{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T12:53:25Z","timestamp":1781787205190,"version":"3.54.5"},"reference-count":38,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Copernicus Marine Environment Monitoring Service (CMEMS) Multi-Observation Thematic Assembly Centre","award":["83-CMEMS-TAC-MULTI-OBS"],"award-info":[{"award-number":["83-CMEMS-TAC-MULTI-OBS"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs), defined by the Global Climate Observing System (GCOS). Salinity is modified by river discharge, land run-off, precipitation, and evaporation, and it is advected by oceanic currents. In turn, ocean circulation, the water cycle, and biogeochemistry are deeply impacted by salinity variations. The Mediterranean Sea represents a hot spot for the variability of salinity. Despite the ever-increasing number of moorings and floating buoys, in situ SSS estimates have low coverage, hindering the monitoring of SSS patterns. Conversely, satellite sensors provide SSS surface data at high spatial and temporal resolution, complementing the sparseness of in situ datasets. Here, we describe a multidimensional optimal interpolation algorithm, specifically configured to provide a new daily SSS dataset at 1\/16\u00b0 grid resolution, covering the entire Mediterranean Sea (Med L4 SSS). The main improvements in this regional algorithm are: the ingestion of satellite SSS estimates from multiple satellite missions (NASA\u2019s Soil Moisture Active Passive (SMAP), ESA\u2019s Soil Moisture and Ocean Salinity (SMOS) satellites), and a new background (first guess), specifically built to improve coastal reconstructions. The multi-sensor Med L4 SSS fields have been validated against independent in situ SSS samples, collected between 2010\u20132020. They have also been compared with global weekly Copernicus Marine Environment Monitoring Service (CMEMS) and Barcelona Expert Centre (BEC) regional products, showing an improved performance. Power spectral density analyses demonstrated that the Med L4 SSS field achieves the highest effective spatial resolution, among all the datasets analysed. Even if the time series is relatively short, a clear interannual trend is found, leading to a marked salinification, mostly occurring in the Eastern Mediterranean Sea.<\/jats:p>","DOI":"10.3390\/rs14102502","type":"journal-article","created":{"date-parts":[[2022,5,24]],"date-time":"2022-05-24T03:16:55Z","timestamp":1653362215000},"page":"2502","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Retrieving Mediterranean Sea Surface Salinity Distribution and Interannual Trends from Multi-Sensor Satellite and In Situ Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Michela","family":"Sammartino","sequence":"first","affiliation":[{"name":"Istituto di Scienze Marine, Consiglio Nazionale delle Ricerche (ISMAR-CNR), 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3489-1473","authenticated-orcid":false,"given":"Salvatore","family":"Aronica","sequence":"additional","affiliation":[{"name":"Istituto per lo Studio degli Impatti Antropici e Sostenibilit\u00e0 in Ambiente Marino, Consiglio Nazionale delle Ricerche (IAS-CNR), S.S. di Capo Granitola, 91021 Campobello di Mazara, Trapani, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2900-5054","authenticated-orcid":false,"given":"Rosalia","family":"Santoleri","sequence":"additional","affiliation":[{"name":"Istituto di Scienze Marine, Consiglio Nazionale delle Ricerche (ISMAR-CNR), 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3416-7189","authenticated-orcid":false,"given":"Bruno","family":"Buongiorno Nardelli","sequence":"additional","affiliation":[{"name":"Istituto di Scienze Marine, Consiglio Nazionale delle Ricerche (ISMAR-CNR), 80133 Naples, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111769","DOI":"10.1016\/j.rse.2020.111769","article-title":"Sea surface salinity estimates from spaceborne L-band radiometers: An overview of the first decade of observation (2010\u20132019)","volume":"242","author":"Reul","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1080\/19475721.2010.491656","article-title":"The circulation of the Mediterranean Sea: A historical review of experimental investigations","volume":"1","author":"Bergamasco","year":"2010","journal-title":"Adv. Oceanogr. Limnol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2857","DOI":"10.1007\/s00382-017-4053-7","article-title":"Mediterranean sea water budget long-term trend inferred from salinity observations","volume":"51","author":"Skliris","year":"2018","journal-title":"Clim. Dyn."