Articles | Volume 19, issue 6
https://doi.org/10.5194/os-19-1579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-19-1579-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact of surface and subsurface-intensified eddies on sea surface temperature and chlorophyll a in the northern Indian Ocean utilizing deep learning
Yingjie Liu
CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
Xiaofeng Li
CORRESPONDING AUTHOR
CAS Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
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In the Southern Ocean, abundant eddies behave opposite to our expectations. That is, anticyclonic (cyclonic) eddies are cold (warm). By investigating the variations of physical and biochemical parameters in eddies, we find that abnormal eddies have unique and significant effects on modulating the parameters. This study fills a gap in understanding the effects of abnormal eddies on physical and biochemical parameters in the Southern Ocean.
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In the Southern Ocean, abundant eddies behave opposite to our expectations. That is, anticyclonic (cyclonic) eddies are cold (warm). By investigating the variations of physical and biochemical parameters in eddies, we find that abnormal eddies have unique and significant effects on modulating the parameters. This study fills a gap in understanding the effects of abnormal eddies on physical and biochemical parameters in the Southern Ocean.
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Integrating wide swath altimetry data into Level-4 multi-mission maps
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Blending 2D topography images from SWOT into the altimeter constellation with the Level-3 multi-mission DUACS system
Estimating ocean currents from the joint reconstruction of absolute dynamic topography and sea surface temperature through deep learning algorithms
Regional mapping of energetic short mesoscale ocean dynamics from altimetry: performances from real observations
Ocean 2D eddy energy fluxes from small mesoscale processes with SWOT
Georges Baaklini, Julien Brajard, Leila Issa, Gina Fifani, Laurent Mortier, and Roy El Hourany
Ocean Sci., 20, 1707–1720, https://doi.org/10.5194/os-20-1707-2024, https://doi.org/10.5194/os-20-1707-2024, 2024
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Menghong Dong and Xinyu Guo
Ocean Sci., 20, 1527–1546, https://doi.org/10.5194/os-20-1527-2024, https://doi.org/10.5194/os-20-1527-2024, 2024
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We employed a gradient-based algorithm to identify the position and intensity of the fronts in a coastal sea using sea surface temperature data, thereby quantifying their variations. Our study provides a comprehensive analysis of these fronts, elucidating their seasonal variability, intra-tidal dynamics, and the influence of winds on the fronts. By capturing the temporal and spatial dynamics of these fronts, our understanding of the complex oceanographic processes within this region is enhanced.
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Maxime Ballarotta, Clément Ubelmann, Valentin Bellemin-Laponnaz, Florian Le Guillou, Guillaume Meda, Cécile Anadon, Alice Laloue, Antoine Delepoulle, Yannice Faugère, Marie-Isabelle Pujol, Ronan Fablet, and Gérald Dibarboure
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Gerald Dibarboure, Cécile Anadon, Frédéric Briol, Emeline Cadier, Robin Chevrier, Antoine Delepoulle, Yannice Faugère, Alice Laloue, Rosemary Morrow, Nicolas Picot, Pierre Prandi, Marie-Isabelle Pujol, Matthias Raynal, Anaelle Treboutte, and Clément Ubelmann
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Oceanic eddies are the structures carrying most of the energy in our oceans. They are key to climate regulation and nutrient transport. We prepare for the Surface Water and Ocean Topography mission, studying eddy dynamics in the region south of Africa, where the Indian and Atlantic oceans meet, using models and simulated satellite data. SWOT will provide insights into the structures smaller than what is currently observable, which appear to greatly contribute to eddy kinetic energy and strain.
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Short summary
The study developed a deep learning model that effectively distinguishes between surface- and subsurface-intensified eddies in the northern Indian Ocean by integrating sea surface height and temperature data. The accurate distinction between these types of eddies provides valuable insights into their dynamics and their impact on marine ecosystems in the northern Indian Ocean and contributes to understanding the complex interactions between eddy dynamics and biogeochemical processes in the ocean.
The study developed a deep learning model that effectively distinguishes between surface- and...