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.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
The file contains time series of meteorological near-surface parameters measured on a temporary meteorological mast on the southern side of the coast of Adventdalen, Svalbard, from July to August 2022: Both temperature, humidity, wind speed, wind direction were measured at two levels.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, University of Bergen, University of Bergen, The University Centre in Svalbard, Norwegian Meteorological Institute / Arctic Data Centre
A scanning Doppler Lidar was placed in Adventdalen (Central Spitsbergen, Svalbard, Norway) close to the permanent weather mast SN99870. The Lidar measured between 4 July and 23 August 2022 with different scanning patterns in an hourly cycle. The cycle consisted of three Plan Position Indicator (PPI) scans at 1, 5 and 10 degree from xx:00 to xx:10, Range Height Indicator (RHI) scans alternating between up-valley and down-valley direction from xx:10 to xx:50, Doppler-Beam-Swinging (DBS) technique from xx:50 to xy:00. The radial resolution was 10 m with overlapping range gates of 50 m. Short periods of power cuts were encountered. Frequently there were conditions with little backscatter and low carrier-to-noise ratio, especially in light down-valley winds.
Institutions: The University Centre in Svalbard, The University Centre in Svalbard, Norwegian Meteorological Institute, Norwegian Meteorological Institute / Arctic Data Centre (NO/MET/ADC)
The Isfjorden Weather Information Network provides standard meteorological near-surface measurements from the Isfjorden region in Svalbard. The network includes weather stations permanently installed on lighthouses around the fjord and onboard small tourist cruise ships trafficking the fjord from the spring to the autumn. Data is available since August 2021 and new observations become available here in near real-time.
Institutions: Norwegian Meteorological Institute / Arctic Data Centre, SU Stockholm University, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T12:45:37Z
Show more...
Abstract:
Arctic Ocean Experiment 2001 AOE-2001 was an icebreaker based field experiment
with a target on the formation of low clouds in the central Arctic summer during
July and August 2001. A main portion of the 2-moth experiment was a 3-week ice
drift from 89 to 88 degN. Main components of the meteorology part of the
experiment were surface-based remote- sensing observations, general meteorology
observations (weather staion and soundings) and boundary-layer observations on
the ice. For a complete review of the experiment and a full list of instruments,
see Tjernström et al. 2004 ("The summertime Arctic atmosphere: Meteorological
measurements during the Arctic Ocean Experiment (AOE-2001)" in Bulletin of the
American Meteorological Society, 85, 1305 - 1321, and its on-line supplement
"Experimental equipment: A supplement to The summertime Arctic atmosphere:
Meteorological measurements during the Arctic Ocean Experiment (AOE-2001)").
Observations included in the dataset:
Observations from 2D-wind sonic anemometer on the mast of Oden during AOE-2001. Beware of flow distortion from the ship.
One-hour averaged cloud base observations from cloud base lidar and cloud radar during AOE-2001
Instant cloud-top observations from S-band cloud radar operating in two modes, a low-range high-resolution and a high-range low-resolution mode, respectively, obtained during AOE-2001. The presented data is the highest cloud top altitude observed.
Various meteorological observations from a mast placed on an ice-floe during AOE-2001
Turbulence statistics from sonic anemometer at 15 meters on the mast averaged over 15 minute obtained during AOE-2001
Turbulence statistics from sonic anemometer at 5 meters on the mast averaged over 15 minute obtained during AOE-2001
Various meteorological observations from Odens weather station situated at 35 metres ASL during AOE-2001. Winds may be subject to considerable flow distortion. Precipitation is in arbitrary units.
One-hour averaged precipitation from present-weather-sensor, which measures no. of precip particles falling past the sensor, during AOE-2001
Wind profile data from 915 MHz profiler on foredeck of Oden obtained during AOE-2001
Atmospheric baloon sounding data obtained during AOE-2001. The observations are interpolated to a fixed grid for plotting purposes.
Measurements from the high range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Measurements from the low range of the S-band cloud radar obtained during AOE-2001. The variables presented are radar reflectivity and hydro-meteor fall velocity.
Temperature profiles measured by a scanning radiometer obtained during AOE-2001.
Measurements from the sodar obtained during AOE-2001. Note that the altitude for each record varies in time.
Observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 2 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
Observations 5 metres AGL from mobile ISSF PAM station 3 during AOE-2001.
Turbulence observations 5 metres AGL from mobile ISSF PAM station 1 during AOE-2001.
One-hour averaged visibility observations from back-scatter sensor during AOE-2001.
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: NORCE Tromsø, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-12-05T13:18:30Z
Show more...
