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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Copernicus Publications
2022
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00063226 2023-05-15T15:08:33+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 electronic https://doi.org/10.5194/gi-11-359-2022 https://noa.gwlb.de/receive/cop_mods_00063226 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00062336/gi-11-359-2022.pdf https://gi.copernicus.org/articles/11/359/2022/gi-11-359-2022.pdf eng eng Copernicus Publications Geoscientific Instrumentation, Methods and Data Systems -- Geosci. Instrum. Meth. Data Syst. -- http://www.geoscientific-instrumentation-methods-and-data-systems.net/home.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2690575 -- 2193-0864 https://doi.org/10.5194/gi-11-359-2022 https://noa.gwlb.de/receive/cop_mods_00063226 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00062336/gi-11-359-2022.pdf https://gi.copernicus.org/articles/11/359/2022/gi-11-359-2022.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2022 ftnonlinearchiv https://doi.org/10.5194/gi-11-359-2022 2022-10-31T00:12:06Z 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. Article in Journal/Newspaper Arctic North Atlantic Niedersächsisches Online-Archiv NOA Arctic Geoscientific Instrumentation, Methods and Data Systems 11 2 359 373 |
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Niedersächsisches Online-Archiv NOA |
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English |
topic |
article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Rollo, Callum Heywood, Karen J. Hall, Rob A. Glider observations of thermohaline staircases in the tropical North Atlantic using an automated classifier |
topic_facet |
article Verlagsveröffentlichung |
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 |
Article in Journal/Newspaper |
author |
Rollo, Callum Heywood, Karen J. Hall, Rob A. |
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 |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/gi-11-359-2022 https://noa.gwlb.de/receive/cop_mods_00063226 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00062336/gi-11-359-2022.pdf https://gi.copernicus.org/articles/11/359/2022/gi-11-359-2022.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic North Atlantic |
genre_facet |
Arctic North Atlantic |
op_relation |
Geoscientific Instrumentation, Methods and Data Systems -- Geosci. Instrum. Meth. Data Syst. -- http://www.geoscientific-instrumentation-methods-and-data-systems.net/home.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2690575 -- 2193-0864 https://doi.org/10.5194/gi-11-359-2022 https://noa.gwlb.de/receive/cop_mods_00063226 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00062336/gi-11-359-2022.pdf https://gi.copernicus.org/articles/11/359/2022/gi-11-359-2022.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
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 |
container_start_page |
359 |
op_container_end_page |
373 |
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1766339895428644864 |