{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T17:55:42Z","timestamp":1762624542915,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T00:00:00Z","timestamp":1610064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Sea surface temperature (SST) is an essential climate variable used for ocean and weather monitoring and forecasting. The NOAA\u2019s next generation geostationary satellite GOES-16 was declared operational at the east position (75\u00b0W) in December 2017, carrying onboard an Advanced Baseline Imager (ABI). The hyperspectral ABI sensor now allows SST estimates every 10\u201315 min at both day and nighttime, with advanced options for cloud screening and water vapor correction. In the present work, we compare the first operational ABI SST product (OSI SAF, 2018) with an in situ match-up database (MDB) across the Tropical and Southwestern Atlantic Ocean, off the Brazilian coast, throughout the year of 2018. The MDB was obtained from two long-term programs, i.e., PIRATA moored buoys (FOLTZ et al., 2016) and PNBoia moored and drifting buoys (MARINHA DO BRASIL, 2017). Separate comparisons were made for each data set, analyzing the uncertainties according to the program (i.e., buoy type and region), satellite SST quality level and influence of diurnal heating. We also compare the ABI product with the OSTIA analysis L4 SST (DONLON et al., 2012) to increment our analyses on the spatio-temporal biases within the study region. The results show that the OSI SAF ABI SST L3C has a mean bias (0.1 \u00b0C) and error (RMSE, 0.5 \u00b0C) within the GHRSST standards, with an exception being coastal waters off the southeast Brazilian coast (RMSE, 0.65 \u00b0C), which are subjected to sharp thermal fronts. The highest biases are for regions\/seasons subjected to persistent cloud coverage and high water-vapor content, i.e., the Intertropical and South Atlantic Convergence Zones, as well as highly dynamic frontal zones, i.e., the Brazil Malvinas Confluence Zone, the Subtropical Front and coastal waters. The ABI SST product is suitable for operational use, and applications should explore more deeply the new set of information provided.<\/jats:p>","DOI":"10.3390\/rs13020192","type":"journal-article","created":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T23:03:42Z","timestamp":1610319822000},"page":"192","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Evaluation of the ABI\/GOES-16 SST Product in the Tropical and Southwestern Atlantic Ocean"],"prefix":"10.3390","volume":"13","author":[{"given":"Mayna Helena","family":"Azevedo","sequence":"first","affiliation":[{"name":"Instituto Nacional de Pesquisas Espaciais, Dutra km 39, Cachoeira Paulista 12227-010, S\u00e3o Paulo, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3451-4512","authenticated-orcid":false,"given":"Nat\u00e1lia","family":"Rudorff","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Pesquisas Espaciais, Dutra km 39, Cachoeira Paulista 12227-010, S\u00e3o Paulo, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3498-4995","authenticated-orcid":false,"given":"Jos\u00e9 Ant\u00f4nio","family":"Arav\u00e9quia","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Pesquisas Espaciais, Dutra km 39, Cachoeira Paulista 12227-010, S\u00e3o Paulo, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1177\/0309133316638957","article-title":"Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea ice","volume":"40","author":"Shutler","year":"2016","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_2","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_3","doi-asserted-by":"crossref","first-page":"3158","DOI":"10.1175\/MWR3465.1","article-title":"Real-time, High-resolution, space-time analysis of sea surface temperatures from multiple platforms","volume":"135","author":"Lazarus","year":"2007","journal-title":"Mon. Weather Rev."},{"key":"ref_4","first-page":"S12","article-title":"Use of satellite observations for operational oceanography: Recent achievements and future prospects","volume":"8","author":"Antoine","year":"2015","journal-title":"J. Oper. Oceanogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1029\/RG014i004p00609","article-title":"Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation","volume":"14","author":"Rodgers","year":"1976","journal-title":"Rev. Geophys."