EMODnet bathymetry is composed of a multitude of datasets from a multitude of data providers. Users of the resulting grid and associated datasets need to be able to evaluate at the grid node level the quality of the bathymetric data and product they will be using. For this EMODnet Bathymetry has introduced a Quality index (QI). The QI is available as a WFS service providing vector data and as WMS providing the QI as an image service. The aim of the quality index is to: • help data users to evaluate quickly the dataset they are about to request, • indicate to the EMODnet Basin coordinators what are the limitations of the dataset they are about to merge while building the EMODnet DTM and to • be used as the basis of the evaluation of the quality of the EMODnet DTM. Service URL: https://ows.emodnet-bathymetry.eu/wfs

The objective of this tender is to examine the current data collection, observation and data assembly programmes in the Meditterranean Sea, identify gaps and to evaluate how they can be optimised.

ERA‐40 is a re‐analysis of meteorological observations from September 1957 to August 2002 produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF)

EMODnet Bathymetry has adopted the CDI Data Discovery & Access service as developed and operated by SeaDataNet, the pan-European network of NODCs, to bring together and provide access to available high resolution bathymetric survey data sets from many data providers, such as National Hydrographic Institutes, Research Institutes, and Survey companies. All bathymetric survey data are described with INSPIRE compliant metadata, following the CDI metadata profile, based on ISO 19115 – 19139 standards. This way, the CDI service gives users a highly detailed insight in the availability and geographical spreading of bathymetric survey data sets that are acquired and managed by an increasing group of data providers and for which users can request access for downloading. The CDI metadata are public domain and freely available for all users. However, a major part of the survey data sets is not freely available and requires negotiation with the data owners. The SeaDataNet CDI search, shopping and tracking mechanism facilitates identifying and requesting access to these background data sets from data providers. Note that all data sets are used internally with permission of the data owners for contributing to the EMODnet Digital Terrain Model (DTM) for the European sea regions. The service URL is : https://geo-service.maris.nl/emodnet_bathymetry/wfs?service=WFS&request=GetCapabilities. The layer in the Map Viewer facilitates users to view the locations of the CDI entries and to retrieve details of individual surveys by clicking on the map. From there users are linked to the actual CDI Data Discovery and Access service (https://cdi-bathymetry.seadatanet.org/search) for performing more queries and submitting requests for data access.

Moving 6-year analysis of Water body dissolved inorganic nitrogen (DIN) for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of the season. 6-years periods span from 1990-1995 until 2017-2022. Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Units: umol/l. Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.9, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is dx=dy=0.125 degrees (around 13.5km and 10.9km accordingly). The vertical resolution is 21 depth levels: [0.,5.,10.,20.,30.,50.,75.,100., 125.,150.,200.,250.,300.,400.,500.,600.,700.,800.,900.,1000.,1100.]. The horizontal correlation length is 200km. The vertical correlation length (in meters) was set twices the vertical resolution: [10.,10.,20.,20.,40.,50.,50.,50.,50.,100.,100.,100.,200.,200.,200.,200.,200.,200.,200.,200.,200.]. Duplicates check was performed using the following criteria for space and time: dlon=0.001deg., dlat=0.001deg., ddepth=1m, dtime=1hour, dvalue=0.1. The error variance (epsilon2) was set equal to 1 for profiles and 10 for time series to reduce the influence of close data near the coasts. An anamorphosis transformation was applied to the data (function DIVAnd.Anam.loglin) to avoid unrealistic negative values: threshold value=200. A background analysis field was used for all years (1990-2022) with correlation length equal to 600km and error variance (epsilon2) equal to 20. Quality control of the observations was applied using the interpolated field (QCMETHOD=3). Residuals (differences between the observations and the analysis (interpolated linearly to the location of the observations) were calculated. Observations with residuals outside the minimum and maximum values of the 99% quantile were discarded from the analysis. 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.

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

The Shom uses a 2D barotropic version of the HYCOM code (https://hycom.org/) to compute water level /surge forecasts (astronomical tides and meteorological surges) for the Atlantic, Mediterranean, Antilles-Guyane and Indian Ocean domains. The configurations use curvilinear grid with resolutions of several km offshore and ranging from 1.5km to around 500m on the french mainland coasts and the Antilles-Guyana coast. A downscaling by nesting allows a resolution of 800m to 200m over the Indian domain. These models have been adapted by the Shom to be operable in coastal areas by taking into account, in particular, the tide and high resolution bathymetry in these areas (from 100m for DTMs of facade to 20m for coastal DTMs) using Litto3D surveys by airborne LIDAR. The models are operated by Météo-France and the Shom in the framework of the HOMONIM project for the coastal flood/wave warning system.