Moving 10-years analysis of Chlorophyll-a -1.0-ANA at Northeast Atlantic Ocean 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 centred average of each season. Decades span from 1985-1994 until 2005-2014. Observational data span from 1970 to 2015. Depth range (IODE standard depths): -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -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. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Signal to noise ratio and correlation length were 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. Units: mg/m^3

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.

The Drifting Buoys GDAC -Global Data Assembly Centre- is the repository of surface drifters data. Both NRT -Near Real Time- and DM -Delayed Mode- data are available on the GDAC. Drifters report generally trajectories, sea-surface temperatures, atmospheric pressures at sea-level, as well as sea-surface salinity or sub-surface temperature in the ocean top layer.

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.

A total number of 277 water samples were collected during distinct oceanographic cruises or at fixed stations across coastal systems of France and Senegal. The seawater samples were progressively filtered onto size-fractionated filters (representing micro, nano and pico-plankton). Metabarcoding of the V4 domain of the Eukaryotic 18S rDNA region was carried out to characterize the genetic diversity of the sampled communities. Genomic DNA was extracted following the DNA extraction kit Nucleospin Plant II (Macherey-Nagel) and the V4 markers were amplified with a taq polymerase (Phusion High-Fidelity PCR Master Mix with GC Buffer). Sequencing was performed by the Genotoul sequencing platform (get.genotoul.fr) with the Illumina MISeq method (2x250 bp). The present dataset gathers the different results issued from sequencing. This dataset was submitted to sequence cleaning, filtering, taxonomic assignment and OTU clustering, which resulted in a final dataset also presented.

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.

Description of attributes for time series of sea level trend for the last 10 yrs for the Mediterranean basin and for each NUTS3 region along the coast.

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.

Specification of the desirable and recommended product attributes for generating time series of sea level trend for the last 10 years for the Mediterranean basin for each NUTS3 region along the coast.

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.