{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:10:11Z","timestamp":1770754211337,"version":"3.50.0"},"reference-count":85,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T00:00:00Z","timestamp":1610496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Swedish National Space Board","award":["174\/17"],"award-info":[{"award-number":["174\/17"]}]},{"name":"BONUS","award":["2015-101"],"award-info":[{"award-number":["2015-101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002\u2013October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables\u2019 importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 \u00b5atm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables\u2019 importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.<\/jats:p>","DOI":"10.3390\/rs13020259","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T21:50:54Z","timestamp":1610574654000},"page":"259","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea"],"prefix":"10.3390","volume":"13","author":[{"given":"Shuping","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Earth Sciences, Uppsala University, SE-752 36 Uppsala, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7656-1881","authenticated-orcid":false,"given":"Anna","family":"Rutgersson","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, Uppsala University, SE-752 36 Uppsala, Sweden"}]},{"given":"Petra","family":"Philipson","sequence":"additional","affiliation":[{"name":"Brockmann Geomatics Sweden AB, SE-164 40 Kista, Sweden"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3082-8728","authenticated-orcid":false,"given":"Marcus B.","family":"Wallin","sequence":"additional","affiliation":[{"name":"Department of Earth Sciences, Uppsala University, SE-752 36 Uppsala, Sweden"},{"name":"Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1126\/science.aau5153","article-title":"The oceanic sink for anthropogenic CO2 from 1994 to 2007","volume":"363","author":"Gruber","year":"2019","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-017-02738-z","article-title":"Continental shelves as a variable but increasing global sink for atmospheric carbon dioxide","volume":"9","author":"Laruelle","year":"2018","journal-title":"Nat. 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