L'État a confié à l'IGN le développement du référentiel à grande échelle (RGE). Pour ce faire, il fait appel à ses moyens propres ainsi qu’à des partenariats avec des producteurs principalement de la sphère publique. Le RGE est constitué de 5 composantes: - orthophotographique (BD ORTHO), - topographique (BD TOPO), - adresse (BD adresse), - parcellaire (BD parcellaire) - et altimétrique (RGE ALTI). Remarque : seules les BD TOPO thème hydrographique, BD ORTHO 5m, BD ORTHO 50 cm sont sous Licence Ouverte. Les autres données du RGE sont soumises aux licences IGN. ----- Etat de la disponibilité de la donnée (sous Licence Ouverte): - Data.gouv : les BD TOPO thème hydrographique, BD ORTHO 5m, BD ORTHO 50 cm (pour certains départements) sont accessibles sous format shape, xml et htlm. Mise à jour irrégulière. - PIGMA : données BD ORTHO 50 cm (2015) et BD TOPO v2.2 (2016) accessibles au format shape sous licence IGN. Aucune mise à jour. - Géocatalogue : données BD ORTHO v2 (2013) au format Tif et BD TOPO v2.1 (2015) au format shape, MIF/MID accessibles sous licence IGN. Aucune mise à jour. - IGN : renvoi direct au site IGN où les données sont téléchargeables au format JPEG et shape sous licence IGN. Mise à jour irrégulière.

'''Short description:''' The IBI-MFC provides a high-resolution wave reanalysis product for the Iberia-Biscay-Ireland (IBI) area starting in 01/01/1980 and being regularly extended on a yearly basis. The model system is run by Nologin with the support of CESGA in terms of supercomputing resources. The Multi-Year model configuration is based on the MFWAM model developed by Météo-France (MF), covering the same region as the IBI-MFC Near Real Time (NRT) analysis and forecasting product and with the same horizontal resolution (1/36º). The system assimilates significant wave height (SWH) altimeter data and wave spectral data (Envisat and CFOSAT), supplied by MF. Both, the MY and the NRT products, are fed by ECMWF hourly winds. Specifically, the MY system is forced by the ERA5 reanalysis wind data. As boundary conditions, the NRT system uses the 2D wave spectra from the Copernicus Marine GLOBAL forecast system, whereas the MY system is nested to the GLOBAL reanalysis. The product offers hourly instantaneous fields of different wave parameters, including Wave Height, Period and Direction for total spectrum; fields of Wind Wave (or wind sea), Primary Swell Wave and Secondary Swell for partitioned wave spectra; and the highest wave variables, such as maximum crest height and maximum crest-to-trough height. Besides, air-sea fluxes are provided. Additionally, climatological parameters of significant wave height (VHM0) and zero -crossing wave period (VTM02) are delivered for the time interval 1993-2016. '''DOI (Product)''': https://doi.org/10.48670/moi-00030

'''DEFINITION''' Heat transport across lines are obtained by integrating the heat fluxes along some selected sections and from top to bottom of the ocean. The values are computed from models’ daily output. The mean value over a reference period (1993-2014) and over the last full year are provided for the ensemble product and the individual reanalysis, as well as the standard deviation for the ensemble product over the reference period (1993-2014). The values are given in PetaWatt (PW). '''CONTEXT''' The ocean transports heat and mass by vertical overturning and horizontal circulation, and is one of the fundamental dynamic components of the Earth’s energy budget (IPCC, 2013). There are spatial asymmetries in the energy budget resulting from the Earth’s orientation to the sun and the meridional variation in absorbed radiation which support a transfer of energy from the tropics towards the poles. However, there are spatial variations in the loss of heat by the ocean through sensible and latent heat fluxes, as well as differences in ocean basin geometry and current systems. These complexities support a pattern of oceanic heat transport that is not strictly from lower to high latitudes. Moreover, it is not stationary and we are only beginning to unravel its variability. '''CMEMS KEY FINDINGS''' The mean transports estimated by the ensemble global reanalysis are comparable to estimates based on observations; the uncertainties on these integrated quantities are still large in all the available products. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00245

