EMODnet Product Catalogue
Chlorophyll pigment concentrations in water bodies
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Moving 10-years analysis of chlorophyll-a at Mediterranean 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 10-year centered average of each season. Decades span from 1972-1981 until 2006-2015. Observational data span from 1911 to 2015. Depth range (IODE standard depths): -2500.0, -2000.0, -1750.0, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0, -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. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5. DIVA settings: A constant value for signal-to-noise ratio was used equal to 1. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. 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. Originators of Italian data sets-List of contributors: o Brunetti Fabio (OGS) o Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 o Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 o Cataletto Bruno (OGS) o Cinzia Comici Cinzia (OGS) o Civitarese Giuseppe (OGS) o DeVittor Cinzia (OGS) o Giani Michele (OGS) o Kovacevic Vedrana (OGS) o Mosetti Renzo (OGS) o Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 o Celio Massimo (ARPA FVG) o Malaguti Antonella (ENEA) o Fonda Umani Serena (UNITS) o Bignami Francesco (ISAC/CNR) o Boldrini Alfredo (ISMAR/CNR) o Marini Mauro (ISMAR/CNR) o Miserocchi Stefano (ISMAR/CNR) o Zaccone Renata (IAMC/CNR) o Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011. Units: mg/m^3
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Gridded product for visualization of Water body chlorophyll-a in the Western part of Black Sea generated by DIVA 4.6.11 using all EMODNET Chemistry data from 2000 to 2014. Depth range (IODE standard depths): 0, -5, -10, –20m. DIVA settings: signal-to-noise ratio and correlation length were estimated using data mean distance as a minimum (for L), and both parameters vertically filtered. Background field: the data mean value is subtracted from the data. Detrending of data: no. Advection constraint applied: no. Analysis: logaritmic transformation. Every year of the time dimension corresponds to a 10-year centred average for each season: - winter: December - February, - spring: March - May, - summer: June - August, - autumn: September - November Units: mg/m^3
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EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants (48 parameters), and covers the Black Sea with 21504 CDI records divided per matrices: 7 biota profiles, 19677 water profiles, 1820 sediment profiles. Vertical profiles temporal range is from 1974-08-24 to 2017-10-06. Data were aggregated and quality controlled by ‘National Institute for Marine Research and Development "Grigore Antipa"’ from Romania. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: http://seadatanet.maris2.nl/bandit/browse_step.php . Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names”, but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV spreadsheet (TXT file), 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 same dataset is offered also as XLSX file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The 48 parameter names in this metadata record are based on P02, SeaDataNet Parameter Discovery Vocabulary, which is available at: http://seadatanet.maris2.nl/v_bodc_vocab_v2/vocab_relations.asp?lib=P02 . Detailed documentation will be published soon. The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
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EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants (49 parameters), and covers the Baltic Sea with 3818 CDI records divided per matrices: 1358 biota (396 Vertical profiles and 962 Time series),906 water profiles, 2510 sediment profiles. Vertical profiles temporal range is from 1985-04-16 to 2016-09-27. Time series temporal range is from 1972-05-02 to 2017-10-30. Data were aggregated and quality controlled by ‘Swedish Meteorological and Hydrological Institute (SMHI)’ from Sweden. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: http://seadatanet.maris2.nl/bandit/browse_step.php . Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV spreadsheet (TXT file), 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 same dataset is offered also as XLSX file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The 49 parameter names in this metadata record are based on P02, SeaDataNet Parameter Discovery Vocabulary, which is available at: http://seadatanet.maris2.nl/v_bodc_vocab_v2/vocab_relations.asp?lib=P02 . Detailed documentation will be published soon. The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
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EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants (20 parameters), and covers the North East Atlantic Ocean with 2400 CDI records divided per matrices: 122 in biota (as time series), 1689 in water (as vertical profiles), 589 in sediment (478 Vertical profiles and 111 Time series). Vertical profiles temporal range is from 1970-07-29 to 2017-02-28. Time series temporal range is from 1979-02-28 to 2014-10-21. Data were aggregated and quality controlled by ‘IFREMER / IDM / SISMER - Scientific Information Systems for the SEA’ from France. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: http://seadatanet.maris2.nl/bandit/browse_step.php . Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV spreadsheet (TXT file), 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 same dataset is offered also as XLSX file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The 20 parameter names in this metadata record are based on P02, SeaDataNet Parameter Discovery Vocabulary, which is available at: http://seadatanet.maris2.nl/v_bodc_vocab_v2/vocab_relations.asp?lib=P02 . Detailed documentation will be published soon. The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