Abstract:
Sentinel-1 Wet snow product: The warming climate on Svalbard impacts the amounts of wet snow significantly. Sentinel-1 is sensitive to wet snow as compared with dry snow or bare soil, and the current dataset provides up to daily maps over Svalbard of the spatial distribution of wet snow. The maps are derived from three SAR instriments (Envisat ASAR 2004-2012, Radarsat-2 2012-2014, and Sentinel-1 A/B from 2014-2020). Grid cells are classified with codes where 20=water, 30=nodata, 100=bare ground, 200=dry snow, 205=wetsnow
Institutions: Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-11-15T13:56:05Z
Show more...
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.
Time series from March 19th 2012 of solar radiation and photosynthetic active radiation (PAR)
from data loggers located at the roof of the University Centre in Svalbard (UNIS) in Longyearbyen, Norway. Location 78o13’21’’N/15o39’9’’E,
20 m above sea level. Measurements were recorded every 10 minutes
Institutions: NILU, Norwegian Meteorological Institute / Arctic Data Centre
Last metadata update: 2022-08-16T12:14:40Z
Show more...
Abstract:
Remote-sensing observations performed using the Differential Optical Absorption Spectroscopy (DOAS) technique to quantify the abundance of NO2. The dataset ranges from 2020-03-13T09:22:02 to 2021-10-02T13:57:40, and contains the variables altitude_instrument, angle_solar_azimuth, angle_solar_zenith_astronomical, latitude, longitude, no2_column_absorption_solar, no2_column_absorption_solar_amf, no2_column_absorption_solar_flag, no2_column_absorption_solar_uncertainty_combined_standard, no2_column_absorption_solar_uncertainty_mixed_standard, no2_column_absorption_solar_uncertainty_random_standard, no2_column_absorption_solar_uncertainty_systematic_standard, temperature_effective_no2, temperature_effective_no2_uncertainty_combined_standard, temperature_effective_no2_uncertainty_mixed_standard, temperature_effective_no2_uncertainty_random_standard and temperature_effective_no2_uncertainty_systematic_standard. The datset is provided by Ann Mari Fjaeraa,NILU.
Near-surface remote sensing techniques including hyperspectral sensors are essential monitoring tools to provide spatial and temporal resolution. More frequent and finer scale observations help to monitor specific plant communities and accurately time the phenological stages of vegetation and snow cover, A Hyperspectral field sensor (FloX) was installed as an integral part of an automatic system for monitoring vegetation and environmental seasonal changes (phenology) on Svalbard (AsMoVEn) funded by SIOS. The fluorescence box (FloX) is a unique instrument, enabling continuous observation of sun-induced chlorophyll fluorescence (SIF). FLoX measures spectral data of extremely high resolution, The FloX is specifically designed to passively measure chlorophyll fluorescence under natural light conditions. The core of the system is the QEPro spectrometer from Ocean Optics covering the Red/Near Infrared region (650 – 800 nm) with a spectral resolution (FWHM) of 0.3 nm. This is the spectral range where chlorophyll fluorescence is emitted and where the two atmospheric oxygen absorption bands (O2B and O2A, at 689 nm and 760 nm respectively) are used to measure it. The FLoX has an additional spectrometer measuring in visible and NIR-region (400– 950 nm) with a spectral resolution (FWHM) of 1.5 nm allowing extraction of different vegetation indices from the visible and near-infrared region.
Meteorological data from 10m weather mast during the N-ICE2015 expedition: wind speed, wind direction, air temperature, air pressure, and relative humidity. Please read the Readme files for detailed information on processing and quality control.
The data has been collected during the Nansen Legacy Joint Cruise 3, 19th February – 11th March 2022 on the research vessel RV Kronprins Haakon (cruise number 2022702), along a transect from 76N to 82N east of Svalbard. The dataset contains mesozooplankton occurrence. It has been sampled using a BongoNet, HydroBios 60 cm. Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton with a mesh-size 180 µm. All specimens are identified to the lowest taxonomical level and the occurrence is given for a specific species and stage or size group as ind/m3.
Sampling method:
The sampling covers a transect from 76 N to 82 N in the northern Barents Sea and Arctic Ocean. Zooplankton has been collected using a BongoNet 60 cm (HydroBios, opening: 0.2827 m2, net length: 250 cm). Small mesozooplankton were collected with a mesh-size 64 µm and large mesozooplankton with a mesh-size 180 µm. All samples were added 4 % formaldehyde free from acid.