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1800","DOI":"10.1175\/2009JPO4109.1","article-title":"On the Source of Mediterranean Overflow Water Property Changes","volume":"39","author":"Lozier","year":"2009","journal-title":"J. Phys. Oceanogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"L01202","DOI":"10.1029\/2003GL018161","article-title":"On the warming and salinification of the Mediterranean outflow waters in the North Atlantic","volume":"31","author":"Potter","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Goffredo, S., and Dubinsky, Z. (2014). Past, present and future patterns of the Thermohaline Circulation and characteristic water masses of the Mediterranean Sea. The Mediterranean Sea, Springer.","DOI":"10.1007\/978-94-007-6704-1"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"L21609","DOI":"10.1029\/2007GL031179","article-title":"Interannual salinification of the Mediterranean inflow","volume":"34","author":"Millot","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"243","DOI":"10.3389\/fmars.2019.00243","article-title":"Satellite Salinity Observing System: Recent Discoveries and the Way Forward","volume":"6","author":"Vinogradova","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"109312","DOI":"10.1016\/j.palaeo.2019.109312","article-title":"Decoding sea surface and paleoclimate conditions in the eastern Mediterranean over the Tortonian-Messinian Transition","volume":"534","author":"Kontakiotis","year":"2019","journal-title":"Palaeogeogr. Palaeoclimatol. Palaeoecol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"110903","DOI":"10.1016\/j.palaeo.2022.110903","article-title":"Hypersalinity accompanies tectonic restriction in the eastern Mediterranean prior to the Messinian Salinity Crisis","volume":"592","author":"Kontakiotis","year":"2022","journal-title":"Palaeogeogr. Palaeoclimatol. Palaeoecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1029\/2018PA003438","article-title":"Large Sea Surface Temperature, Salinity, and Productivity-Preservation Changes Preceding the Onset of the Messinian Salinity Crisis in the Eastern Mediterranean Sea","volume":"34","author":"Vasiliev","year":"2019","journal-title":"Paleoceanogr. Paleoclimatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1175\/1520-0426(2000)017<0512:RAOTSV>2.0.CO;2","article-title":"Retrospective Analysis of the Salinity Variability in the Western Tropical Pacific Ocean Using an Indirect Minimization Approach","volume":"17","author":"Maes","year":"2000","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_13","first-page":"11","article-title":"Reconstructing Synthetic Profiles from Surface Data","volume":"21","author":"Santoleri","year":"2004","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jmarsys.2003.11.022","article-title":"Combining Argo and remote-sensing data to estimate the ocean three-dimensional temperature fields\u2014A first approach based on simulated observations","volume":"46","author":"Guinehut","year":"2004","journal-title":"J. Mar. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1762","DOI":"10.1175\/JTECH1792.1","article-title":"Methods for the Reconstruction of Vertical Profiles from Surface Data: Multivariate Analyses, Residual GEM, and Variable Temporal Signals in the North Pacific Ocean","volume":"22","author":"Santoleri","year":"2005","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_16","first-page":"C04007","article-title":"Subsurface geostrophic velocities inference from altimeter data: Application to the Sicily Channel (Mediterranean Sea)","volume":"111","author":"Cavalieri","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1016\/j.dsr.2009.05.017","article-title":"Linear and non-linear T\u2013S models for the eastern North Atlantic from Argo data: Role of surface salinity observations","volume":"56","author":"Mourre","year":"2009","journal-title":"Deep Sea Res. Part Oceanogr. Res. Pap."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1175\/JTECH-D-17-0226.1","article-title":"Salinity Profile Estimation in the Pacific Ocean from Satellite Surface Salinity Observations","volume":"36","author":"Bao","year":"2019","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Su, H., Yang, X., Lu, W., and Yan, X.