501db834-2108-4e27-9982-e7e2dfb94c6a Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2025-11-21T14:17:13.866109Z ISO 19139, MyOcean profile 0.2 2 1 1 false Mediterranean Sea Chlorophyll-a time series and trend from Observations Reprocessing OMI_HEALTH_CHL_MEDSEA_OCEANCOLOUR_area_averaged_mean 2018-02-12 3.4 2025-11-25 ef932fc0-04e7-4a25-b7b2-08a2d85d4039 '''DEFINITION''' The time series are derived from the regional chlorophyll reprocessed (MY) product as distributed by CMEMS (OCEANCOLOUR_MED_BGC_L3_NRT_009_141). This dataset, derived from multi-sensor (SeaStar-SeaWiFS, AQUA-MODIS, NOAA20-VIIRS, NPP-VIIRS, Envisat-MERIS and Sentinel3-OLCI) Rrs spectra produced by CNR using an in-house processing chain, is obtained by means of the Mediterranean Ocean Colour regional algorithms: an updated version of the MedOC4 (Case 1 (off-shore) waters, Volpe et al., 2019, with new coefficients) and AD4 (Case 2 (coastal) waters, Berthon and Zibordi, 2004). The processing chain and the techniques used for algorithms merging are detailed in Colella et al. (2023). Monthly regional mean values are calculated by performing the average of 2D monthly mean (weighted by pixel area) over the region of interest. The deseasonalized time series is obtained by applying the X-11 seasonal adjustment methodology on the original time series as described in Colella et al. (2016), and then the Mann-Kendall test (Mann, 1945; Kendall, 1975) and Sens’s method (Sen, 1968) are subsequently applied to obtain the magnitude of trend. This OMI has been introduced since the 2nd issue of Ocean State Report in 2017. '''CONTEXT''' Phytoplankton and chlorophyll concentration as a proxy for phytoplankton respond rapidly to changes in environmental conditions, such as light, temperature, nutrients and mixing (Colella et al. 2016). The character of the response depends on the nature of the change drivers, and ranges from seasonal cycles to decadal oscillations (Basterretxea et al. 2018). Therefore, it is of critical importance to monitor chlorophyll concentration at multiple temporal and spatial scales, in order to be able to separate potential long-term climate signals from natural variability in the short term. In particular, phytoplankton in the Mediterranean Sea is known to respond to climate variability associated with the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) (Basterretxea et al. 2018, Colella et al. 2016). '''KEY FINDINGS''' In the Mediterranean Sea, the average chlorophyll trend for the 1997–2024 period is slightly negative, at -0.77 ± 0.59% per year, reinforcing the findings of the previous releases. This result contrasts with the analysis by Sathyendranath et al. (2018), which reported increasing chlorophyll concentrations across all European seas. From around 2010–2011 onward, excluding the 2018–2019 period, a noticeable decline in chlorophyll levels is evident in the deseasonalized time series (green line) and in the observed maxima (grey line), particularly from 2015. This sustained decline over the past decade contributes to the overall negative trend observed in the Mediterranean Sea. '''DOI (product):''' https://doi.org/10.48670/moi-00259 E.U. Copernicus Marine Service Information OC-CNR-ROMA-IT P0M0D0H/P0M0D0H N/A https://documentation.marine.copernicus.eu/IMG/OMI_HEALTH_CHL_MEDSEA_area_averaged_mean.png Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2009-09-22 satellite-observation Discipline 2024-07-26 geonetwork.thesaurus.local.discipline.myocean.discipline mass_concentration_of_chlorophyll_in_seawater Climate and Forecast Standard Names 2017-04-04 geonetwork.thesaurus.external.parameter.myocean.ocean-variables multi-year Temporal scale 2024-07-26 geonetwork.thesaurus.local.temporal-scale.myocean.temporal-scale marine-safety marine-resources weather-climate-and-seasonal-forecasting coastal-marine-environment Area of benefit 2025-07-29 geonetwork.thesaurus.local.area-of-benefit.myocean.area-of-benefit mediterranean-sea Reference Geographical Areas 2024-07-26 geonetwork.thesaurus.local.reference-geographical-area.myocean.reference-geographical-area Level 4 Processing level 2024-07-26 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 Basterretxea, G., Font-Muñoz, J. S., Salgado-Hernanz, P. M., Arrieta, J., & Hernández-Carrasco, I. (2018). Patterns of chlorophyll interannual variability in Mediterranean biogeographical regions. Remote Sensing of Environment, 215, 7-17. 2019-05-08 Berthon, J.-F., Zibordi, G. (2004). Bio-optical relationships for the northern Adriatic Sea. Int. J. Remote Sens., 25, 1527-1532. 2019-05-08 Colella, S., Falcini, F., Rinaldi, E., Sammartino, M., Santoleri, R., 2016. Mediterranean ocean colour chlorophyll trends. PLoS One 11, 1 16. https://doi.org/10.1371/journal.pone.0155756. 2019-05-08 Colella, S., Brando, V.E., Cicco, A.D., D’Alimonte, D., Forneris, V., Bracaglia, M., 2021. Quality Information Document. Copernicus Marine Service. OCEAN COLOUR PRODUCTION CENTRE, Ocean Colour Mediterranean and Black Sea Observation Product. (https://documentation.marine.copernicus.eu/QUID/CMEMS-OC-QUID-009-141to144-151to154.pdf). 2019-05-08 Kendall MG. 1975. Multivariate analysis. London: Charles Griffin & Co; p. 210, 43. 2019-05-08 Mann HB. 1945. Nonparametric tests against trend. Econometrica. 13:245 259. p. 42. 2019-05-08 Sathyendranath, S., Pardo, S., Benincasa, M., Brando, V. E., Brewin, R. J.W., Mélin, F., Santoleri, R., 2018, 1.5. Essential Variables: Ocean Colour in Copernicus Marine Service Ocean State Report - Issue 2, Journal of Operational Oceanography, 11:sup1, 1-142, doi: 10.1080/1755876X.2018.1489208 2019-05-08 Sen PK. 1968. Estimates of the regression coefficient based on Kendall’s tau. J Am Statist Assoc. 63:1379 1389. 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 87d115ed-3221-4b12-9154-3fcaa5eeb0d5 1daeb022-9297-46d1-a5d5-08bd032417d1 75c2f83c-7159-492a-b383-a1cc3f5f2ede eng oceans bounding box -6.00 36.50 30.00 46.00 0 1997-09-04 0 0.0 display priority: 99999 observation vertical level number: 1 false Point series NetCDF-4 Classic model https://stac.marine.copernicus.eu/metadata/OMI_HEALTH_CHL_MEDSEA_OCEANCOLOUR_area_averaged_mean/omi_health_chl_medsea_oceancolour_area_averaged_mean_202311/dataset.stac.json WWW:STAC omi_health_chl_medsea_oceancolour_area_averaged_mean For accessing native data and Analysis-ready Cloud-optimized data services, consult this STAC metadata endpoint https://wmts.marine.copernicus.eu/teroWmts/OMI_HEALTH_CHL_MEDSEA_OCEANCOLOUR_area_averaged_mean/omi_health_chl_medsea_oceancolour_area_averaged_mean_202311?service=WTMS&request=GetCapabilities OGC:WMTS omi_health_chl_medsea_oceancolour_area_averaged_mean 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']")