{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:19:25Z","timestamp":1774351165776,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T00:00:00Z","timestamp":1654992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Central Weather Bureau of Taiwan","award":["1102084A"],"award-info":[{"award-number":["1102084A"]}]},{"name":"Central Weather Bureau of Taiwan","award":["MOST110-2611-M-019-001"],"award-info":[{"award-number":["MOST110-2611-M-019-001"]}]},{"name":"Ministry of Science and Technology of Taiwan","award":["1102084A"],"award-info":[{"award-number":["1102084A"]}]},{"name":"Ministry of Science and Technology of Taiwan","award":["MOST110-2611-M-019-001"],"award-info":[{"award-number":["MOST110-2611-M-019-001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite remote sensing sea surface temperature (SST) data are lost due to cloud cover. Missing data often cause inconvenience in subsequent applications and thus need to be reconstructed. In this study, the Data Interpolating Empirical Orthogonal Function (DINEOF) method was used to reconstruct the hourly SST data missing from the Himawari-8 satellite in the waters near Taiwan. The SST characteristics in the waters around Taiwan are quite complex, with high SST at Kuroshio in the east of Taiwan and great variation in the SST west of Taiwan due to the influence of tides. Therefore, the analysis with DINEOF was conducted using 25-h data to match the tidal cycle. The influence of SST characteristics on the accuracy of SST reconstruction is also discussed. The results show that in the western sea area where the variation of SST is large, the average root-mean-square error of SST between the original SST and the reconstructed SST is the lowest and the average coefficient of determination is the highest. The accuracy of the reconstructed SST is positively correlated with the SST variation. Furthermore, the statistical results also show that the DINEOF method can effectively reconstruct the SST regardless of the missing data rate.<\/jats:p>","DOI":"10.3390\/rs14122818","type":"journal-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T23:55:24Z","timestamp":1655078124000},"page":"2818","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["On the Reconstruction of Missing Sea Surface Temperature Data from Himawari-8 in Adjacent Waters of Taiwan Using DINEOF Conducted with 25-h Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6098-6022","authenticated-orcid":false,"given":"Yi-Chung","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Marine Environmental Informatics, National Taiwan Ocean University, 2 Pei-Ning Road, Keelung 202301, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3822-9324","authenticated-orcid":false,"given":"Ching-Yuan","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Marine Environmental Informatics, National Taiwan Ocean University, 2 Pei-Ning Road, Keelung 202301, Taiwan"}]},{"given":"Shih-Jen","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Marine Environmental Informatics, National Taiwan Ocean University, 2 Pei-Ning Road, Keelung 202301, Taiwan"}]},{"given":"Thwong-Zong","family":"Yang","sequence":"additional","affiliation":[{"name":"Meteorological Satellite Center, Central Weather Bureau, 64 Gongyuan Road, Taipei 100006, Taiwan"}]},{"given":"Yu-Cheng","family":"Chang","sequence":"additional","affiliation":[{"name":"Meteorological Satellite Center, Central Weather Bureau, 64 Gongyuan Road, Taipei 100006, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7629-2765","authenticated-orcid":false,"given":"Chung-Ru","family":"Ho","sequence":"additional","affiliation":[{"name":"Department of Marine Environmental Informatics, National Taiwan Ocean University, 2 Pei-Ning Road, Keelung 202301, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,12]]},"reference":[{"key":"ref_1","unstructured":"Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., P\u00e9an, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., and Gomis, M.I. (2021). Climate Change 2021: The Physical Science Basis, Cambridge University Press."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Martin, S. (2014). An Introduction to Ocean Remote Sensing, Cambridge University Press. [2nd ed.].","DOI":"10.1017\/CBO9781139094368"},{"key":"ref_3","unstructured":"Cochran, J.K., Bokuniewicz, H.J., and Yager, P.L. (2019). Encyclopedia of Ocean Sciences, Elsevier Science. [3rd ed.]."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1175\/1520-0450(1972)011<0887:EOROTS>2.0.CO;2","article-title":"Empirical orthogonal representation of time series in the frequency domain. Part I: Theoretical considerations","volume":"11","author":"Wallace","year":"1972","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1175\/1520-0426(2003)020<1839:ECADFF>2.0.CO;2","article-title":"EOF calculations and data filling from incomplete oceanographic datasets","volume":"20","author":"Beckers","year":"2003","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.ocemod.2004.08.001","article-title":"Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: Application to the Adriatic Sea surface temperature","volume":"9","author":"Barth","year":"2005","journal-title":"Ocean Model."