Specification of the desirable and recommended products attributes for generating spatial layers of sea mid-water and sea-bottom temperature for the last 10, 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

Data from FerryBoxes on ships of opportunity going on permanent routes are stored inside this database (ferrydata.hzg.de). Parameters are temperature, salinity, chlorophyll-a fluorescence, oxygen and different others. The data model is transect oriented. A data portal to access and visualise the data is also provided.

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.

Description of spatial layers attributes of sea-level trend (units: mm/year) from tide gauges over periods of 50 years (1963-2012) and 100 years (1913-2012), to characterize and assess average annual sea-level rise at the coast.

Specifications of the desirable and recommended product attributes for generating spatial layers of sea level trend for the last 10 years for the Mediterranean basin and for each NUTS3 region along the coast.

Businesses, policymakers, and local communities need to access reliable weather and climate information to safeguard human health, wellbeing, economic growth, and environmental sustainability. However, important changes in climate variability and extreme weather events are difficult to pinpoint and account for in existing modelling and forecasting tools. Moreover, many changes in the global climate are linked to the Arctic, where climate change is occurring rapidly, making weather and climate prediction a considerable challenge. Blue-Action evaluated the impact of Arctic warming on the northern hemisphere and developed new techniques to improve forecast accuracy at sub-seasonal to decadal scales. Blue-Action specifically worked to understand and simulate the linkages between the Arctic and the global climate system, and the Arctic’s role in generating weather patterns associated with hazardous conditions and climatic extremes. In doing so, Blue-Action aimed to improve the safety and wellbeing of people in the Arctic and across the Northern Hemisphere, reduce the risks associated with Arctic operations and resource exploitation, and support evidence-based decision-making by policymakers worldwide.

VOS/SOOP tracks are usually repeated several times a year and inform about the marine sinks and sources of atmospheric carbon dioxide on a global bases and their variability. Data from this network has been made available to the scientific community and interested public via the Carbon Dioxide Information Analysis Centre (CDIAC) Oceans at the Department of Energy, USA, since the early 1990’s where PIs submitted and shared their data. In 2017, CDIAC Ocean will be named Ocean Carbon Data System (OCADS) and join NOAA’s National Centers for Environmental Information (NCEI). In 2007, the marine biogeochemistry community coordinated by the International Ocean Carbon Coordination Project (IOCCP), launched the Surface Ocean Carbon Dioxide ATlas (SOCAT) in order to uniformly quality control and format the data with detailed documentation. Underway carbon dioxide data from the VOS network are integrated in SOCAT.

Output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats and aggregated into the predominant habitats of the Marine Strategy Framework Directive. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to Norway in the North. The map was produced using a "top-down" modelling approach using classified habitat descriptors to determine a final output habitat. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Habitat descriptors (excepting Substrate) are calculated using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced in Arc Model Builder (10.1). For more information on the modelling process please read the EMODnet Seabed Habitats The model was created using raster input layers with a cell size of 0.002dd (roughly 250 meters). The model includes the sublittoral zone only; due to the high variability of the littoral zone, a lack of detailed substrate data and the resolution of the model, it is difficult to predict littoral habitats at this scale.

Confidence in the full output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. Values are on a range from 1 (low confidence) to 3 (high confidence). Confidence is calculated by amalgamating the confidence values of the underlying applicable habitat descriptors used to generate the habitat value in the area in question. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Confidence in habitat descriptors are driven by the confidence in the source data used to determine the descriptor, and the confidence in the threshold/margin (areas closer to a boundary between two classes will have lower confidence). Confidence values are also available for each habitat descriptor and input data layer.

Level 2 sub-skin Sea Surface Temperature derived from AVHRR on Metop, global and provided in full-resolution swath (1 km at nadir), in GHRSST compliant netCDF format. The satellite input data has successively come from Metop-A, Metop-B and Metop-C level 1 data processed at EUMETSAT. SST is retrieved from AVHRR infrared channels (3.7, 10.8 and 12.0 µm) using a multispectral algorithm and a cloud mask. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, Sea Surface Temperature from an analysis, together with a radiative transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. The quality of the products is monitored regularly by daily comparison of the satellite estimates against buoy measurements.The product format is compliant with the GHRSST Data Specification (GDS) version 2. Users are advised to use data only with quality levels 3,4 and 5.