TY - JOUR
T1 - Near-Automatic Routine Field Calibration/Correction of Glider Salinity Data Using Whitespace Maximization Image Analysis of Theta/S Data
AU - Allen, John T.
AU - Munoz, Cristian
AU - Gardiner, Jim
AU - Reeve, Krissy A.
AU - Alou-Font, Eva
AU - Zarokanellos, Nikolaos
N1 - Generated from Scopus record by KAUST IRTS on 2023-10-11
PY - 2020/6/26
Y1 - 2020/6/26
N2 - Glider vehicles are now perhaps some of the most prolific providers of real-time and near-real-time operational oceanographic data. However, the data from these vehicles can and should be considered to have a long-term legacy value capable of playing a critical role in understanding and separating inter-annual, inter-decadal, and long-term global change. To achieve this, we have to go further than simply assuming the manufacturer’s calibrations, and field correct glider data in a more traditional way, for example, by careful comparison to water bottle calibrated lowered CTD datasets and/or “gold” standard recent climatologies. In this manuscript, we bring into the 21st century a historical technique that has been used manually by oceanographers for many years/decades for field correction/inter-calibration, thermal lag correction, and adjustment for biological fouling. The technique has now been made semi-automatic for machine processing of oceanographic glider data, although its future and indeed its origins have far wider scope. The subject of this manuscript is drawn from the original Description of Work (DoW) for a key task in the recently completed JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatories) EU-funded program, but goes on to consider future application and the suitability for integration with machine learning.
AB - Glider vehicles are now perhaps some of the most prolific providers of real-time and near-real-time operational oceanographic data. However, the data from these vehicles can and should be considered to have a long-term legacy value capable of playing a critical role in understanding and separating inter-annual, inter-decadal, and long-term global change. To achieve this, we have to go further than simply assuming the manufacturer’s calibrations, and field correct glider data in a more traditional way, for example, by careful comparison to water bottle calibrated lowered CTD datasets and/or “gold” standard recent climatologies. In this manuscript, we bring into the 21st century a historical technique that has been used manually by oceanographers for many years/decades for field correction/inter-calibration, thermal lag correction, and adjustment for biological fouling. The technique has now been made semi-automatic for machine processing of oceanographic glider data, although its future and indeed its origins have far wider scope. The subject of this manuscript is drawn from the original Description of Work (DoW) for a key task in the recently completed JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatories) EU-funded program, but goes on to consider future application and the suitability for integration with machine learning.
UR - https://www.frontiersin.org/article/10.3389/fmars.2020.00398/full
UR - http://www.scopus.com/inward/record.url?scp=85087910458&partnerID=8YFLogxK
U2 - 10.3389/fmars.2020.00398
DO - 10.3389/fmars.2020.00398
M3 - Article
SN - 2296-7745
VL - 7
JO - FRONTIERS IN MARINE SCIENCE
JF - FRONTIERS IN MARINE SCIENCE
ER -