-H. (2019). Estimating Subsurface Thermohaline Structure of the Global Ocean Using Surface Remote Sensing Observations. Remote Sens., 11.","DOI":"10.3390\/rs11131598"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Buongiorno Nardelli, B. (2020). A Deep Learning Network to Retrieve Ocean Hydrographic Profiles from Combined Satellite and In Situ Measurements. Remote Sens., 12.","DOI":"10.1002\/essoar.10503703.1"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.rse.2013.09.018","article-title":"New blending algorithm to synergize ocean variables: The case of SMOS sea surface salinity maps","volume":"146","author":"Umbert","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.rse.2015.12.052","article-title":"Multi-dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data","volume":"180","author":"Droghei","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1175\/JTECH-D-11-00099.1","article-title":"A Novel Approach for the High-Resolution Interpolation of In Situ Sea Surface Salinity","volume":"29","year":"2012","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1175\/JTECH-D-15-0194.1","article-title":"Combining in Situ and Satellite Observations to Retrieve Salinity and Density at the Ocean Surface","volume":"33","author":"Droghei","year":"2016","journal-title":"J. Atmos. Ocean Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"84","DOI":"10.3389\/fmars.2018.00084","article-title":"A New Global Sea Surface Salinity and Density Dataset from Multivariate Observations (1993\u20132016)","volume":"5","author":"Droghei","year":"2018","journal-title":"Front. Mar. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Olmedo, E., Taupier-Letage, I., Turiel, A., and Alvera-Azc\u00e1rate, A. (2018). Improving SMOS Sea Surface Salinity in the Western Mediterranean Sea through Multivariate and Multifractal Analysis. Remote Sens., 10.","DOI":"10.3390\/rs10030485"},{"key":"ref_27","unstructured":"Kolodziejczyk, N., Diverres, D., Jacquin, S., Gouriou, Y., Grelet, J., Le Menn, M., Tassel, J., Reverdin, G., Maes, C., and Gaillard, F. (2021). Sea Surface Salinity from French RESearcH Vessels: Delayed mode dataset, annual release. SEANOE."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.5194\/essd-10-1281-2018","article-title":"Mediterranean Sea Hydrographic Atlas: Towards optimal data analysis by including time-dependent statistical parameters","volume":"10","author":"Iona","year":"2018","journal-title":"Earth Syst. Sci."},{"key":"ref_29","unstructured":"Fore, A., Yueh, S., Tang, W., and Hayashi, A. (2020). SMAP Salinity and Wind Speed Data User\u2019s Guide, California Institute of Technology."},{"key":"ref_30","unstructured":"NASA Jet Propulsion Laboratory (NASA\/JPL) (2022, April 03). JPL SMAP Level 2B near Real-time CAP Sea Surface Salinity V5.0 Validated Dataset 2020, Available online: https:\/\/podaac.jpl.nasa.gov\/dataset\/SMAP_JPL_L2B_NRT_SSS_CAP_V5."},{"key":"ref_31","unstructured":"BEC Team (2019). SMOS-BEC Mediterranean Region SSS Product Description, Instituto de Ciencias del Mar (ICM)\u2014CSIC."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2012.10.012","article-title":"High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project","volume":"129","author":"Tronconi","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Colella, S., Falcini, F., Rinaldi, E., Sammartino, M., and Santoleri, R. (2016). Mediterranean Ocean Colour Chlorophyll Trends. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0155756"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Pisano, A., Marullo, S., Artale, V., Falcini, F., Yang, C., and Leonelli, F.E. (2020). New Evidence of Mediterranean Climate Change and Variability from Sea Surface Temperature Observations. Remote Sens., 12.","DOI":"10.3390\/rs12010132"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1379","DOI":"10.1080\/01621459.1968.10480934","article-title":"Estimates of the Regression Coefficient Based on Kendall\u2019s Tau","volume":"63","author":"Sen","year":"1968","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"103190","DOI":"10.1016\/j.jmarsys.2019.103190","article-title":"Eastern Mediterranean salinification observed in satellite salinity from SMAP mission","volume":"198","author":"Grodsky","year":"2019","journal-title":"J. Mar. Syst."},{"key":"ref_37","unstructured":"Kendall, M. (1975). Multivariate Analysis, Charles Griffin b Co. Ltd."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2307\/1907187","article-title":"Nonparametric Tests against Trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/10\/2502\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:17:05Z","timestamp":1760138225000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/10\/2502"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":38,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["rs14102502"],"URL":"https:\/\/doi.org\/10.3390\/rs14102502","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,23]]}}}