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Advance in the visualization of the bathymetric and geological data from charted to digital maps and models opened the possibility to analyse data within Geographic Information System (GIS) functionalities. In this paper, bathymetric and geological properties of the Adriatic Sea were analysed using the General Bathymetric Chart of the Ocean (GEBCO) 2020 digital bathymetric model (DBM) and data from the European Marine Observation and Data Network (EMODnet). The bathymetric analysis includes depth statistics, area and volume calculation, hypsometry, and analysis of the heterogeneity of bathymetric data from the GEBCO 2020 DBM within the limits of the Adriatic defined by the International Hydrographic Organization (IHO) and 3 sub-basins delineated according to the bathymetry. The geological analysis includes seabed substrate map from EMODnet data and kilometre-scale seabed variability in the Adriatic. The GEBCO 2020 DBM shows that the Adriatic Sea is a shallow sea with a mean depth of -253 metres and over 50% of area shallower than 100 metres. The area of the Adriatic Sea is 138 516 km2 with a total volume of 35 521 km3. Patterns describing morphological variability coincide with the heterogeneity of the underlying source data of the GEBCO 2020 digital bathymetry model and major structures in the Adriatic Sea.

Offshore wind energy resources are not fully exploited renewable energy resources until now and could play a crucial role in mitigating the impacts of climate change by the generation of renewable electricity. Planning processes such as technical, social, environmental, various agents, and political concerns are necessary for the development of offshore wind energy projects. The objective of this study was to assess the comprehensive feasibility of a desired offshore wind power plant applying Geographical Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) guidance for the coastal area of Turkey. Furthermore, EMODnet (the European Marine Observation and Data Network) was employed for data acquisition to unlock fragmented and hidden marine data resources and to facilitate investment in sustainable coastal and offshore activities. For the determination of potential site with Multi-Criteria Decision Maker Method, 3 main criteria Technical (C1), Environmental (C2), and Social (C3), and 13 sub-criteria were determined. Based on these criteria, the suitability map was created by using all criteria map layers with their buffer zones. The final map indicated that %1.38 (3294.8 km2) of Turkey Seas was suitable for offshore wind farms. The most suitable region was determined in the Marmara Sea with 1194 km2. The Aegean Sea, the Black Sea, and the Mediterranean Sea were following the Marmara Sea in terms of the huge suitable regions respectively. It was apparent that the growth of offshore wind farms in Turkey would increase if the supporting mechanism and the necessary legislation were ensured. [ABSTRACT FROM AUTHOR]

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In this paper the latest versions of six publicly available bathymetry models: DTU10bat, EMODnet 2018, ETOPO1, GEBCO 2020, Smith and Sandwell V20.1 and SRTM15+ V.2.1. are compared and evaluated in the area of continental shelf of Croatia settled along well intended east Adriatic coast. Survey data in the area is not available through open access data bases, but publicly accessible in agreement with data holders (hydrographic institute, research centres and industry). These grids provide alternative sources of information about seafl oor topography. Marine researchers should be acquainted with the main characteristics as well as pros and cons of bathymetry models in order to choose the best one for a specifi c purpose. In this paper the most important characteristics and information about grids are presented: resolution, coverage, release date, horizontal and vertical datum, data source, registration method, producer and link to website with an emphasis on the underlying source data. The underlying source data is one of the most important parameters that determine the quality of the bathymetric model. Hypsometry curve that is describing the area distribution of depth is calculated for each bathymetry model over the test area of the east Adriatic. For pixel to pixel comparison, grids were resampled to same one-minute resolution and absolute diff erences between models are calculated in identical points. Absolute diff erences between models show level of mutual compatibility between models as well as areas of highest disagreements that indicate the presence of outliers or systematic errors within models. In order to demonstrate how well publicly available bathymetry models fi t the true topography of the sea fl oor, grids were compared to high-resolution digital bathymetry model interpolated from the multibeam survey in the area of Murter Sea. This paper should assist in the choice of a most suited bathymetry grid in future maritime studies in the Adriatic. [ABSTRACT FROM AUTHOR]

