{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:18:47Z","timestamp":1771024727803,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:00:00Z","timestamp":1671840000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Baltic Sea is one of the fastest-warming marginal seas globally, and its temperature rise has adversely affected its physical and biochemical characteristics. In this study, forty years (1982\u20132021) of sea surface temperature (SST) data from the advanced very high resolution radiometer (AVHRR) were used to investigate spatial and temporal SST variability of the Baltic Sea. To this end, annual maximum and minimum SST stacked series, i.e., time series of stacked layers of satellite data, were generated using high-quality observations acquired at night and were fed to an automatic algorithm to detect linear and non-linear trend patterns. The linear trend pattern was the dominant trend type in both stacked series, while more pixels with non-linear trend patterns were detected when using the annual minimum SST. However, both stacked series showed increases in SST across the Baltic Sea. Annual maximum SST increased by an average of 0.062 \u00b1 0.041 \u00b0C per year between 1982 and 2021, while annual minimum SST increased by an average of 0.035 \u00b1 0.017 \u00b0C per year over the same period. Averaging annual maximum and minimum trends produces a spatial average of 0.048 \u00b1 0.022 \u00b0C rise in SST per year over the last four decades.<\/jats:p>","DOI":"10.3390\/rs15010102","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T02:50:01Z","timestamp":1672109401000},"page":"102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Satellite-Observed Spatial and Temporal Sea Surface Temperature Trends of the Baltic Sea between 1982 and 2021"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0961-9497","authenticated-orcid":false,"given":"Sadegh","family":"Jamali","sequence":"first","affiliation":[{"name":"Department of Technology and Society, Faculty of Engineering, Lund University, 221 00 Lund, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8406-683X","authenticated-orcid":false,"given":"Arsalan","family":"Ghorbanian","sequence":"additional","affiliation":[{"name":"Department of Technology and Society, Faculty of Engineering, Lund University, 221 00 Lund, Sweden"},{"name":"Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6486-8747","authenticated-orcid":false,"given":"Abdulhakim M.","family":"Abdi","sequence":"additional","affiliation":[{"name":"Center for Environmental and Climate Science, Lund University, 223 62 Lund, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1175\/BAMS-D-13-00047.1","article-title":"The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy","volume":"95","author":"Bojinski","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2529","DOI":"10.1175\/JCLI-D-15-0663.1","article-title":"Sea Surface Temperature Climate Data Record for the North Sea and Baltic Sea","volume":"29","author":"Karagali","year":"2016","journal-title":"J. Clim."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1175\/BAMS-D-11-00254.1","article-title":"The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables","volume":"94","author":"Hollmann","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"18813","DOI":"10.1038\/s41598-019-55303-7","article-title":"Climate Change over the Mediterranean and Current Destruction of Marine Ecosystem","volume":"9","author":"Kim","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.fishres.2014.07.014","article-title":"Are Regional Fisheries\u2019 Catches Changing with Climate?","volume":"161","author":"Gamito","year":"2015","journal-title":"Fish. Res."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sobrino, J.A., Garc\u00eda-Monteiro, S., and Julien, Y. (2020). Surface Temperature of the Planet Earth from Satellite Data over the Period 2003\u20132019. Remote Sens., 12.","DOI":"10.3390\/rs12122036"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/JSTARS.2021.3130789","article-title":"Remote Sensing Systems for Ocean: A Review (Part 1: Passive Systems)","volume":"15","author":"Amani","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/s41597-019-0236-x","article-title":"Satellite-based time-series of sea-surface temperature since 1981 for climate applications","volume":"6","author":"Merchant","year":"2019","journal-title":"Sci. Data"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"420","DOI":"10.3389\/fmars.2019.00420","article-title":"Observational Needs of Sea Surface Temperature","volume":"6","author":"Armstrong","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3021","DOI":"10.1007\/s00382-021-06084-1","article-title":"Understanding Past and Future Sea Surface Temperature Trends in the Baltic Sea","volume":"58","author":"Dutheil","year":"2021","journal-title":"Clim. Dyn."