3bcd4e8a-39c9-4744-b383-84e06ab192ba Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2025-10-27T09:52:31.363861Z ISO 19139, MyOcean profile 0.2 2 false EPSG Global Ocean Sea Surface Temperature time series and trend from Observations Reprocessing GLOBAL_OMI_TEMPSAL_sst_area_averaged_anomalies 2019-11-28 3.4 2025-11-25 a78600a4-a280-47b5-8ddd-0dc8b5e9c9d9 '''DEFINITION''' Based on daily, global climate sea surface temperature (SST) analyses generated by the Copernicus Climate Change Service (C3S) (product SST-GLO-SST-L4-REP-OBSERVATIONS-010-024). Analysis of the data was based on the approach described in Mulet et al. (2018) and is described and discussed in Good et al. (2020). The processing steps applied were: 1. The daily analyses were averaged to create monthly means. 2. A climatology was calculated by averaging the monthly means over the period 1991 - 2020. 3. Monthly anomalies were calculated by differencing the monthly means and the climatology. 4. An area averaged time series was calculated by averaging the monthly fields over the globe, with each grid cell weighted according to its area. 5. The time series was passed through the X11 seasonal adjustment procedure, which decomposes the time series into a residual seasonal component, a trend component and errors (e.g., Pezzulli et al., 2005). The trend component is a filtered version of the monthly time series. 6. The slope of the trend component was calculated using a robust method (Sen 1968). The method also calculates the 95% confidence range in the slope. '''CONTEXT''' Sea surface temperature (SST) is one of the Essential Climate Variables (ECVs) defined by the Global Climate Observing System (GCOS) as being needed for monitoring and characterising the state of the global climate system (GCOS 2010). It provides insight into the flow of heat into and out of the ocean, into modes of variability in the ocean and atmosphere, can be used to identify features in the ocean such as fronts and upwelling, and knowledge of SST is also required for applications such as ocean and weather prediction (Roquet et al., 2016). '''CMEMS KEY FINDINGS''' Over the period 1982 to 2024, the global average linear trend was 0.012 ± 0.001°C / year (95% confidence interval). 2024 is nominally the warmest year in the time series. Aside from this trend, variations in the time series can be seen which are associated with changes between El Niño and La Niña conditions. For example, peaks in the time series coincide with the strong El Niño events that occurred in 1997/1998 and 2015/2016 (Gasparin et al., 2018). '''DOI (product):''' https://doi.org/10.48670/moi-00242 E.U. Copernicus Marine Service Information SST-METOFFICE-EXETER-UK P0M0D0H/P0M0D0H N/A https://documentation.marine.copernicus.eu/IMG/GLOBAL_OMI_TEMPSAL_sst_area_averaged_anomalies.png Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2009-09-22 satellite-observation Discipline 2023-03-16 geonetwork.thesaurus.local.discipline.myocean.discipline 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 weather-climate-and-seasonal-forecasting marine-resources coastal-marine-environment marine-safety Area of benefit 2025-07-29 geonetwork.thesaurus.local.area-of-benefit.myocean.area-of-benefit global-ocean Reference Geographical Areas 2024-07-26 geonetwork.thesaurus.local.reference-geographical-area.myocean.reference-geographical-area N/A 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 Kuala Lumpur Ocean Hackathon - Ville geonetwork.thesaurus.local.place.oh_ville 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 cb172763-d288-49a8-81c1-18250b065ea1 GCOS. Global Climate Observing System. 2010. Update of the Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC (GCO-138). 2019-05-08 Gasparin, F., von Schuckmann, K., Desportes, C., Sathyendranath, S. and Pardo, S. 2018. El Niño southern oscillation. In: Copernicus marine service ocean state report, issue 2. J Operat Oceanogr. 11(Sup1):s11–ss4. doi:10.1080/1755876X.2018.1489208. 2019-05-08 Good, S.A., Kennedy, J.J, and Embury, O. Global sea surface temperature anomalies in 2018 and historical changes since 1993. In: von Schuckmann et al. 2020, Copernicus Marine Service Ocean State Report, Issue 4, Journal of Operational Oceanography, 13:sup1, S1-S172, doi: 10.1080/1755876X.2020.1785097. 2019-05-08 Merchant, C.J., Embury, O., Bulgin, C.E. et al. Satellite-based time-series of sea-surface temperature since 1981 for climate applications. Sci Data 6, 223 (2019) doi:10.1038/s41597-019-0236-x.  2019-05-08 Mulet S., Nardelli B.B., Good S., Pisano A., Greiner E., Monier M., Autret E., Axell L., Boberg F., Ciliberti S. 2018. Ocean temperature and salinity. In: Copernicus marine service ocean state report, issue 2. J Operat Oceanogr. 11(Sup1):s11–ss4. doi:10.1080/1755876X.2018.1489208. 2019-05-08 Pezzulli, S., Stephenson, D.B. and Hannachi A. 2005. The variability of seasonality. J Clim. 18: 71– 88, doi: 10.1175/JCLI-3256.1. 2019-05-08 Roquet H , Pisano A., Embury O. 2016. Sea surface temperature. In: von Schuckmann et al. 2016, The Copernicus marine environment monitoring service ocean state report. J Oper Ocean. 9(suppl. 2). doi:10.1080/1755876X.2016.1273446. 2019-05-08 Sen, P.K. 1968. Estimates of the regression coefficient based on Kendall’s tau. J Am Statist Assoc. 63: 1379– 1389, doi: 10.1080/01621459.1968.10480934. 2019-05-08 5dc87a5b-eddc-458e-b054-b263605bda91 df37995d-1d52-41d7-ba7b-dceba581b908 eng oceans bounding box -180.00 180.00 -90.00 90.00 1982-01-01 0 0 display priority: 53800 observation vertical level number: 1 temporal resolution: monthly mean false Point series NetCDF-4 https://stac.marine.copernicus.eu/metadata/GLOBAL_OMI_TEMPSAL_sst_area_averaged_anomalies/global_omi_tempsal_sst_area_averaged_anomalies_202211/dataset.stac.json WWW:STAC global_omi_tempsal_sst_area_averaged_anomalies For accessing native data and Analysis-ready Cloud-optimized data services, consult this STAC metadata endpoint 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']")