Moving 6-year analysis of Water body chlorophyll-a in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1980-1985 and 2013-2018. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. 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 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the Correlation length in the horizontal direction were fixed to 80 km and in the vertical direction to 25 m. Signal to noise ratio were fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is mg/m3.

Moving 6-year analysis of Water body ammonium in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to the 6-year centred average. Periods span between 1980-1985 and 2011-2016. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. 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_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the Correlation length and Signal to noise ratio were fixed to 0.7 and 1.0 respectively. Background fields were created using all data (1980-2016) for the given season. Log transformation (option 11) was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l. The entire set of related maps can be found in the viewing service: http://ec.oceanbrowser.net/emodnet/ .

Moving 6-year analysis of Water body dissolved inorganic nitrogen (DIN) in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1980-1985 and 2013-2018. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. 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 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the Correlation length in the horizontal direction were fixed to 80 km and in the vertical direction to 25 m. Signal to noise ratio were fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

Moving 6-year analysis and visualization of Water body dissolved oxygen concentration in the North Sea, four seasons: winter (dec-feb), spring (mar-may), summer (jun-aug), autumn (sep-nov). 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 2.7.2. 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.

The SDC_BAL_CLIM_TS_V2 product contains temperature and salinity climatologies for the Baltic Sea, including seasonal and monthly fields for the period 1955-2018 and seasonal and monthly fields for 6 decades starting from 1955 to 2018. The climatological fields were computed from a merged Baltic Sea data set that combines data extracted from two major sources: 1) SeaDataNet infrastructure and 2) Coriolis Ocean Dataset for Reanalysis. The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.6.3.

Moving 6-year analysis and visualization of Water body dissolved inorganic nitrogen (DIN ) in the North Sea, four seasons: winter (dec-feb), spring (mar-may), summer (jun-aug), autumn (sep-nov). 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 2.7.2. 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.

Moving 6-year analysis and visualization of Water body chlorophyll-a in the North Sea, four seasons: winter (dec-feb), spring (mar-may), summer (jun-aug), autumn (sep-nov). 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 2.7.2. 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.

The SeaDataCloud Temperature and Salinity historical data collection for the Baltic Sea V2 includes open access in situ data on temperature and salinity of water column. The data were retrieved from the SeaDataNet infrastructure during summer 2019. Data have been quality controlled according to the SeaDataNet2 project QC procedures in conjunction with the visual expert check using the ODV software. The final number of stations in the collection is 481695, containing around 14.4 million values for both temperature and salinity. The dataset format is ODV binary collection which you can read, analyse and export from with the ODV application provided by the Alfred Wegener institute at http://odv.awi.de/. For data access please register at http://www.marine-id.org/.

Moving 6-year analysis and visualization of Water body silicate in the North Sea, four seasons: winter (dec-feb), spring (mar-may), summer (jun-aug), autumn (sep-nov). 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 2.7.2. 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.

The SDC_BAL_TS_statistics_DP1 contains temperature and salinity means and standard deviation at different depths in basins in the Baltic Sea for every month. Based on the SeaDataCloud historical dataset SDC_BAL_DATA_TS_V2 covering the period 1900 – 2019 and merged with the Coriolis ocean dataset for reanalysis (CORA) dataset (https://www.seanoe.org/data/00351/46219/).