Marine data are needed for many purposes: for acquiring a better scientific understanding of the marine environment, but also, increasingly, as marine knowledge for decision making as well as developing products and services supporting economic growth. Data must be of sufficient quality to meet the specific users' needs. It must also be accessible in a timely manner. And yet, despite being critical, this timely access to known-quality data proves challenging. Europe's marine data have traditionally been collected by a myriad of entities with the result that much of our data are scattered throughout unconnected databases and repositories. Even when data are available, they are often not compatible, making the sharing of the information and data aggregation particularly challenging. In this paper, we present how the European Marine Observation and Data network (EMODnet) has developed over the last decade to tackle these issues. Today, EMODnet is comprised of more than 150 organizations which gather marine data, metadata, and data products and make them more easily accessible for a wider range of users. EMODnet currently consists of seven sub-portals: bathymetry, geology, physics, chemistry, biology, seabed habitats, and human activities. In addition, Sea-basin Checkpoints have been established to assess the observation capacity in the North Sea, Mediterranean, Atlantic, Baltic, Artic, and Black Sea. The Checkpoints identify whether the observation infrastructure in Europe meets the needs of users by undertaking a number of challenges. To complement this, a Data Ingestion Service has been set up to tackle the problem of the wealth of marine data that remain unavailable, by reaching out to data holders, explaining the benefits of sharing their data and offering a support service to assist them in releasing their data and making them available through EMODnet. The EMODnet Central Portal (www.emodnet.eu) provides a single point of access to these services, which are free to access and use. The strategic vision of EMODnet in the next decade is also presented, together with key focal areas toward a more user-oriented service, including EMODnet for business, internationalization for global users, and stakeholder engagement to connect the diverse communities across the marine knowledge value chain.

Abstract Scientific research as well as management of the marine environment, and sustainable blue growth are based on the availability of quality-assured observations, reliable data and solid scientific-based information. These represent three consecutive steps of Data-Information-Knowledge-Wisdom paradigm on the pyramid of wisdom, providing different layers of information. EMODnet (European Marine Observation and Data network) is one of the key infrastructures engaged in collecting, facilitating access and promoting use and re-use of marine observation and data products for both scientific research and marine environmental management. Its Spatial Data Infrastructure (SDI) represents a powerful mechanism to support the implementation of the Marine Strategy Framework Directive Article 19.3 in accordance with the INSPIRE Directive standards and implementing rules. Standardized, harmonized and validated chemical data collections are made available for water quality evaluation at a regional scale, establishing interoperability between the data sets from the many different providers (more than 60 in EMODnet Chemistry). 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 Open Geospatial Consortium 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. These results can provide knowledge layers and can also answer the needs of the directive on Maritime Spatial Planning (EU, 2014), which requires the integration of multidisciplinary data and information on the state of the marine environment with maritime and human activities. Highlights • Results achieved by the EMODnet Chemistry and the viewing services developed to download and share them. • Observations and information are discussed, in relation to MSFD, INSPIRE Directive standards and Maritime Spatial Planning. • Data availability is an important component of the MSP process for environmental management of protected areas. • In the framework of EMODnet Chemistry, 160 maps were realized, covering 11 parameters, 4 seasons and aggregated for 30 depth. [ABSTRACT FROM AUTHOR]