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The ibi_omi_tempsal_sst_area_averaged_anomalies product for 2021 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1993 and averaged over the Iberia-Biscay-Irish Seas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish Seas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-ATL-SST.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the European North West Shelf Seas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish Seas built from the ESA Climate Change Initiative (CCI) (Merchant et al., 2019) and Copernicus Climate Change Service (C3S) initiatives. Anomalies are computed against the 1993-2014 reference period. '''CONTEXT''' Sea surface temperature (SST) is a key climate variable since it deeply contributes in regulating climate and its variability (Deser et al., 2010). SST is then essential to monitor and characterise the state of the global climate system (GCOS 2010). Long-term SST variability, from interannual to (multi-)decadal timescales, provides insight into the slow variations/changes in SST, i.e. the temperature trend (e.g., Pezzulli et al., 2005). In addition, on shorter timescales, SST anomalies become an essential indicator for extreme events, as e.g. marine heatwaves (Hobday et al., 2018). '''CMEMS KEY FINDINGS''' The overall trend in the SST anomalies in this region is 0.011 ±0.001 °C/year over the period 1993-2021. '''DOI (product):''' https://doi.org/10.48670/moi-00256

'''DEFINITION''' The Strong Wave Incidence index is proposed to quantify the variability of strong wave conditions in the Iberia-Biscay-Ireland regional seas. The anomaly of exceeding a threshold of Significant Wave Height is used to characterize the wave behavior. A sensitivity test of the threshold has been performed evaluating the differences using several ones (percentiles 75, 80, 85, 90, and 95). From this indicator, it has been chosen the 90th percentile as the most representative, coinciding with the state-of-the-art. Two CMEMS products are used to compute the Strong Wave Incidence index: • IBI-WAV-MYP: IBI_REANALYSIS_WAV_005_006 • IBI-WAV-NRT: IBI_ANALYSIS_FORECAST_WAV_005_005 The Strong Wave Incidence index (SWI) is defined as the difference between the climatic frequency of exceedance (Fclim) and the observational frequency of exceedance (Fobs) of the threshold defined by the 90th percentile (ThP90) of Significant Wave Height (SWH) computed on a monthly basis from hourly data of IBI-WAV-MYP product: SWI = Fobs(SWH > ThP90) – Fclim(SWH > ThP90) Since the Strong Wave Incidence index is defined as a difference of a climatic mean and an observed value, it can be considered an anomaly. Such index represents the percentage that the stormy conditions have occurred above/below the climatic average. Thus, positive/negative values indicate the percentage of hourly data that exceed the threshold above/below the climatic average, respectively. '''CONTEXT''' Ocean waves have a high relevance over the coastal ecosystems and human activities. Extreme wave events can entail severe impacts over human infrastructures and coastal dynamics. However, the incidence of severe (90th percentile) wave events also have valuable relevance affecting the development of human activities and coastal environments. The Strong Wave Incidence index based on the CMEMS regional analysis and reanalysis product provides information on the frequency of severe wave events. The IBI-MFC covers the Europe’s Atlantic coast in a region bounded by the 26ºN and 56ºN parallels, and the 19ºW and 5ºE meridians. The western European coast is located at the end of the long fetch of the subpolar North Atlantic (Mørk et al., 2010), one of the world’s greatest wave generating regions (Folley, 2017). Several studies have analyzed changes of the ocean wave variability in the North Atlantic Ocean (Bacon and Carter, 1991; Kursnir et al., 1997; WASA Group, 1998; Bauer, 2001; Wang and Swail, 2004; Dupuis et al., 2006; Wolf and Woolf, 2006; Dodet et al., 2010; Young et al., 2011; Young and Ribal, 2019). The observed variability is composed of fluctuations ranging from the weather scale to the seasonal scale, together with long-term fluctuations on interannual to decadal scales associated with large-scale climate oscillations. Since the ocean surface state is mainly driven by wind stresses, part of this variability in Iberia-Biscay-Ireland region is connected to the North Atlantic Oscillation (NAO) index (Bacon and Carter, 1991; Hurrell, 1995; Bouws et al., 1996, Bauer, 2001; Woolf et al., 2002; Tsimplis et al., 2005; Gleeson et al., 2017). However, later studies have quantified the relationships between the wave climate and other atmospheric climate modes such as the East Atlantic pattern, the Arctic Oscillation pattern, the East Atlantic Western Russian pattern and the Scandinavian pattern (Izaguirre et al., 2011, Matínez-Asensio et al., 2016). The Strong Wave Incidence index provides information on incidence of stormy events in four monitoring regions in the IBI domain. The selected monitoring regions (Figure 1.A) are aimed to provide a summarized view of the diverse climatic conditions in the IBI regional domain: Wav1 region monitors the influence of stormy conditions in the West coast of Iberian Peninsula, Wav2 region is devoted to monitor the variability of stormy conditions in the Bay of Biscay, Wav3 region is focused in the northern half of IBI domain, this region is strongly affected by the storms transported by the subpolar front, and Wav4 is focused in the influence of marine storms in the North-East African Coast, the Gulf of Cadiz and Canary Islands. More details and a full scientific evaluation can be found in the CMEMS Ocean State report (Pascual et al., 2020). '''CMEMS KEY FINDINGS''' The analysis of the index in the last decades do not show significant trends of the strong wave conditions over the period 1992-2021 with 99% confidence. The maximum wave event reported in region WAV1 (B) occurred in February 2014, producing an increment of 25% of strong wave conditions in the region. Two maximum wave events are found in WAV2 (C) with an increment of 15% of high wave conditions in November 2009 and February 2014. As in regions WAV1 and WAV2, in the region WAV3 (D), a strong wave event took place in February 2014, this event is one of the maximum events reported in the region with an increment of strong wave conditions of 20%, two months before (December 2013) there was a storm of similar characteristics affecting this region, other events of similar magnitude are detected on October 2000 and November 2009. The region WAV4 (E) present its maximum wave event in January 1996, such event produced a 25% of increment of strong wave conditions in the region. Despite of each monitoring region is affected by independent wave events; the analysis shows several past higher-than-average wave events that were propagated though several monitoring regions: November-December 2010 (WAV3 and WAV2); February 2014 (WAV1, WAV2, and WAV3); and February-March 2018 (WAV1 and WAV4). The analysis of the NRT period (January 2022 onwards) depicts a significant event that occurred in November 2022, which affected the WAV2 and WAV3 regions, resulting in a 15% and 25% increase in maximum wave conditions, respectively. In the case of the WAV3 region, this event was the strongest event recorded in this region. In the WAV4 region, an event that occurred in February 2024 was the second most intense on record, showing an 18% increase in strong wave conditions in the region. In the WAV1 region, the NRT period includes two high-intensity events that occurred in February 2024 (21% increase in strong wave conditions) and April 2022 (18% increase in maximum wave conditions). '''Figure caption''' (A) Mean 90th percentile of Sea Wave Height computed from IBI_REANALYSIS_WAV_005_006 product at an hourly basis. Gray dotted lines denote the four monitoring areas where the Strong Wave Incidence index is computed. (B, C, D, and E) Strong Wave Incidence index averaged in monitoring regions WAV1 (A), WAV2 (B), WAV3 (C), and WAV4 (D). Panels show merged results of two CMEMS products: IBI_REANALYSIS_WAV_005_006 (blue), IBI_ANALYSIS_FORECAST_WAV_005_005 (orange). The trend and 99% confidence interval of IBI-MYP product is included (bottom right). '''DOI (product):''' https://doi.org/10.48670/moi-00251

