In September 2009, a ship-based study was carried out in the Davis Strait/southern Baffin Bay along a range of transects covering the area between the west coast of Greenland and Baffin Island (Canada) from 68-72º N . Water temperature, salinity and in situ chlorophyll a (chl. a) measured in 0-500 m depths followed the general hydrographical characteristics of the late summer situation. Surface chl. a concentration based on remote sensing satellite data from September 2009 supported these findings. Measurement of in situ chl. a concentrations revealed a maximum in the subsurface (30-50 m water depths). Thus, spatial distribution of the phytoplankton bloom was often restricted to subsurface rather than the surface waters and therefore not detected by the remote sensing during September.

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.

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.

Measurement data on the "Rossiya" icebreaker.This dataset is included the following parameters:temperature of water,salinity,dencity.Additionally, meteorological data are presented:wind speed,wind direction, air temperature, visibility.

Data of the 27th cruise of the research vessel "Akademik Fyodorov ".

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,direction of primary swell waves and etc. Research vessel:"Viktor Buynitsky". Callsign:"UAJX".

This dataset is included the following parameters: water temperature, sound velocity in the water body .

Results of measurements of the CO2 flow from water from various depths using the bathometers of the oceanographic station No. 67 on the 26th cruise of the research vessel "Akademik Fedorov" Numerical results of measurements of the IR gas analyzer. Parameter:chamber temperature,atmospheric pressure inside the optical element of the gas analyzer,concentration of water vapor inside the chamber, CO2 concentration inside the chamber, CO2 concentration inside the chamber, corrected for water vapor, relative humidity inside the chamber, water salinity by bathometer, water sampling temperature by bathometer, water temperature before measurements, water temperature after measurements.

This dataset is included the following parameters: Meteorological: air tTemperature,humidity,pressure,wind speed,wind direction. Hydrology: temperature,salinity,density. Hydrochemistry: oxygen,phosphate,silicate,oxygen,pH,alkalinity.

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.