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"159","DOI":"10.5194\/esd-13-159-2022","article-title":"Oceanographic Regional Climate Projections for the Baltic Sea until 2100","volume":"13","author":"Meier","year":"2022","journal-title":"Earth Syst. Dyn."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bradtke, K. (2021). Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea. Remote Sens., 13.","DOI":"10.3390\/rs13224619"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4168","DOI":"10.1029\/2018JC013948","article-title":"Temperature variability of the baltic sea since 1850 and attribution to atmospheric forcing variables","volume":"124","author":"Kniebusch","year":"2019","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"525","DOI":"10.5194\/os-14-525-2018","article-title":"Assimilating High-Resolution Sea Surface Temperature Data Improves the Ocean Forecast Potential in the Baltic Sea","volume":"14","author":"Liu","year":"2018","journal-title":"Ocean Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.oceano.2015.04.004","article-title":"Spatial and Temporal Variability of Sea Surface Temperature in the Baltic Sea Based on 32-Years (1982\u20132013) of Satellite Data","volume":"57","author":"Stramska","year":"2015","journal-title":"Oceanologia"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2268","DOI":"10.1175\/JCLI-D-12-00296.1","article-title":"Connecting Changing Ocean Circulation with Changing Climate","volume":"26","author":"Winton","year":"2013","journal-title":"J. Clim."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.oceano.2021.12.004","article-title":"Regime Shift in Sea-Ice Characteristics and Impact on the Spring Bloom in the Baltic Sea","volume":"64","author":"Friedland","year":"2022","journal-title":"Oceanologia"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"711","DOI":"10.5194\/esd-13-711-2022","article-title":"Global Climate Change and the Baltic Sea Ecosystem: Direct and Indirect Effects on Species, Communities and Ecosystem Functioning","volume":"13","author":"Viitasalo","year":"2022","journal-title":"Earth Syst. Dyn."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.earscirev.2008.10.001","article-title":"Past Occurrences of Hypoxia in the Baltic Sea and the Role of Climate Variability, Environmental Change and Human Impact","volume":"91","author":"Conley","year":"2008","journal-title":"Earth-Sci. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5945","DOI":"10.1007\/s00382-019-04908-9","article-title":"Summer Hydrographic Changes in the Baltic Sea, Kattegat and Skagerrak Projected in an Ensemble of Climate Scenarios Downscaled with a Coupled Regional Ocean\u2013Sea Ice\u2013Atmosphere Model","volume":"53","author":"Arneborg","year":"2019","journal-title":"Clim. Dyn."},{"key":"ref_21","unstructured":"(2022, December 20). Copernicus Climate Change Service 2020 Warmest Year on Record for Europe; Globally, 2020 Ties with 2016 for Warmest Year Recorded. Available online: https:\/\/climate.copernicus.eu\/copernicus-2020-warmest-year-record-europe-globally-2020-ties-2016-warmest-year-recorded#:~:text=The%20Copernicus%20Climate%20Change%20Service%20(C3S)%20today%20reveals%20that%20globally,2020%20the%20warmest%20decade%20recorded."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.rse.2013.10.019","article-title":"Automated Mapping of Vegetation Trends with Polynomials Using NDVI Imagery over the Sahel","volume":"141","author":"Jamali","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/S1385-1101(03)00035-2","article-title":"One Hundred Years of Hydrographic Measurements in the Baltic Sea","volume":"49","author":"Fonselius","year":"2003","journal-title":"J. Sea Res."