},{"key":"ref_6","first-page":"06112","article-title":"Implementation of the Community Radiative Transfer Model in Advanced Clear-Sky Processor for Oceans and validation against nighttime AVHRR radiances","volume":"114","author":"Liang","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_7","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_8","doi-asserted-by":"crossref","first-page":"11587","DOI":"10.1029\/JC090iC06p11587","article-title":"Comparative performance of AVHRR-based multichannel sea surface temperatures","volume":"90","author":"McClain","year":"1985","journal-title":"J. Geophys. Res."},{"key":"ref_9","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_10","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.isprsjprs.2020.06.008","article-title":"Machine learning techniques for regional scale estimation of high-resolution cloud-free daily sea surface temperatures from MODIS data","volume":"166","author":"Sunder","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","unstructured":"GHRSST Science Team (2010). The Recommended GHRSST Data Specification (GDS) 2.0, Document Revision 4, GHRSST Project Office."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Petrenko, B., Ignatov, A., Kihai, Y., and Pennybacker, M. (2019). Optimization of sensitivity of GOES-16 ABI sea surface temperature by matching satellite observations with L4 analysis. Remote Sens., 11.","DOI":"10.3390\/rs11020206"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.rse.2006.03.007","article-title":"Saharan dust in nighttime thermal imagery: Detection and reduction of related biases in retrieved sea surface temperature","volume":"104","author":"Merchant","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1175\/BAMS-88-8-1197","article-title":"Global Ocean Data Assimilation Experiment (GODAE) High Resolution Sea Surface Temperature Pilot Project (GHRSST-PP)","volume":"88","author":"Donlon","year":"2007","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","unstructured":"A (NOAA\/NESDIS\/STAR) Ignatov (2010). GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for Sea Surface Temperature, NOAA\/NESDIS\/STAR."},{"key":"ref_16","unstructured":"OSI SAF (2021, January 04). Geostationary Sea Surface Temperature Product User Manual v1.9, Available online: http:\/\/www.osi-saf.org."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005GL023866","article-title":"Ocean-atmosphere in situ observations at the Brazil-Malvinas Confluence region","volume":"32","author":"Pezzi","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.csr.2019.05.008","article-title":"First measurements of the ocean-atmosphere CO2 fluxes at the Cabo Frio upwelling system region, Southwestern Atlantic Ocean","volume":"181","author":"Oliveira","year":"2019","journal-title":"Cont. Shelf Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmars.2019.00206","article-title":"The tropical atlantic observing system","volume":"6","author":"Foltz","year":"2019","journal-title":"Front. Mar. Sci."},{"key":"ref_20","unstructured":"Marinha do Brasil (2017). Programa Nacional De Boias\u2014Pnboia-Plano Nacional De Trabalho, Marinha do Brasil."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"813","DOI":"10.2151\/jmsj1965.70.4_813","article-title":"Large-scale common features of subtropical precipitation zones (the Baiu Frontal Zone, the SPCZ, and the SACZ) Part I: Characteristics of subtropical frontal zones","volume":"70","author":"Kodama","year":"1992","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/nature13636","article-title":"Migrations and dynamics of the intertropical convergence zone","volume":"513","author":"Schneider","year":"2014","journal-title":"Nature"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5527","DOI":"10.1007\/s00382-018-4460-4","article-title":"Dynamics-based regression models for the South Atlantic Convergence Zone","volume":"52","author":"Nielsen","year":"2019","journal-title":"Clim. Dyn."},{"key":"ref_24","first-page":"13","article-title":"A Lagrangian study of the Brazil-Malvinas confluence: Lagrangian coherent structures and several lyapunov exponents","volume":"7","author":"Morel","year":"2014","journal-title":"J. Oper. Oceanogr."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"983","DOI":"10.5194\/os-6-983-2010","article-title":"The influence of the Brazil and Malvinas Currents on the Southwestern Atlantic Shelf circulation","volume":"6","author":"Matano","year":"2010","journal-title":"Ocean Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0079-6611(91)90006-8","article-title":"Upper-level circulation in the South Atlantic Ocean","volume":"26","author":"Peterson","year":"1991","journal-title":"Prog. Oceanogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1175\/1520-0442(2002)015<0353:TIVOSS>2.0.CO;2","article-title":"Toward improved validation of satellite sea surface skin temperature measurements for climate research","volume":"15","author":"Donlon","year":"2002","journal-title":"J. Clim."