'''DEFINITION''' The indicator of Volume Transport Anomaly in Selected Vertical Sections in the Iberia–Biscay–Ireland (IBI) region (OMI_CIRCULATION_VOLTRANS_IBI_section_integrated_anomalies) is defined as the time series of annual mean volume transport calculated across a set of vertical ocean sections. These sections have been selected to represent the temporal variability of key ocean currents within the IBI domain. The monitored ocean currents include the transport towards the North Sea through the Rockall Trough (RTE) (Holliday et al., 2008; Lozier and Stewart, 2008), the Canary Current (CC) (Knoll et al., 2002; Mason et al., 2011), the Azores Current (AC) (Mason et al., 2011), the Algerian Current (ALG) (Tintoré et al., 1988; Benzohra and Millot, 1995; Font et al., 1998), and the net transport along the 48° N latitude parallel (N48) (see OMI figure). To produce ensemble-based results, six datasets provided by the Copernicus Marine Service have been used: * '''IBI-REA''' & '''IBI-INT''': IBI_MULTIYEAR_PHY_005_002 (reanalysis and interim datasets) * '''GLO-REA''': GLOBAL_MULTIYEAR_PHY_001_030 (reanalysis) * '''ARMOR''': MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 (reprocessed observations) * '''MED-REA''': MEDSEA_MULTIYEAR_PHY_006_004 (reanalysis) * '''NWS-REA''': NWSHELF_MULTIYEAR_PHY_004_009 (reanalysis) The time series displays the ensemble mean (blue line), the ensemble spread (grey shaded area), and the mean transport with reversed sign (red dashed line), which indicates the threshold of anomaly values corresponding to a reversal in the direction of the current transport. In addition, the trend analysis at the 95% confidence level is shown in the bottom-right corner of each diagram. Further details on the product are provided in the corresponding Product User Manual (de Pascual-Collar et al., 2026a) and Quality Information Document (de Pascual-Collar et al., 2026b), as well as in de Pascual-Collar et al., 2024. '''CONTEXT''' The IBI area is a highly complex region characterized by a remarkable variety of ocean currents. Among them, we can highlight those that originate as a result of the closure of the North Atlantic Drift (Mason et al., 2011; Holliday et al., 2008; Peliz et al., 2007; Bower et al., 2002; Knoll et al., 2002; Pérez et al., 2001; Jia, 2000); the subsurface currents flowing northward along the continental slope (de Pascual-Collar et al., 2019; Pascual et al., 2018; Machín et al., 2010; Fricourt et al., 2007; Knoll et al., 2002; Mazé et al., 1997; White & Bowyer, 1997); and the exchange currents occurring in the Strait of Gibraltar and the Alboran Sea (Sotillo et al., 2016; Font et al., 1998; Benzohra & Millot, 1995; Tintoré et al., 1988). The variability of ocean currents in the IBI domain is relevant to the global thermohaline circulation and other climatic and environmental processes. For example, as discussed by Fasullo and Trenberth (2008), subtropical gyres play a crucial role in the meridional energy balance. The poleward salt transport of Mediterranean water, driven by subsurface slope currents, has significant implications for salinity anomalies in the Rockall Trough and the Nordic Seas, as studied by Holliday (2003), Holliday et al. (2008), and Bozec et al. (2011). The Algerian Current serves as the only pathway for Atlantic Water to reach the Western Mediterranean. '''CMEMS KEY FINDINGS''' The volume transport time series reveal periods during which the monitored currents exhibited notably high or low variability. Specifically, the RTE current shows pronounced variability in 2010 and during 2014–2015; the N48 section between 2012 and 2014; the ALG current in 2006 and 2017; the AC current between 2005–2007 and in 2021; and the CC current between 2005–2007. Furthermore, certain periods display anomalies of sufficient magnitude (in absolute value) to indicate a reversal in the net transport direction of the current. This is the case for the ALG current in 2017 and 2024 (with net transport towards the west), and for the CC current in 2010 (with net transport towards the north). Trend analysis over the period 1993–2023 does not reveal any statistically significant trends for the monitored currents. However, the confidence interval for the trend in the ALG section is close to rejecting the null hypothesis of no trend. '''DOI (product):''' https://doi.org/10.48670/mds-00351

