The core partner data centres that are integrated in NorDataNet are listed in https://www.nordatanet.no/en/node/69. In addition to this NorDataNet harvests information on relevant datasets from a number of other data centres. The data centre responsible for the data presented is usually (but not always) listed in the discovery metadata. In essence NorDataNet is an aggregating service that combines information from a number of existing data centres.
Citation of data and service
If you use data retrieved through this portal, please acknowledge our funding source:
Research Council of Norway, project number 245967/F50, Norwegian Scientific Data Network.
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)
All partner repositories of NorDataNet support Digital Object Identifiers (DOI), but not all datasets are minted. Whether or not minted depends often on source of the data (e.g. operational data are often yet not minted). However, all data centres support persistent identifiers according to local systems. The information required to properly cite a dataset is normally provided in the discovery metadata the datasets.
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 identified in the drop down menu with and phrases embedded in quotation marks. Prefixing a phrase with '-' negates the phrase (i.e. should not occur in the results). 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. The combination of search fields (including facets) is based on a logical "AND" combination of the fields, i.e. all conditions are fulfilled for the results provided.
Total ice and snow thickness was measured with portable electromagnetic instruments (EM31 and EM31SH, Geonics Ltd., Mississauga, Ontario, Canada) mounted on a sledge. The EM31s measure the received secondary electromagnetic field, induced by highly conductive seawater (Kovacs et al., 1991). Conductivity values are calibrated with drill hole measurements and post processed according to Haas et al., 1997. Figure 1 (https://api.npolar.no/dataset/70352512-fed8-4f1d-8b9c-30e6a764f5c2/_file/f5fa353f31a63b4d4167379acc785e73) shows the calibration curves for the two EM instruments used throughout the experiment. In total 101 and 145 calibration drillings were made for EM31SH and EM31, respectively, covering a thickness range from 0.15 m to 4.50 m ice. Analysis of the calibration measurements did not reveal any drift in the fitting curve parameters on the temporal or spatial scales.
The footprint size of the EM31 ranges from 3 m to 5 m, depending on the ice and snow thickness. Accuracy of EM31 measurements is in the range of +-0.1 m for level ice, becoming higher for rough and deformed ice.
On all four Floes, independent (i) and repeated transects (t, tF, tM) with combined EM31 and snow depth measurements were performed.
Repeated transects are considered as repetitions of marked tracks on a weekly basis to observe temporal change, while independent transects are long surveys in different directions from the main ice camp are to cover the spatial variability of the surrounding area.
Quality
Data is provided as CSV textfiles.
The filename contains date in format YYYYMMDD, thereafter unique line number, thereafter either i (independant), t (transect), tF (transect on FYI only), or tM (transect on MYI only).
Variables
- lonres: driftcorrected WGS84 longitude
- latres: driftcorrected WGS84 latitude
- thickres [m]: total thickness
- gpstimeres: time (matlab)
On the four N-ICE2015 floes we installed in total seven hot-wire fields and seven snow-stake fields following the routine outlined in Perovich [2003]. A rectangular hot-wire field with a side length of approximately 10 m was designed in a way that in each corner a wire was installed close to an ablation stake, and in the middle of the hot-wire field nine snow-stakes with even spacing were set up. Snow depth and ice thickness changes were recorded on a regular basis, and the readings were averaged in space to cover small scale spatial variability.
Data position, ice floe, instrument number (stake number) are added in the json files. Positions are taken from the ice_floe_track at noon (=12:05 UTC). The ice floe name and the stake number are indicated in the original file name. The unit of snow thickness are converted to meters.
Quality
Filename contains snowstake_floe, thereafter floe number, thereafter unique number for field
file contains 2 headerlines and 3 columns, seperator: [space]
#header1: fieldnumber #header2: [date] [thickness in cm] [standard deviation in cm]
Field1 Date cm std 23.01.2015 55.0 12.9 25.01.2015 52.7 13.6 27.01.2015 NAN NAN 01.02.2015 53.4 12.7 08.02.2015 56.1 13.6 12.02.2015 56.6 13.9 16.02.2015 66.4 20.2
On the four N-ICE2015 floes we installed in total seven hot-wire fields and seven snow-stake fields following the routine outlined in Perovich [2003]. A rectangular hot-wire field with a side length of approximately 10 m was designed in a way that in each corner a wire was installed close to an ablation stake, and in the middle of the hot-wire field nine snow-stakes with even spacing were set up. Snow depth and ice thickness changes were recorded on a regular basis, and the readings were averaged in space to cover small scale spatial variability.
Data position, ice floe, instrument number (wire number) are added in the json files. Positions are taken from the ice_floe_track at noon (=12:05 UTC). Ice floe and the wire number are indicated in the original file name. The unit of ice thickness are converted to meters (original files = cm).
Quality
variables: date, ice thickness, standard deviation