a83fe207-85af-44eb-88ec-0dcfcf2f5365 Copernicus Marine Service product specification CMEMS servicedesk.cmems@mercator-ocean.eu http://marine.copernicus.eu/ 2025-10-27T09:34:51.665288Z ISO 19139, MyOcean profile 0.2 2 0.05 0.05 false equirectangular EPSG Arctic Sea and Sea Ice Surface Temperature 2D trend from climatology based on reprocessed observations OMI_CLIMATE_SST_IST_ARCTIC_trend 2023-11-30 3.4 2025-11-25 a83fe207-85af-44eb-88ec-0dcfcf2f5365 '''DEFINITION''' The OMI_CLIMATE_sst_ist_ARCTIC_sst_ist_trend product includes the cumulative/net trend in combined sea and ice surface temperature anomalies for the Arctic Ocean from 1982-2024. The cumulative trend is the rate of change (°C/year) scaled by the number of years (43 years). The SST/IST Level 4 analysis that provides the input to the trend calculations are taken from the reprocessed product SEAICE_ARC_PHY_CLIMATE_L4_MY_011_016 with a recent update to include 2024. The product has a spatial resolution of 0.05 degrees in latitude and longitude. The OMI time series runs from Jan 1, 1982 to December 31, 2024 and is constructed by calculating monthly averages from the reference climatology defined over the period 1991-2020, according to the WMO recommendation (WMO, 2017) and recent U.S. National Oceanic and Atmospheric Administration practice (https://wmo.int/media/news/updated-30-year-reference-period-reflects-changing-climate), using daily level 4 SST/IST analysis fields of the SEAICE_ARC_PHY_CLIMATE_L4_MY_011_016 product. See the Copernicus Marine Service Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018) for more information on the temperature OMI product. The times series of monthly anomalies have been used to calculate the trend in surface temperature (combined SST and IST) using Sen’s method with confidence intervals from the Mann-Kendall test (section 3 in Von Schuckmann et al., 2018). '''CONTEXT''' SST and IST are essential climate variables that act as important input for initializing numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change. Especially in the Arctic, SST/IST feedbacks amplify climate change (AMAP, 2021). In the Arctic Ocean, the surface temperatures play a crucial role for the heat exchange between the ocean and atmosphere, sea ice growth and melt processes (Key et al., 1997) in addition to weather and sea ice forecasts through assimilation into ocean and atmospheric models (Rasmussen et al., 2018). The Arctic Ocean is a region that requires special attention regarding the use of satellite SST and IST records and the assessment of climatic variability due to the presence of both seawater and ice, and the large seasonal and inter-annual fluctuations in the sea ice cover which lead to increased complexity in the SST mapping of the Arctic region. Combining SST and ice surface temperature (IST) is identified as the most appropriate method for determining the surface temperature of the Arctic (Minnett et al., 2020). Previously, climate trends have been estimated individually for SST and IST records (Bulgin et al., 2020; Comiso and Hall, 2014). However, this is problematic in the Arctic region due to the large temporal variability in the sea ice cover including the overlying northward migration of the ice edge on decadal timescales, and thus, the resulting climate trends are not easy to interpret (Comiso, 2003). A combined surface temperature dataset of the ocean, sea ice and the marginal ice zone (MIZ) provides a consistent climate indicator, which is important for studying climate trends in the Arctic region. '''CMEMS KEY FINDINGS''' SST/IST trends were calculated for the Arctic Ocean over the period January 1982 to December 2024. The cumulative trends are upwards of 2°C for the greatest part of the Arctic Ocean, with the largest trends occur in the Beaufort Sea, Chukchi Sea, East Siberian Sea, Laptev Sea, Kara Sea and parts of Baffin Bay. Zero to slightly negative trends are found at the North Atlantic part of the Arctic Ocean. The combined sea and sea ice surface temperature trend is 0.104+/-0.005°C/yr, i.e. an increase by around 4.47°C between 1982 and 2024. The 2d map of Arctic anomalies reveals regional peak warming exceeding 5.5°C. '''DOI (product):''' https://doi.org/10.48670/mds-00324 E.U. Copernicus Marine Service Information