacial debris area, and debris-free glacier covered area.
This data set contains annual surface melt onset and freeze onset dates across all glaciers in the Hindu Kush Himalayas (HKH) retrieved from time series synthetic aperture radar (SAR) imagery. The data set was based on analysis of C-band Sentinel-1 A/B SAR time series, comprising 32,741 Sentinel-1 A/B SAR images. The duration of annual glacier surface melt was determined for 105,432 mapped glaciers (83,102 km2 glacierized area) during the calendar years 2017-2020.