The poor access to data on the marine environment is a handicap to government decision-making, a barrier to scientific understanding and an obstacle to economic growth. In this light, the European Commission initiated the European Marine Observation and Data Network (EMODnet) in 2009 to assemble and disseminate hitherto dispersed marine data. In the ten years since then, EMODnet has become a key producer of publicly available, harmonised datasets covering broad areas. This paper describes the methodologies applied in EMODnet Geology project to produce fully populated GIS layers of seabed substrate distribution for the European marine areas. We describe steps involved in translating national seabed substrate data, conforming to various standards, into a uniform EMODnet substrate classification scheme (i.e., the Folk sediment classification). Rock and boulders form an additional substrate class. Seabed substrate data products at scales of 1:250,000 and 1:1 million, compiled using descriptions and analyses of seabed samples as well as interpreted acoustic images, cover about 20% and 65% of the European maritime areas, respectively. A simple confidence assessment, based on sample and acoustic coverage, is helpful in identifying data gaps. The harmonised seabed substrate maps are particularly useful in supraregional, transnational and pan-European marine spatial planning.

Wind–wave characterization and modeling around a group of islands can have significant challenges due to strong diffraction, shoaling, and reflection. In this work, the wind–wave climate of the Azores archipelago (North Atlantic Ocean) is characterized based on wave buoy measurements recorded between 2012 and 2021 at five different locations with water depth ranging from 80 to 110 m. Moreover, wave measurements during four storms of extratropical origin and two storms of tropical origin are analyzed in detail. Due to identified island shadow effects, the average significant wave height (H s) ranged between 1.50 m (S. Miguel island) and 1.86 m (Graciosa island) in the south and north of the archipelago, respectively. Under storm conditions, shadow effects can lead to differences up to approximately 7 m in H s between the north and south of the archipelago. The ability to simulate the local wave conditions by an unstructured WAVEWATCH III model covering the north Atlantic with high resolution around the Azores Archipelago is analyzed. In addition, the model performance and scalability on two different High Performance Computing environments are analyzed considering different numerical schemes and parallelization algorithms. • Wind–wave characterization based on five long-term buoy measurements. • Islands shadow effects are identified. • Unstructured WW3 North Atlantic model with high resolution in the Azores is implemented. • Model scalability and performance analysis for up to 1000 CPU cores. [ABSTRACT FROM AUTHOR]