PLEASE NOTE: THIS DATASET CONTAINS TWO COMPLETE DATASETS OF ZOOPLANKTON: ONE FOR SMALL MESOZOOPLANKTON (APPROX BODY SIZE BELOW 2 MM) COLLECTED WITH MULTINET 64 µM AND ONE FOR LARGE MESOZOOPLANKTON (APPROX BODY SIZE ABOVE 2 MM) COLLECTED WITH MULTINET 180 µM MESH SIZE. THE INFO ABOUT WHICH NET IS USED CAN BE FOUND IN gearType, USE EITHER 64 UM OR 180 UM DEPENDING ON WHETHER THE FOCUS IS SMALL OR LARGE MESOZOOPLANKTON
Analyse method:
All samples have been analysed at Institute of Oceanology of the Polish Academy of Sciences (IOPAN). The organisms were identified and counted under a stereomicroscope equipped with an ocular micrometer, according to standard procedures (Harris et al. 2000). Small-sized zooplankters (most of Copepoda, juvenile stages of Pteropoda, Euphausiacea, Ostracoda, Amphipoda and Chaetognatha) were identified and counted in sub-samples obtained from the fixed sample volume by automatic pipette (approximately 500 individuals). Large zooplankters (big Copepoda, Pteropoda, Euphausiacea, Ostracoda, Amphipoda, Decapoda, Appendicularia, Chaetognatha, and Pisces larvae) were sorted out and identified from the whole sample. Representatives of Calanus spp. were identified at the species level based on morphology and prosome lengths of individual copepodid stages (Kwasniewski et al. 2003).
Data structure:
The data is following Darwin Core nomenclature as far as possible but also include variables that aren’t supported by Darwin Core. All information about the sampling such as eventDate, latitude, longitude, depts etc is located in event file while the result such as scientificName, lifeStage, occurrence etc. are found in the occurrence file
Header name index - events
- expedition: cruise number for R/V Kronprins Haakon
- eventID: UUID for the sampel
- parentID: UUID for the gear deployment (each MultiNet deployment has a unique parentID)
- eventDate: the date-time when an event occurred, using ISO 8601-1:2019 format (2020-07-27T07:16:03.446Z).
- fieldNumber: human-readable sample ID (e.g. ZOT-001)
- locationID: station name
- decimalLongitude: geographic latitude (in decimal degrees, using the spatial reference system given in geodetic datum)
- decimalLatitude: geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum)
- bottomDepthInMeters: bottom depth in meters
- eventRemarks: comments or remarks about the event (free text field)
- gearType: the gear used to take the sample e.g. MultiNet 200 µm
- maximumDepthInMeters: bottom depth of the sampled layer
- minimumDepthInMeters: top depth of the sampled layer
- sampleType: description of the sample type according to a standard list
- fieldSplit: info about whether the sample is splitted. If the sample was split in 2 then fieldSplit = 2
- initialSampleVolume: The volume of water filtered through the plankton net. (initialSampleVolume = (netOpeningArea * (maximumDepthInMeters – minimumDepthInMeters)/field Split), Bongonet opening area: 3.14*(0.3)^2=0.2826 m2
- recordedBy: name of the person who took the samples
- principalInvestigatorName: name of the person in charge of the sample collection
- principalInvestigatorEmail: email address of the person in charge of the sample collection
- principalInvestigatorInstitution: affiliated institution of the person in charge of the sample collection
Header name index - occurrence
- analysedFraction: fraction of the sampled volume that is examined for organism counted
- individualCount: the number of individuals present in the analysed volume (see extra information below)
- phylum, class, order, family, genus & taxonKey-LSID: Taxonomical information for given species according to Worms
- scientificName: full scientific name of the identified organism at the lowest taxonomic level that can be ascertained. The scientificName should be selected from a drop-down menu linked to the list in taxonomy sheet. (e.g Calanus finmarchicus).
- identificationQualifier: A standard term (sp., spp., and indet.) to express the determiner’s doubts about the Identification.
- lifeStage: the age class, life stage, or life form/morph of the organism.
- sizeGroupOperator: describes if the size group is less than or greater than a value (It = less than, gte = greater or equal to)
- sizeGroup: the size group in mm.
- organismRemark: indicates whether it is mesozooplankton, macrozooplankton, rare species
- identificationRemarks: a free text field for adding information relevant to the analysis. Used to indicate the speciemen that were dead. When nothing was remarked they were alive.
- identifiedBy: person who did the lab-analyse
- sampleSizeValue: the sample volume used to calculate the organismQuantity (sampleSizeValue 0 initialSampleVolume *analysedFraction)
- sampleSizeUnit: m3
- organismQuantity: the quantity of the organism per volume water in the environment (organismQuantity = individualCount/sampleSizeValue)
- organismQuantityType: ind/m3
Additional information for some of the fields
individualCount: The number of (all) organisms found in the sample examined
- for “mesozooplankton”, the number of mesozooplankton (medium size zooplankton organisms) encountered in all sub-samples
- for “macrozooplankton”, the number of macrozooplankton (large size zooplankton organisms, total length > 5 mm) encountered, identified in the entire sample
- for “rare” zooplankton, we only enter information about the finding of “rare” zooplankton in the database template, and its absolute number (“organismQuantity”) is not estimated
Funding:
The Nansen Legacy is funded by the Research Council of Norway and the Norwegian Ministry of Education and Research. They provide 50% of the budget while the participating institutions contribute 50% in-kind. The total budget for the Nansen Legacy project is 740 mill. NOK.
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.