d8e59de2-8521-4641-a9f4-9b65ef93e9ad Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2022-06-29T09:02:25.911Z ISO 19139, MyOcean profile 0.2 2 1 1 false WGS 84 / Plate Carree (EPSG:32662) EPSG [ARCHIVE] Mediterranean Sea Reprocessed Surface Chlorophyll Concentration and Phytoplankton Functional Types from Multi Satellite observations OCEANCOLOUR_MED_CHL_L3_REP_OBSERVATIONS_009_073 2013-03-13 2.1 2021-04-26 d8e59de2-8521-4641-a9f4-9b65ef93e9ad '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine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 E.U. Copernicus Marine Service Information Emanuele BÖHM OC-CNR-ROMA-IT gsdk@isac.cnr.it Rosalia SANTOLERI OC-CNR-ROMA-IT rosalia.santoleri@cnr.it Gianluca VOLPE OC-CNR-ROMA-IT gianluca.volpe@cnr.it Simone COLELLA OC-CNR-ROMA-IT simone.colella@cnr.it Javier CONCHA OC-CNR-ROMA-IT gsdk@isac.cnr.it / N/A https://catalogue.marine.copernicus.eu/documents/IMG/OCEANCOLOUR_MED_CHL_L3_REP_OBSERVATIONS_009_073.png OCEANCOLOUR_MED_CHL_L3_REP_OBSERVATIONS_009_073 Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2009-09-22 satellite-observation Discipline 2017-04-25 geonetwork.thesaurus.local.discipline.myocean.discipline mass_concentration_of_picophytoplankton_expressed_as_chlorophyll_in_sea_water mass_concentration_of_chlorophyll_a_in_sea_water mass_concentration_of_diatoms_expressed_as_chlorophyll_in_sea_water Climate and Forecast Standard Names 2017-04-04 geonetwork.thesaurus.external.parameter.myocean.ocean-variables multi-year Temporal scale 2009-06-12 geonetwork.thesaurus.local.temporal-scale.myocean.temporal-scale coastal-marine-environment marine-resources weather-climate-and-seasonal-forecasting marine-safety Area of benefit 2009-09-09 geonetwork.thesaurus.local.area-of-benefit.myocean.area-of-benefit mediterranean-sea Reference Geographical Areas 2009-09-09 geonetwork.thesaurus.local.reference-geographical-area.myocean.reference-geographical-area Level 3 Processing level 2021-07-26 geonetwork.thesaurus.local.processing-level.myocean.processing-level Not Applicable Model assimilation 2016-02-03 geonetwork.thesaurus.external.theme.myocean.model-assimilation See Copernicus Marine Environment Monitoring Service Data commitments and licence at: http://marine.copernicus.eu/web/27-service-commitments-and-licence.php No limitations on public access 7bdc830b-6321-4ffb-ae76-8707256c6d03 e0f8a482-d960-4c72-8976-8c63873ea4de Berthon, J.-F., Zibordi, G.: Bio-optical relationships for the northern Adriatic Sea. Int. J. Remote Sens., 25, 1527-1532, 2004 2019-05-08 Di Cicco A,a Sammartino M, Marullo S and Santoleri R (2017) Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data. Front. Mar. Sci. 4:126. doi: 10.3389/fmars.2017.00126 2019-05-08 Mélin, F., & Vantrepotte, V. (2015). How optically diverse is the coastal ocean?. Remote Sensing of Environment, 160, 235-251 2019-05-08 Vidussi, F., Claustre, H., Manca, B. B., Luchetta, A., & Marty, J. C. (2001). Phytoplankton pigment distribution in relation to upper thermocline circulation in the eastern Mediterranean Sea during winter. Journal of Geophysical Research: Oceans, 106(C9), 19939-19956 2019-05-08 Volpe, G., Santoleri, R., Vellucci, V., Ribera d Acalà, M., Marullo, S., and D Ortenzio, F. (2007). The colour of the Mediterranean Sea: Global versus regional bio-optical algorithms evaluation and implication for satellite chlorophyll estimates. Remote Sens. Environ., 107, 625-638. 2019-05-08 Volpe, G., Colella, S., Brando, V. E., Forneris, V., Padula, F. L., Cicco, A. D., ... & Santoleri, R. (2019). Mediterranean ocean colour Level 3 operational multi-sensor processing. Ocean Science, 15(1), 127-146. 2019-05-08 eng oceans bounding box -6.00 36.50 30.00 46.00 daily-mean 1997-09-04 0 0 display priority: 11760 observation temporal resolution: daily mean vertical level number: 1 false Grid NetCDF-4 Classic model COMMISSION REGULATION (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 See the referenced specification The myOcean products depends on other products for production or validation. The detailed list of dependencies is given in ISO19115's aggregationInfo (ISO19139 Xpath = "gmd:MD_Metadata/gmd:identificationInfo/gmd:aggregationInfo[./gmd:MD_AggregateInformation/gmd:initiativeType/gmd:DS_InitiativeTypeCode/@codeListValue='upstream-validation' or 'upstream-production']")