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Oceans

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    As part of the STeP project (STorfjorden Polynya multidisciplinary study), two moorings, M1 and M2, were deployed in Storfjorden (Svalbard) on July 14, 2016 from the French R/V L’Atalante and were recovered one year later, on September 28, 2017, from the French R/V Pourquoi-Pas?. The two moorings, deployed a few hundred meters apart at 78°N and 20°E at a depth of 100m, documented the formation of dense Brine-enriched Shelf Water (BSW).  The moorings included both physical oceanography (PO) and biogeochemistry sensors. The present dataset is composed of PO data only: the 3 components of the currents, backscatter, salinity, temperature and dissolved oxygen. PO sensors on M1, spanning the whole water column, included 6 Seabird SBE37 microcat (CTD),  15 RBR solo (T), and 1 RBR duet (TD) for hydrography, while currents were monitored with a RDI WH 300kHz upward looking ADCP and 1 Nortek Aquadopp underneath. PO sensors on the shorter M2 mooring included 1 Seabird SBE63 (CTD-O2), 1 RBR solo (T) and 1 RBR duo (TD). Data have been calibrated and validated and the different steps of this processing are discussed in the technical report provided with the dataset. Two netcdf4 files are provided for M1: one for hydrography (STEP2016_M1_hydrography.nc), the other one (STEP2016_M1_current.nc)  for currents and backscatter. Only one netcdf4 files (STEP2016_M2_hydrography.nc) is provided for the shorter M2. Temperature and salinity data from SBE sensors have been interpolated on a common time grid with a 20’ time step. Likewise temperature data from RBR are provided on a 30” time grid. A merged SBE-RBR dataset has also been built for increased vertical resolution, providing temperature every 20’. ADCP data are provided on a 100’ time grid. The user is referred to the technical report provided with the dataset for further information on the different fields. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

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    In the Northwest Atlantic, Pandalus borealis (northern shrimp) serve as key mid-trophic consumers and prey for higher-trophic predators, including commercially important fish species. However, the impact of changing environmental conditions on trophic interactions and lipid storage in sub-Arctic ecosystems is not well understood. We employed biochemical tracers (fatty acids and stable isotopes) to investigate the trophic ecology and stage-specific nutritional condition of P. borealis across spatial and seasonal scales. A total of 68 different fatty acids (FAs) were identified in P. borealis tissues (i.e., muscle and eggs). The relative abundances of these FAs varied among sex, tissues, seasons, and fishing areas. Results revealed that P. borealis primarily fed on diatoms and zooplankton, with opportunistic feeding on sinking phytodetritus. Lipid composition showed strong seasonality, with storage triacylglycerols being the predominant lipid class. Ovigerous females exhibited the highest lipid concentrations and essential fatty acids, emphasizing the ecological importance of eggs as high-quality lipid sources. Additionally, total lipid content in eggs increased from spring to summer, highlighting vulnerability to shifts in seasonal primary production. This study underscores the significant seasonal variability in the nutritional status of P. borealis and the need to understand lipid dynamics to assess population resilience to environmental changes. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

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    Meteorological data of the R/V "Mikhail Somov" in the Arctic. This dataset is included the following meteorological parameters:Wind Speed,Wind Direction,Visibility,Total Clouds Cover,Air Temperature,Sea Level Pressure,Pressure Tendency,Amount of Pressure Tendency,Present Weather,Height of Wind Waves.

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    This dataset is included the following meteorological parameters: wind speed, wind direction, visibility, total clouds cover, air temperature, sea level pressure, pressure tendency, amount of pressure tendency, present weather(code), sea surface temperature, height of wind waves and etc. Ship Callsign:"UANA". Research vessel:"Fridtjof Nansen".

