Pentadal time-series of the area in the North Atlantic (IHO, 1953) where ice occurred. On a 1 degree grid find all cells that experienced ice in at least 1 month of each 5 year period between 1915 and 2014, and then calculate the total area that these cells covered.

The All-Atlantic Ocean Research and Innovation Alliance (AAORIA) is the result of science diplomacy efforts involving countries from both sides of the Atlantic Ocean. It builds upon the success of two existing cooperative agreements – the Galway Statement on Atlantic Ocean Cooperation which was signed by the European Union, United States, and Canada in 2013; and the Belem Statement on Atlantic Ocean Research and Innovation Cooperation which was signed by the European Union, Brazil, and South Africa in 2017 as well as on several other bilateral and multilateral agreements. AAORIA aims to enhance marine research and innovation cooperation along and across the Atlantic Ocean. In 2022, the “All-Atlantic Declaration” was signed to revitalize collaboration among current initiatives and enhance the coordination between the Galway Working Groups, All-Atlantic Joint Pilot Actions, and related projects. Additionally, it aims to engage new partners and initiatives to join the All-Atlantic community.

It's a study of MPA connectivity with assessment of : -size -shape -spacing between each MPA

'''DEFINITION''' The global annual chlorophyll anomaly is computed by subtracting a reference climatology (1997-2014) from the annual chlorophyll mean, on a pixel-by-pixel basis and in log10 space. Both the annual mean and the climatology are computed employing ESA Ocean Colour Climate Change Initiative (ESA OC-CCI, Sathyendranath et al., 2018a) global products (i.e. using the standard OC-CCI chlorophyll algorithms, OCI) as distributed by CMEMS. '''CONTEXT''' Phytoplankton – and chlorophyll concentration as a proxy for phytoplankton – respond rapidly to changes in their physical environment. Some of those changes are seasonal and are determined by light and nutrient availability (Racault et al., 2012). By comparing annual mean values to a climatology, we effectively remove the seasonal signal, while retaining information on potential events during the year. Chlorophyll anomalies can be correlated to climate indexes in particular regions, such as the ENSO index in the equatorial Pacific (Behrenfeld et al. 2006; Racault et al., 2012) and the IOD index in the Indian Ocean (Brewin et al., 2012). It is important to study chlorophyll anomalies in consonance with sea surface temperature and sea level anomalies, as increases in chlorophyll are generally consistent with decreases in SST and sea level anomalies, suggesting an increase in mixing and vertical nutrient transport (von Schuckmann et al., 2016). '''CMEMS KEY FINDINGS''' The average global chlorophyll anomaly 2019 is -0.02 log10(mg m-3), with a maximum value of 1.7 log10(mg m-3) and a minimum value of -3.2 log10(mg m-3). That is to say that, in average, the annual 2019 mean value is slightly lower (96%) than the 1997-2014 climatological value. The positive signals reported in 2016 and 2017 (Sathyendranath et al., 2018b) in the southern Pacific Ocean could still be observed in the 2019 map, while the significant negative anomalies in the tropical waters of the northern Pacific Ocean were also detected to a lesser extent. Areas showing a change of anomaly sign from 2019 include the southern coast of Japan (no anomaly to positive) and the tropical Atlantic (anomalies close to zero for 2019). A marked increase in chlorophyll concentration was observed during 2019 in the Great Australian Bight, while negative anomalies became stronger in the Guatemala Basin and the region south of the Gulf of Guinea and, with values of chlorophyll reaching as low as 30% of the climatological value (anomaly < -0.5 log10(mg m-3)). The persistent positive anomalies in the higher latitudes of the North Atlantic (> 40°) match the cooling observed in the 2018 and previous years SST anomaly maps.

This product attempt to follow up on the sea level rise per stretch of coast of the North Atlantic, over past 10 years as follows: • Characterization of absolute sea level trend at annual resolution, along the coasts of EU Member States (including Outermost Regions), Canada, Faroes, Greenland, Iceland, Mexico, Morocco, Norway and USA; The stretchs or coast are defined by the administrative regions of the Atlantic Coast: • from NUTS3** administrative division for EU countries (see Eurostat), and • from GADM*** administrative divisions for non-EU countries. ** Third level of Nomenclature of Territorial Units for Statistics *** Global Administrative Areas For absolute sea level trend for 10 years we extract the information from grided satellite altimetry data and extrapolate it to the nearest strecth of coast. The product is Provided in tabular form and as a map layer.

Maisons éclusières sur les départements de la Gironde et du Lot-et-Garonne.

Assessment of the confidence limits of the data base by means of evaluation of the two involved numerical models: The wave model WAM (Parameter: Significant wave height Hs) and the Atmospheric model SKIRON (Parameter: Wind Speed 10m)

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The time series are derived from the regional chlorophyll reprocessed (REP) products as distributed by CMEMS which, in turn, result from the application of the regional chlorophyll algorithms over remote sensing reflectances (Rrs) provided by the ESA Ocean Colour Climate Change Initiative (ESA OC-CCI, Sathyendranath et al. 2019; Jackson 2020). Daily regional mean values are calculated by performing the average (weighted by pixel area) over the region of interest. A fixed annual cycle is extracted from the original signal, using the Census-I method as described in Vantrepotte et al. (2009). The deasonalised time series is derived by subtracting the mean seasonal cycle from the original time series, and then fitted to a linear regression to, finally, obtain the linear trend. '''CONTEXT''' Phytoplankton – and chlorophyll concentration as a proxy for phytoplankton – respond rapidly to changes in environmental conditions, such as temperature, light and nutrients availability, and mixing. The response in the North Atlantic ranges from cyclical to decadal oscillations (Henson et al., 2009); it is therefore of critical importance to monitor chlorophyll concentration at multiple temporal and spatial scales, in order to be able to separate potential long-term climate signals from natural variability in the short term. In particular, phytoplankton in the North Atlantic are known to respond to climate variability associated with the North Atlantic Oscillation (NAO), with the initiation of the spring bloom showing a nominal correlation with sea surface temperature and the NAO index (Zhai et al., 2013). '''CMEMS KEY FINDINGS''' While the overall trend average for the 1997-2020 period in the North Atlantic Ocean is slightly positive (0.92 ± 0.13 % per year), an underlying low frequency harmonic signal can be seen in the deseasonalised data. The annual average for the region in 2020 is 0.31 mg m-3. Though no appreciable changes in the timing of the spring and autumn blooms have been observed during 2020, these reached higher chlorophyll values than the average for the time series. In particular, the spring bloom maximum in 2020, circa 0.80 mg m-3, showed an increase in chlorophyll concentration from the observations during the 2016-2019 spring blooms. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00194

Calculation of the average annual sediment balance per stretch of coast for the past 10 years.

This product attempt to follow up on the sea level rise per stretch of coast of the North Atlantic, over 50 years as follows: • Characterization of absolute sea level trend at annual resolution, along the coasts of EU Member States (including Outermost Regions), Canada, Faroes, Greenland, Iceland, Mexico, Morocco, Norway and USA; The stretchs or coast are defined by the administrative regions of the Atlantic Coast: • from NUTS3** administrative division for EU countries (see Eurostat), and • from GADM*** administrative divisions for non-EU countries. ** Third level of Nomenclature of Territorial Units for Statistics *** Global Administrative Areas For relative sea level trend for 50 years we extract the information from coastal tide gauges data available at each stretch of coast, if there is not a tide gauge there is a data gap. The product is Provided in tabular form and as a map layer.