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 using logical operators and phrases embedded in quotation marks. Logical operators include AND, OR and NOT. Remember to add space around operators. Text strings that are not quoted are trated as separate words and will match any of the words (i.e. assuming the OR operator). E.g. in order to find WMO synoptic weather station data from Verlegenhuken use the search phrase: [synop AND verlegenhuken]. Searches are case insensitive.
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.
Collections
Collections allows the user to search in subsets of the existing catalogue. The collections are primarily data management projects that have been incorporated in the ADC catalogue after the project has ended. In this context the ADC is the long term access solution for these data. The collections currently served through ADC include (datasets may belong to multiple data collections):
ADC is the full collection of this service CC is the CryoClim collection
In order to search a specific data collection select that collection. If no data collection is selected all collections are searched.
AeN are data related to the Nansen Legacy project and are better explored through the SIOS Data Access Point using the collection defined there which is available through this URL.
SIOS, InfraNOR, SIOSCD, SIOSAP, SESS_* are collections related to SIOS. These are better explored through the SIOS Data Access Portal
Some cleaning is pending between InfraNOR and SIOSIN, for some of the SESS collections.
Citation of data and service
Always remember to cite data when used!
Citation information for individual datasets is often provided in the metadata. However, not all datasets have this information embedded in the discovery metadata. On a general basis a citation of a dataset include the same components as any other citation:
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)
The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
If you use data retrieved through this portal, please acknowledge the Norwegian Meteorological Institute/Arctic Data Centre.
As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. This dataset contains the CTD, PAR and fluorescence data from Kongsfjorden 2016-2017. Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. No post-recovery processing of light data (to correct for fouling) has been performed. The observatory layout is available in the mooring diagram provided. At this deployment, two settlement plates were deployed (25m and 208m).
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 data set contains CropScan observations (solar irradiance and incidence angle) collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This data set contains geotagged images collected over Gabon, Africa. The images were taken by the NASA Digital Mapping Camera paired with the Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of a NASA campaign, in collaboration with the European Space Agency (ESA) mission AfriSAR.
This data set contains in situ Leaf Area Index (LAI) data collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This data set contains brightness temperatures obtained by in situ L-band radiometers. The data were collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This data set contains in situ measurements of soil moisture and bulk density collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, consists of surface velocity estimates for selected Greenland Ice Sheet outlet glaciers. Velocity fields were generated by tracking visible features in optical images acquired between 2016–2022 by the U.S. Geological Survey (USGS) Landsat 8 Operational Land Imager (OLI) and the European Space Agency (ESA) Copernicus Sentinel-2A and Sentinel-2B satellites.
This product contains data derived from permanent in situ soil stations and observations by the Passive Active L-band System (PALS) microwave aircraft instrument. The PALS instrument was mounted to a DC-3 aircraft, which flew six parallel flight lines at an altitude of 3000 m in order to map a 26 km x 48 km domain in Manitoba, Canada. Nine permanent soil stations were distributed throughout this same area.
The soil characteristics included in this data set are volumetric soil moisture, vertically and horizontally polarized brightness temperature, effective soil temperature, effective vegetation temperature, vegetation water content, land cover classification, sand and clay fraction, and volumetric soil moisture uncertainty estimates.
This data set contains land cover classification data collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This data set contains a time series of snow depth maps and related intermediary snow-on and snow-off DEMs for Grand Mesa, Colorado derived from very-high-resolution (VHR) satellite stereo images and lidar point cloud data. Two of the snow depth maps coincide temporally with the 2017 NASA SnowEx Grand Mesa field campaign, providing a comparison between the satellite derived snow depth and in-situ snow depth measurements. The VHR stereo images were acquired each year between 2016 and 2022 during the approximate timing of peak snow depth by the Maxar WorldView-2, WorldView-3, and CNES/Airbus Pléiades-HR 1A and 1B satellites, while lidar data was sourced from the USGS 3D Elevation Program.
This data set contains in situ measurements of crop density, height, and biomass collected for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign.
This product contains data derived from permanent in situ soil stations and observations by the Passive Active L-band System (PALS) microwave aircraft instrument. The PALS instrument was mounted to a DC-3 aircraft, which flew six parallel flight lines at an altitude of 3000 m in order to map a study area in South Fork, Iowa, United States. A total of 20 soil stations were distributed throughout this same area.
The soil characteristics included in this data set are volumetric soil moisture, vertically and horizontally polarized brightness temperature, effective soil temperature, effective vegetation temperature, vegetation water content, land cover classification, sand and clay fraction, and volumetric soil moisture uncertainty estimates.
The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation.
This NISE Version 5 product contains DMSP-F18, SSMIS-derived sea ice concentrations and snow extents derived from the Special Sensor Microwave Imager/Sounder (SSMIS) aboard the Defense Meteorological Satellite Program (DMSP) F18 satellite. For DMSP-F16, SSMIS-derived data, see <a href="https://doi.org/10.5067/JAQDJKPX0S60"> NISE Version 3</a>. For DMSP-F17, SSMIS-derived data, see <a href="https://doi.org/10.5067/VF7QO90IHZ99"> NISE Version 4</a>. For the older, DMSP-F13, Special Sensor Microwave Imager (SSMI) derived data, see <a href="https://doi.org/10.5067/4FSODMDM1WEJ">NISE Version 2</a>.