'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR) in Rome distributes reprocessed surface chlorophyll concentration (Chl) and phytoplankton functional types (PFT). Input Rrs multi-sensor (MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS, Sentinel3A-OLCI) spectra at the state-of-the-art algorithms for multi-sensor merging. Single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged. Reprocessed (multi-year) products are consistent and homogeneous in terms of format, algorithms and processing software. Chl is obtained by means of the Mediterranean regional algorithms: an updated version of the MedOC4 (Volpe et al., 2019) and AD4 (Berthon and Zibordi, 2004). Discrimination between the two water types is performed by comparing the satellite spectrum with the average spectrum from in situ measurements. Reference insitu dataset is MedBiOp (Volpe et al., 2019) where Case II spectra are selected with a k-mean cluster analysis (Melin et al., 2015). Merging of Case I and Case II information is performed estimating the Mahalanobis distance between observed and reference spectra and using it as weight for the final value. The PFT provides estimates of Chl concentration of 9 phytoplankton groups: Micro, Nano, Pico, Diato, Dino, Crypto, Hapto, Green and Prokar. Micro consists of Diato and Dino, Nano includes Crypto and Hapto and Pico is referred to Green and Prokar with the adjustment of Brewin et al. (2010) in the ultra-oligotrophic water for Pico and Nano. These classes are estimated via empirical regional functions, correlating Chl concentration with each in-situ PFT fraction computed by a regional diagnostic pigment analysis (Di Cicco et al. 2017). '''Processing information:''' Multi-sensor product is constituted by MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS and Sentinel3A-OLCI. For consistency with NASA L2 dataset, BRDF correction was applied to Sentinel3A-OLCI prior to band shifting and multi sensor merging. Single sensor NASA Level-2 data are destriped and then all Level-2 data are remapped at 1 km spatial resolution using cylindrical equirectangular projection. Afterwards, single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged with a technique aimed at smoothing the differences among different sensors. This technique is developed by The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR, Rome). Then geophysical fields (i.e. chlorophyll and kd490) are estimated via state-of-the-art algorithms for better product quality. The entire data set is consistent and processed in one-shot mode (with an unique software version and identical configurations). '''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. '''Quality / Accuracy / Calibration information:''' A detailed description of the calibration and validation activities performed over this product can be found on the CMEMS web portal. '''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. '''Dataset names:''' * dataset-oc-med-chl-multi-l3-chl_1km_daily-rep-v02 * dataset-oc-med-pft-multi-l3-pft_1km_daily-rep-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant '''DOI (product) :''' https://doi.org/10.48670/moi-00112

Bathymetric datasets are an extraction of surveys belonging to the Shom public database. For depth up to 50m, the vertical precision of soundings varies from 30cm to 1m and the horizontal precision varies from 1 to 20m. In deep ocean, the vertical precision is mainly around 1 or 2% of the bottom depth. It is sometimes more, it depends on the technology used. The data are referenced to ZH which is assimilated to LAT. Data are corrected for sound velocity variations. <br /> October 27 2025 version

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR), in Rome, distributes Level-4 product including the daily interpolated chlorophyll field with no data voids starting from the multi-sensor (MODIS-Aqua, NOAA-20-VIIRS, NPP-VIIRS, Sentinel3A-OLCI), the monthly averaged chlorophyll concentration for the multi-sensor and climatological fields, all at 1 km resolution. Chlorophyll field are obtained by means of the Mediterranean regional algorithms: an updated version of the MedOC4 (Case 1 waters, Volpe et al., 2019, with new coefficients) and AD4 (Case 2 waters, Berthon and Zibordi, 2004). Discrimination between the two water types is performed by comparing the satellite spectrum with the average water type spectral signature from in situ measurements for both water types. Reference insitu dataset is MedBiOp (Volpe et al., 2019) where pure Case II spectra are selected using a k-mean cluster analysis (Melin et al., 2015). Merging of Case I and Case II information is performed estimating the Mahalanobis distance between the observed and reference spectra and using it as weight for the final merged value. The interpolated gap-free Level-4 Chl concentration is estimated by means of a modified version of the DINEOF algorithm by GOS (Volpe et al., 2018). DINEOF is an iterative procedure in which EOF are used to reconstruct the entire field domain. As first guess, it uses the SeaWiFS-derived daily climatological values at missing pixels and satellite observations at valid pixels. Monthly Level-4 dataset is the time averages of the L3 fields and includes the standard deviation and the number of observations in the monthly period of integration. SeaWiFS daily climatology provides reference for the calculation of Quality Indices (QI) for Chl observations. '''Processing information:''' Multi-sensor product is constituted by MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS and Sentinel3A-OLCI. For consistency with NASA L2 dataset, BRDF correction was applied to Sentinel3A-OLCI prior to band shifting and multi sensor merging. Single sensor NASA Level-2 data are destriped and then all Level-2 data are remapped at 1 km spatial resolution using cylindrical equirectangular projection. Afterwards, single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged with a technique aimed at smoothing the differences among different sensors. This technique is developed by The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR, Rome). Then geophysical fields (i.e. chlorophyll) are estimated via state-of-the-art algorithms for better product quality. Level-4 includes both monthly time averages and the daily-interpolated fields. Time averages are computed on the delayed-time data. The interpolated product starts from the L3 products at 1 km resolution. At the first iteration, DINEOF procedure uses, as first guess for each of the missing pixels the relative daily climatological pixel. A procedure to smooth out spurious spatial gradients is applied to the daily merged image (observation and climatology). From the second iteration, the procedure uses, as input for the next one, the field obtained by the EOF calculation, using only a number of modes: that is, at the second round, only the first two modes, at the third only the first three, and so on. At each iteration, the same smoothing procedure is applied between EOF output and initial observations. The procedure stops when the variance explained by the current EOF mode exceeds that of noise. The entire data set is consistent and processed in one-shot mode (with an unique software version and identical configurations). For the climatology Rrs data are derived from the latest SeaWiFS NASA reprocessing (R2018.0) and converted to chlorophyll concentrations with the same algorithm as the one used for other L4 and/or L3 products. '''Description of observation methods/instruments:''' Ocean color technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so called ocean color which is affected by the presence of phytoplankton. '''Quality / Accuracy / Calibration information:''' A detailed description of both the cal/val and a more in depth view of the method is given in QUID-009-038to045-071-073-078-079-095-096.pdf over Copernicus web portal. '''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. '''Dataset names:''' *dataset-oc-med-chl-multi-l4-chl_1km_monthly-rep-v02 *dataset-oc-med-chl-multi-l4-interp_1km_daily-rep *dataset-oc-med-chl-seawifs-l4-chl_1km_daily-climatology-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant. '''DOI (product) :''' https://doi.org/10.48670/moi-00114