'''Short description:''' The IBI-MFC provides the biogeochemical multi-year (non assimilative) product for the Iberia-Biscay-Ireland region starting in 01/01/1993, extended every year to use available reprocessed upstream data and regularly updated on a monthly basis to cover the period up to month M-4 using an interim processing system. The model system is designed, developed and run by Mercator Ocean International, while the operational product post-processing and interim processing system are run by NOW Systems with the support of CESGA supercomputing centre. The biogeochemical model PISCES is run simultaneously with the ocean physical NEMO model, generating products at 1/36° horizontal resolution. The PISCES model is able to simulate the first levels of the marine food web, from nutrients up to mesozooplankton and it has 24 state variables. The product provides daily, monthly and yearly averages of the main biogeochemical variables. Additionally, climatological parameters (monthly mean and standard deviation) of these variables for the period 1993-2016 are delivered. '''DOI (Product)''': https://doi.org/10.48670/moi-00028

'''Short description:''' For the Atlantic Ocean - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Near Real-Time Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are updated several times daily to provide the best product timeliness. '''DOI (product) :''' https://doi.org/10.48670/mds-00331

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the '''Global''' Ocean '''Satellite Observations''', ACRI-ST company (Sophia Antipolis, France) is providing '''Chlorophyll-a''' and '''Optics''' products [1997 - present] based on the '''Copernicus-GlobColour''' processor. * '''Chlorophyll and Bio''' products refer to Chlorophyll-a, Primary Production (PP) and Phytoplankton Functional types (PFT). Products are based on a multi sensors/algorithms approach to provide to end-users the best estimate. Two dailies Chlorophyll-a products are distributed: ** one limited to the daily observations (called L3), ** the other based on a space-time interpolation: the '''Cloud Free''' (called L4). * '''Optics''' products refer to Reflectance (RRS), Suspended Matter (SPM), Particulate Backscattering (BBP), Secchi Transparency Depth (ZSD), Diffuse Attenuation (KD490) and Absorption Coef. (ADG/CDM). * The spatial resolution is 4 km. For Chlorophyll, a 1 km over the Atlantic (46°W-13°E , 20°N-66°N) is also available for the '''Cloud Free''' product, plus a 300m Global coastal product (OLCI S3A & S3B merged). *Products (Daily, Monthly and Climatology) are based on the merging of the sensors SeaWiFS, MODIS, MERIS, VIIRS-SNPP&JPSS1, OLCI-S3A&S3B. Additional products using only OLCI upstreams are also delivered. * Recent products are organized in datasets called NRT (Near Real Time) and long time-series in datasets called REP/MY (Multi-Year). The NRT products are provided one day after satellite acquisition and updated a few days after in Delayed Time (DT) to provide a better quality. An uncertainty is given at pixel level for all products. To find the '''Copernicus-GlobColour''' products in the catalogue, use the search keyword '''GlobColour'''. See [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-OC-QUID-009-030-032-033-037-081-082-083-085-086-098.pdf QUID document] for a detailed description and assessment. '''DOI (product) :''' https://doi.org/10.48670/moi-00075

