An Algorithm for Classifying Unknown Expendable Bathythermograph (XBT) Instruments Based on Existing Metadata.
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Palmer, Matthew D.
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Time-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, w.....
JournalJournal of Atmospheric and Oceanic Technology
Sustainable Development Goals (SDG)14.A
Essential Ocean Variables (EOV)Subsurface temperature
Best Practice TypeBest Practice
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-17-0129.1
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