Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier

Thermohaline staircases are stepped structures of alternating thick mixed layers and thin high-gradient interfaces. These structures can be up to several tens of metres thick and are associated with double-diffusive mixing. Thermohaline staircases occur across broad swathes of the Arctic and tropica...

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Published in:Geoscientific Instrumentation, Methods and Data Systems
Main Authors: Rollo, Callum, Heywood, Karen J., Hall, Rob A.
Format: Text
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.5194/gi-11-359-2022
https://gi.copernicus.org/articles/11/359/2022/
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spelling ftcopernicus:oai:publications.copernicus.org:gi98131 2023-05-15T15:07:06+02:00 Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier Rollo, Callum Heywood, Karen J. Hall, Rob A. 2022-10-25 application/pdf https://doi.org/10.5194/gi-11-359-2022 https://gi.copernicus.org/articles/11/359/2022/ eng eng doi:10.5194/gi-11-359-2022 https://gi.copernicus.org/articles/11/359/2022/ eISSN: 2193-0864 Text 2022 ftcopernicus https://doi.org/10.5194/gi-11-359-2022 2022-10-31T17:22:43Z Thermohaline staircases are stepped structures of alternating thick mixed layers and thin high-gradient interfaces. These structures can be up to several tens of metres thick and are associated with double-diffusive mixing. Thermohaline staircases occur across broad swathes of the Arctic and tropical and subtropical oceans and can increase rates of diapycnal mixing by up to 5 times the background rate, driving substantial nutrient fluxes to the upper ocean. In this study, we present an improved classification algorithm to detect thermohaline staircases in ocean glider profiles. We use a dataset of 1162 glider profiles from the tropical North Atlantic collected in early 2020 at the edge of a known thermohaline staircase region. The algorithm identifies thermohaline staircases in 97.7 % of profiles that extend deeper than 300 m. We validate our algorithm against previous results obtained from algorithmic classification of Argo float profiles. Using fine-resolution temperature data from a fast-response thermistor on one of the gliders, we explore the effect of varying vertical bin sizes on detected thermohaline staircases. Our algorithm builds on previous work by adding improved flexibility and the ability to classify staircases from profiles with noisy salinity data. Using our results, we propose that the incidence of thermohaline staircases is limited by strong background vertical gradients in conservative temperature and absolute salinity. Text Arctic North Atlantic Copernicus Publications: E-Journals Arctic Geoscientific Instrumentation, Methods and Data Systems 11 2 359 373
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description Thermohaline staircases are stepped structures of alternating thick mixed layers and thin high-gradient interfaces. These structures can be up to several tens of metres thick and are associated with double-diffusive mixing. Thermohaline staircases occur across broad swathes of the Arctic and tropical and subtropical oceans and can increase rates of diapycnal mixing by up to 5 times the background rate, driving substantial nutrient fluxes to the upper ocean. In this study, we present an improved classification algorithm to detect thermohaline staircases in ocean glider profiles. We use a dataset of 1162 glider profiles from the tropical North Atlantic collected in early 2020 at the edge of a known thermohaline staircase region. The algorithm identifies thermohaline staircases in 97.7 % of profiles that extend deeper than 300 m. We validate our algorithm against previous results obtained from algorithmic classification of Argo float profiles. Using fine-resolution temperature data from a fast-response thermistor on one of the gliders, we explore the effect of varying vertical bin sizes on detected thermohaline staircases. Our algorithm builds on previous work by adding improved flexibility and the ability to classify staircases from profiles with noisy salinity data. Using our results, we propose that the incidence of thermohaline staircases is limited by strong background vertical gradients in conservative temperature and absolute salinity.
format Text
author Rollo, Callum
Heywood, Karen J.
Hall, Rob A.
spellingShingle Rollo, Callum
Heywood, Karen J.
Hall, Rob A.
Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
author_facet Rollo, Callum
Heywood, Karen J.
Hall, Rob A.
author_sort Rollo, Callum
title Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
title_short Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
title_full Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
title_fullStr Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
title_full_unstemmed Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier
title_sort glider observations of thermohaline staircases in the tropical north atlantic using an automated classifier
publishDate 2022
url https://doi.org/10.5194/gi-11-359-2022
https://gi.copernicus.org/articles/11/359/2022/
geographic Arctic
geographic_facet Arctic
genre Arctic
North Atlantic
genre_facet Arctic
North Atlantic
op_source eISSN: 2193-0864
op_relation doi:10.5194/gi-11-359-2022
https://gi.copernicus.org/articles/11/359/2022/
op_doi https://doi.org/10.5194/gi-11-359-2022
container_title Geoscientific Instrumentation, Methods and Data Systems
container_volume 11
container_issue 2
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