An algorithm for classifying unknown expendable bathythermograph (XBT) instruments based on existing metadata

Matthew D. Palmer, Tim Boyer, Rebecca Cowley, Shoichi Kizu, Franco Reseghetti, Toru Suzuki, Ann Thresher

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty 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 variables.
Original languageEnglish
Pages (from-to)429 - 440
Number of pages12
JournalJournal of Atmospheric and Oceanic Technology
Volume35
Issue number3
DOIs
Publication statusPublished - 1 Mar 2018
Externally publishedYes

Fingerprint

metadata
Metadata
probe
ocean
Enthalpy
temperature profile
Temperature
rate
world

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Atmospheric Science

Cite this

Palmer, Matthew D. ; Boyer, Tim ; Cowley, Rebecca ; Kizu, Shoichi ; Reseghetti, Franco ; Suzuki, Toru ; Thresher, Ann. / An algorithm for classifying unknown expendable bathythermograph (XBT) instruments based on existing metadata. In: Journal of Atmospheric and Oceanic Technology. 2018 ; Vol. 35, No. 3. pp. 429 - 440.
@article{f13d644cdc2847adb1ce96470f93b2aa,
title = "An algorithm for classifying unknown expendable bathythermograph (XBT) instruments based on existing metadata",
abstract = "Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty 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 variables.",
author = "Palmer, {Matthew D.} and Tim Boyer and Rebecca Cowley and Shoichi Kizu and Franco Reseghetti and Toru Suzuki and Ann Thresher",
year = "2018",
month = "3",
day = "1",
doi = "10.1175/JTECH-D-17-0129.1",
language = "English",
volume = "35",
pages = "429 -- 440",
journal = "Journal of Atmospheric and Oceanic Technology",
issn = "0739-0572",
publisher = "American Meteorological Society",
number = "3",

}

An algorithm for classifying unknown expendable bathythermograph (XBT) instruments based on existing metadata. / Palmer, Matthew D.; Boyer, Tim; Cowley, Rebecca; Kizu, Shoichi; Reseghetti, Franco; Suzuki, Toru; Thresher, Ann.

In: Journal of Atmospheric and Oceanic Technology, Vol. 35, No. 3, 01.03.2018, p. 429 - 440.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An algorithm for classifying unknown expendable bathythermograph (XBT) instruments based on existing metadata

AU - Palmer, Matthew D.

AU - Boyer, Tim

AU - Cowley, Rebecca

AU - Kizu, Shoichi

AU - Reseghetti, Franco

AU - Suzuki, Toru

AU - Thresher, Ann

PY - 2018/3/1

Y1 - 2018/3/1

N2 - Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty 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 variables.

AB - Time-varying biases in expendable bathythermograph (XBT) instruments have emerged as a key uncertainty 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 variables.

UR - http://www.scopus.com/inward/record.url?scp=85044647617&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044647617&partnerID=8YFLogxK

U2 - 10.1175/JTECH-D-17-0129.1

DO - 10.1175/JTECH-D-17-0129.1

M3 - Article

VL - 35

SP - 429

EP - 440

JO - Journal of Atmospheric and Oceanic Technology

JF - Journal of Atmospheric and Oceanic Technology

SN - 0739-0572

IS - 3

ER -