'''Short description:''' This product consists of 3D fields of Particulate Organic Carbon (POC), Particulate Backscattering coefficient (bbp) and Chlorophyll-a concentration (Chla) at depth. The reprocessed product is provided at 0.25°x0.25° horizontal resolution, over 36 levels from the surface to 1000 m depth. A neural network method estimates both the vertical distribution of Chla concentration and of particulate backscattering coefficient (bbp), a bio-optical proxy for POC, from merged surface ocean color satellite measurements with hydrological properties and additional relevant drivers. '''DOI (product):''' https://doi.org/10.48670/moi-00046

Bulletin Sanitaire Végétale: nombre de parcelles à maturité par commune. (métadonnée en cours)

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' Experimental altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean with a 5Hz (~1.3km) sampling. All the missions are homogenized with respect to a reference mission (see QUID document or http://duacs.cls.fr [http://duacs.cls.fr] pages for processing details). The product gives additional variables (e.g. Mean Dynamic Topography, Dynamic Atmosphic Correction, Ocean Tides, Long Wavelength Errors, Internal tide, …) that can be used to change the physical content for specific needs This product was generated as experimental products in a CNES R&D context. It was processed by the DUACS multimission altimeter data processing system. '''DOI (product) :''' https://doi.org/10.48670/moi-00137

'''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