Climatology done from the SeaDataNet aggregated dataset v1.1 for the North Arctic Ocean. The version used for the DIVA software is the 4.6.10 (prerelease 4.6.11). The period covers 1900-2013. For data access please register at http://www.marine-id.org

The SDC_ARC_CLIM_TS_V1 product contains Temperature and Salinity Climatologies for Arctic Ocean including seasonal and monthly fields for 6 decades starting from 1955 to 2014. The climatological fields were computed from merged Arctic Ocean data that combines data extracted from the 2 major sources: 1) SeaDataNet infrastructure and 2) World Ocean Database (2018) for reanalysis. The computation was done with the DIVA Classic (Data-Interpolating Variational Analysis), version 4.7.2.

The SeaDataCloud Temperature and Salinity Climatologies have been processed from the historical Data Collection of the Arctic Ocean (from 56°N to 83°N and from 45°W to 70°E) including temperature and salinity in situ data of the water column for the period 1955 – 2019. The analysis was run in six decadal periods (1955-1964/1965-1974/1975-1984/1985-1994/1995-2004/2005-2014). A subset of the World Ocean Database 2018 (WOD18, https://www.nodc.noaa.gov/OC5/WOD/pr_wod.html) dataset has been integrated as external data-source to improve data availability for analysis.

SeaDataCloud Temperature and Salinity historical data collection for the Arctic Ocean, including revised quality flags after quality control with ODV. The dataset format is ODV binary collections. You can read, analyse and export from the ODV application provided by Alfred Wegener institute at http://odv.awi.de/. For data access please register at http://www.marine-id.org/.

SeaDataCloud Temperature and Salinity historical data collection for the Arctic Ocean, including revised quality flags after quality control with ODV. The dataset format is ODV binary collections. You can read, analyse and export from the ODV application provided by Alfred Wegener institute at http://odv.awi.de/. For data access please register at http://www.marine-id.org/.

SeaDataNet Temperature and Salinity historical data collection for the North Arctic Ocean, including revised quality flags after quality control with ODV. For data access please register at http://www.marine-id.org The dataset format is ODV binary collections. You can read, analyse and export from the ODV application provided by Alfred Wegener institute at http://odv.awi.de/

SeaDataNet Temperature and Salinity historical data collection for the North Arctic Ocean, including revised quality flags after quality control with ODV. For data access please register at http://www.marine-id.org The dataset format is ODV binary collections. You can read, analyse and export from the ODV application provided by Alfred Wegener institute at http://odv.awi.de/

Moving 6-year analysis of Chlorophyll-a at Atlantic Sea for each season. - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1972-1977 until 2012-2020. Observational data span from 1972 to 2020. Depth range (IODE standard depths): -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: mg/m^3

Moving 6-year analysis of Water body chlorophyll-a in the NorthEast Atlantic for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1971/1976 until 2019/2024. Observation data span from 1971 to 2024. High-frequency observation trails were filtered to a 3h temporal resolution. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 200km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.loglin) was applied to the data prior to the analysis. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: mg/m3.

Moving 6-year analysis and visualization of Water body chlorophyll-a in the North Sea. Four seasons (December-February, March-May, June-August, September-November). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.12. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.