'''DEFINITION''' The sea level ocean monitoring indicator has been presented in the Copernicus Ocean State Report #8. The ocean monitoring indicator on regional mean sea level is derived from the DUACS delayed-time (DT-2024 version, “my” (multi-year) dataset used when available) sea level anomaly maps from satellite altimetry based on a stable number of altimeters (two) in the satellite constellation. These products are distributed by the Copernicus Climate Change Service and the Copernicus Marine Service (SEALEVEL_GLO_PHY_CLIMATE_L4_MY_008_057). The time series of area averaged anomalies correspond to the area average of the maps in the Irish-Biscay-Iberian (IBI) Sea weighted by the cosine of the latitude (to consider the changing area in each grid with latitude) and by the proportion of ocean in each grid (to consider the coastal areas). The time series are corrected from regional mean GIA correction (weighted GIA mean of a 27 ensemble model following Spada et Melini, 2019). The time series are adjusted for seasonal annual and semi-annual signals and low-pass filtered at 6 months. Then, the trends/accelerations are estimated on the time series using ordinary least square fit.The trend uncertainty is provided in a 90% confidence interval. It is calculated as the weighted mean uncertainties in the region from Prandi et al., 2021. This estimate only considers errors related to the altimeter observation system (i.e., orbit determination errors, geophysical correction errors and inter-mission bias correction errors). The presence of the interannual signal can strongly influence the trend estimation considering to the altimeter period considered (Wang et al., 2021; Cazenave et al., 2014). The uncertainty linked to this effect is not considered. ""CONTEXT "" Change in mean sea level is an essential indicator of our evolving climate, as it reflects both the thermal expansion of the ocean in response to its warming and the increase in ocean mass due to the melting of ice sheets and glaciers (WCRP Global Sea Level Budget Group, 2018). At regional scale, sea level does not change homogenously. It is influenced by various other processes, with different spatial and temporal scales, such as local ocean dynamic, atmospheric forcing, Earth gravity and vertical land motion changes (IPCC WGI, 2021). The adverse effects of floods, storms and tropical cyclones, and the resulting losses and damage, have increased as a result of rising sea levels, increasing people and infrastructure vulnerability and food security risks, particularly in low-lying areas and island states (IPCC, 2022a). Adaptation and mitigation measures such as the restoration of mangroves and coastal wetlands, reduce the risks from sea level rise (IPCC, 2022b). In IBI region, the RMSL trend is modulated by decadal variations. As observed over the global ocean, the main actors of the long-term RMSL trend are associated with anthropogenic global/regional warming. Decadal variability is mainly linked to the strengthening or weakening of the Atlantic Meridional Overturning Circulation (AMOC) (e.g. Chafik et al., 2019). The latest is driven by the North Atlantic Oscillation (NAO) for decadal (20-30y) timescales (e.g. Delworth and Zeng, 2016). Along the European coast, the NAO also influences the along-slope winds dynamic which in return significantly contributes to the local sea level variability observed (Chafik et al., 2019). ""KEY FINDINGS "" Over the [1999/02/20 to 2025/10/18] period, the area-averaged sea level in the IBI area rises at a rate of 5.0 ± 0.8 mm/yr with an acceleration of 0.29 ± 0.06 mm/yr². This trend estimation is based on the altimeter measurements corrected from global GIA correction (Spada et Melini, 2019) to consider the ongoing movement of land. The TOPEX-A is no longer included in the computation of regional mean sea level parameters (trend and acceleration) with version 2024 products due to potential drifts, and ongoing work aims to develop a new empirical correction. Calculation begins in February 1999 (the start of the TOPEX-B period). '''DOI (product):''' https://doi.org/10.48670/moi-00252

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The ibi_omi_tempsal_sst_trend product includes the Sea Surface Temperature (SST) trend for the Iberia-Biscay-Irish Seas over the period 1993-2019, i.e. the rate of change (°C/year). This OMI is derived from the CMEMS REP ATL L4 SST product (SST_ATL_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 SST trend over the Iberia-Biscay-Irish Seas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps built from the ESA Climate Change Initiative (CCI) (Merchant et al., 2019) and Copernicus Climate Change Service (C3S) initiatives. Trend analysis has been performed by using the X-11 seasonal adjustment procedure (see e.g. Pezzulli et al., 2005), which has the effect of filtering the input SST time series acting as a low bandpass filter for interannual variations. Mann-Kendall test and Sens’s method (Sen 1968) were applied to assess whether there was a monotonic upward or downward trend and to estimate the slope of the trend and its 95% confidence interval. '''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''' Over the period 1993-2021, the Iberia-Biscay-Irish Seas mean Sea Surface Temperature (SST) increased at a rate of 0.011 ± 0.001 °C/Year. '''DOI (product):''' https://doi.org/10.48670/moi-00257

