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  • '''DEFINITION''' The OMI_CLIMATE_SST_BAL_trend product includes the cumulative/net trend in sea surface temperature anomalies for the Baltic Sea from 1993-2022. The cumulative trend is the rate of change (°C/year) scaled by the number of years (30 years). The SST Level 4 analysis products that provide the input to the trend calculations are taken from the reprocessed product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 with a recent update to include 2022. The product has a spatial resolution of 0.02 in latitude and longitude. The OMI time series runs from Jan 1, 1993 to December 31, 2022 and is constructed by calculating monthly averages from the daily level 4 SST analysis fields of the SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 from 1993 to 2022. See the Copernicus Marine Service Ocean State Reports for more information on the OMI product (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). The times series of monthly anomalies have been used to calculate the trend in SST using Sen’s method with confidence intervals from the Mann-Kendall test (section 3 in Von Schuckmann et al., 2018). '''CONTEXT''' SST is an essential climate variable that is an important input for initialising numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change. The Baltic Sea is a region that requires special attention regarding the use of satellite SST records and the assessment of climatic variability (Høyer and She 2007; Høyer and Karagali 2016). The Baltic Sea is a semi-enclosed basin with natural variability and it is influenced by large-scale atmospheric processes and by the vicinity of land. In addition, the Baltic Sea is one of the largest brackish seas in the world. When analysing regional-scale climate variability, all these effects have to be considered, which requires dedicated regional and validated SST products. Satellite observations have previously been used to analyse the climatic SST signals in the North Sea and Baltic Sea (BACC II Author Team 2015; Lehmann et al. 2011). Recently, Høyer and Karagali (2016) demonstrated that the Baltic Sea had warmed 1-2oC from 1982 to 2012 considering all months of the year and 3-5oC when only July- September months were considered. This was corroborated in the Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). '''CMEMS KEY FINDINGS''' SST trends were calculated for the Baltic Sea area and the whole region including the North Sea, over the period January 1993 to December 2022. The average trend for the Baltic Sea domain (east of 9°E longitude) is 0.048°C/year, which represents an average warming of 1.44°C for the 1993-2022 period considered here. When the North Sea domain is included, the trend decreases to 0.029°C/year corresponding to an average warming of 0.87°C for the 1993-2022 period. Trends are highest for the Baltic Sea region and North Atlantic, especially offshore from Norway, compared to other regions. '''Figure caption''' Cumulative trends in sea surface temperature anomalies calculated from 1993 to 2022 for the Baltic Sea (OMI_CLIMATE_SST_BAL_trend). Trend calculations are based on the multi-year Baltic Sea L4 SST satellite product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016. '''DOI (product):''' https://doi.org/10.48670/moi-00206

  • '''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The BALTIC_OMI_TEMPSAL_sst_area_averaged_anomalies product includes time series of monthly mean SST anomalies over the period 1993-2021, relative to the 1993-2014 climatology, averaged for the Baltic Sea. The OMI time series runs from Jan 1, 1993 to December 31, 2021 and is constructed by calculating monthly averages from the daily level 4 SST analysis fields of the SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 product from 1993 to 2021. 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 OMI product. '''CONTEXT''' Sea Surface Temperature (SST) is an Essential Climate Variable (GCOS), that is an important input for initialis-ing numerical weather prediction models and fundamental for understanding air-sea interactions and moni-toring climate change (GCOS 2010). The Baltic Sea is a region that requires special attention regarding the use of satellite SST records and the assessment of climatic variability (Høyer and She 2007; Høyer and Karagali 2016). The Baltic Sea is a semi-enclosed basin affected bynatural variability, influenced by large-scale atmos-pheric processes and by the vicinity of land. In addition, the Baltic Sea is one of the largest brackish seas in the world. When analysing regional-scale climate variability, all these effects have to be considered, which re-quires dedicated regional and validated SST products. Satellite observations have previously been used to ana-lyse the climatic SST signals in the North Sea and Baltic Sea (BACC II Author Team 2015; Lehmann et al. 2011). Recently, Høyer and Karagali (2016) demonstrated that the Baltic Sea had warmed 1-2 oC from 1982 to 2012 considering all months of the year and 3-5 oC when only July-September months were considered. This was corroborated in the Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016 and section 3 in Von Schuckmann et al., 2018). '''CMEMS KEY FINDINGS''' The basin-average trend of SST anomalies for Baltic Sea region amounts to 0.049±0.006 °C/year over the pe-riod 1993-2021 which corresponds to an average warming of 1.42°C. Adding the North Sea area, the average trend amounts to 0.03±0.003 °C/year over the same period, which corresponds to an average warming of 0.87°C for the entire region since 1993. '''DOI (product):''' https://doi.org/10.48670/moi-00205

  • '''Short description:''' For the Baltic Sea- The DMI Sea Surface Temperature reprocessed analysis aims at providing daily gap-free maps of sea surface temperature, referred as L4 product, at 0.02deg. x 0.02deg. horizontal resolution, using satellite data from infra-red radiometers. The product uses SST satellite products from the ESA CCI and Copernicus C3S projects, including the sensors: NOAA AVHRRs 7, 9, 11, 12, 14, 15, 16, 17, 18 , 19, Metop, ATSR1, ATSR2, AATSR and SLSTR. '''DOI (product) :''' https://doi.org/10.48670/moi-00156

