dc.contributor.author | Palmer, Matthew D. | |
dc.contributor.author | Boyer, Tim | |
dc.contributor.author | Cowley, Rebecca | |
dc.contributor.author | Kizu, Shoichi | |
dc.contributor.author | Reseghetti, Franco | |
dc.contributor.author | Suzuki, Toru | |
dc.contributor.author | Thresher, Ann | |
dc.date.accessioned | 2019-01-06T18:17:05Z | |
dc.date.available | 2019-01-06T18:17:05Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Palmer, 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 | en_US |
dc.identifier.uri | http://hdl.handle.net/11329/627 | |
dc.identifier.uri | http://dx.doi.org/10.25607/OBP-186 | |
dc.description.abstract | 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, 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.iso | en | en_US |
dc.rights | Attribution 4.0 | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.other | XBT | en_US |
dc.subject.other | Expendable bathythermgraphs | en_US |
dc.subject.other | Heat content | en_US |
dc.subject.other | Climate records | |
dc.subject.other | Ocean observations | |
dc.subject.other | SCOR WG 148 | |
dc.subject.other | Scientific Committee on Oceanic Research Working Group 148 | |
dc.title | An Algorithm for Classifying Unknown Expendable Bathythermograph (XBT) Instruments Based on Existing Metadata. | en_US |
dc.type | Journal Contribution | en_US |
dc.description.refereed | Refereed | en_US |
dc.format.pagerange | pp.429-440 | en_US |
dc.identifier.doi | 10.1175/JTECH-D-17-0129.1 | |
dc.subject.parameterDiscipline | Parameter Discipline::Physical oceanography::Water column temperature and salinity | en_US |
dc.subject.instrumentType | Instrument Type Vocabulary::bathythermographs | en_US |
dc.subject.dmProcesses | Data Management Practices::Data archival/stewardship/curation | en_US |
dc.subject.dmProcesses | Data processing | |
dc.bibliographicCitation.title | Journal of Atmospheric and Oceanic Technology | en_US |
dc.bibliographicCitation.volume | 35 | en_US |
dc.description.sdg | 14.A | en_US |
dc.description.eov | Subsurface temperature | en_US |
dc.description.bptype | Best Practice | en_US |
dc.description.bptype | Guide | en_US |
obps.contact.contactemail | matthew.palmer@metoffice.gov.uk | |
obps.resourceurl.publisher | https://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-17-0129.1 | en_US |