The European Marine Observation and Data Network (EMODnet) is a Project aimed at the collection and harmonization in European Seas of existing data, to be represented on digital maps freely available through a dedicated portal (https://www.emodnet.eu/en). It is subdivided into Lots concerning Bathymetry, Geology, Biology, Chemistry, Physics, Seabed Habitats and Human activities. Data displayed on the Portal are harmonized at different scales. The EMODnet Geology Lot is realized by a Consortium of European Geological Surveys covering all of the European Seas. It includes information on seafloor sediments grainsize, sedimentation rates, Quaternary geology, pre-Quaternary geology and stratigraphy, geomorphology, coastal behaviour, geological events, mineral resources. The sources of data are all pre-existing data in literature which also include cartography, databases, national and European projects. All these data were processed in order to produce digital cartography distributed as WMS services on the EMODnet Geology Portal (http://www.emodnet-geology.eu/). As partner of the EMODnet Geology Consortium, the Geological Survey of Italy provides data to the Project, mainly relying on the comprehensive database complementing the Italian Geological Maps at 1:50,000 scale realized within the CARG mapping Project. Moreover, the Geological Survey of Italy coordinates the "Geological events and probabilities" Work Package n.6 (WP6), which aims to identify and map significant geological events such as earthquakes, volcanic centers, submarine landslides, tsunamis, fluid emissions and Quaternary faults. Geological events are collated into layers subdivided by type of event and organized as shapefiles according to their geometric primitives (polygons, points, lines). Each occurrence is complemented, where available, by a comprehensive and detailed pattern of Attributes for each feature in order to represent their diverse characteristics, deriving also from the different geological settings of European sea areas. Datasets are elaborated according to guidelines provided by the WP coordinator after thorough discussion with all partners, aimed at identifying parameters to be used to characterize events and addressed to achieve the best degree of harmonization and standardization according to the European INSPIRE Directive. The realization of the digital cartography of WP6 has been divided into several phases:. - elaboration of Guidelines and preparation of the instructions and technical specifications on how to supply GIS layers; during this step the parameters that should be used to characterize events were identified together with any additional relevant information. Particular attention has been devoted to the definition of the Attribute tables - systematic collection of basic data, visualization and identification of any area without data - generalization. Maps are generalized at the scale of representation established for each phase of the Project. Datasets consist of shapefiles representing each type of event at 1:250,000 scale in EMODnet Geology 2 and at 1:100,000 scale and more detailed in the following phases - harmonization of data according to the specifications contained in the guidelines - data processing, compilation and structuring of shapefiles in European-wide layers - update, correction and implementation of files after review by partners The amount of existing data is considerable: 3,000 records of landslides occurrences, more than 1,000 volcanic structures, almost 3,500 fluid emission areas, more than 500 tsunami events and more than 15,000 records of Quaternary faults have been entered into the database. Concerning earthquakes a link is provided to the Seismic Portal (www.seismicportal.eu), although additional data (approximately 3,000 entries) have also been recorded. Information gathered during the Project, including metadata, is displayed on the Portal. Each occurrence reported must be complemented by the appropriate reference; additional information, including the names of specific features, can also be provided if available. Submarine slides have been characterized by type of movement, material involved (lithology), volume, thickness, slope, age and source area. Terms adopted for type description were mainly obtained from Varnes (1978) also cited in the INSPIRE data specification on Natural Risk Zones. Volcanic centers were complemented by information on their morphological and activity types, age of activity, chemical composition, eruption frequency, height, volcanic district and the presence of fluid emissions. The Volcanic Explosivity Index (VEI) is also relevant, if available; in this case the age of its reference eruption is required (VEI age). The layer regarding tsunamis was subdivided into two shapefiles, one reporting locations of events which originated a tsunami and another one reporting the coasts affected by a tsunami, to be compiled only in case of unknown origin. Attributes listed for tsunamis are: date, type, cause, run-up, intensity, affected coast. Fluid emissions have been classified according to the process that generates them or based on the associated materials of geological or biological derivation. Morphological types have also been considered since features are related to erosional or depositional processes as well as to the composition and escaping mechanisms of the fluid. Tectonics was also considered relevant for the Geological events WP. Only faults active during the Quaternary were taken into account. It is necessary to specify whether they are buried or crop out as well as their type and age. Most of the terms adopted are listed within the INSPIRE data specification on Geology. Based on landslides data gathered within WP6 and on information available from the EMODnet Bathymetry Portal (https://www.emodnet-bathymetry.eu/), a map of susceptibility to submarine landslides has been developed using the maximum entropy model. Interoperability of data was one of the objectives pursued by the Project, in order to provide more complete, correct and reliable information and facilitate the exchange and reuse of data even among non-homogeneous systems. Besides combining these harmonized and standardized datasets, it might be possible to develop additional thematic maps that could support further research, as well as the planning and management of submerged areas. [ABSTRACT FROM AUTHOR]

