The two platforms IAOOS 23 and IAOOS 24 were deployed within 600 m from each other at the North Pole from the Russia-operated Barneo ice camp on April 12, 2017. They followed a meandering trajectory, reaching as far as 30°E in the Nansen Basin, before turning back to the western Fram Strait. On both IAOOS 23 and 24, the ocean profiler was a PROVOR SPI (from French manufacturer NKE) equipped with a Seabird SBE41 CTD (Conductivity, Temperature, Depth) and a dissolved oxygen (DO) Aandera 4330 optode. For the first time, the profiler on IAOOS 23 also carried biogeochemical sensors. It featured a bio-optics sensor suite and a submersible ultraviolet nitrate analyzer (SUNA, Satlantic-Seabird Inc.). The bio-optics sensor suite (called Pack Rem A) combines a three-optical-sensor instrument (ECO Triplet, WET Labs Inc.) and a multispectral radiometer (OCR-504, Satlantic Inc.). The present dataset is composed of CTD-DO data from IAOOS 23 and 24, corrected from the thermal lag and the sensor lag, despiked and interpolated vertically every 0.5 m. It also comprises nitrate concentrations from the SUNA and CDOM fluorescence from the WETLabs ECO sensor on IAOOS 23. Other biogeochemical data will be added to this dataset. The profilers were set to perform two upward profiles a day from 250 m (IAOOS 23) and 350 m (IAOOS 24) upward starting at approximately 6 am and 6 pm. They provided a unique 8-month long dataset, gathering a total of 793 profiles of the temperature, salinity and oxygen (upper 350m) and 427 profiles of CDOM and nitrates concentrations (upper 250m).   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.

Two ice mass balance instruments (part of IAOOS7 and IAOOS8 platforms) deployed near 83°N on the same ice floe, documented the evolution of snow and ice conditions in the Arctic Ocean north of Svalbard in Jan-Mar 2015. Frequent profiles of temperature (every 3 hours) and temperature change after 30s and 120s heating (once a day) were recorded. The ratio of the temperature changes after heating provides a proxy for thermal diffusivity. Both instruments documented flooding and snow-ice formation. Flooding was clearly detectable in the simultaneous changes in thermal diffusivity proxy, increased temperature, and heat propagation through the underlying ice. Slush then progressively transformed into snow-ice. Flooding resulted from two different processes; i) after storm-induced break-up of snow-loaded floes for IAOOS8 and ii) after loss of buoyancy due to basal ice melt for IAOOS7. The instrument on IAOOS7 documented basal sea-ice melt over warm Atlantic waters and ocean-to-ice heat flux peaked at up to 400 Wm-2 in winter. 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.

Surface Ocean CO2 Atlas (SOCAT)

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.

The mooring was deployed on 15 September 2017 from Norwegian Research Vessel Lance at 80.6°N and 7.26°E (depth of 730 m) in the Yermak Pass over the Yermak Plateau north of Svalbard. It comprised 3 instruments: an upward-looking RDI 75kHz, a Long Ranger Acoustic Doppler Current Profiler (ADCP) at 340 m with 16 m vertical resolution (25 bins of 16 m each) and a 2-hour sampling time; a Seabird SBE37 measuring temperature, salinity and pressure at 348 m with 10-minute sampling time; and an Aquadopp current meter at 645 m with a 2-hour sampling time. The mooring was retrieved on the 19 July 2020 by Norwegian Icebreaker K.V. Svalbard. The present dataset features: The ADCP 50-hour high pass filtered velocities and  the Aquadopp 50-hour high pass filtered velocities. 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.

The provided microplastic dataset was generated during The Ocean Race Europe in May-June 2021. The samples were collected onboard two 65’ one-design yachts known as VolvoOcean65, called AmberSail2 and AkzoNobel Ocean Racing in the Baltic Sea, North Atlantic Ocean and Mediterranean Sea. The instruments used for underway measurements were the same as used in Tanuha et al., 2020. The system consists of a specially built OceanPack RACE manufactured by SubCtech GmbH in Kiel, which was connected to a microplastic filtration unit built by bbe Moldaenke GmbH. (Data submission https://www.emodnet-ingestion.eu/submissions/submissions_details.php?menu=39&tpd=232&step=0103_001volvo%20ocean%20race). The mixed-layer surface water (~1.5 m depending on the heel of the yachts) was sampled in the Baltic Sea, North Atlantic Ocean and Mediterranean Sea. The laboratory analysis of collected samples was undertaken by GEOMAR (Kiel), under the supervision of Aaron Beck and Toste Tanuha. The data variables includes GPS positions, time, temperature, salinity, flow rates and durations, sample ID, measured microplastic fiber, fragments and total concentration in [particles/m³]. Respetive concentrations of fiber and fragments are also provided for different colors: blue,red, orange, pink, yellow, green, black, clear, purple, grey, brown. Acknowledgements go to 11th Hour, teams AmberSail2 (Tomas Ivanauskas,Regimantas Buozius) and AkzoNobel (Liz Wardley), TheOcean Race Sustainability and Science programmes, bbe Moldaenke GmbH and SubCtech GmbH.

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.

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.

Global phytoplankton production monthly maps for 2017 are produced using an artificial neural network to perform a generalized nonlinear regression of PP on several predictive variables, including latitude, longitude, day length, MLD, SST, PBopt computed according to Behrenfeld and Falkowski (1997), PAR and CHL(0 m). More details about this model can be found in Scardi (2001). Behrenfeld, M. J., Falkowski, P. G. (1997), Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology & Oceanography, 42(1), 1–20. Scardi, M. (2001), Advances in neural network modeling of phytoplankton primary production, Ecological Modelling, 146, 33–45.

Profiles collected during the cruise GLICE on RV Sanna (August 2022) in Disko Bay