'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the European Ocean, the L4 multi-sensor daily satellite product is a 2km horizontal resolution subskin sea surface temperature analysis. This SST analysis is run by Meteo France CMS and is built using the European Ocean L3S products originating from bias-corrected European Ocean L3C mono-sensor products at 0.02 degrees resolution. This analysis uses the analysis of the previous day at the same time as first guess field. '''DOI (product) :''' https://doi.org/10.48670/moi-00161

'''DEFINITION''' The OMI_EXTREME_SL_IBI_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset ibi_omi_sl_extreme_var_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018). '''CONTEXT''' Sea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one metre by the end of the century (Vousdoukas et al., 2020). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves. The Iberian Biscay Ireland region shows positive sea level trend modulated by decadal-to-multidecadal variations driven by ocean dynamics and superposed to the long-term trend (Chafik et al., 2019). ''' KEY FINDINGS''' The completeness index criteria is fulfilled by 55 stations in 2021, three more than those available in 2020 (52), recently added to the multi-year product INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The mean 99th percentiles reflect the great tide spatial variability around the UK and the north of France. Minimum values are observed in the Irish coast (e.g.: 0.66 m above mean sea level in Arklow Harbour), South of England (e.g.: 0.70 m above mean sea level in Bournemouth), and the Canary Islands (e.g.: 0.96 m above mean sea level in Hierro). Maximum values are observed in the Bristol and English Channels (e.g.: 6.26 m and 5.17 m above mean sea level in Newport and St. Helier, respectively). The standard deviation reflects the south-north increase of storminess, ranging between 2 cm in the Canary Islands to 12 cm in Newport (Bristol Channel). Negative or close to zero anomalies of 2021 99th percentile are observed this year for most of the stations in the region, reaching up to -17.8 cm in Newport, or -15 cm in St.Helier (Jersey Island, Channel Islands). '''DOI (product):''' https://doi.org/10.48670/moi-00253

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the North Atlantic and Arctic oceans, the ESA Ocean Colour CCI Remote Sensing Reflectance (merged, bias-corrected Rrs) data are used to compute surface Chlorophyll (mg m-3, 1 km resolution) using the regional OC5CCI chlorophyll algorithm. The Rrs are generated by merging the data from SeaWiFS, MODIS-Aqua, MERIS, VIIRS and OLCI-3A sensors and realigning the spectra to that of the MERIS sensor. The algorithm used is OC5CCI - a variation of OC5 (Gohin et al., 2002) developed by IFREMER in collaboration with PML. As part of this development, an OC5CCI look up table was generated specifically for application over OC-CCI merged daily remote sensing reflectances. The resulting OC5CCI algorithm was tested and selected through an extensive calibration exercise that analysed the quantitative performance against in situ data for several algorithms in these specific regions. Processing information: PML's Remote Sensing Group has the capability to automatically receive, archive, process and map global data from multiple polar-orbiting sensors in both near-real time and delayed time. OLCI products are downloaded at level-2 from CODA, the Copernicus Hub and/or via EUMETCAST. These products are remapped at nominal 300m and 1 Km spatial resolution using cylindrical equirectangular projection. Description of observation methods/instruments: Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so called ocean colour which is affected by the presence of phytoplankton. By comparing reflectances at different wavelengths and calibrating the result against in situ measurements, an estimate of chlorophyll content can be derived. '''Processing information:''' ESA OC-CCI Rrs raw data are provided by Plymouth Marine Laboratory, currently at 4km resolution globally. These are processed to produce chlorophyll concentration using the same in-house software as in the operational processing. The entire CCI data set is consistent and processing is done in one go. Both OC CCI and the REP product are versioned. Standard masking criteria for detecting clouds or other contamination factors have been applied during the generation of the Rrs, i.e., land, cloud, sun glint, atmospheric correction failure, high total radiance, large solar zenith angle (70deg), large spacecraft zenith angle (56deg), coccolithophores, negative water leaving radiance, and normalized water leaving radiance at 560 nm 0.15 Wm-2 sr-1 (McClain et al., 1995). For the regional products, a variant of the OC-CCI chain is run to produce high resolution data at the 1km resolution necessary. A detailed description of the ESA OC-CCI processing system can be found in OC-CCI (2014e). '''Description of observation methods/instruments:''' Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so called ocean colour which is affected by the presence of phytoplankton. By comparing reflectances at different wavelengths and calibrating the result against in-situ measurements, an estimate of chlorophyll content can be derived. '''Quality / Accuracy / Calibration information:''' Detailed description of cal/val is given in the relevant QUID, associated validation reports and quality documentation. '''DOI (product) :''' https://doi.org/10.48670/moi-00070