'''DEFINITION''' The Iberia-Biscay-Ireland (IBI) Ocean Heat Content (OHC) indicator, OMI_CLIMATE_OHC_IBI_area_averaged_anomalies, provides estimates of OHC anomalies computed over the reference period 1993–2024. The values are integrated from the surface down to 2000 m depth, using a reference density of ρ₀ = 1030 kg·m⁻³ and a specific heat capacity of cₚ = 3980 J·kg⁻¹·°C⁻¹ (e.g., von Schuckmann et al., 2009). This variable is directly proportional to the average temperature change in the ocean. Averaged time series of OHC anomalies and their associated uncertainties are computed for the IBI region (26° N–56° N; 19° W–5° E) using the following Copernicus Marine products: * '''IBI-MYP''' & '''IBI-INT''': IBI_MULTIYEAR_PHY_005_002 (reanalysis and interim datasets) * '''GLO-MYP''': GLOBAL_REANALYSIS_PHY_001_031 (reanalysis) * '''CORA''': INSITU_GLO_PHY_TS_OA_MY_013_052 (in situ observations) * '''ARMOR''': MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 (reprocessed observations) The figure displays the ensemble mean (blue line) and the ensemble spread (grey shading). Further details on the indicator and data processing are provided in the corresponding Product User Manual (de Pascual-Collar et al., 2026) and in de Pascual-Collar et al. (2023), von Schuckmann et al. (2016), and von Schuckmann et al. (2018). '''CONTEXT''' Change in OHC is a key player in ocean-atmosphere interactions and sea level change (WCRP, 2018) and can impact marine ecosystems and human livelihoods (IPCC, 2019). Additionally, OHC is one of the six Global Climate Indicators recommended by the World Meteorological Organization (WMO, 2017). In the last decades, the upper North Atlantic Ocean experienced a reversal of climatic trends for temperature and salinity. While the period 1990-2004 is characterized by decadal-scale ocean warming, the period 2005-2014 shows a substantial cooling and freshening. Such variations are discussed to be linked to ocean internal dynamics, and air-sea interactions (Fox-Kemper et al., 2021; Collins et al., 2019; Robson et al 2016). Together with changes linked to the connectivity between the North Atlantic Ocean and the Mediterranean Sea (Masina et al., 2022; Potter and Lozier, 2004), these variations affect the temporal evolution of regional ocean heat content in the IBI region. Recent studies (de Pascual-Collar et al., 2023) highlight the key role that subsurface water masses play in the OHC trends in the IBI region. These studies conclude that the vertically integrated trend is the result of different trends (both positive and negative) contributing at different layers. Therefore, the lack of representativeness of the OHC trends in the surface-intermediate waters (from 0 to 1000 m) causes the trends in intermediate and deep waters (from 1000 m to 2000 m) to be masked when they are calculated by integrating the upper layers of the ocean (from surface down to 2000 m). Among the different periods of interannual variability identified by the indicator, a sustained increase in OHC from 2023 onwards is particularly noteworthy. This short-term trend results in 2024 exhibiting the highest OHC value recorded in the time series. '''CMEMS KEY FINDINGS''' The ensemble mean OHC anomaly time series over the Iberia–Biscay–Ireland region is characterized by marked interannual variability and a a statistically significant ocean warming trend of 0.55 ± 0.3 W m⁻² (99% confidence interval). In addition, the final year of the time series (2024) exhibits the highest OHC value recorded, following a period of sustained warming that began in 2023. '''DOI (product):''' https://doi.org/10.48670/mds-00316

'''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

'''Short description:''' For the NWS/IBI Ocean- Sea Surface Temperature L3 Observations . This product provides daily foundation sea surface temperature from multiple satellite sources. The data are intercalibrated. This product consists in a fusion of sea surface temperature observations from multiple satellite sensors, daily, over a 0.02° resolution grid. It includes observations by polar orbiting and geostationary satellites . The L3S SST data are produced selecting only the highest quality input data from input L2P/L3P images within a strict temporal window (local nightime), to avoid diurnal cycle and cloud contamination. The observations of each sensor are intercalibrated prior to merging using a bias correction based on a multi-sensor median reference correcting the large-scale cross-sensor biases. 3 more datasets are available that only contain "per sensor type" data : Polar InfraRed (PIR), Polar MicroWave (PMW), Geostationary InfraRed (GIR) '''DOI (product) :''' https://doi.org/10.48670/moi-00310

'''DEFINITION''' The omi_climate_sst_ibi_area_averaged_anomalies product for 2024 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1982 and averaged over the IBI areas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish areas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-CLIMATE-SST- IBI_v3.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the IBI areas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish areas built from re-processed ESA SST CCI, C3S (Embury et al., 2019). Anomalies are computed against the 1991-2020 reference period. The reference for this OMI can be found in the first and second issue of the Copernicus Marine Service Ocean State Report (OSR), Section 1.1 (Roquet et al., 2016; Mulet et al., 2018). '''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 0.012 ±0.002 °C/year over the period 1982-2024. '''DOI (product):''' https://doi.org/10.48670/moi-00256