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dc.contributor.authorPalmer, Matthew D.
dc.contributor.authorBoyer, Tim
dc.contributor.authorCowley, Rebecca
dc.contributor.authorKizu, Shoichi
dc.contributor.authorReseghetti, Franco
dc.contributor.authorSuzuki, Toru
dc.contributor.authorThresher, Ann
dc.date.accessioned2019-01-06T18:17:05Z
dc.date.available2019-01-06T18:17:05Z
dc.date.issued2018
dc.identifier.citationPalmer, M.D.; Boyer, T.; Cowley, R.; Kizu, S.; Reseghetti, F.; Suzuki, T. and Threshe, A.r (2018) An Algorithm for Classifying Unknown Expendable Bathythermograph (XBT) Instruments Based on Existing Metadata. Journal of Atmospheric and Oceanic Technology, 35, pp.429-440. DOI: 10.1175/JTECH-D-17-0129.1en_US
dc.identifier.urihttp://hdl.handle.net/11329/627
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-186
dc.description.abstractTime-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key un- certainty in estimates of historical ocean heat content variability and change. One of the challenges in the development of XBT bias corrections is the lack of metadata in ocean profile databases. Approximately 50% of XBT profiles in the World Ocean database (WOD) have no information about manufacturer or probe type. Building on previous research efforts, this paper presents a deterministic algorithm for assigning missing XBT manufacturer and probe type for individual temperature profiles based on 1) the reporting country, 2) the maximum reported depth, and 3) the record date. The criteria used are based on bulk analysis of known XBT profiles in the WOD for the period 1966–2015. A basic skill assessment demonstrates a 77% success rate at correctly assigning manufacturer and probe type for profiles where this information is available. The skill rate is lowest during the early 1990s, which is also a period when metadata information is particularly poor. The results suggest that substantive improvements could be made through further data analysis and that future algorithms may benefit from including a larger number of predictor variable.en_US
dc.language.isoenen_US
dc.rightsAttribution 4.0*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherXBTen_US
dc.subject.otherExpendable bathythermgraphsen_US
dc.subject.otherHeat contenten_US
dc.subject.otherClimate records
dc.subject.otherOcean observations
dc.subject.otherSCOR WG 148
dc.subject.otherScientific Committee on Oceanic Research Working Group 148
dc.titleAn Algorithm for Classifying Unknown Expendable Bathythermograph (XBT) Instruments Based on Existing Metadata.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerangepp.429-440en_US
dc.identifier.doi10.1175/JTECH-D-17-0129.1
dc.subject.parameterDisciplineParameter Discipline::Physical oceanography::Water column temperature and salinityen_US
dc.subject.instrumentTypeInstrument Type Vocabulary::bathythermographsen_US
dc.subject.dmProcessesData Management Practices::Data archival/stewardship/curationen_US
dc.subject.dmProcessesData processing
dc.bibliographicCitation.titleJournal of Atmospheric and Oceanic Technologyen_US
dc.bibliographicCitation.volume35en_US
dc.description.sdg14.Aen_US
dc.description.eovSubsurface temperatureen_US
dc.description.bptypeBest Practiceen_US
dc.description.bptypeGuideen_US
obps.contact.contactemailmatthew.palmer@metoffice.gov.uk
obps.resourceurl.publisherhttps://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-17-0129.1en_US


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Except where otherwise noted, this item's license is described as Attribution 4.0