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EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). This regional aggregated dataset contains all unrestricted EMODnet Chemistry data on contaminants (59 parameters), and covers the North Sea with 34978 CDI records divided per matrices: 3909 biota time series, 28071 water profiles, 2998 sediment profiles. Vertical profiles temporal range is from 1970-02-17 to 2017-10-26. Time series temporal range is from 1979-02-26 to 2017-02-28. Data were aggregated and quality controlled by ‘Aarhus University, Department of Bioscience, Marine Ecology Roskilde from Denmark. Regional datasets concerning contaminants are automatically harvested. Parameter names in these datasets are based on P01, BODC Parameter Usage Vocabulary, which is available at: http://seadatanet.maris2.nl/bandit/browse_step.php . Each measurement value has a quality flag indicator. The resulting data collections for each Sea Basin are harmonised, and the collections are quality controlled by EMODnet Chemistry Regional Leaders using ODV Software and following a common methodology for all Sea Regions. Harmonisation means that: (1) unit conversion is carried out to express contaminant concentrations with a limited set of measurement units (according to EU directives 2013/39/UE; Comm. Dec. EU 2017/848) and (2) merging of variables described by different “local names” ,but corresponding exactly to the same concepts in BODC P01 vocabulary. The harmonised dataset can be downloaded as ODV spreadsheet (TXT file), 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 same dataset is offered also as XLSX file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms in subcomponents (measure, substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications users (e.g. LibreOffice Calc). The 59 parameter names in this metadata record are based on P02, SeaDataNet Parameter Discovery Vocabulary, which is available at: http://seadatanet.maris2.nl/v_bodc_vocab_v2/vocab_relations.asp?lib=P02 . Detailed documentation will be published soon. The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search
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Physical data associated with the AMAZOMIX cruise. The Amazon shelf encompasses a variety of physical processes, such as fluvial inputs, coastal currents, mesoscale, filaments, tides, internal waves and upwelling, influencing nutrient concentrations, chlorophyll and suspended matter. They also affect energy, salt and heat balances; parameters that condition physical/biogeochemical interactions and ecosystem functioning, from bacteria to plankton to fish resources. In particular, internal tidal waves are very energetic in this region. They impact biogeochemical cycles via the vertical mixture induced by their dissipation or vertical movements induced by their propagation. They thus allow a significant input of nutriments into the euphotic layer enhancing primary production, as observed on the surface from watercolour data. Internal tidal waves could thus influence the biological pump and the carbon cycle. In addition, overall marine biodiversity of the region, from bacteria to fish is not well described. The connectivity of species in the tropical Atlantic is also still an open question. The Caribbean region is by far more bio-diverse than the Brazilian one. One of the hypotheses is that the Amazon plume, which can extend up to 3,000 km off the mouth, would constitute a barrier for some organisms. The Amazon Shelf is thus an ideal experimental laboratory to study the impact of physical processes on the structure and function of neritic and oceanic marine ecosystems. In this context, the objective of the multidisciplinary AMAZOMIX survey was to study the impact of the Amazon River plume, internal tides and associated turbulent mixing, on marine ecosystem in contrasting regions off the Amazon shelf. For that purpose, the multidisciplinary AMAZOMIX project brings together physicists, biogeochemists, bioopticians and biologists. The sampling strategy consists in the simultaneous acquisition of a comprehensive set of environmental and biological compartments, including micro-organisms (bacteria, phyto and zooplankton) and higher trophic levels (micronekton, demersal and pelagic fish). AMAZOMIX is the first campaign to develop this multi-disciplinary approach off the Amazon shelf. In situ results will be analysed in interaction with digital tools and data, modelling (1/36°, with and without tides, 1/12° coupled) and satellite data analyses. This dataset contains the AMAZOMIX 2021 qualified measurements of - The hydrographic CTD-02 (netCDF and csv text files) - Ship Acoustic Doppler Current Profilers (OS 75 kHz, netCDF and csv text files) - Lowered Acoustic Doppler Current Profilers (WH300 downlooking and WH300 uplooking, netCDF and csv text files) - Thermosalinometer (netCDF and csv text files) - Vertical microstructure profile (VMP-250, binary file) 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.
