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dc.contributor.authorSwain, D.
dc.contributor.authorAli, M. M.
dc.contributor.authorWeller, Robert A.
dc.date.accessioned2007-02-09T19:29:49Z
dc.date.available2007-02-09T19:29:49Z
dc.date.issued2006-09
dc.identifier.citationJournal of Marine Research 64 (2006): 745-758en
dc.identifier.urihttp://hdl.handle.net/1912/1502
dc.descriptionAuthor Posting. © Sears Foundation for Marine Research, 2006. This article is posted here by permission of Sears Foundation for Marine Research for personal use, not for redistribution. The definitive version was published in Journal of Marine Research 64 (2006): 745-758, doi:10.1357/002224006779367285.en
dc.description.abstractMixed layer depth (MLD) is an important oceanographic parameter. However, the lack of direct observations of MLD hampers both specification and investigation of its spatial and temporal variability. An important alternative to direct observation would be the ability to estimate MLD from surface parameters easily available from satellites. In this study, we demonstrate estimation of MLD using Artificial Neural Network methods and surface meteorology from a surface mooring in the Arabian Sea. The estimated MLD had a root mean square error of 7.36 m and a coefficient of determination (R2) of 0.94. About 67% (91%) of the estimates lie within ± 5 m (± 10 m) of the MLD determined from temperature sensors on the mooring.en
dc.format.extent308260 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen
dc.publisherSears Foundation for Marine Researchen
dc.relation.urihttps://doi.org/10.1357/002224006779367285
dc.titleEstimation of mixed-layer depth from surface parametersen
dc.typeArticleen
dc.identifier.doi10.1357/002224006779367285


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