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Barale, V., Gower, J.F.R., and Alberotanza, L. (2010). The Past, Present, and Future of the AVHRR Pathfinder SST Program. Oceanography from Space: Revisited, Springer.","DOI":"10.1007\/978-90-481-8681-5"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"27999","DOI":"10.1029\/98JC02370","article-title":"The Development and Operational Application of Nonlinear Algorithms for the Measurement of Sea Surface Temperatures with the NOAA Polar-Orbiting Environmental Satellites","volume":"103","author":"Walton","year":"1998","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"9179","DOI":"10.1029\/1999JC000065","article-title":"Overview of the NOAA\/NASA Advanced Very High Resolution Radiometer Pathfinder Algorithm for Sea Surface Temperature and Associated Matchup Database","volume":"106","author":"Kilpatrick","year":"2001","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Saha, K., Dash, P., Zhao, X., and Zhang, H. (2020). Error Estimation of Pathfinder Version 5.3 Level-3C SST Using Extended Triple Collocation Analysis. Remote Sens., 12.","DOI":"10.3390\/rs12040590"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5326","DOI":"10.1109\/JSTARS.2020.3021052","article-title":"Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review","volume":"13","author":"Amani","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"745","DOI":"10.5194\/os-10-745-2014","article-title":"Characterisation and Quantification of Regional Diurnal SST Cycles from SEVIRI","volume":"10","author":"Karagali","year":"2014","journal-title":"Ocean Sci."},{"key":"ref_31","first-page":"102086","article-title":"Surface Temperature Trends in the Mediterranean Sea from MODIS Data during Years 2003\u20132019","volume":"49","author":"Sobrino","year":"2022","journal-title":"Reg. Stud. Mar. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"e2020EF001835","DOI":"10.1029\/2020EF001835","article-title":"Linear and Nonlinear Trend Analyzes in Global Satellite-Based Precipitation, 1998\u20132017","volume":"9","author":"Kazemzadeh","year":"2021","journal-title":"Earth\u2019s Futur."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Jamali, S., Klingmyr, D., and Tagesson, T. (2020). Global-Scale Patterns and Trends in Tropospheric NO2 Concentrations, 2005\u20132018. Remote Sens., 12.","DOI":"10.3390\/rs12213526"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1007\/s13351-022-1184-5","article-title":"Four Decades of Air Temperature Data over Iran Reveal Linear and Nonlinear Warming","volume":"36","author":"Kazemzadeh","year":"2022","journal-title":"J. Meteorol. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"L22602","DOI":"10.1029\/2008GL035730","article-title":"Multi-Satellite Measurements of Large Diurnal Warming Events","volume":"35","author":"Gentemann","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1002\/joc.1779","article-title":"Updated and Extended European Dataset of Daily Climate Observations","volume":"29","author":"Klok","year":"2009","journal-title":"Int. J. Climatol. A J. R. Meteorol. Soc."},{"key":"ref_37","first-page":"119","article-title":"Sea Surface Temperature Development of the Baltic Sea in the Period 1990\u20132004","volume":"48","author":"Siegel","year":"2006","journal-title":"Oceanologia"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"185","DOI":"10.3354\/cr00876","article-title":"Detailed Assessment of Climate Variability in the Baltic Sea Area for the Period 1958 to 2009","volume":"46","author":"Lehmann","year":"2011","journal-title":"Clim. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"162","DOI":"10.5670\/oceanog.2018.205","article-title":"Categorizing and Naming Marine Heatwaves","volume":"31","author":"Hobday","year":"2018","journal-title":"Oceanography"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"734","DOI":"10.3389\/fmars.2019.00734","article-title":"Projected Marine Heatwaves in the 21st Century and the Potential for Ecological Impact","volume":"6","author":"Oliver","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"174","DOI":"10.3389\/feart.2019.00174","article-title":"Stratification Has Strengthened in the Baltic Sea\u2014An Analysis of 35 Years of Observational Data","volume":"7","author":"Liblik","year":"2019","journal-title":"Front. Earth Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/102\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:50:30Z","timestamp":1760147430000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/102"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,24]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15010102"],"URL":"https:\/\/doi.org\/10.3390\/rs15010102","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,24]]}}}