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4707","DOI":"10.1080\/01431160500166128","article-title":"MSG\/SEVIRI cloud mask and type from SAFNWC","volume":"26","author":"Derrien","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1016\/j.rse.2008.10.012","article-title":"Sea surface temperature from a geostationary satellite by optimal estimation","volume":"113","author":"Merchant","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.rse.2010.08.004","article-title":"Estimation of Sea Surface Temperature from the Spinning Enhanced Visible and Infrared Imager, improved using numerical weather prediction","volume":"115","author":"Roquet","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/S0034-4257(02)00008-1","article-title":"Definition of a radiosounding database for sea surface brightness temperature simulations","volume":"81","author":"Brisson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2010.10.017","article-title":"The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system","volume":"116","author":"Donlon","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_33","unstructured":"OSI SAF (2015). Global Sea Ice Concentration Reprocessing Product User Manual v 2.0, OSI SAF. Available online: http:\/\/www.osi-saf.org."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1002\/qj.49711749704","article-title":"The Meteorological Office analysis correction data assimilation scheme","volume":"117","author":"Lorenc","year":"1991","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1002\/qj.74","article-title":"Data assimilation in the FOAM operational short-range ocean forecasting system: A description of the scheme and its impact","volume":"133","author":"Martin","year":"2007","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_36","unstructured":"Picart, S.S., and Marsouin, A. (2021, January 04). Geostationary Satellite Sea Surface Temperature Scientific Validation Report Meteosat SST: OSI-206-a GOES-East SST: OSI-207-a Meteosat Indian Ocean SST: OSI-IO-SST v1.0. Available online: http:\/\/www.osi-saf.org."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1002\/2015GL067159","article-title":"Sea surface temperature from the new Japanese geostationary meteorological Himawari-8 satellite","volume":"43","author":"Kurihara","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Woo, H.J., Park, K.A., Li, X., and Lee, E.Y. (2018). Sea surface temperature retrieval from the first Korean geostationary satellite COMS data: Validation and error assessment. Remote Sens., 10.","DOI":"10.3390\/rs10121916"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1175\/JTECH-D-15-0226.1","article-title":"Estimating infrared radiometric satellite sea surface temperature retrieval cold biases in the tropics due to unscreened optically thin cirrus clouds","volume":"34","author":"Marquis","year":"2017","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1208","DOI":"10.1175\/2008JTECHO560.1","article-title":"Determination of AATSR biases using the OSTIA SST analysis system and a matchup database","volume":"25","author":"Stark","year":"2008","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1607","DOI":"10.1016\/j.csr.2008.03.012","article-title":"The effects of river discharge and seasonal winds on the shelf off southeastern South America","volume":"28","author":"Piola","year":"2008","journal-title":"Cont. Shelf Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Brewin, R.J.W., Smale, D.A., Moore, P.J., Nencioli, F., Miller, P.I., Taylor, B.H., Smyth, T.J., Fishwick, J., and Yang, M. (2018). Evaluating Operational AVHRR Sea Surface Temperature Data at the Coastline Using Benthic Temperature Loggers. Remote Sens., 10.","DOI":"10.3390\/rs10060925"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yang, M., Guan, L., Beggs, H., Morgan, N., Kurihara, Y., and Kachi, M. (2020). Comparison of Himawari-8 AHI SST with shipboard skin SST measurements in the Australian region. Remote Sens., 12.","DOI":"10.3390\/rs12081237"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/192\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:08:19Z","timestamp":1760159299000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/192"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,8]]},"references-count":43,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13020192"],"URL":"https:\/\/doi.org\/10.3390\/rs13020192","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,1,8]]}}}