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    Gridded fields of salinity for 50 N - 67 N, 41,5 W - 61,5 W geographic region (yearly, 2000 - 2016), 29 standard depths

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    We defined the interfaces between the air/snow, snow/ice, and ice/ocean and calculated the ocean heat flux for two SIMBA recordings (SIMBA2015a and SIMBA_2015f) of repeated temperature profiles at 6h interval and 2cm vertical resolution, during N-ICE 2015 experiment floe1. The snow/ice interface is derived from the sharp contrast in the diffusivity proxy values between both media. The snow/ice interface does not change except for slush formation associated with flooding events. The air/snow interface is calculated using simultaneous information from the vertical gradient of the temperature and the standard deviation over 24, 48, and 72 h period. Snow accumulation of more than 10 centimeters happened at different time for the 2 SIMBA. The ice/ocean interface is estimated from temperature profiles alone since the winter sea-ice remains colder than the ocean. The ocean just below the ice is at or just above the freezing temperature (estimated from a near surface conductivity-temperature-depth (CTD) sensor see Koenig et al. [2016]). The method detects (1) the first sensor, downward of the snow/ice interface, with a temperature above the ocean freezing temperature and (2) the last sensor in the ice with a temperature below the mean ocean temperature by at least twice the ocean temperature standard deviation in that profile. The ice/ocean interface is then defined as half way between the last sensor in the ice and the first sensor in the ocean. Note it take 3-4 days for the deployment hole to refreeze. Then the ice thickness remains constant up to 20 February when floe1 breaks. Simba_2015f stops working and SIMBA_2015a features basal melt events corresponding to temperature changes in the ocean. The consistency of the 3 interfaces estimate is validated with the thermal diffusivity proxy and the vertical and temporal derivatives of temperature. The ocean heat flux is derived from the latent heat flux which is directly proportional to the change in time of the ice/ocean interface depth and the conductive heat flux in the lower portion of the ice estimated 6 cm above the ice/ocean interface. The ocean heat flux values for SIMBA_2015a and SIMBA2015f range from -50 to 350 W/m2, and -50 to 150 W/m2 respectively, while the basal melt events associated with ocean temperature increase stand out in SIMBA_2015a.   The SIMBA data are available through the Norwegian Polar Institute’s data center (https://data.npolar.no/dataset/6ed9a8ca-95b0-43be-bedf-8176bf56da80) and the method of interface detection is thoroughly described in Provost et al. (2017). Note that all time series have been smoothed with a 36-h running mean.   Provost, C., N. Sennechael, J. Miguet, P. Itkin, A. Rosel, Z. Koenig, N. Villacieros-Robineau, and M. A. Granskog (2017), Observations of flooding and snow-ice formation in a thinner Arctic sea-ice regime during the N-ICE2015 campaign: Influence of basal ice melt and storms, J. Geophys. Res. Oceans, 122, 7115–7134, doi:10.1002/2016JC012011. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

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    Basic biogeochemical parameters obtained from the GLICE cruise in Disko Bay (August 2022), either analyzed at sea or preserved and returned to GEOMAR for analysis.

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    Surface Ocean CO2 Atlas (SOCAT)

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    Datawell Waverider data collected at southern part of full-scale wave test site at EMEC (Orkney, UK), in year 2017. Data was processed using Datawell W@ves21 software, no QC had been applied. Location: Billia Croo; Resolution of data: 1.28 Hz; Sample period (s): 1800; Number of data records: 17520; Pings (readings) per Ens: 2304; Mode: Integrated parameters. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

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    The Green Edge project was designed to investigate the onset, life and fate of a phytoplankton spring bloom (PSB) in the Arctic Ocean. The lengthening of the ice-free period and the warming of seawater, amongst other factors, have induced major changes in arctic ocean biology over the last decades. Because the PSB is at the base of the Arctic Ocean food chain, it is crucial to understand how changes in the arctic environment will affect it. Green Edge was a large multidisciplinary collaborative project bringing researchers and technicians from 28 different institutions in seven countries, together aiming at understanding these changes and their impacts on the future. The fieldwork for the Green Edge project took place over two years (2015 and 2016) and was carried out from both an ice camp and a research vessel in the Baffin Bay, Canadian arctic. Here, we describe the data set obtained during the research cruise, which took place aboard the Canadian Coast Guard Ship (CCGS) Amundsen in spring 2016. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.