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 SAON Data Portal.
Brief user guide
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 through the drop down menu above the text field. Text strings that are not quoted are treated as separate words and will match any of the words (i.e. assuming the OR operator). Phrases may be prefixed with '-' to indicate no occurence of the phrase 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.
NDVI, GCC, soil and surface temperature, and soil water content data from Adventdalen, Svalbard. This data was collected with a time-lapse RGB camera and NDVI sensor installed on a two meter high metal rack to monitor tundra vegetation. The time-lapse photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. A mask was used to calculate Green Chromatic Channel (GCC) from the photos. The NDVI data was quality controlled by removing outliers that were two standard deviations removed from the mean value of the growing season, and by removing dates where there was snow on the ground (as indicated by the time-lapse photos). In addition, soil and surface temperature and soil moisture were measured to facilitate the interpretation of shifts in the vegetation indices.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance and runoff in Franz Josef Land and Novaya Zemlya from 1991-2022, situated in one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2022). Each variable is available at both a daily and monthly resolution.
This collection contains a high-resolution (2.5 km) dataset of glacier mass balance, runoff and snow conditions in Svalbard from 1991-2022, one of the fastest warming regions in the Arctic. The dataset is created using a full energy balance model (the CryoGrid community model) forced by both the Copernicus Arctic Regional ReAnalysis (CARRA) dataset (1991-2021) and AROME-ARCTIC forecasts (2016-2022). Each variable is available at both a daily and monthly resolution.
The Nansen Legacy cruise Q1 was part of the seasonal investigation of the northern Barents Sea and adjacent Arctic Basin. The cruise was conducted in 2-24 March 2021 onboard R/V Kronprins Haakon, and focused on studying the physical, chemical and biological conditions along the Nansen Legacy main transect in open waters and within the sea ice. While in sea ice we conducted ten regional scale sea ice helicopter-borne surveys of ice conditions along the Nansen Legacy transect using a helicopter-borne electromagnetic instrument (HEM) EM-bird. This dataset presents processed EM-bird data on total snow and sea-ice thickness along the flight tracks.
This is a contribution to the Research Council of Norway project “Nansen Legacy” (https://arvenetternansen.com/), WP RF-1 “Physical drivers”.
Quality
See the attached docuement “AeN_Q1_202103_HEM_icethickness_metadata_v1.0.pdf” for details on the data acqusition, processing and structure.
Digital geological map of Svalbard at the scale of 1:750000.
Subdivision of geology is according to stratigraphic group, subgroup or formation, depending on which is best applicable to the given scale. Where no formations are defined in parts of the geological basement, lithological units are defined instead
Quality
Spatial Reference: WGS84/UTM zone 33N (EPSG: 32633)
Upwelling and downwelling longwave and shortwave radiation and shortwave albedo from station deployed out on the ice floe, nearby surface meteorology observations.
WP2
Quality
Albedo data is on a different time step and is a heavily processed version of a subset of the the radiation data, see attributes in the NetCDF files and the READMEs:
Dataset of annual mass balances of Svenbreen, a small valley glacier in Central Spitsbergen, 2010/2011 - 2017/2018
To date (31st Jan 2020), the data have not been published in an article in a peer-reviewed journal, which is planned for 2021 or 2022, following the completion of ten years of measurements. It is possible that the exact values might differ slightly between this dataset and the planned paper due to differences in methodology, eg. updated glacier hypsometries. If this dataset is of your interest, please check Jakub Malecki’s publication record for the most up-to-date data..
Quality
Annual mass balance of Svenbreen has been measured with a glaciological method since 2010/2011, typically between 1st and 15th day of September every year. Ablation stake network comprises 12-16 stakes distributed along the glacier tongue and in two (out of three) high-elevation sections, i.e. in the cirque and along an ice patch leading towards neighbouring glacier Hoelbreen.
Kartdata tilpasset målestokksområdet 1:100 000 til 1:300 000 for landarealet av Svalbard. Kartdataene er en generalisering av S100 Kartdata.
Map data adapted for the scale range 1:100 000 to 1:300 000 for the land area of Svalbard. The map data is a generalization of S100 Kartdata.
Quality
Deler av kartgrunnlaget er av eldre dato og ikke egnet for navigasjon. Dataene er generalisert fra S100 Kartdata. —– Parts of the map data are of older dates and not suited for navigation. The data are generalized from S100 Kartdata.
This dataset contains annually averaged ice surface velocity and thickness for all 202 tidewater glacier fronts on Svalbard, dating from 2012 to 2021. This is combined with mapping of front position changes to derive annual ice mass rates for retreat/advance, ice flux (discharge) and total frontal ablation.
The dataset is planned to be updated with new results every autumn.
Quality
Ice thickness was calculated with the help of surface (annual mosaics of ArcticDEM strip data) and bedrock DEMs (SVIFT v1.0 from Fürst et al., 2018; NPI DEM, and available bathymetry data from the Norwegian Mapping Authority). Velocity data were obtained from 3 datasets: Landsat-8 velocities from the ITS-Live product (2013 to 2018), and Sentinel-1 velocities derived by Adrian Luckman (2015 to 2020) and by Friedl et al. (2021) (2015 to 2021).Mean velocities values were calculated for each glacier when different datasets were available for similar years. Mass rates for retreat/advance were derived from front position changes manually digitized based on available satellite or aerial imagery, mainly acquired by Sentinel-2 or Landsat-8 during the period 15 Aug. to 15 Sept. each year and from ice thickness data. Ice flux (discharge) was derived from annual velocity data and ice thickness data. Frontal ablation was calculated as the combination of the ice mass rate and the discharge of ice.
Dataset of net, winter and summer mass balances of Austre Gronfjordbreen, a valley glacier in western part of Nordenskiold land. Following dataset covers the period of 2012/2013 - 2018/2019. The data is planned to be published in a peer-reviewed journal in 2020. The dates of field surveys, the number of stakes and methods of winter measurements are also attached.