Moving 6-year analysis of chlorophyll-a in the Arctic Region for each season: winter (December-February), spring (March-May), summer (June-August) and autumn (September-November). Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1980-1985, 1981-1986, ....., until 2012-2017. 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. Analysed field masked using relative error threshold 0.3 and 0.5. DIVA settings: signal-to-noise ratio and correlation length were estimated using data mean distance as a minimum (for L) and vertically filtered. Background field: A reference field of all seasonal data between 1980-2017. Detrending of data: no. Advection constraint applied: no. Units: 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 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/ .

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters with 220031 CDI stations. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)'. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12 ). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://doi.org/10.6092/ec8207ef-ed81-4ee5-bf48-e26ff16bf02e The aggregated dataset can be downloaded as ODV spreadsheet, which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

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/.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Baltic Sea with 175834 CDI stations (175778 Vertical profiles and 56 Time series). Vertical profiles temporal range is from 1902-08-05 to 2020-10-10. Time series temporal range is from 2010-01-12 to 2016-02-10. Data were aggregated and quality controlled by "Swedish Meteorological and Hydrological Institute (SMHI)" from Sweden. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication%3EBaltic The aggregated dataset can also be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters with 114721 CDI stations. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)'. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12 ). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication>Arctic The aggregated dataset can also be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

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.

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/).

The data collection of the North Sea is divided in two datasets : the discrete collection and the trajectories collection. The Discrete SeaDataCloud Temperature and Salinity Historical Data Collection for the North Sea includes open access in situ data on temperature and salinity measured with “discrete” instruments (CTD, XBT, discrete water samplers…). The data span between 4°W and 10°E in longitude, and from 49°N to 62°N in latitude. It covers the time period 1893 – 2017. The data were retrieved from the SeaDataNet infrastructure in November 2017. The “Trajectories” SeaDataCloud Temperature and Salinity Historical Data Collection for the North Sea includes open access in situ data on temperature and salinity measured by continuously recording sensors (e.g. Ferryboxes). The data span between 4°W and 10°E in longitude, and from 49°N to 62°N in latitude. It covers the time period 1989 – 2017. The data were retrieved from the SeaDataNet infrastructure in November 2017. The quality control of the data has been performed with the help of ODV software. Data Quality Flags have been revised following common recommended procedures defined under SeaDataNet 2 project in conjunction with visual expert check. 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/.

The SDC_MED_DP2 product contains 55 sliding decadal temperature fields (1955-1964, 1956-1965, 1957-1966, …, 2009-2018) at 1/8° horizontal resolution obtained in the 0-2000m layer and two derived OHC annual anomaly estimates for the 0-700m and the 0-2000m layers. Sliding decades of annual Temperature fields were obtained from an integrated Mediterranean Sea dataset covering the time period 1955-2018, which combines data extracted from SeaDataNet infrastructure at the end of July 2019 (SDC_MED_DATA_TS_V2, https://doi.org/10.12770/3f8eaace-9f9b-4b1b-a7a4-9c55270e205a) and the Coriolis Ocean Dataset for Reanalysis (CORA 5.2, accessed in July 2020, https://archimer.ifremer.fr/doc/00595/70726/). The resulting annual OHC anomaly time series span the 1960-2014 period. The analysis was performed with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.6.1.