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.
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.
The North Slope of Alaska (NSA) atmospheric observatory at Utqiaġvik (formerly Barrow) provides data about cloud and radiative processes at high latitudes. The NSA is a focal point for atmospheric and ecological research activity in the Arctic. Scientists use data from the NSA to improve the representation of high-latitude cloud and radiation processes in earth system models.
Eureka is a node for a number of global observation programs, and the science focus is on atmosphere-surface exchanges, radiation, aerosols, and climate grade meteorological measurements.
Tiksi is a node for a number of global observation programs, and the science focus is on atmosphere-surface exchanges, radiation, aerosols, and climate grade meteorological measurements.
This MODF contains measurements from the Sodankyla supersite, located in the Arctic boreal
forest of northern Finland. This environment is characterised by alternating patches of dense
and sparse forest, wetland, lakes, and rivers, and the footprint of most satellite sensors
and model grids will typically encompass more than one of these surface types. To capture the
impact that the variation in surface type can have on surface and atmospheric processes, the
supersite comprises multiple stations and instrument installations measuring the same
parameters deployed in multiple locations.
Merged model Data Files (MMDFs) for the operational forecasts with the IFS high resolution deterministic forecasts are available for the period starting Jan 2018. MMDFs is provided at the model timestep (7.5 min) for a single model grid point closest to the observatory. In addition to the grid point data a number of parameters (including albedo, surface temperature and surface energy fluxes) are provided on the land-surface model tiles to enable detailed evaluation of processes even at heterogeneous sites. A complete description for the two versions of the IFS can be found here: https://www.ecmwf.int/en/publications/ifs-documentation.
Merged model Data Files (MMDFs) from DWD’s ICON are available from February 2018 onwards containing 7.5-day forecasts starting at 00 and 12 UTC for Sodankylä, Ny-Ålesund, and Utqiaġvik (Barrow). The mesh width is 13 km. Different model versions are used during this period. In February icon-nwp-2.1.02 was used followed by icon-2.3.0-nwp0 during 2018-02-14 to 2028-06-06, and from 2018-09-19 to 2018-12-05 icon-2.3.0-nwp2 was in operation. Since 2018-02-14, a new orographic data set came in operations, however, for the 3 data points provided the changes were less than 1 m in height.
Institutions: CNRM/ Universite de Toulouse/ Meteo-France/CNRS, CNRM/ Universite de Toulouse/ Meteo-France/CNRS, Norwegian Meteorological Institute / Arctic Data Centre
The version of ARPEGE submitted to YOPPsiteMIP was a pre-operational version based on the cy43t2_op1 operational system but coupled with the 1D sea-ice model GELATO. The resolution of the model used for these simulations is the same as is used operationally at Meteo France which is variable (using a stretching factor of 2.2) with the pole (highest resolution of 7.5 km) over France for SOP1 and SOP2 and over Antarctica in SOP-SH and 105 vertical levels. The horizontal resolution is about 8-9 km over the North-Pole and timeseries have been provided for the three SOPs in the MMDF format for the 21 YOPP observatories with an hourly output for both state variables (instantaneous) and fluxes (accumulated).
Merged model Data Files (MMDFs) were produced by the SLAV model for both SOP1 and SOP2 containing 7-day forecasts starting at 00 UTC. The output is available for 4 horizontal grid points surrounding selected observatories, every 15 minutes (i.e. every fourth timestep). Depending on variable, the output is instantaneous or a 15-min averaged value.
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, AWI Alfred Wegener Institute for Polar and Marine Research, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
Show more...
Abstract:
Data from aircraft observations during two flights of the aircraft campaign
ARTIST (Arctic Radiation and Turbulence Interaction Study) caried out by AWI
1998. The first set of delivered files contain data from on-ice flow over the
Fram Strait (26 March 1998) including profiles of radiation fluxes in stratus
clouds over a region with closed pack ice. The second set of delivered files
contain data from a day with clod-air advection over the Barents Sea covered
with sea ice. The cold-air advection causes slight unstable stratification over
sea ice. A detailed description of both data sets is given in the Damocles
Deliverable Report D2.3-01 by Lüpkes and Hartmann (2007). The case with cold-air
advectiob is described also in Vihma et al. (2005, BLM, 117(2), 275-300)
Institutions: AWI Alfred Wegener Institute for Polar and Marine Research, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
Show more...
Abstract:
The data contain observations over lead with the helicopter borne instrument
HELIPOD, carried out by AWI during the winter arctic polynya study (WARPS) 2003
in the northern Fram Strait region. Data of 8 horizontal flight legs and of the
downstream and upstream profiles are given. A more detailed data description is
given in the Damocles Deliverable report D2.2-1 by Lüpkes and Hartmann, 2006
The Hive Wireless sensor network project designed and assembled automatic weather stations that are currently installed at Kongsvegen glacier in Svalbard and records near surface meteorological variables: air temperature, relative humidity, air pressure, snow height, wind, surface skin temperature... The HiveWSN kit consists of: 1) a brain box containing the power system, the microcontroller, the communication system and the connectivity to the sensors, 2) A set of sensors either commercially available or custom built at the Department of Geosciences at UiO as part of the UiO Hive project. The kit is autonomous and packaged as a beam that can be installed on simple mast. Currently, there are two versions of the WSN system: v1 from 2019, and v2 from 2021. Both are based on the board Wasmpote v15 which handle power, communication, and data brokerage. The firmware running all instances has been written as part of the project UiO Hive, and include a set of tools described on the HiveWSN project website: https://www.mn.uio.no/geo/english/research/projects/hive. Important note: the height of the sensor to the snow/ice surface is not corrected for variations in surface deposition or melt over time. The sensor box is fixed to a stake drilled into the snow/ice.