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the European Ocean - Sea Surface Temperature Mono-Sensor L3 Observations. One SST file per 24h per area and per sensor (bias corrected) closest to the original resolution: SLSTR-A, AMSR2, SEVIRI, AVHRR_METOP_B, AVHRR18_G, AVHRR_19L, MODIS_A, MODIS_T, VIIRS_NPP. One SST file per file window per area and per sensor (bias corrected) closest to the original resolution , while still manageable in terms volume over the processed area. '''Description of observation methods/instruments:''' The METOP_B derived SSTs are not bias corrected because METOP_B is used as the reference sensor for the correction method. '''DOI (product) :''' https://doi.org/10.48670/moi-00162

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the North Atlantic and Arctic oceans, the ESA Ocean Colour CCI Remote Sensing Reflectance (merged, bias-corrected Rrs) data are used to compute surface Chlorophyll (mg m-3, 1 km resolution) using the regional OC5CCI chlorophyll algorithm. The Rrs are generated by merging the data from SeaWiFS, MODIS-Aqua, MERIS, VIIRS and OLCI-3A sensors and realigning the spectra to that of the MERIS sensor. The algorithm used is OC5CCI - a variation of OC5 (Gohin et al., 2002) developed by IFREMER in collaboration with PML. As part of this development, an OC5CCI look up table was generated specifically for application over OC- CCI merged daily remote sensing reflectances. The resulting OC5CCI algorithm was tested and selected through an extensive calibration exercise that analysed the quantitative performance against in situ data for several algorithms in these specific regions. L3 products are daily files, while the L4 are monthly composites. ESA-CCI Rrs raw data are provided by PML. These are processed to produce chlorophyll concentration using the same in-house software as in the operational processing. Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so called ocean colour which is affected by the presence of phytoplankton. By comparing reflectances at different wavelengths and calibrating the result against in-situ measurements, an estimate of chlorophyll content can be derived. '''Processing information:''' ESA OC-CCI Rrs raw data are provided by Plymouth Marine Laboratory, currently at 4km resolution globally. These are processed to produce chlorophyll concentration using the same in-house software as in the operational processing. The entire CCI data set is consistent and processing is done in one go. Both OC CCI and the REP product are versioned. Standard masking criteria for detecting clouds or other contamination factors have been applied during the generation of the Rrs, i.e., land, cloud, sun glint, atmospheric correction failure, high total radiance, large solar zenith angle (70deg), large spacecraft zenith angle (56deg), coccolithophores, negative water leaving radiance, and normalized water leaving radiance at 560 nm 0.15 Wm-2 sr-1 (McClain et al., 1995). For the regional products, a variant of the OC-CCI chain is run to produce high resolution data at the 1km resolution necessary. A detailed description of the ESA OC-CCI processing system can be found in OC-CCI (2014e). '''Description of observation methods/instruments:''' Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so called ocean colour which is affected by the presence of phytoplankton. By comparing reflectances at different wavelengths and calibrating the result against in-situ measurements, an estimate of chlorophyll content can be derived. '''Quality / Accuracy / Calibration information:''' Detailed description of cal/val is given in the relevant QUID, associated validation reports and quality documentation. '''Suitability, Expected type of users / uses:''' This product is meant for use for educational purposes and for the managing of the marine safety, marine resources, marine and coastal environment and for climate and seasonal studies. '''DOI (product) :''' https://doi.org/10.48670/moi-00074

