The SDC_MED_DP2 product contains 55 sliding decadal temperature fields (1955-1964, 1956-1965, 1957-1966, …, 2009-2018) at 1/8° horizontal resolution obtained in the 0-2000m layer and two derived OHC annual anomaly estimates for the 0-700m and the 0-2000m layers. Sliding decades of annual Temperature fields were obtained from an integrated Mediterranean Sea dataset covering the time period 1955-2018, which combines data extracted from SeaDataNet infrastructure at the end of July 2019 (SDC_MED_DATA_TS_V2, https://doi.org/10.12770/3f8eaace-9f9b-4b1b-a7a4-9c55270e205a) and the Coriolis Ocean Dataset for Reanalysis (CORA 5.2, accessed in July 2020, https://archimer.ifremer.fr/doc/00595/70726/). The resulting annual OHC anomaly time series span the 1960-2014 period. The analysis was performed with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.6.1.

This data set corresponds to the global offshore wind farm boundaries with the following attributes for each project: + WindfarmId (ID of the windfarm) + Name (Name of the windfarm) + Country (Country code) + Status (Status code) + WindfarmStatus (Windfarm Status or Project Status) + StatusComments (Comments on the Windfarm Status or Project Status) + CapacityMWMin (Capacity of the windfarm - Min) + CapacityMWMax (Capacity of the windfarm - Max) + NoTurbinesMin (Number of turbines - Min) + NoTurbinesMax (Number of turbines - Max) + Comments (Comments) + TurbineMWMin (Capacity of the turbine (set-up in the windfarm) - Min) + TurbineMWMax (Capacity of the turbine (set-up in the windfarm) - Max) + OtherNames (Other name of the windfarm) + CountryName (Country where the windfarm is set) + Lat (Geographic coordinate - centre latitude) + Lon (Geographic coordinate - centre longitude) + IsEstimatedLocation (This is where we know that a project exists but we don't know its exact location.) + IsOnHold + Developers (Developer(s) of the windfarm) + Owners (Owner of the windfarm) + Operators (Operator of the windfarm) + OffshoreConstructionStarts The frequency of the database release is monthly. This data set corresponds to the release of January 2020. This data set is strictly for internal EEA use as is subjected to a commercial license. Given the limited user subscriptions available, interested users should contact the SDI Team (sdi@eea.europa.eu) to be granted access to the data set.

'''This product has been archived''' '''Short description''': You can find here the OMEGA3D observation-based quasi-geostrophic vertical and horizontal ocean currents developed by the Consiglio Nazionale delle RIcerche. The data are provided weekly over a regular grid at 1/4° horizontal resolution, from the surface to 1500 m depth (representative of each Wednesday). The velocities are obtained by solving a diabatic formulation of the Omega equation, starting from ARMOR3D data (MULTIOBS_GLO_PHY_REP_015_002 which corresponds to former version of MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012) and ERA-Interim surface fluxes. '''DOI (product) :''' https://doi.org/10.25423/cmcc/multiobs_glo_phy_w_rep_015_007

Itinéraires de randonnée et pistes cyclables du Département des Landes. Le Département des Landes propose 3 500 km d’itinéraires inscrits au Plan départemental des itinéraires de promenade et de randonnée (PDIPR) et près de 2 500 km d’itinéraires cyclables. Ces circuits sont entretenus et balisés avec des niveaux de difficultés mentionnés sur chaque parcours.

Périmètre de la CAPB

Cette couche recense les Zones d’Activités Economiques (ZAE) présentes sur le département de la Charente. Initialement crée par Charente Développement, il s'agit d'un surfacique qui permet d'identifier précisément le contour de ces zones en se calant sur les données du Cadastre.

L'orthophotographie de précision planimétrique de classe A (arrêté du 16 septembre 2003) et produit en RVB (couleurs : Rouge, Vert, Bleu) constitue la composante image du géostandard PCRS. Un PCRS constitue le socle commun topographique minimal de base décrivant à très grande échelle les limites apparentes de la voirie. Il est limité aux objets les plus utiles et n'aborde aucune des logiques "métiers" par ailleurs traitées chez les gestionnaires de réseaux. Le PCRS est destiné à servir de support topographique à un grand nombre d'applications requérant la meilleure précision possible. Il répond essentiellement aux exigences de la réglementation dite "anti-endommagement" ou réforme DT-DICT portant sur les travaux à proximité des réseaux, notamment sous la forme d'un fond de plan utilisable dans le cadre des échanges entre gestionnaires et exploitants. Conçu pour facilité les échanges entre les plans de type DAO et les SIG des collectivité et exploitants, les objets du PCRS gèrent peu d'attributs autres que ceux liés à la généalogie de leur acquisition, majoritairement par levé topographique.

