Topic
 

oceans

3604 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Scale
Resolution
From 1 - 10 / 3604
  • A marine end-to-end ecosystem model and R package. The aim is to represent the entire interconnected marine ecosystem (from physics and chemistry, to whales and fisheries in continental shelf regions) by exploring 'what if' experiments and explore uncertainty. View the application, the website or the latest publication.

  • Phyto plankton Abundance: Identify the 3 most abundant phytoplankton species in the North Atlantic and calculate a timeseries of their abundance within the basin.

  • Moving 10-years analysis of nitrates 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 1960-1969 until 2004-2013. Observational data span from 1960 to 2013. Depth range (IODE standard depths): -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 3. 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 • Brunetti Fabio (OGS) • Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 • Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 • Cataletto Bruno (OGS) • Cinzia Comici Cinzia (OGS) • Civitarese Giuseppe (OGS) • DeVittor Cinzia (OGS) • Giani Michele (OGS) • Kovacevic Vedrana (OGS) • Mosetti Renzo (OGS) • 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 • Celio Massimo (ARPA FVG) • Malaguti Antonella (ENEA) • Fonda Umani Serena (UNITS) • Bignami Francesco (ISAC/CNR) • Boldrini Alfredo (ISMAR/CNR) • Marini Mauro (ISMAR/CNR) • Miserocchi Stefano (ISMAR/CNR) • Zaccone Renata (IAMC/CNR) • 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: umol/l

  • This visualization product displays the size of litter in percent per net per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. To calculate percentages for each size, formula applied is: Size (%) = (∑number of particles of each size)*100 / (∑number of particles of all size) When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter size classes are taken from Seadatanet's H03 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H03 ). Different protocols with different degrees of precision were used to classify the sampled micro-litters. Consequently, on the map, the distribution of micro-litter in the size classes depends on the protocol applied during the survey. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.

  • Combined product of Water body phosphate based on DIVA 4D 10-year analysis on five regions : Northeast Atlantic Ocean, North Sea, Baltic Sea, Black Sea, Mediterranean Sea. The boundaries and overlapping zones between these five regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body phosphate product is masked using the relative error threshold 0.5. Units: umol/l

  • to deliver maps showing the extent of the trawling fishing grounds for identifying the changes in level of disturbance over the past ten years and identifying the gaps of fishing vessels’ tracking systems in the Mediterranean Sea