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  Using GEBCO digital bathymetry to infer depth biases in the XBT data

Gouretski, V. (2012). Using GEBCO digital bathymetry to infer depth biases in the XBT data. DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS, 62, 40-52. doi:10.1016/j.dsr.2011.12.012.

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 Creators:
Gouretski, Viktor1, Author           
Affiliations:
1I 1 - Integrated Climate Data Center, Integrated Activities, The CliSAP Cluster of Excellence, External Organizations, ou_1863492              

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Free keywords: EXPENDABLE BATHYTHERMOGRAPH; FALL RATE; TEMPERATURE; OCEAN; SEA; T-7Expendable bathythermograph; Depth bias; Temperature bias; Global ocean bathymetry;
 Abstract: A global ocean 30 arc-second gridded GEBCO bathymetry is used as a reference to infer depth biases in expendable bathythermograph (XBT) data. In agreement with earlier studies we diagnose a depth varying XBT depth bias, with XBT sample depth being overestimated within the upper 50-200 m and underestimated below 200 m. The depth bias also exhibits certain time variability, with the fall rate for the majority of the XBT types being slower in the 1970s, with a minimum around 1975-77, again in agreement with earlier studies. However, when applied to the global XBT dataset, the new depth- and time varying depth corrections do not eliminate the total XBT temperature bias relative to the quasi-collocated Conductivity-Temperature-Depth (CTD) and bottle data thus implying the existence of a fall-rate-independent XBT thermal bias. In agreement with earlier works, the largest positive thermal bias is observed before 1980-85. The analysis also suggests different fall-rates for the probes produced by the two main XBT manufacturers. (c) 2012 Elsevier Ltd. All rights reserved.

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Language(s): eng - English
 Dates: 2012-04
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000302672000005
DOI: 10.1016/j.dsr.2011.12.012
 Degree: -

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Title: DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 62 Sequence Number: - Start / End Page: 40 - 52 Identifier: ISSN: 0967-0637