  • '''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The BALTIC_OMI_TEMPSAL_sst_trend product includes the cumulative/net trend in sea surface temperature anomalies for the Baltic Sea from 1993-2021. The cumulative trend is the rate of change (°C/year) scaled by the number of years (29 years). The SST Level 4 analysis products that provide the input to the trend calculations are taken from the reprocessed product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 with a recent update to include 2021. The product has a spatial resolution of 0.02 degrees in latitude and longitude. The OMI time series runs from Jan 1, 1993 to December 31, 2021 and is constructed by calculating monthly averages from the daily level 4 SST analysis fields of the SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 from 1993 to 2021. See the Copernicus Marine Service Ocean State Reports for more information on the OMI product (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). The times series of monthly anomalies have been used to calculate the trend in SST using Sen’s method with confidence intervals from the Mann-Kendall test (section 3 in Von Schuckmann et al., 2018). '''CONTEXT''' SST is an essential climate variable that is an important input for initialising numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change. The Baltic Sea is a region that requires special attention regarding the use of satellite SST records and the assessment of climatic variability (Høyer and She 2007; Høyer and Karagali 2016). The Baltic Sea is a semi-enclosed basin with natural variability and it is influenced by large-scale atmospheric processes and by the vicinity of land. In addition, the Baltic Sea is one of the largest brackish seas in the world. When analysing regional-scale climate variability, all these effects have to be considered, which requires dedicated regional and validated SST products. Satellite observations have previously been used to analyse the climatic SST signals in the North Sea and Baltic Sea (BACC II Author Team 2015; Lehmann et al. 2011). Recently, Høyer and Karagali (2016) demonstrated that the Baltic Sea had warmed 1-2oC from 1982 to 2012 considering all months of the year and 3-5oC when only July- September months were considered. This was corroborated in the Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). '''CMEMS KEY FINDINGS''' SST trends were calculated for the Baltic Sea area and the whole region including the North Sea, over the period January 1993 to December 2021. The average trend for the Baltic Sea domain (east of 9°E longitude) is 0.049 °C/year, which represents an average warming of 1.42 °C for the 1993-2021 period considered here. When the North Sea domain is included, the trend decreases to 0.03°C/year corresponding to an average warming of 0.87°C for the 1993-2021 period. Trends are highest for the Baltic Sea region and North Atlantic, especially offshore from Norway, compared to other regions. '''DOI (product):''' https://doi.org/10.48670/moi-00206

  • '''DEFINITION''' The OMI_CLIMATE_SST_BAL_area_averaged_anomalies product includes time series of monthly mean SST anomalies over the period 1993-2022, relative to the 1993-2014 climatology, averaged for the Baltic Sea. The SST Level 4 analysis products that provide the input to the monthly averages are taken from the reprocessed product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 with a recent update to include 2022. The product has a spatial resolution of 0.02 in latitude and longitude. The OMI time series runs from Jan 1, 1993 to December 31, 2022 and is constructed by calculating monthly averages from the daily level 4 SST analysis fields of the SST_BAL_SST_L4_REP_OBSERVATIONS_010_016 product from 1993 to 2022. 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 OMI product. '''CONTEXT''' Sea Surface Temperature (SST) is an Essential Climate Variable (GCOS) that is an important input for initialising numerical weather prediction models and fundamental for understanding air-sea interactions and monitoring climate change (GCOS 2010). The Baltic Sea is a region that requires special attention regarding the use of satellite SST records and the assessment of climatic variability (Høyer and She 2007; Høyer and Karagali 2016). The Baltic Sea is a semi-enclosed basin with natural variability and it is influenced by large-scale atmospheric processes and by the vicinity of land. In addition, the Baltic Sea is one of the largest brackish seas in the world. When analysing regional-scale climate variability, all these effects have to be considered, which requires dedicated regional and validated SST products. Satellite observations have previously been used to analyse the climatic SST signals in the North Sea and Baltic Sea (BACC II Author Team 2015; Lehmann et al. 2011). Recently, Høyer and Karagali (2016) demonstrated that the Baltic Sea had warmed 1-2 oC from 1982 to 2012 considering all months of the year and 3-5 oC when only July-September months were considered. This was corroborated in the Ocean State Reports (section 1.1 in Von Schuckmann et al., 2016; section 3 in Von Schuckmann et al., 2018). '''CMEMS KEY FINDINGS''' The basin-average trend of SST anomalies for Baltic Sea region amounts to 0.048±0.006°C/year over the period 1993-2022 which corresponds to an average warming of 1.44°C. Adding the North Sea area, the average trend amounts to 0.029±0.003°C/year over the same period, which corresponds to an average warming of 0.87°C for the entire region since 1993. '''Figure caption''' Time series of monthly mean (turquoise line) and annual mean (blue line) of sea surface temperature anomalies for January 1993 to December 2022, relative to the 1993-2014 mean, combined for the Baltic Sea and North Sea SST (OMI_CLIMATE_SST_BAL_area_averaged_anomalies). The data are based on the multi-year Baltic Sea L4 satellite SST reprocessed product SST_BAL_SST_L4_REP_OBSERVATIONS_010_016. '''DOI (product):''' https://doi.org/10.48670/moi-00205

  • '''Short description:''' For the Baltic Sea- The DMI Sea Surface Temperature L3S aims at providing daily multi-sensor supercollated data at 0.03deg. x 0.03deg. horizontal resolution, using satellite data from infra-red radiometers. Uses SST satellite products from these sensors: NOAA AVHRRs 7, 9, 11, 14, 16, 17, 18 , Envisat ATSR1, ATSR2 and AATSR. '''DOI (product) :''' https://doi.org/10.48670/moi-00154