{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:52:44Z","timestamp":1771548764256,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2021,8,3]],"date-time":"2021-08-03T00:00:00Z","timestamp":1627948800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004281","name":"Narodowe Centrum Nauki","doi-asserted-by":"publisher","award":["2017\/25\/B\/ST10\/00159"],"award-info":[{"award-number":["2017\/25\/B\/ST10\/00159"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Among the most frequently used satellite data are surface chlorophyll concentration (Chl) and temperature (SST). These data can be degraded in some coastal areas, for example, in the Baltic Sea. Other popular sources of data are reanalysis models. Before satellite or model data can be used effectively, they should be extensively compared with in situ measurements. Herein, we present results of such comparisons. We used SST and Chl from model reanalysis and satellites, and in situ data measured at eight open Baltic Sea stations. The data cover time interval from 1 January 1998 to 31 December 2019, but some satellite data were not always available. Both the model and the satellite SST data had good agreement with in situ measurements. In contrast, satellite and model estimates of Chl concentrations presented large errors. Modeled Chl presented the lowest bias and the best correlation with in situ data from all Chl data sets evaluated. Chl estimates from a regionally tuned algorithm (SatBaltic) had smaller errors in comparison with other satellite data sets and good agreement with in situ data in summer. Statistics were not as good for the full data set. High uncertainties found in chlorophyll satellite algorithms for the Baltic Sea highlight the importance of continuous regional validation of such algorithms with in situ data.<\/jats:p>","DOI":"10.3390\/rs13153049","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T02:16:07Z","timestamp":1628043367000},"page":"3049","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Comparisons of Satellite and Modeled Surface Temperature and Chlorophyll Concentrations in the Baltic Sea with In Situ Data"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3424-9846","authenticated-orcid":false,"given":"Malgorzata","family":"Stramska","sequence":"first","affiliation":[{"name":"Institute of Oceanology of the Polish Academy of Sciences, Powsta\u0144c\u00f3w Warszawy 55, 81-712 Sopot, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1145-9127","authenticated-orcid":false,"given":"Marta","family":"Konik","sequence":"additional","affiliation":[{"name":"Institute of Oceanology of the Polish Academy of Sciences, Powsta\u0144c\u00f3w Warszawy 55, 81-712 Sopot, Poland"}]},{"given":"Paulina","family":"Aniskiewicz","sequence":"additional","affiliation":[{"name":"Institute of Oceanology of the Polish Academy of Sciences, Powsta\u0144c\u00f3w Warszawy 55, 81-712 Sopot, Poland"}]},{"given":"Jaromir","family":"Jakacki","sequence":"additional","affiliation":[{"name":"Institute of Oceanology of the Polish Academy of Sciences, Powsta\u0144c\u00f3w Warszawy 55, 81-712 Sopot, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4326-5212","authenticated-orcid":false,"given":"Miroslaw","family":"Darecki","sequence":"additional","affiliation":[{"name":"Institute of Oceanology of the Polish Academy of Sciences, Powsta\u0144c\u00f3w Warszawy 55, 81-712 Sopot, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,3]]},"reference":[{"key":"ref_1","unstructured":"Axell, L., Huess, V., and Derval, C. 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