'''Short description:''' Altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean. 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) that can be used to change the physical content for specific needs This product is processed by the DUACS multimission altimeter data processing system. It serves in near-real time the main operational oceanography and climate forecasting centers in Europe and worldwide. It processes data from all altimeter missions: Jason-3, Sentinel-3A, HY-2A, Saral/AltiKa, Cryosat-2, Jason-2, Jason-1, T/P, ENVISAT, GFO, ERS1/2. It provides a consistent and homogeneous catalogue of products for varied applications, both for near real time applications and offline studies. To produce maps of SLA (Sea Level Anomalies) in near-real time, the system exploits the most recent datasets available based on the enhanced OGDR+IGDR production. The system acquires and then synchronizes altimeter data and auxiliary data; each mission is homogenized using the same models and corrections. The Input Data Quality Control checks that the system uses the best altimeter data. The multi-mission cross-calibration process removes any residual orbit error, or long wavelength error (LWE), as well as large scale biases and discrepancies between various data flows; all altimeter fields are interpolated at crossover locations and dates. After a repeat-track analysis, a mean profile, which is peculiar to each mission, or a Mean Sea Surface (MSS) (when the orbit is non repetitive) is subtracted to compute sea level anomaly. The MSS is available via the Aviso+ dissemination (http://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mss.html [http://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mss.html]). Data are then cross validated, filtered from residual noise and small scale signals, and finally sub-sampled (sla_filtered variable). The ADT (Absolute Dynamic Topography, adt_filtered variable) can computed as follows: adt_filtered=sla_filtered+MDT where MDT. The Mean Dynamic Topography distributed by Aviso+ (http://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html [http://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt.html]). '''Associated products:''' A time invariant product [http://marine.copernicus.eu/services-portfolio/access-to-products/?option=com_csw&view=details&product_id=SEALEVEL_GLO_NOISE_L4_NRT_OBSERVATIONS_008_032] describing the noise level of along-track measurements is available. It is associated to the sla_filtered variable. It is a gridded product. One file is provided for the global ocean and those values must be applied for Arctic and Europe products. For Mediterranean and Black seas, one value is given in the QUID document.

'''DEFINITION:''' The regional 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 the regional products as distributed by CMEMS, derived by 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., 2018a). '''CONTEXT:''' Phytoplankton – and chlorophyll concentration as their proxy – respond rapidly to changes in their physical environment. In the North Atlantic region these changes present a distinct seasonality and are mostly determined by light and nutrient availability (González Taboada et al., 2014). By comparing annual mean values to a climatology, we effectively remove the seasonal signal at each grid point, while retaining information on potential events during the year (Gregg and Rousseaux, 2014). In particular, North Atlantic anomalies can then be correlated with oscillations in the Northern Hemisphere Temperature (Raitsos et al., 2014). Chlorophyll anomalies also provide information on the status of the North Atlantic oligotrophic gyre, where evidence of rapid gyre expansion has been found for the 1997-2012 period (Polovina et al. 2008, Aiken et al., 2017, Sathyendranath et al., 2018b). '''CMEMS KEY FINDINGS:''' The average chlorophyll anomaly in the North Atlantic is -0.02 log10(mg m-3), with a maximum value of 1.0 log10(mg m-3) and a minimum value of -1.0 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. A moderate increase in chlorophyll concentration was observed in 2019 over the Bay of Biscay and regions close to Iceland and Greenland, such as the Irminger Basin and the Denmark Strait. In particular, the annual average values for those areas are around 160% of the 1997-2014 average (anomalies > 0.2 log10(mg m-3)). While the significant negative anomalies reported for 2016-2017 (Sathyendranath et al., 2018c) in the area west of the Ireland and Scotland coasts continued to manifest, the Irish and North Seas returned to their normative regime during 2019, with anomalies close to zero. A change in the anomaly sign (positive to negative) was also detected for the West European Basin, with annual values as low as 60% of the 1997-2014 average. This reduction in chlorophyll might be matched with negative anomalies in sea level during the period, indicating a dominance of upwelling factors over stratification.

'''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

'''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

'''Short description:''' For the European North West Shelf Ocean Iberia Biscay Irish Seas. The IFREMER Sea Surface Temperature reprocessed analysis aims at providing daily gap-free maps of sea surface temperature, referred as L4 product, at 0.05deg. x 0.05deg. horizontal resolution, over the 1982-present period, using satellite data from the European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) L3 products (1982-2016) and from the Copernicus Climate Change Service (C3S) L3 product (2017-present). The gridded SST product is intended to represent a daily-mean SST field at 20 cm depth. '''DOI (product) :''' https://doi.org/10.48670/moi-00153