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

'''Short description:''' For the Mediterranean Sea - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Near Real-Time Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are updated several times daily to provide the best product timeliness. '''DOI (product) :''' https://doi.org/10.48670/mds-00334

HF Radar System

The glider operations in the MOOSE network started to be deployed regularly in 2010 in the North Western Mediterranean Sea, thanks to the setup of national glider facilities at DT-INSU/Ifremer (http://www.dt.insu.cnrs.fr/gliders/gliders.php) and with the support of the European project FP7-PERSEUS. Two endurance lines are operated: MooseT00 (Nice-Calvi; Ligurian Sea) and MooseT02 (Marseille-Menorca; Gulf of Lion). The all dataset here corresponds to raw data in the EGO format.

EMODnet (European Marine Observation and Data Network) is the long term marine data initiative supported by the European Commission since 2009 to ensure that European marine data will become easily accessible, interoperable, and free on restrictions on use. EMODnet Chemistry provides access to standardized, harmonized and validated chemical data collections for water quality evaluation at a regional scale, as defined by the Marine Strategy Framework Directive (MSFD). The data portal has adopted and adapted SeaDataNet standards and services, establishing interoperability between the data sets from the many different providers (more than 60 in EMODnet Chemistry network). Concentration maps of nutrients, chlorophyll-a and dissolved oxygen are computed on a standard grid, providing information at a regular time interval, per season and over several vertical layers, including the deepest one. Dedicated OGC standard services for browsing, viewing and downloading chemistry observation, data and data products for the European waters have been developed, and are actively maintained and monitored.

Seasonal Climatology of Dissolved Inorganic Nitrogen (DIN) for Loire River for the period 1990-2019 and for the following seasons: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Observational data span from 1990 to 2019. Depth levels (m): -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -25.0, -20.0, -15.0, -10.0, -8.0, -6.0, -4.0, -2.0, -0.0 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 2.7.4, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.01 degrees. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1 for vertical profiles and to 0.1 for time series to account for the redundancy in the time series observations. 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: umol/l.