The aim of this paper is to apply a new lane separation methodology for the maritime sector emissions attributed to the different vessel types and marine traffic loads in the Mediterranean and the Black Sea defined via the European Marine and Observation Data network (EMODnet), developed in 2016. This methodology is implemented for the first time on the Copernicus Atmospheric Monitoring Service Global Shipping (CAMS-GLOB-SHIP v2.1) nitrogen oxides (NOX) emissions inventory, on the Sentinel-5 Precursor Tropospheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) tropospheric vertical column densities, and on the LOTOS-EUROS (Long Term Ozone Simulation—European Operational Smog) CTM (chemical transport model) simulations. By applying this new EMODnet-based lane separation method to the CAMS-GLOB-SHIP v2.1 emission inventory, we find that cargo and tanker vessels account for approximately 80% of the total emissions in the Mediterranean, followed by fishing, passenger, and other vessel emissions with contributions of 8%, 7%, and 5%, respectively. Tropospheric NO2 vertical column densities sensed by TROPOMI for 2019 and simulated by the LOTOS-EUROS CTM have been successfully attributed to the major vessel activities in the Mediterranean; the mean annual NO2 load of the observations and the simulations reported for the entire maritime EMODnet-reported fleet of the Mediterranean is in satisfactory agreement, 1.26 ± 0.56 × 1015 molecules cm−2 and 0.98 ± 0.41 × 1015 molecules cm−2, respectively. The spatial correlation of the annual maritime NO2 loads of all vessel types between observation and simulation ranges between 0.93 and 0.98. On a seasonal basis, both observations and simulations show a common variability. The wintertime comparisons are in excellent agreement for the highest emitting sector, cargo vessels, with the observations reporting a mean load of 0.98 ± 0.54 and the simulations of 0.81 ± 0.45 × 1015 molecules cm−2 and correlation of 0.88. Similarly, the passenger sector reports 0.45 ± 0.49 and 0.39 ± 0.45 × 1015 molecules cm−2 respectively, with correlation of 0.95. In summertime, the simulations report a higher decrease in modelled tropospheric columns than the observations, however, still resulting in a high correlation between 0.85 and 0.94 for all sectors. These encouraging findings will permit us to proceed with creating a top-down inventory for NOx shipping emissions using S5P/TROPOMI satellite observations and a data assimilation technique based on the LOTOS-EUROS chemical transport model. [ABSTRACT FROM AUTHOR]

Deep-water spectral wave steepness (s m) is used in several ocean engineering activities to characterise sea states. However, difficulties in maintaining wave buoys offshore the continental shelf results in a lack of deep-water s m variability studies based on long-term field observations in high-energetic environments. In this work, we analysed s m variability between 1200 and 1900 m water depth offshore mainland Portugal (North Atlantic Ocean) based on field measurements recorded between 2009 and 2020 at three different locations. Results show similar s m variability at the three sites with mean, minimum and maximum values of 0.031, 0.004 and 0.072, respectively. A decrease in the monthly average s m to 0.027 is observed for all locations during September and October. Values of s m displayed a decreasing tendency with a rotation of the mean wave direction towards the North. Under storm conditions, s m ranged between 0.020 and 0.060 and no correlation was found between s m and other wave parameters, such as significant wave height, mean wave period or mean wave direction. For the most severe storms, values of s m were in general larger than 0.030, which points out that storm waves display larger s m. • Deep-water spectral wave steepness (s m) variability at approximately 1000 m depth is analysed. • Similar s m variability was found at three different locations. • Mean s m is 0.031 • Monthly average s m decreases during September and October. • s m ranged between 0.020 and 0.060 under storm conditions. [ABSTRACT FROM AUTHOR]

The poor access to data on the marine environment is a handicap to government decision-making, a barrier to scientific understanding and an obstacle to economic growth. In this light, the European Commission initiated the European Marine Observation and Data Network (EMODnet) in 2009 to assemble and disseminate hitherto dispersed marine data. In the ten years since then, EMODnet has become a key producer of publicly available, harmonised datasets covering broad areas. This paper describes the methodologies applied in EMODnet Geology project to produce fully populated GIS layers of seabed substrate distribution for the European marine areas. We describe steps involved in translating national seabed substrate data, conforming to various standards, into a uniform EMODnet substrate classification scheme (i.e., the Folk sediment classification). Rock and boulders form an additional substrate class. Seabed substrate data products at scales of 1:250,000 and 1:1 million, compiled using descriptions and analyses of seabed samples as well as interpreted acoustic images, cover about 20% and 65% of the European maritime areas, respectively. A simple confidence assessment, based on sample and acoustic coverage, is helpful in identifying data gaps. The harmonised seabed substrate maps are particularly useful in supraregional, transnational and pan-European marine spatial planning. [ABSTRACT FROM AUTHOR]