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The aim of this campaign was to understand and identify controls on biogeochemistry of Belize's coastal zone and the influence of the Belize river. Data were collected in October 2019 over five days - during daylight hours, with the aim of capturing wet season influence of the river, however Belize experienced a drought. Data were collected to enhance and calibrate data collected by the Autonomous Surface Vehicle C-worker 4 as part Commonwealth Marine Economies Programme Belize (CMEP Belize). Discrete water samples were collected for dissolved O2, chlorophyll, nutrients, dissolved organic carbon (DOC), absorbance, and fluorescent dissolved organic matter (FDOM), total alkalinity (TA), dissolved inorganic carbon (DIC), particulate nitrogen (PN), stable carbon-13 isotope DIC (d13C-DIC) and stable nitrogen-15 isotope PN (d15N-PN) and particulate organic carbon (POC). This is an update to a previous version of the dataset (published 2021) which additionally includes (TA, DIC, d13C-DIC and POC, PN and salinity data). All samples were collected using a 5L Niskin at ~0.5 m depth - the depth of C-worker 4 sensors. Dissolved O2, absorbance and chlorophyll samples were run in country by Winkler Method, Spectrophotometry Absorbance and Fluorescence respectively. Samples for nutrients, DOC, FDOM, TA, DIC, d13C-DIC, POC, PN were transported back to the UK for analysis. Both frozen (nutrients) and refrigerated samples (DOC and FDOM) were transported back to the UK in cool bags with frozen samples defrosting enroute back to the UK in preparation for immediate analysis. Absorbance was run a second time back in the UK at the same time as FDOM (both absorbance runs are included).
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The ocean’s meso- and submeso-scales (1-100 km, days to weeks) host features like filaments and eddies that have a key structuring effect on phytoplankton distribution, but that due to their ephemeral nature, are challenging to observe. This problem is exacerbated in regions with heavy cloud coverage and/or difficult access like the Southern Ocean, where observations of phytoplankton distribution by satellite are sparse, manned campaigns costly, and automated devices limited by power consumption. Here, we address this issue by considering high-resolution in-situ data from 18 bio-logging devices deployed on southern elephant seals (Mirounga leonina) in the Kerguelen Islands between 2018 and 2020. These devices have submesoscale-resolving capabilities of light profiles due to the high spatio-temporal frequency of the animals’ dives (on average 1.1 +-0.6 km between consecutive dives, up to 60 dives per day), but observations of fluorescence are much coarser due to power constraints. Furthermore, the chlorophyll a concentrations derived from the (uncalibrated) bio-logging devices’ fluorescence sensors lack a common benchmark to properly qualify the data and allow comparisons of observations. By proposing a method based on functional data analysis, we show that a reliable predictor of chlorophyll a concentration can be constructed from light profiles (14 686 in our study) and matchups with satellite ocean-color data, thus enabling effective (1) homogenization then calibration of the bio-logging devices’ fluorescence data and (2) filling of the spatial gaps in coarse-grained fluorescence sampling. The developed method improves the spatial resolution of the chlorophyll a field description from ~30 km to ~12 km. These results open the way to empirical study of the coupling between physical forcing and biological response at submesoscale in the Southern Ocean, especially useful in the context of upcoming high-resolution ocean-circulation satellite missions like SWOT. 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.
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These datasets were derived from the water samples obtained at the Rabnabad channel, which is located in the Bay of Bengal's upstream region. From March 3rd to 6th 2022, a detailed field survey was conducted. Chlorophyll – a (chl-a) measurements were taken from 32 water samples collected from eight different locations. The sampling was carried out with the help of the Payra Port's vessel 'SAGOR JATRA-1.' Water samples were collected from various depths using a Niskin sampler of HYDRO-BIOS with a non-metallic interior. To obtain in-situ data, water samples were tested in the laboratory according to conventional procedures. In this channel, a large community relies on fishing as a means of their livelihood. Understanding the chlorophyll status in this region is crucial because it forms the basis of the food web and serves as an indicator of primary production, which in turn influences secondary output. In order to isolate the pigments from this murky upstream location, a trustworthy extraction technique need to be identified. 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.