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)
International Polar Year, Integrated Arctic Ocean Observing System - Norway, Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies (IPY, iAOOS-Norway, DAMOCLES)
Institutions: Norwegian Polar Institute, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2023-08-14T15:28:42Z
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Abstract:
Radiation measurements made during the spring 2008 cruise to the Fram Strait. Transmission of light through ice, measured by divers on day 4 of fifth floe. At fourth site, approx. 20 m from ice edge, 0.42 m snow on 1.04 m ice. Each measurement type (incident, reflected, etc) was made with a different TriOS Ramses spectroradiometer. These are known to have calibration issues at the longest and shortest wavelengths for which data are reported; we recommend using only data from about 350 to 920 nm. No significant quality control has been done to these data.
Snow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. Ref: Nagler, T.; Schwaizer, G.; Mölg, N.; Keuris, L.; Hetzenecker, M.; Metsämäki, S. (2022): ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2020), version 2.0. NERC EDS Centre for Environmental Data Analysis, 23 March 2022. doi:10.5285/8847a05eeda646a29da58b42bdf2a87c. http://dx.doi.org/10.5285/8847a05eeda646a29da58b42bdf2a87c
Institutions: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
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Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Weekly Southern Ocean ice limits, have been digitized from U.S. Navy Fleet Weather Facility ice charts, at the Max-Planck Institut fur Meteorologie, Hamburg. Coverage is from 1 January 1973 to 31 June 1978. Data are gridded at 5 degree longitude intervals and are available via ftp.
<strong>Note:</strong> NOAA@NSIDC believes these data to be of value, however, they should be used with caution because we are unable to quality check the data or provide documentation due to lack of funding. If you have any information about this data set that others would find useful, please contact <a href="mailto:nsidc@nsidc.org">NSIDC User Services</a>.
This data set contains measurements of the bidirectional reflectance distribution function (BRDF) for two locations in Colorado, USA: Grand Mesa, a snow-covered, forested study site about 40 miles east of Grand Junction; and Senator Beck Basin approximately 80 miles to the SSE of Grand Mesa.
Measurements were acquired using the NASA Cloud Absorption Radiometer (CAR), an airborne multi-angular, multi-wavelength scanning radiometer. The CAR instrument measures scattered light in 14 spectral bands between 0.34 μm and 2.30 μm, which lie in the UV, visible, and near-infrared atmospheric windows.
Data were obtained for a variety of conditions including snow grain size (or age), snow liquid water content, solar zenith angle, cloud cover, and snowpack thickness. The data set can be used to assess the accuracy of satellite reflectance and albedo products in snow-covered, forested landscapes.
This data set represents a typical single iceberg capsize experiment. Included in this data set are all the parameters of the plastic iceberg's density and dimensions, the density of the water surrounding the iceberg, and the value of gravitational acceleration. The timeseries data consists of all the kinematic and energetic variables as a function of time for the iceberg capsize experiment.
This data set includes estimates of the location of the grounding zone of Antarctic ice shelves based on laser altimeter data acquired during the Ice, Cloud, and Land Elevation Satellite (ICESat) mission, October 2003 through October 2009. The estimates are based on ICESat repeat-track analysis, which can be used to detect the region of ice flexure across the grounding line, since each repeated pass is acquired at a different tidal phase. The technique provides estimates for the landward limit of flexure, the point where the ice becomes hydrostatically balanced, and the break-in-slope associated with the flexure.
Data files are available via FTP in ASCII text (.txt) format.
This data set contains data on the physical flow characteristics, mass balance, sub-glacial topography, and recent fluctuations of the Heard Island glacier. The data were collected for The Antarctic Science Advisory Committee (ASAC) project 2363, a continuation of ASAC project 1158. A full report of the data collected and the work completed are available for download with the data.
The data were collected by the Heard Island glaciology team during the 2003-04 Australian Antarctic Division expedition, as well as some data from the previous expedition in November 2000.
The data set SMEX03 Surface Roughness Data is comprised of data collected over the regional study areas of Alabama, Georgia, and Oklahoma, USA as part of the 2003 Soil Moisture Experiment (SMEX03).
The files in this data set contain landfast sea ice data (monthly means) gathered from both Russian Arctic and Antarctic Research Institute (AARI) and Canadian Ice Service (CIS) sources. Details on processing and treatment are given in the contributor's PhD thesis (Konig 2007). The data are provided in netCDF format.
The time span over which data are available is split into 3 ranges: for 1953-1967 there are only AARI data, for 1968-1990 both AARI and CIS data are available, and from 1991-1998 only CIS data are available. There are a total of six files: two for the 1953-1967 data, two for the 1968-1990 data, and two for the 1991-1998 data. There are two files for each range because the files with "_noNaN" in their names contain "-1000" as the missing value, and the other files use "nan" as the missing value. Otherwise the data in those files are identical.
AARI data were obtained from NSIDC retired data set AARI 10-Day Arctic Ocean EASE-Grid Sea Ice Observations that was later replaced by Sea Ice Charts of the Russian Arctic in Gridded Format, 1933-2006 (AARI, 2007).
Arctic and Antarctic Research Institute. 2007. Sea ice charts of the Russian Arctic in gridded format, 1933-2006. Edited and compiled by V. Smolyanitsky, V. Borodachev, A. Mahoney, F. Fetterer, and R. Barry. Boulder, Colorado USA: National Snow and Ice Data Center. https://nsidc.org/data/g02176.
Notice to Data Users: The documentation for this data set was provided solely by the contributor and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.
This data set contains 15-min snow depth observations for two study sites on Grand Mesa, CO, USA, acquired as part of NASA's 2017 SnowEx campaign. The data were recorded using two arrays of Judd Communications Ultrasonic Depth Sensors, configured as a TLS K footprint on the west side of the mesa and a TLS N footprint in the east. The sensors were positioned to represent three primary vegetation conditions: open-canopy; canopy-edge; and closed-canopy. A total of 10 and 7 sensors recorded usable data at the west and east sites, respectively, from the beginning of the snow season in November 2016 through the end in June 2017.
These data can be used for a variety of purposes, including: model forcing, calibration, and validation; evaluation of airborne and satellite remote sensing data; to analyze how vegetation affects snow accumulation and ablation.
This Near Real-Time (NRT) data set corresponds to the standard SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture (SPL2SMP) product. The data provide estimates of global land surface conditions measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product SPL2SMP (<a href="https://doi.org/10.5067/LPJ8F0TAK6E0">https://doi.org/10.5067/LPJ8F0TAK6E0</a>).
GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.
This data set reports daily, along-track winter sea ice thickness across the Arctic Ocean. Sea ice thickness is estimated using ATLAS/ICESat-2 L3A Sea Ice Freeboard (ATL10), Version 5 data and NASA Eulerian Snow On Sea Ice Model (NESOSIM) snow loading.