SIW-DMI-COPENHAGEN-DK P0M0D0H/P0M0D0H N/A https://documentation.marine.copernicus.eu/IMG/OMI_CLIMATE_SST_IST_ARCTIC_trend.png target-application#seaiceinformation Target Application 2009-06-12 geonetwork.thesaurus.local.target-application.myocean.target-application Oceanographic geographical features GEMET - INSPIRE themes, version 1.0 2009-09-22 satellite-observation Discipline 2023-03-16 geonetwork.thesaurus.local.discipline.myocean.discipline ice_surface_temperature sea_surface_temperature 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 weather-climate-and-seasonal-forecasting marine-resources coastal-marine-environment Area of benefit 2025-07-29 geonetwork.thesaurus.local.area-of-benefit.myocean.area-of-benefit arctic-ocean 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 AMAP, 2021. Arctic Climate Change Update 2021: Key Trends and Impacts. Summary for Policy-makers. Arctic Monitoring and Assessment Programme (AMAP), Tromsø, Norway. 2019-05-08 Bulgin, C.E., Merchant, C.J., Ferreira, D., 2020. Tendencies, variability and persistence of sea surface temperature anomalies. Sci Rep 10, 7986. https://doi.org/10.1038/s41598-020-64785-9 2019-05-08 Comiso, J.C., 2003. Warming Trends in the Arctic from Clear Sky Satellite Observations. Journal of Climate. https://doi.org/10.1175/1520-0442(2003)016<3498:WTITAF>2.0.CO;2 2019-05-08 Comiso, J.C., Hall, D.K., 2014. Climate trends in the Arctic as observed from space: Climate trends in the Arctic as observed from space. WIREs Clim Change 5, 389–409. https://doi.org/10.1002/wcc.277 2019-05-08 Kendall MG. 1975. Multivariate analysis. London: CharlesGriffin & Co; p. 210, 4 2019-05-08 Key, J.R., Collins, J.B., Fowler, C., Stone, R.S., 1997. High-latitude surface temperature estimates from thermal satellite data. Remote Sensing of Environment 61, 302–309. https://doi.org/10.1016/S0034-4257(97)89497-7 2019-05-08 Minnett, P.J., Kilpatrick, K.A., Podestá, G.P., Evans, R.H., Szczodrak, M.D., Izaguirre, M.A., Williams, E.J., Walsh, S., Reynolds, R.M., Bailey, S.W., Armstrong, E.M., Vazquez-Cuervo, J., 2020. Skin Sea-Surface Temperature from VIIRS on Suomi-NPP—NASA Continuity Retrievals. Remote Sensing 12, 3369. https://doi.org/10.3390/rs12203369 2019-05-08 Rasmussen, T.A.S., Høyer, J.L., Ghent, D., Bulgin, C.E., Dybkjaer, G., Ribergaard, M.H., Nielsen-Englyst, P., Madsen, K.S., 2018. Impact of Assimilation of Sea-Ice Surface Temperatures on a Coupled Ocean and Sea-Ice Model. Journal of Geophysical Research: Oceans 123, 2440–2460. https://doi.org/10.1002/2017JC013481 2019-05-08 Sen PK. 1968. Estimates of the regression coefficient based on Kendall’s tau. J AmStatist Assoc. 63:1379–1389 2019-05-08 von Schuckmann et al., 2016: The Copernicus Marine Environment Monitoring Service Ocean State Report, Journal of Operational Oceanography, Volume 9, 2016 - Issue sup2: The Copernicus Marine Environment Monitoring Service Ocean, http://dx.doi.org/10.1080/1755876X.2016.1273446. 2019-05-08 von Schuckmann, K., Le Traon, P.-Y., Smith, N., Pascual, A., Brasseur, P., Fennel, K., Djavidnia, S., Aaboe, S., Fanjul, E. A., Autret, E., Axell, L., Aznar, R., Benincasa, M., Bentamy, A., Boberg, F., Bourdallé-Badie, R., Nardelli, B. B., Brando, V. E., Bricaud, C., … Zuo, H. (2018). Copernicus Marine Service Ocean State Report. Journal of Operational Oceanography, 11(sup1), S1–S142. https://doi.org/10.1080/1755876X.2018.1489208 2019-05-08 4505125a-de9a-4a46-9aab-63631a60bf5a c221d0b4-deaf-4581-9424-db2f3923df28 370de780-2e97-4520-bfa0-bef23705de9a WMO, Guidelines on the Calculation of Climate Normals, 2017, WMO-No-.1203 2019-05-08 eng oceans bounding box -180.00 180.00 58.00 90.00 1982-01-01 2024-12-31 0 0.0 display priority: 53705 observation temporal resolution: annual mean vertical level number: 0 false Grid NetCDF-4 https://stac.marine.copernicus.eu/metadata/OMI_CLIMATE_SST_IST_ARCTIC_trend/omi_climate_sst_ist_arctic_anomaly_202311/dataset.stac.json WWW:STAC omi_climate_sst_ist_arctic_trend For accessing native data and Analysis-ready Cloud-optimized data services, consult this STAC metadata endpoint https://wmts.marine.copernicus.eu/teroWmts/OMI_CLIMATE_SST_IST_ARCTIC_trend/omi_climate_sst_ist_arctic_anomaly_202311 OGC:WMTS omi_climate_sst_ist_arctic_trend 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']")