This metadata describes the ICES data on the temporal development of the Lusitanian/Boreal species ratio in the period from 19657 to 2016. Key message: The ratio between the number of Lusitanian (warm-favouring) and Boreal (cool-favouring) species are significantly increasing in several North-East Atlantic marine areas whereas there is no significant changes in all the southern areas. Changes in ratios are most apparent in the North Sea, Irish Sea and West of Scotland. Furthermore, it seems that Lusitanian species have not spread in all northward directions, but have followed two particular routes, through the English Channel and north around Scotland Blue dots indicates L/B ratios below 1 (dominance of Boreal species) Yellow dots indicates L/B ratios >=1 and <2 (dominance of Lusitanian species) Red dots indicates L/B ratios >=2 (high dominance of Lusitanian species) The dataset is derived from the ICES data portal 'DATRAS' (the Database of Trawl Surveys). DATRAS is an online database of trawl surveys with access to standard data products. DATRAS stores data collected primarily from bottom trawl fish surveys coordinated by ICES expert groups. The survey data are covering the Baltic Sea, Skagerrak, Kattegat, North Sea, English Channel, Celtic Sea, Irish Sea, Bay of Biscay and the eastern Atlantic from the Shetlands to Gibraltar. At present, there are more than 56 years of continuous time series data in DATRAS, and survey data are continuously updated by national institutions. The dataset has been used in the EEA Indicator "Changes in fish distribution in European seas" https://www.eea.europa.eu/data-and-maps/indicators/fish-distribution-shifts/assessment-1. The dataset has been used for this static map: https://www.eea.europa.eu/en/analysis/indicators/changes-in-fish-distribution-in/temporal-development-of-the-ratio

'''DEFINITION''' The CMEMS NORTHWESTSHELF_OMI_tempsal_extreme_var_temp_mean_and_anomaly OMI indicator is based on the computation of the annual 99th percentile of Sea Surface Temperature (SST) from model data. Two different CMEMS products are used to compute the indicator: The North-West Shelf Multi Year Product (NWSHELF_MULTIYEAR_PHY_004_009) and the Analysis product (NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013). Two parameters are included on this OMI: * Map of the 99th mean percentile: It is obtained from the Multi Year Product, the annual 99th percentile is computed for each year of the product. The percentiles are temporally averaged over the whole period (1993-2019). * Anomaly of the 99th percentile in 2020: The 99th percentile of the year 2020 is computed from the Analysis product. The anomaly is obtained by subtracting the mean percentile from the 2020 percentile. This indicator is aimed at monitoring the extremes of sea surface temperature every year and at checking their variations in space. The use of percentiles instead of annual maxima, makes this extremes study less affected by individual data. This study of extreme variability was first applied to the sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, such as sea surface temperature and significant wave height (Pérez Gómez et al 2018 and Alvarez Fanjul et al., 2019). More details and a full scientific evaluation can be found in the CMEMS Ocean State report (Alvarez Fanjul et al., 2019). '''CONTEXT''' This domain comprises the North West European continental shelf where depths do not exceed 200m and deeper Atlantic waters to the North and West. For these deeper waters, the North-South temperature gradient dominates (Liu and Tanhua, 2021). Temperature over the continental shelf is affected also by the various local currents in this region and by the shallow depth of the water (Elliott et al., 1990). Atmospheric heat waves can warm the whole water column, especially in the southern North Sea, much of which is no more than 30m deep (Holt et al., 2012). Warm summertime water observed in the Norwegian trench is outflow heading North from the Baltic Sea and from the North Sea itself. '''CMEMS KEY FINDINGS''' The 99th percentile SST product can be considered to represent approximately the warmest 4 days for the sea surface in Summer. Maximum anomalies for 2020 are up to 4oC warmer than the 1993-2019 average in the western approaches, Celtic and Irish Seas, English Channel and the southern North Sea. For the atmosphere, Summer 2020 was exceptionally warm and sunny in southern UK (Kendon et al., 2021), with heatwaves in June and August. Further north in the UK, the atmosphere was closer to long-term average temperatures. Overall, the 99th percentile SST anomalies show a similar pattern, with the exceptional warm anomalies in the south of the domain. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product)''' https://doi.org/10.48670/moi-00273

This dataset is the coastal zone land surface region from Europe, derived from the coastline towards inland, as a series of 10 consecutive buffers of 1km width each. The coastline is defined by the extent of the Corine Land Cover 2018 (raster 100m) version 20 accounting layer. In this version all Corine Land Cover pixels with a value of 523, corresponding to sea and oceans, were considered as non-land surface and thus were excluded from the buffer zone.