d212a28f-b198-43da-b7ab-85909f56994a Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2022-11-28T15:33:19.283Z ISO 19139, MyOcean profile 0.2 2 1 1 false [ARCHIVE] Mediterranean Sea Chlorophyll-a time series and trend from Observations Reprocessing MEDSEA_OMI_HEALTH_OceanColour_area_averaged_mean 2018-02-12 3.4 2018-02-12 ef932fc0-04e7-4a25-b7b2-08a2d85d4039 '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The time series are derived from the regional chlorophyll reprocessed (REP) product as distributed by CMEMS. This dataset, derived from multi-sensor (SeaStar-SeaWiFS, AQUA-MODIS, NOAA20-VIIRS, NPP-VIIRS, Envisat-MERIS and Sentinel3A-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. (2021). 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. '''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). '''CMEMS KEY FINDINGS''' In the Mediterranean Sea, the trend average for the 1997-2020 period is slightly negative (-0.580.62% per year). Due to the change in processing techniques and chlorophyll retrieval, this trend estimate cannot be compared directly to those previously reported. The observations time series (in grey) shows minima values have been quite constant until 2015 and then there is a little decrease up to 2020, when an absolute minimum occurs with values lower than 0.04 mg m-3. Throughout the time series, maxima are variable year by year (with absolute maximum in 2015, >0.14 mg m-3), showing an evident reduction since 2016. In the last years of the series, the decrease of chlorophyll concentrations is also observed in the deseasonalized timeseries (in green) with a marked step in 2020. This attenuation of chlorophyll values in the last years results in an overall negative trend for the Mediterranean Sea. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00259 E.U. Copernicus Marine Service Information Rosalia SANTOLERI OC-CNR-ROMA-IT rosalia.santoleri@artov.isac.cnr.it Gianluca VOLPE OC-CNR-ROMA-IT gianluca.volpe@cnr.it CMEMS-DU OC-CNR-ROMA-IT gsdk@isac.cnr.it Simone COLELLA OC-CNR-ROMA-IT simone.colella@cnr.it MOI-OMI-SERVICE MOI-OMI-SERVICE omi.service@mercator-ocean.fr P0M0D0H/P0M0D0H N/A https://catalogue.marine.copernicus.eu/documents/IMG/MEDSEA_OMI_HEALTH_OceanColour_area_averaged_mean.png 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_chlorophyll_in_seawater 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 marine-safety weather-climate-and-seasonal-forecasting marine-resources coastal-marine-environment 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 4 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 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. Berthon, J.-F., Zibordi, G.: Bio-optical relationships for the northern Adriatic Sea. Int. J. Remote Sens., 25, 1527-1532, 200. 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. OCEAN COLOUR PRODUCTION CENTRE, Ocean Colour Mediterranean and Black Sea Observation Product. Copernicus Marine Environment Monitoring Centre. Quality Information Document (https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-OC-QUID-009-038to045-071-073-078-079-095-096.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 9162a49d-930e-47cb-92f5-27f3b2493e83 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 a5022b84-2435-4ef8-bf29-764fd1b24f36 09c381ce-7502-453c-af3a-c1e63297d26e eng oceans bounding box -6.00 36.50 30.00 46.00 0 1901-01-01 1901-01-01 0 0.0 display priority: 99999 observation vertical level number: 1 false Point series 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']")