Articles | Volume 18, issue 14
https://doi.org/10.5194/gmd-18-4685-2025
https://doi.org/10.5194/gmd-18-4685-2025
Model description paper
 | 
30 Jul 2025
Model description paper |  | 30 Jul 2025

Comparing an idealized deterministic–stochastic model (SUP model, version 1) of the tide- and wind-driven sea surface currents in the Gulf of Trieste to high-frequency radar observations

Sofia Flora, Laura Ursella, and Achim Wirth

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Cited articles

Alberti, T., Consolini, G., De Michelis, P., Laurenza, M., and Marcucci, M. F.: On fast and slow Earth’s magnetospheric dynamics during geomagnetic storms: a stochastic Langevin approach, J. Space Weather Space Clim., 8, A56, https://doi.org/10.1051/swsc/2018039, 2018. a
Baldovin, M., Puglisi, A., and Vulpiani, A.: Langevin equation in systems with also negative temperatures, J. Stat. Mech. Theor. Exp., 2018, 043207, https://doi.org/10.1088/1742-5468/aab687, 2018. a
Beck, C. and Cohen, E. G.: Superstatistics, Physica A, 322, 267–275, 2003. a
Beck, C., Cohen, E. G. D., and Swinney, H. L.: From time series to superstatistics, Phys. Rev. E, 72, 056133, https://doi.org/10.1103/PhysRevE.72.056133, 2005. a
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Short summary
We developed a hierarchy of idealized deterministic–stochastic models to simulate sea surface currents in the Gulf of Trieste. They include tide- and wind-driven sea surface current components, resolving the slowly varying part of the flow, and a stochastic signal, representing the fast-varying small-scale dynamics. The comparison with high-frequency radar observations shows that the non-Gaussian stochastic model captures key dynamics and mimics the observed fat-tailed probability distribution.
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