Articles | Volume 20, issue 5
https://doi.org/10.5194/os-20-1351-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-20-1351-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
North Atlantic Subtropical Mode Water properties: intrinsic and atmospherically forced interannual variability
Olivier Narinc
Univ Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Univ Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, IGE, 38000 Grenoble, France
Guillaume Maze
Univ Brest, Ifremer, CNRS, IRD, LOPS, 29280 Plouzané, France
Stéphanie Leroux
Datlas, 30000 Grenoble, France
Jean-Marc Molines
Univ Grenoble Alpes, CNRS, INRAE, IRD, Grenoble INP, IGE, 38000 Grenoble, France
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Flows in the ocean are driven either by atmospheric forces or by small-scale internal disturbances that are inherently chaotic. We use computer simulation results to show that these chaotic oceanic disturbances can attain spatial scales large enough to alter the motion of Earth's pole of rotation. Given their size and unpredictable nature, the chaotic signals are a source of uncertainty when interpreting observed year-to-year polar motion changes in terms of other processes in the Earth system.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3847, https://doi.org/10.5194/egusphere-2024-3847, 2024
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Particle-tracking simulations compute how ocean currents transport material. However, initialising these simulations is often ad-hoc. Here, we explore how two different strategies (releasing particles over space or over time) compare. Specifically, we compare the variability in particle trajectories to the variability of particles computed in a 50-member ensemble simulation. We find that releasing the particles over 20 weeks gives variability that is most like that in the ensemble.
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The goal of the study is to evaluate the predictability of the ocean circulation
at a kilometric scale, in order to anticipate the requirements of the future operational forecasting systems. For that purpose, ensemble experiments have been performed with a regional model for the Western Mediterranean (at 1/60° horizontal resolution). From these ensemble experiments, we show that it is possible to compute targeted predictability scores, which depend on initial and model uncertainties.
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Temperature and salinity profiles are essential for studying the ocean’s stratification, but there are not enough of these data. Satellites are able to measure daily maps of the surface ocean. We train a machine to learn the link between the satellite data and the profiles in the Gulf Stream region. We can then use this link to predict profiles at the high resolution of the satellite maps. Our prediction is fast to compute and allows us to get profiles at any locations only from surface data.
Sophie Cravatte, Guillaume Serazin, Thierry Penduff, and Christophe Menkes
Ocean Sci., 17, 487–507, https://doi.org/10.5194/os-17-487-2021, https://doi.org/10.5194/os-17-487-2021, 2021
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The various currents in the southwestern Pacific Ocean contribute to the redistribution of waters from the subtropical gyre equatorward and poleward. The drivers of their interannual variability are not completely understood but are usually thought to be related to well-known climate modes of variability. Here, we suggest that oceanic chaotic variability alone, which is by definition unpredictable, explains the majority of this interannual variability south of 20° S.
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Short summary
This study examines how the ocean's chaotic variability and atmospheric fluctuations affect yearly changes in North Atlantic Subtropical Mode Water (STMW) properties, using an ensemble of realistic ocean simulations. Results show that while yearly changes in STMW properties are mostly paced by the atmosphere, a notable part of these changes are random in phase. This study also illustrates the value of ensemble simulations over single runs in understanding oceanic fluctuations and their causes.
This study examines how the ocean's chaotic variability and atmospheric fluctuations affect...