{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:07:21Z","timestamp":1772554041818,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,6]],"date-time":"2018-08-06T00:00:00Z","timestamp":1533513600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["NNX17AK08G, NNX17AK02G"],"award-info":[{"award-number":["NNX17AK08G, NNX17AK02G"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring the cold and productive waters of the Gulf of Maine and their interactions with the nearby northwestern (NW) Atlantic shelf is important but challenging. Although remotely sensed sea surface temperature (SST), ocean color, and sea level have become routine, much of the water exchange physics is reflected in salinity fields. The recent invention of satellite salinity sensors, including the Soil Moisture Active Passive (SMAP) radiometer, opens new prospects in regional shelf studies. However, local sea surface salinity (SSS) retrieval is challenging due to both cold SST limiting salinity sensor sensitivity and proximity to land. For the NW Atlantic, our analysis shows that SMAP SSS is subject to an SST-dependent bias that is negative and amplifies in winter and early spring due to the SST-related drop in SMAP sensor sensitivity. On top of that, SMAP SSS is subject to a land contamination bias. The latter bias becomes noticeable and negative when the antenna land contamination factor (LC) exceeds 0.2%, and attains maximum negative values at LC = 0.4%. Coastward of LC = 0.5%, a significant positive land contamination bias in absolute SMAP SSS is evident. SST and land contamination bias components are seasonally dependent due to seasonal changes in SST\/winds and terrestrial microwave properties. Fortunately, it is shown that SSS anomalies computed relative to a satellite SSS climatology can effectively remove such seasonal biases along with the real seasonal cycle. SMAP monthly SSS anomalies have sufficient accuracy and applicability to extend nearer to the coasts. They are used to examine the Gulf of Maine water inflow, which displayed important water intrusions in between Georges Banks and Nova Scotia in the winters of 2016\/17 and 2017\/18. Water intrusion patterns observed by SMAP are generally consistent with independent measurements from the European Soil Moisture Ocean Salinity (SMOS) mission. Circulation dynamics related to the 2016\/2017 period and enhanced wind-driven Scotian Shelf transport into the Gulf of Maine are discussed.<\/jats:p>","DOI":"10.3390\/rs10081232","type":"journal-article","created":{"date-parts":[[2018,8,7]],"date-time":"2018-08-07T03:44:18Z","timestamp":1533613458000},"page":"1232","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Assessing Coastal SMAP Surface Salinity Accuracy and Its Application to Monitoring Gulf of Maine Circulation Dynamics"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0670-1356","authenticated-orcid":false,"given":"Semyon A.","family":"Grodsky","sequence":"first","affiliation":[{"name":"Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4367-5457","authenticated-orcid":false,"given":"Douglas","family":"Vandemark","sequence":"additional","affiliation":[{"name":"Ocean Process Analysis Laboratory, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6275-1553","authenticated-orcid":false,"given":"Hui","family":"Feng","sequence":"additional","affiliation":[{"name":"Ocean Process Analysis Laboratory, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mountain, D.G. 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Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1232\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:16:49Z","timestamp":1760195809000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1232"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,6]]},"references-count":27,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["rs10081232"],"URL":"https:\/\/doi.org\/10.3390\/rs10081232","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,6]]}}}