},{"key":"ref_7","unstructured":"Daley, R. (1991). Atmospheric Data Analysis, Cambridge University Press."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"183","DOI":"10.5194\/os-2-183-2006","article-title":"DINEOF reconstruction of clouded images including error maps-application to the Sea-Surface Temperature around Corsican Island","volume":"2","author":"Beckers","year":"2006","journal-title":"Ocean Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"232","DOI":"10.3389\/feart.2019.00232","article-title":"Reconstruction of large-scale sea surface temperature and salinity fields using sub-regional EOF patterns from models","volume":"7","author":"Elken","year":"2019","journal-title":"Front. Earth Sci."},{"key":"ref_10","first-page":"C03008","article-title":"Multivariate reconstruction of missing data in sea surface temperature, chlorophyll, and wind satellite fields","volume":"112","author":"Barth","year":"2007","journal-title":"J. Geophys. Res."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hsu, P.C., Lu, C.Y., Hsu, T.W., and Ho, C.R. (2020). Diurnal to seasonal variations in ocean chlorophyll and ocean currents in the north of Taiwan observed by Geostationary Ocean Color Imager and coastal radar. Remote Sens., 12.","DOI":"10.3390\/rs12172853"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"L07308","DOI":"10.1029\/2003GL019373","article-title":"The anomalous amplification of M2 tide in the Taiwan Strait","volume":"31","author":"Jan","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1016\/j.csr.2009.01.015","article-title":"Summertime sea surface temperature fronts associated with upwelling around the Taiwan Bank","volume":"29","author":"Lan","year":"2009","journal-title":"Cont. Shelf Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.dsr.2017.11.006","article-title":"Zonal migration and transport variations of the Kuroshio east of Taiwan induced by eddy impingements","volume":"131","author":"Chang","year":"2018","journal-title":"Deep-Sea Res. Part I Oceanogr. Res. Pap."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hsu, P.C., Ho, C.Y., Lee, H.J., Lu, C.Y., and Ho, C.R. (2019). Temporal variation and spatial structure of the Kuroshio-induced submesoscale island vortices observed from GCOM-C and Himawari-8 data. Remote Sens., 12.","DOI":"10.3390\/rs12050883"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hu, J.Y., Ho, C.R., Xie, L.L., and Zheng, Q. (2019). Advances in research of regional oceanography of the South China Sea: Overview. Regional Oceanography of the South China Sea, World Scientific.","DOI":"10.1142\/11461"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1175\/1520-0493(1982)110<0481:EOEEOF>2.0.CO;2","article-title":"Examples of extended empirical orthogonal function analyses","volume":"110","author":"Weare","year":"1982","journal-title":"Mon. Weather Rev."},{"key":"ref_18","unstructured":"Thomson, R.E., and Emery, W.J. (2014). Data Analysis Methods in Physical Oceanography, Elsevier Science. [3rd ed.]."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ping, B., Su, F., and Meng, Y. (2016). An improved DINEOF algorithm for filling missing values in spatio-temporal sea surface temperature data. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0155928"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s10872-016-0365-1","article-title":"Reconstruction and analysis of long-term satellite-derived sea surface temperature for the South China Sea","volume":"72","author":"Huynh","year":"2016","journal-title":"J. Oceanogr."},{"key":"ref_21","unstructured":"Central Weather Bureau (2022, April 27). Climate Monitoring: 2018 Annual Report, Available online: https:\/\/www.cwb.gov.tw\/Data\/service\/notice\/download\/publish_20191104141027.pdf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4539","DOI":"10.1175\/2009JCLI2901.1","article-title":"Intraseasonal latent heat flux based on satellite observations","volume":"22","author":"Grodsky","year":"2009","journal-title":"J. Clim."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"9475","DOI":"10.1175\/JCLI-D-17-0140.1","article-title":"Subseasonal variations of wintertime North Pacific evaporation, cold air surges, and water vapor transport","volume":"30","author":"Rex","year":"2017","journal-title":"J. Clim."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1175\/JTECH-D-13-00121.1","article-title":"In situ SST quality monitor (iQuam)","volume":"31","author":"Xu","year":"2014","journal-title":"J. Atmos. Ocean. Technol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/12\/2818\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:28:22Z","timestamp":1760138902000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/12\/2818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,12]]},"references-count":24,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["rs14122818"],"URL":"https:\/\/doi.org\/10.3390\/rs14122818","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,12]]}}}