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.
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: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T13:56:05Z
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Abstract:
The climate in Svalbard has been warming dramatically compared with the global average for the last few decades. Seasonal snow cover, which is sensitive to temperature and precipitation changes, is therefore expected to undergo both spatial and temporal changes in response to the changing climate in Svalbard. This dataset contains a daily snow cover fraction maps for the Svalbard archipelago, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra data.
The dataset contains 2 archives. The first archive contains all data (saved as netCDF files) relative to the Figures presented in Boutin et al. (2023). The second archive contains monthly averaged fields (saved as netCDF files) of the simulation described in Boutin et al. (2023). They include quantities relative to sea ice properties (icemod files) and to the mass balance (ice growth/melt etc... simba files). They cover the north Atlantic and the Arctic Ocean (north of Bering Strait) for the period 2000-2018.
icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018.Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment).transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport.In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.
Svalbard rock ptarmigan spring breeding habitat suitability raster map from Pedersen et al. (2017). The habitat suitability map was developed using 11 years (2000–2010) of presence/absence data of territorial males from monitoring, a multi-scale generalized linear modelling framework (glms), and digital satellite-based vegetation mapping. The final habitat model contained four significant predictors related to vegetation, terrain (elevation and slope) and heat load index. High values indicate better breeding habitat suitability. Spatial resolution of the map is 100 x 100 m. Provided in UTM 33N / WGS84 (CRS: 32633). See Pedersen et al. (2017) for more information.
Pedersen, Å.Ø., Fuglei, E., Hörnell-Willebrand, M., Biuw, M. and Jepsen, J.U. (2017), Spatial distribution of Svalbard rock ptarmigan based on a predictive multi-scale habitat model. Wildlife Biology, 2017: 1-11 wlb.00239. https://doi.org/10.2981/wlb.00239
European project for ice coring in antarctica (EPICA)
Last metadata update: 2021-08-03T11:44:28Z
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Abstract:
The dataset contains stake positions and exposed stake heights along the EPICA Traverse route from Troll Station to “Site M” at 75 deg. S, 15 deg. E.
During the EPICA traverse in 1996-1997 along the same route in 1996-1997 a series of stakes were set out along the traverse line and precisely positioned by GPS. The stakes were re-measured during the next EPICA traverse four years later, during the 2000-2001 season. The stakes were positioned at 60 km intervals up to Site M, the drill site for a 150 metre ice core. “Strain nets” and “coffee cans” were included at two, respectively three sites. Most of the stakes were re-measured a third time during the IPY Traverse in 2007-2008.
Quality
This dataset contains the data from the 2000-2001 season:
- Raw data from the GPS receivers, in folders named by date
- Data report with precise, calculated positions and heights for all stakes (in Norwegian)
- Traverse map
- Field log (in Norwegian)
- Excerpt from the NARE field report (pp. 24-26)
- Equipment list (in Norwegian)
Satellite albedo data from MODIS is used to track snow-line on glaciers in Svalbard, with snow-line serving as a proxy for the Equilibrium Line Altitude (ELA). Eventually the results will be available as shapefiles.
A table with snow lines derived with this method is available and snow line can be plotted against time
Method: albedo data and snow line tracking. Sensors: MODIS.
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it.There are two types of data available: (data1: geometrically corrected data) and (data2: raw image data).
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it.There are two types of data available: (data1: geometrically corrected data) and (data2: raw image data).
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it.There are two types of data available: (data1: geometrically corrected data) and (data2: raw image data).
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it.There are two types of data available: (data1: geometrically corrected data) and (data2: raw image data).
Orthophoto Image is an image that color aerial photograph is converted to orthophoto and mosaic effects are added to it. Geometrically corrected data is available